Intellectual Property Protection, Product Life-cycle Lengths, and the Boundaries of Multinational Corporations

Intellectual Property Protection, Product Life-cycle Lengths, and the Boundaries of Multinational Corporations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Intellectual Property Protection, Product Life-cycle Lengths, and the Boundaries of Multinational Corporations Yiming Zhang, Zuoliang Ye, Yunong Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3877554/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper presents a theoretical model based on transaction cost analysis and the resource-based view. It establishes that the corporate boundaries of multinational corporations are determined by the length of the product life cycle and the level of intellectual property protection in the host country. The empirical results based on the panel data of U.S. multinational corporations' import trade of 208 types of products in 18 countries from 2002 to 2013 validate the extrapolation results of the theoretical model. The study finds that the most significant determinants of multinational corporations' boundaries are the length of the product life cycle and the level of IPR protection in the host country. Boundaries of the multinational firm Intellectual property protection Product life-cycle lengths Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction The establishment and management of boundaries for multinational corporations (MNCs), as significant players in global commerce, have far-reaching implications for the global economic system. Deciding how to set the boundaries of MNCs is a crucial decision for operators in the international trading system. Economists and management scientists have extensively researched the factors that determine the boundaries of MNCs. Most explanations are based on transaction cost analysis or resource-based view. However, these two explanations are driven by different logics: cost minimisation and revenue maximisation, respectively (Cuervo-Cazurra et al., 2018 ). This paper integrates transaction cost analysis and the resource base view to explain how intellectual property rights (IPR) protection and product life-cycle lengths affect the boundaries of MNCs. The model setup and derivation are presented based on a summary of existing literature. MNCs are significant players in US trade. The study uses US MNCs' trade data to validate the theory that U.S. overseas market penetration and sourcing are highly selective, and the main types of import sourcing (related-party and unrelated-party trade) vary by market (Co, 2010 ). The paper examines the inter-firm trade ratio as a measure of the propensity of MNCs to cross corporate borders. When reviewing theories on the study of firm boundaries, the most commonly used are transaction cost analysis and the resource-based view (Brouthers and Hennart, 2007 ). These two different lines of thought have sparked a debate in academia as to whether the main driver behind a firm's competitive advantage is the minimization of transaction costs or the exploitation of resources to maximize revenues. The debate on the study of firm boundaries continues to pit cost minimization against revenue maximization. Several scholars are currently working on integrating transaction cost analysis and resource-based concepts (Silverman, 1999 ; Foss and Foss, 2005 ; Cuervo-Cazurra et al., 2018 ). The challenge of integration arises from the assumptions made. The transaction cost analysis assumes that firms have developed their own sources of advantage and therefore need to focus on minimizing operating costs. On the other hand, the resource-based view assumes that the transaction problem can be solved and focuses on ensuring that advantages and revenues are maximized. This paper aims to integrate transaction cost analysis and the resource-based view to construct a theoretical model for MNCs’ boundary choice. Transaction cost analysis is a widely used theory in the study of international trade patterns. The transaction cost analysis framework assumes that decision making is influenced by three factors: asset specificity, uncertainty, and frequency (Williamson, 1985 ). Most of these studies use asset specificity as the central explanatory variable. Some studies based on transaction cost analysis have found that high asset specificity is associated with high control patterns (Gatignon and Anderson, 1988 ; Erramilli and Rao, 1993 ; Hennart and Larimo, 1998 ; Makino and Neupert, 2000 ; Brouthers and Brouthers, 2003 ; Brouthers et al., 2003 ). Integration is chosen for knowledge assets when asset specificity is high (Brouthers and Hennart, 2007 ). However, it has been found that the opposite conclusion is true in other studies (Delios and Beamish, 1999 ; Palenzuela and Bobilo, 1999; Grossman and Helpman, 2003 ). Some studies suggest that there is no significant relationship between asset specificity and the choice of international trade patterns (Hennart, 1991 ; Kim and Hwang, 1992 ; Taylor et al., 1998 ). The firm's R&D or advertising intensity (the sum of R&D and advertising expenditures divided by total sales) is a common measure of asset-specificity. Other studies have used perceived measures of asset-specific investments, including physical (service) asset specificity (Joskow, 1988 ; Klein and Roth, 1990; Erramilli and Rao, 1993 ; Klein et al., 1993 ; Brouthers and Brouthers, 2003 ; Brouthers et al., 2003 ;Wang et al., 2019 ), technology asset specificity (Taylor et al., 1998 ; Palenzuela and Bobilom, 1999), human asset specificity (Dyer, 1996 ; Handfield and Bechtel, 2002 ; Brouthers and Brouthers, 2003 ; Brouthers et al., 2003 ; Shakir and Ahmed, 2023 ), site asset specificity (Handfield and Bechtel, 2002 ; Williamson, 2007 ; Parker et al., 2019 ), and specialised asset specificity (Brouthers and Brouthers, 2003 ; Brouthers et al., 2003 ). One innovation of this paper is the use of the product life cycle length as a measure of asset specificity. The second factor is uncertainty, which comprises of internal behaviour and external market idiosyncrasies. Internal uncertainty makes it difficult to verify performance ex post, while external uncertainty makes it difficult to specify all possible contingent events in the contract in advance. Previous research employs various measures to assess external uncertainty, including the Eurocurrency Country Risk Index (Delios and Beamish, 1999 ), Frost and Sullivan Country Risk Guide (Contractor and Kundu, 1998 ), industry growth (Kim and Hwang, 1992 ; Makino and Neupert, 2000 ; Luo, 2001 ), industry concentration (Kim and Hwang, 1992 ; Makino and Neupert, 2000 ), market size (Gomes-Casseres, 1989 ; Contractor and Kundu, 1998 ), perceived indicators of volatility and diversity in target markets (Klein et al., 1990 ; Luo, 2001 ), political and economic stability (Kim and Hwang, 1992 ; Luo, 2001 ; Brouthers, 2002 ; Brouthers and Brouthers, 2003 ; Brouthers et al., 2003 ) and perceived market potential (Brouthers, 2002 ). According to Williamson's model, uncertainty becomes problematic only when combined with asset specificity or higher switching costs. Uncertainty often leads to high levels of asset-specific integration (Leiblein and Miller, 2003 ). The prevalence of offshoring has increased due to better contractual regimes in host countries (Antràs and Helpman, 2006 ).The patent law of the host country is used as an indicator for measuring external uncertainty, based on the length of the product life cycle as a measure of asset specificity. This is one of the innovations of this paper. This paper examines the impact of product life cycle length (asset specificity) and patent law (uncertainty) on changes in the boundaries of the MNCs. Resource-based view, including knowledge-based theory and organizational capability theory, suggest that firms develop unique resources that they can exploit in foreign markets or use foreign markets as a source for acquiring or developing new resource-based advantages (Madhok, 1997; Tsang, 2000; Luo, 2002). Firms can gain foundational advantages by developing or acquiring a set of firm-specific resources and capabilities that are valuable, rare, not fully imitable, and for which there are no universally available substitutes (Barney, 1991). Researchers have attempted to identify, measure, and test various resource-based advantages. For instance, Ekeledo and Sivakumar (2004) used multiple perceptual scales to measure firm-specific resources, including proprietary technology, tacit knowledge, corporate reputation, and international business experience. Integrating transaction cost analysis and resource-based view in the analysis of MNCs’ boundaries refines and extends both approaches. The initial research argued that firm boundaries are driven by minimizing transaction costs, while later analyses proposed that firm boundaries are driven by developing and utilizing resources to maximize value creation and capture. To improve the discussion, we could consider (a) the link between asset specificity and uncertainty under transaction cost analysis, (b) the characteristics of relationships between headquarters and subsidiaries, as well as those between headquarters and unrelated-party outsourcing entities, from the perspective of the resource-based view, and (c) the differences in the institutional environments of home and host countries in the context of MNCs. The nature of economic systems is not independent of the environment, as they are based on certain social foundations that vary according to the local context (Meyer et al., 2011 ). This paper analyses the influence of product life cycle length and patent law on the boundaries of MNCs. The study is based on transaction cost analysis and the resource-based view. The theoretical model is extrapolated and the results are validated using a real dataset. It is found that changes in the length of the product life cycle and patent law can account for the changes in the boundaries of MNCs between 2002 and 2013. The article is structured as follows: section 2 presents the derivation of the theoretical model, section 3 provides the data and descriptive statistics, section 4 outlines the empirical model, section 5 presents the empirical results, section 6 conducts the robustness test, and the last section presents the conclusion. 2 Theory Model 2.1 Setup There are two countries in the world, South ( S ) and North ( N ) (Antras and Helpman, 2004; Bilir, 2014). According to transaction cost analysis and the resource base view, it is assumed that the R&D component of the MNCs are located in the home country, while the production component is established in the host country through both affiliates and unrelated-party firms. Time is continuous and products are continuously differentiated. Firms produce a variety of products continuously and sell them to consumers in the South and North countries, which are symmetric countries with a monopolistically competitive market of size 1. MNCs incur a one-time fixed cost that is specific to the product for its development and gain exclusive rights over the product until it is either imitated or eliminated. The rate of product obsolescence is determined by idiosyncratic technological developments and is exogenous to individual firms. Therefore, the length of the life cycle T varies from product to product, but the length of the life cycle of a similar product i is the same. Once a product type reaches T years of maturity, it becomes obsolete and loses economic value for consumers. The associated intellectual property rights also become obsolete. The rate of new product entry is constant and exogenous, equal to the rate of category obsolescence. This means that new products immediately replace obsolete ones, keeping the total number of products in each category constant. It is assumed that the total number of all products i is 1. It is assumed that the distribution of the life cycle length of the product maturity at any point in time is uniform with a density \({\psi }_{i}\left(t\right)=1/{T}_{i}\). 2.2 Production MNCs typically have their headquarters located in the North, where they conduct R&D for specific product technologies. However, they may transfer production to subsidiaries in the South at no cost. MNCs carry out R&D in their home country and produce in the host country through subsidiaries or unrelated-party companies.The firm earns flow-through profits from production in the North \({\pi }^{N}\) and the South \({\pi }^{S}\) as a monopolist. It is assumed that economic conditions favour production in the South \({\pi }^{S}>{\pi }^{N}\). These conditions may include differences in regulatory costs, trade costs, and factor prices between the South and North. The objective of profit maximisation, where each firm earns revenue \({r}^{c}=\rho {\pi }^{c}\) when producing in country c , \(\rho >1\) is the elasticity of demand faced by all firms. Therefore, firms earn higher revenues when they produce in Southern countries \({r}^{S}>{r}^{N}\). Imitation can undermine the monopoly power of MNCs. To produce a product, imitators require access to specific information (Arora, 1996; Cohen, Nelson and Walsh, 2000). While MNCs conducting R&D protect proprietary information, they must disclose the information necessary for production (both proprietary and implicit) to their employees. This paper assumes that when production is outsourced to a unrelated party overseas, imitators gain access to undisclosed information about a particular product at a reduced cost. Additionally, the cost of trade secrets obtained across borders is high, which economically constrains imitators to produce locally. When imitators enter a market, it can result in a loss of profits for the MNCs conducting the R&D; therefore, MNCs are cautious about their location. In the presence of imitators, MNCs conducting R&D will only receive a portion of the previously established per-period profits, which is dependent on the quality of local patent enforcement \({\lambda }_{c}\). With reference to the Bilir (2014) setting, \({\lambda }_{c}\) represents the probability or proportion of patents being enforced in country c at any given point in time. Assume that patents are fully protected in the North \({\lambda }_{N}=1\), but not in the South \(0<{\lambda }_{S}<1\). Imitation products only appear in the South where patents are not fully protected. It is important to note that imitators are a direct result of inadequate patent protection. 2.3 Imitation There are potential imitators in the South, but it is uncertain how long it will take for them to successfully imitate \(w=\left[0,\stackrel{-}{w}\right]\). The success rate follows a Poisson distribution and is constant, while w is uniformly distributed (Grossman and Helpman, 1991; Glass and Saggi, 2002; Bilir, 2014). Imitation is a low-cost option, and outsourcing production to unrelated-party overseas companies immediately increases the risk of imitation. 2.4 The Product Cycle MNCs choose locations with the aim of maximising profits, considering the actions of imitators in the southern region. In particular, MNCs relocate production to the South to achieve their profit goals and determine the optimal product maturity \({t}_{i}^{\ast }\in \left[0,{T}_{i}\right]\) for industry i to manufacture in the host country. $${E}_{w}\left[{\varPi }_{i}\left(t\right)\right]=2{\pi }^{N}t+2{\pi }^{S}{E}_{w}\left[\underset{}{\text{min}}\left\{{T}_{i}-t,w\right\}\right]+\left(1+{\lambda }_{S}\right){\pi }^{S}{E}_{w}\left[\underset{}{\text{max}}\left\{0,{T}_{i}-t-w\right\}\right]$$ 1 Optimizing over the initial offshoring maturity t , it is apparent that $${\tau }^{\ast }\left({\lambda }_{S}\right)\equiv {T}_{i}-{t}^{\ast }=\frac{{\pi }^{S}-{\pi }^{N}}{\left(1-{\lambda }_{S}\right)}2\stackrel{-}{w}$$ 2 depends on \({\lambda }_{S}\),innovators’ \({\pi }^{N}\) and \({\pi }^{S}\),and initators’ \(\stackrel{-}{w}\).Notice that firms manufacture in the South earlier in the product life cycle when Southern patents are better protected:\(\frac{\partial {\tau }^{\ast }\left({\lambda }_{S}\right)}{\partial {\lambda }_{S}}>0\). Proposition 1 When the lifecycle length of product i,, the product is manufactured in the South. When the lifecycle length of product i,, the product is initially manufactured in the North, it gradually approaches the phase-out time, at which point it migrates to the South until it is phased out. The initial offshore production time cut-off increases with the degree of patent protection in the South: . Proposition 1 states that product i is produced in the North at time and in the South at time. This means that the inter-firm trade ratio of products i in the South at any give can be measured as: $${S}_{i}\left({\lambda }_{S}\right)\equiv {\int }_{{t}_{i}^{\ast }\left({\lambda }_{S}\right)}^{{T}_{i}}{\psi }_{i}\left(t\right)dt=\frac{{T}_{i}-{t}_{i}^{\ast }\left({\lambda }_{S}\right)}{{T}_{i}}=\underset{}{\text{min}}\left\{1,\frac{{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{i}}\right\}$$ 3 \({T}_{i}\) exhibits a weakly decreasing trend, with longer life cycle products being manufactured more in the North than in the South. The production quantity of product i in the South decreases as the product life cycle lengthens: \(\partial {S}_{i}\left({\lambda }_{S}\right)/\partial {T}_{i}\le 0\). Figure 2 shows the inter-firm trade ratio of product i in the South \({S}_{i}\left({\lambda }_{S}\right)\) (vertical axis) plotted against its life-cycle length \({T}_{i}\) (horizontal axis) ranges between \({T}_{min}<{\tau }^{\ast }\left({\lambda }_{S}\right)<{T}_{max}\). Two different levels of patent protection in the South, \({\lambda }_{S}\) (solid lines) and \({\lambda }_{S}^{{\prime }}\) (dashed lines). The distribution of revenues earned in the South across products i is also determined by the initial offshoring maturity \({\tau }^{\ast }\left({\lambda }_{S}\right)\), $${R}_{i}\left({\lambda }_{S}\right)={\int }_{\underset{}{\text{max}}\left\{0,{T}_{i}-{\tau }^{\ast }\left({\lambda }_{S}\right)\right\}}^{{T}_{i}}\left(2{r}^{S}\left(1-p\left(t\right)\right)+\left(1+{\lambda }_{S}\right){r}^{S}p\left(t\right)\right){\psi }_{i}\left(t\right)dt$$ The given formula calculates the revenues earned in the South, where \({\psi }_{i}\left(t\right)=1/{T}_{i}\) is the density of product maturity and \(p\left(t\right)\) is the probability of a product with maturity t being imitated are the variables. It is important to note that a certain number of products are imitated at any given time, \(p\left(t\right)=\frac{t}{\stackrel{-}{w}}\). This means that the revenue of the product in the southern region is affected. $${R}_{i}\left({\lambda }_{S}\right)=2{r}^{S}\left(1-\frac{{T}_{i}}{2\stackrel{-}{w}}\right)+\left(1+{\lambda }_{S}\right){r}^{S}\frac{{T}_{i}}{2\stackrel{-}{w}}, {T}_{i}<{\tau }^{\ast }\left({\lambda }_{S}\right)$$ $${R}_{i}\left({\lambda }_{S}\right)=2{r}^{S}\left(\frac{{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{j}}-\frac{{{\tau }^{\ast }\left({\lambda }_{S}\right)}^{2}}{2\stackrel{-}{w}{T}_{j}}\right)+\left(1+{\lambda }_{S}\right){r}^{S}\frac{{T}_{i}}{2\stackrel{-}{w}}, {T}_{i}\ge {\tau }^{\ast }\left({\lambda }_{S}\right)$$ 4 2.5 Cross-Product Response to IPR Protection Suppose that the South enacts a policy change that increases the level of patent protection from \({\lambda }_{S}\) to \({\lambda }_{S}^{{\prime }}\), \({\lambda }_{S}^{{\prime }}>{\lambda }_{S}\). According to Eq. (2), this change would lead to firms offshoring production at an earlier stage of the product life cycle. Eq. (3) implies that the inter-industry trade ratio in the South is based on the difference in the degree of patent protection in the country \({\lambda }_{S}\), which is a segmented function based on \({T}_{i}\). \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)=0\), \({T}_{i}<{\tau }^{\ast }\left({\lambda }_{S}\right)\) \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)=\frac{{T}_{i}-{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{i}}\), \({\tau }^{\ast }\left({\lambda }_{S}\right)\le {T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\) \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)=\frac{{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)-{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{i}}\), \({T}_{i}>{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\) (5) The generalised marginal effect \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)\) is plotted in the middle section of Fig. 2. It represents a change in the inter-firm trade ratio of product i in the South immediately after the enhancement of patent protection. MNCs do not respond to enhanced patent protection if the life cycle of product i is shorter than the initial unrelated-party sourcing date, \({T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}\right)\). When the patent protection in the South is \({\lambda }_{S}\), the entire life cycle of product i is produced in the South, \({T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}\right)\); if the intensity of patent protection in the South is high, \({\lambda }_{S}^{{\prime }}\), product i continues to be produced there. However, for products with longer life cycles, \({T}_{i}>{\tau }^{\ast }\left({\lambda }_{S}\right)\), the MNCs outsource the marginal production chain to a unrelated party in the South for the remaining years before obsolescence, \({\tau }^{\ast }\left({\lambda }_{S}\right)\le {T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\). \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)\) is a non-monotonic function depends on \({T}_{i}\). The inter-firm trade ratio in the South increases non-monotonically, \({S}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{S}_{i}\left({\lambda }_{S}\right)\), with the degree of patent protection for product i after the patent reform from \({\lambda }_{S}\) to \({\lambda }_{S}^{{\prime }}\). The increase is zero for \({T}_{i}<{\tau }^{\ast }\left({\lambda }_{S}\right)\), then increases for \({\tau }^{\ast }\left({\lambda }_{S}\right)\le {T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\), and finally decreases for \({T}_{i}>{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\). The point of greatest impact is at \({T}_{i}={\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\). Revenues earned by MNCs are impacted by enhanced protection of intellectual property rights both because of newly shifted manufacturing and existing imitated varieties capture a larger share of Southern sales under the stronger patent regime. Based on equations (4) and (5), the change in product i revenues earned offshore following a Southern enhanced protection of intellectual property rights from \({\lambda }_{S}\) to \({\lambda }_{S}^{{\prime }}\) depends on \({T}_{i}\). The patent reform in South has impacted the revenues of MNCs. This is due to the shift of South production from subsidiaries to unrelated parties and the emergence of South imitations as unrelated-party outsourcing begins to take up a part of the MNCs' earnings. Equations (4) and (5) indicate that the change in revenues affected by offshore production depends on \({T}_{i}\), which is affected by the change in patent protection in South from enhancement from \({\lambda }_{S}\) to \({\lambda }_{S}^{{\prime }}\). \({R}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{R}_{i}\left({\lambda }_{S}\right)={r}^{S}\left({\lambda }_{S}^{{\prime }}-{\lambda }_{S}\right)\frac{{T}_{i}}{2\stackrel{-}{w}}\), \({T}_{i}<{\tau }^{\ast }\left({\lambda }_{S}\right)\) \({R}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{R}_{i}\left({\lambda }_{S}\right)={r}^{S}\left(2\frac{{T}_{j}-{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{j}}+\left({\lambda }_{S}^{{\prime }}-{\lambda }_{S}\right)\frac{{\left[{\tau }^{\ast }\left({\lambda }_{S}\right)\right]}^{2}}{2\stackrel{-}{m}{T}_{i}}\right)\), \({\tau }^{\ast }\left({\lambda }_{S}\right)\le {T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\) \({R}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{R}_{i}\left({\lambda }_{S}\right)={r}^{S}\left(2\frac{{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)-{\tau }^{\ast }\left({\lambda }_{S}\right)}{{T}_{j}}+\left({\lambda }_{S}^{{\prime }}-{\lambda }_{S}\right)\frac{{\left[{\tau }^{\ast }\left({\lambda }_{S}\right)\right]}^{2}}{2\stackrel{-}{m}{T}_{i}}\right)\), \({T}_{i}>{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\) (6) The function at the bottom of Fig. 2 is \({R}_{i}\left({\lambda }_{S}^{{\prime }}\right)-{R}_{i}\left({\lambda }_{S}\right)\) a non-monotonic function based on \({T}_{i}\) that increases for \({T}_{i}\le {\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\) and decreases for \({T}_{i}>{\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\), the point of greatest response to IPR protection reform at \({T}_{i}={\tau }^{\ast }\left({\lambda }_{S}^{{\prime }}\right)\). 3 Data and Descriptive Statistics 3.1 Product Life-Cycle Lengths To measure the length of a product's life cycle \({T}_{i}\) , it is to associate the product with proprietary information such as patents and implicit intellectual property rights that are necessary for production but lose their economic value when the product becomes obsolete (Bilir, 2014 ). The view implies that proprietary information must be separated across products, meaning that the information needed to create a new product must differ from that required for any previous product. Therefore, the main distinction between industries in the model is not the time lag between versions of a product that embody the same innovative idea, but rather the economic lifecycle of the innovative idea itself. This lifecycle may span consecutive versions of the product's lifecycle (Klepper, 1996 ). The length of a product's life cycle is determined by the economic durability of the embedded technology. This paper uses United States patent citation data from 1976 to 2006, which includes 6,832 products from 122 countries. The duration for which a patent is cited by subsequent patents is an indicator of the market longevity of the patented technology. A long average 'pre-citation lag', which is the time between the grant date of the cited patent and the subsequent citation, indicates that the technology has persistent relevance to future innovation. To construct the product life cycle length index \({\widehat{T}}_{i}\) , we used the methodology of Hall et al. ( 2001 ) and Bilir ( 2014 ) and mapped from SIC 3-digit code to NAICS 6-digit code. The product life-cycle length index is constructed without any restrictions on the patent categories in which patents are cited. This allows patented technologies to be relevant not only to future innovations in their own category but also in other patent categories. Figure 3 shows a bar chart of the Product Life Cycle Length Index, highlighting the differences in life cycle length among various products. Table 1 presents the product name, life cycle length, and capital intensity for the top five, median, and bottom five product life cycle lengths. Table 1 shows that products with shorter life cycles have higher capital intensity. This relationship is further supported by the scatter plot in Fig. 4 , which has a correlation coefficient of -0.072. Table 1 Product Life-cycle Lengths and Capital Intensity Name Rank SIC 3-Digit Code Product Life-cycle Lengths Capital Intensity Shortest product life cycle Electronics machinery 1 383 6.73 3.592 Watches, clocks, clockwork operated devices 2 387 7.37 5.691 Computer and office equipment 3 357 8.38 6.891 Agricultural chemicals 4 287 8.69 7.072 Electronic components and accessories 5 367 8.83 4.566 Intermediate-length product life cycles Miscellaneous industrial and commercial 19 359 9.68 2.275 Miscellaneous chemical products 20 289 9.73 3.775 Surgical, medical, dental instruments, and supplies 21 384 9.75 1.452 Farm and garden machinery and equipment 22 352 9.78 2.418 Household appliances 23 363 9.78 2.592 Longest product life cycles Fabricated structural metal products 33 344 10.25 1.182 Cutlery, handtools, and general hardware 34 342 10.41 2.787 Screw machine products, bolts, nuts, screws 35 345 10.42 1.718 Metal cans and shipping containers 36 341 10.63 3.320 Heating equipment, except electric 37 343 10.89 2.187 Notes: This table presents the top five, median, and bottom five product names, life cycle lengths, and capital intensities sorted by product life cycle length. Product life-cycle lengths were measured in years and calculated using patent citation data. 3.2 Intellectual Property Protection in Different Countries This paper utilises Park's (2008) indicator to measure the strength of IPR protection across different countries. The indicator, which is comprehensive and widely applicable, assesses IPR protection in five dimensions: coverage, membership of international patent agreements, provisions for loss of patent, enforcement mechanisms, and duration of protection. Each dimension is scored between 0 and 1 based on objective criteria to determine whether the current patent law meets specific standards. The Patent Protection Index is the sum of these five dimensions, ranging from 0 to 5. Higher values indicate stronger IPR protection. These indices are available at five-year intervals for 122 countries from 1980 to 2005. In this paper, the year of each benchmarking survey is matched to the closest available index year. 3.3 Inter-firm Trade Ratio This paper utilises US MNCs trade data from 2002–2013 for 118 countries import data for 208 products based on the NAICS 6-digit classification. Table 2 presents summary statistics for the aforementioned data. Table 2 Summary Statistics Variables Obs. Mean S. D. Min Max. IFR 229,089 0.194 0.309 0 1 T 229,089 9.523 0.725 6.681 13.500 IPR 229,089 3.447 0.835 0.200 4.800 Capital Intensity 229,089 3.172 2.636 0.989 28.929 GDP per capita 229,089 18697.02 17824.27 0 95012.67 4 Econometric Framework Based on Fig. 2 in the second part of the theory, the safeguarding of host country IPR protection through offshore production activities of MNEs is a non-monotonic function of the product life cycle's length. This paper uses inter-firm trade ratios to characterise the corporate boundaries of MNCs (Antràs, 2003 ; Antràs and Helpman, 2004; Antràs and Helpman, 2006 ; Nunn and Trefler, 2008 ). The baseline regression equation of this paper is based on the results of the theoretical derivation. $${IFR}_{cit}={\beta }_{0}+{\beta }_{1}\bullet {IPR}_{ct}\times {T}_{i}+{\beta }_{2}\bullet {IPR}_{ct}\times {T}_{i}^{2}+{\eta }_{ct}+{\eta }_{i}+{ϵ}_{cit}$$ 7 where \({IFR}_{cit}\) is the inter-firm trade ratio of U.S. MNCs in country c for product i in year t. \({IPR}_{ct}\) is an index of patent protection in country c in year t. \({T}_{i}\) denotes the life cycle length of product i . The main coefficients of interest in this paper are \({\beta }_{1}\) and \({\beta }_{2}\) , which shows the impact of different product life-cycle lengths and host country IPR protection on differences in MNCs' offshore production activities. In order to make the empirical model consistent with the theoretical model, the estimated coefficients of the empirical model must satisfy the following conditions: \({\beta }_{1}>0\) , \({\beta }_{2}<0\) , \({\beta }_{1}\bullet {T}_{i}+{\beta }_{2}\bullet {T}_{i}^{2}\ge 0\) . The country-level control variable \({\eta }_{ct}\) controls for GDP, Log GDPpc×T and \(log GDPpc\times {T}^{2}\) , while the product-level control variable \({\eta }_{i}\) controls for capital intensity, \(IPR\times Capital intensity\) and \(IPR\times {Capital intensity}^{2}\) . The error term includes any omitted factors that affect the offshore production patterns of MNCs. The results are clustered at the country level across all reports, which is robust due to the possibility of measurement error in the host country patent protection index. 5 Results 5.1 Baseline Results Table 3 presents the main regression results, which provide favourable support for the above theoretical results. Column 1 shows that stronger IPR protection leads to a higher rate of MNCs choosing unrelated-party outsourcing in the production chain in host countries. Column 2 shows that host countries with stronger IPR protection have a higher rate of choosing unrelated-party outsourcing for products with longer life cycles. In column 3, the empirical model includes the interaction between \({IPR}_{ct}\) and \({T}_{i}^{2}\) based on the results of the theoretical model. The empirical results show that the coefficient of IPR×T is 0.133 > 0, while the coefficient of \(IPR\times {T}^{2}\) is -0.129 < 0, consistent with the theoretical model. The impact of IPR protection in the host country follows a non-monotonic trend with respect to the length of the product life cycle. The effect is most pronounced in industries with moderately long product life cycles. Column 4 includes \(IPR\times Capital intensity\) and \(IPR\times {Capital intensity}^{2}\) in the model from column 3 to differentiate the impact of product life cycle length from that of product idiosyncrasies. Additionally, column 4 introduces Log GDPpc×T and \(log GDPpc\times {T}^{2}\) to the model from column 3 to better distinguish the effect of IPR protection from that of overall economic development. Column 6 includes all control variables. The empirical regression results are consistent with the theoretical notation, indicating that the addition of control variables has a minimal impact on the main coefficients of interest \({\beta }_{1}\) and \({\beta }_{2}\) in this paper. Table 3 Main Result Inter-firm Trade Ratio (1) (2) (3) (4) (5) (6) IPR 0.108*** (0.017) IPR×T -0.029 (0.021) 0.133*** (0.029) 0.133*** (0.029) 0.098*** (0.025) 0.102*** (0.028) \(IPR\times {T}^{2}\) -0.129*** (0.022) -0.129*** (0.022) -0.095*** (0.023) -0.099*** (0.023) \(IPR\times Capital intensity\) 0.000 (0.002) 0.001 (0.002) \(IPR\times {Capital intensity}^{2}\) -0.000 (0.000) -0.000 (0.000) GDPpc 0.028** (0.011) Log GDPpc×T 0.019* (0.011) 0.018 (0.011) \(log GDPpc\times {T}^{2}\) -0.001* (0.001) -0.001* (0.001) Industry FE Yes Yes Yes Yes Yes Yes Country-year FE No Yes Yes Yes Yes Yes Obs. 229,089 229,089 229,089 229,089 229,089 229,089 \(Pesudo {R}^{2}\) 0.204 0.332 0.333 0.333 0.333 0.333 Notes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level. 5.2 Flexible Estimation To evaluate the influence of IPR protection in the host country on inter-firm trade ratio, we estimate coefficients that vary flexibly over the product life cycle's length \({T}_{i}\) . Table 4 presents the estimates based on Eq. ( 8 ), where the product life cycle length is divided into quartiles ( \({Q}_{1}^{T}\) , \({Q}_{2}^{T}\) , \({Q}_{3}^{T}\) , \({Q}_{4}^{T}\) , \({Q}_{5}^{T}\) and \({Q}_{6}^{T}\) ). Dummy variables corresponding to the last five quintiles intersect with the degree of IPR in the host country, with interactions as shown in Eq. ( 8 ). $${{IF}R}_{{cit}}=\beta +\sum _{k=2}^{6}{\beta }_{k}\bullet {IPR}_{ct}\times {1}_{{T}_{i}\in {Q}_{k}^{T}}+{\eta }_{ct}+{\eta }_{i}+{ϵ}_{cit}$$ 8 so that \(\beta\) and fixed effects \({\eta }_{ct}\) capture the effect of IPR on short-life-cycle sectors in the bottom fifth of the \({T}_{i}\) distribution. An advantage of this approach is that the differential effect of IPR protection, as reflected by the coefficients \({\beta }_{2}\) , \({\beta }_{3}\) , \({\beta }_{4}\) , \({\beta }_{5}\) and \({\beta }_{6}\) , is unrestricted across fifths of the \({T}_{i}\) distribution. A consistent pattern emerges from the estimates in Table 4 : the fourth and fifth sextile coefficients tend to be negative and smaller than the second or third sextile coefficients. This pattern indicates that shrink in inter-firm trade ratio is concentrated within posterior- \({T}_{i}\) industries. This pattern provides additional evidence consistent with the non-monotonicity implications of the theory. Thus, the combination of \(\beta\) and fixed effects \({\eta }_{ct}\) explains that host country \({IPR}_{ct}\) impact on short life cycle lengths \({T}_{i}\) in the bottom quartile of the distribution. This approach allows for coefficients \({\beta }_{2}\) , \({\beta }_{3}\) , \({\beta }_{4}\) , \({\beta }_{5}\) and \({\beta }_{6}\) to reflect the differential impact of IPR protection in different quartiles of the product life cycle length \({T}_{i}\) distribution. The coefficients in Table 4 tend to be positive for the fourth and fifth quintiles. The data indicates that inter-firm trade has increased in the middle and late products of the life-cycle length quartiles. Additionally, the expansion of unrelated-party outsourcing by MNCs in offshore production segments has been concentrated in products with medium- to long-term life-cycle lengths. These findings provide further evidence consistent with the non-monotonicity of the results of the theoretical model. Table 4 Host-country IPR and Inter-firm Trade Ratio Flexible Estimation Inter-firm Trade Ratio (1) (2) (3) (4) \(IPR\times {T}_{2}\) −0.002 (0.005) −0.001 (0.004) −0.001 (0.004) −0.000 (0.004) \(IPR\times {T}_{3}\) −0.001 (0.004) −0.001 (0.004) −0.000 (0.004) 0.001 (0.004) \(IPR\times {T}_{4}\) 0.003 (0.005) 0.003 (0.005) 0.005 (0.006) 0.005 (0.006) \(IPR\times {T}_{5}\) 0.004 (0.005) 0.005 (0.005) 0.007 (0.006) 0.007 (0.005) \(IPR\times {T}_{6}\) −0.011* (0.006) −0.010** (0.005) −0.004* (0.006) −0.004 (0.005) \(IPR\times Capital intensity\) 0.002 (0.002) 0.002 (0.002) \(IPR\times {Capital intensity}^{2}\) −0.000** (0.000) −0.000** (0.000) Log GDPpc×T 0.018 (0.012) 0.018 (0.012) \(log GDPpc\times {T}^{2}\) −0.001* (0.001) −0.001* (0.001) Industry FE Yes Yes Yes Yes Country-year FE Yes Yes Yes Yes Obs. 229,089 229,089 229,089 229,089 \({R}^{2}\) 0.332 0.332 0.332 0.333 Notes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level. 6 Robustness Checks and Heterogeneity Analysis 6.1 Tobit Regression To ensure the robustness of the regression results, the econometric model was replaced with Tobit regressions based on theoretical model extrapolation. Table 5 reports the impact of host country IPR protection and product life-cycle length on inter-firm trade based on Tobit regressions. The results obtained through Tobit regressions are consistent with those obtained through OLS regression, indicating the robustness of the regression results. Table 5 Tobit Regression Inter-firm Trade Ratio (1) (2) (3) (4) (5) (6) IPR 0.140*** (0.036) IPR×T -0.013 (0.013) 0.111** (0.044) 0.204*** (0.062) 0.080 (0.054) 0.154** (0.069) \(IPR\times {T}^{2}\) -0.108** (0.045) -0.178*** (0.054) -0.080 (0.056) -0.136** (0.064) \(IPR\times Capital intensity\) -0.010* (0.005) -0.007 (0.005) \(IPR\times {Capital intensity}^{2}\) 0.000 (0.000) 0.000 (0.000) GDPpc 0.000** (0.000) Log GDPpc×T 0.091** (0.038) 0.077** (0.039) \(log GDPpc\times {T}^{2}\) -0.004** (0.002) -0.004** (0.002) Industry FE Yes Yes Yes Yes Yes Yes Country-year FE No Yes Yes Yes Yes Yes Obs. 136,918 139,596 139,596 139,596 136,918 136,918 \({R}^{2}\) 0.110 0.230 0.230 0.231 0.231 0.231 Notes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level. 6.2 Heterogeneity Analysis Table 6 presents estimates based on whether the host country's IPR protection is above or below its mean (3.447). The results align with expectations, indicating that the IPR protection sensitivity mechanism is more effective in countries with high IP protection. Columns 1 to 5 pertain to the high IPR protection sample. The regression results indicate significantly positive coefficients for IPR×T and significantly negative coefficients for \(IPR\times {T}^{2}\) , which are consistent with the main regression results. However, in the low IPR protection sample, the direction of the coefficients of the regression results is not significant, although it is consistent with the main regression results. The data suggests that the mechanism for protecting intellectual property rights is more effective in countries with stronger IPR protection. Table 7 distinguishes between short, medium, and long product life cycle lengths based on the trichotomy of the product life cycle length. The results indicate that inter-firm trade ratio is more sensitive in samples with longer product life cycles. Specifically, the coefficients of IPR×T are significantly positive and those of \(IPR\times {T}^{2}\) are significantly negative for the sample with longer product life cycles in columns 7 to 10. This is consistent with the results of the main regression. The study shows that long life-cycle products tend to have a higher rate of unrelated-party outsourcing in the host country when they are far from the phase-out deadline. The rate of outsourcing decreases after reaching a peak and gradually approaches the phase-out date. However, for short and medium product life cycles, the coefficients show the opposite sign to that of long product life cycles and are not significant. The reason for the opposite sign may be that the risk of imitation for products with shorter and medium life cycles is relatively lower than that of products with longer life cycles. As a result, products with shorter and medium life cycles tend to outsource to unrelated parties at the initial stage, which is in line with the expected theoretical results. The results indicate that the rate of unrelated-party outsourcing in the host country is explained by both host country IPR protection and product life-cycle length. The relationship between these factors is non-linear, and the rate of host country unrelated-party outsourcing is more sensitive for products with long life-cycle lengths. Table 6 Heterogeneity of IPR High Patent Protection Low Patent Protection (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) IPR×T −0.917** (0.079) 0.916 (0.593) 1.377** (0.599) 1.202* (0.670) 1.659** (0.652) −0.021 (0.041) 0.625 (0.387) 0.525 (0.400) 0.673* (0.397) 0.565 (0.415) \(IPR\times {T}^{2}\) −0.547* (0.280) −0.722** (0.280) −0.657** (0.317) −0.831*** (0.311) −0.321* (0.181) −0.285 (0.185) −0.335* (0.184) −0.296 (0.191) \(IPR\times Capital intensity\) 0.016** (0.008) 0.016* (0.008) −0.002 (0.002) −0.002 (0.002) \(IPR\times {Capital intensity}^{2}\) −0.001** (0.000) −0.001** (0.000) −0.000 (0.000) −0.000 (0.000) Log GDPpc×T −0.015 (0.010) −0.015 (0.010) −0.003 (0.008) −0.002 (0.008) \(log GDPpc\times {T}^{2}\) 0.001 (0.000) 0.001 (0.000) 0.000 (0.000) 0.000 (0.000) Industry FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Country-year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Obs. 113,179 113,179 113,179 113,179 113,179 115,910 115,910 115,910 115,910 115,910 \({R}^{2}\) 0.272 0.272 0.272 0.272 0.272 0.262 0.262 0.262 0.262 0.262 Notes : Standard errors in brackets clustered at country level.***Significant at the 1 percent level; **Significant at the 5 percent level; *Significant at the 10 percent level. Table 7 Heterogeneity in Product Life Cycle Length Short-length Product Life Cycle Intermediate-length Product Life Cycle Long-length Product Life Cycle (1) (2) (3) (4) (5) (6) (7) (8) (9) IPR×T −0.081 (0.060) −0.083 (0.073) −0.154* (0.085) −0.240 (0.227) −0.191 (0.224) −0.069 (0.248) 0.222*** (0.033) 0.212*** (0.035) 0.186*** (0.037) \(IPR\times {T}^{2}\) 0.088 (0.067) 0.093 (0.076) 0.173* (0.089) 0.250 (0.238) 0.174 (0.227) 0.047 (0.257) −0.215*** (0.033) −0.209*** (0.032) −0.184*** (0.033) \(IPR\times Capital intensity\) 0.000 (0.003) 0.000 (0.003) 0.013 (0.011) 0.012 (0.011) 0.003 (0.006) 0.003 (0.006) \(IPR\times {Capital intensity}^{2}\) −0.000 (0.000) −0.000 (0.000) −0.001 (0.002) −0.001 (0.002) −0.000 (0.001) −0.000 (0.001) Log GDPpc×T 0.019 (0.035) −3.799 (1.783) 0.009 (0.043) \(log GDPpc\times {T}^{2}\) −0.001 (0.002) 0.200 (0.093) −0.001 (0.002) Industry FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Country-year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Obs. 76,363 76,363 76,363 76,363 76,363 76,363 76,363 76,363 76,363 \({R}^{2}\) 0.322 0.323 0.323 0.363 0.363 0.363 0.343 0.343 0.343 Notes : Standard errors in brackets clustered at country level.***Significant at the 1 percent level; **Significant at the 5 percent level; *Significant at the 10 percent level. 7 Conclusions This paper explores the sensitivity of MNCs to host country IPR protection regimes from both theoretical and empirical perspectives. The firm's global production location decision model applies two dimensions, namely product life cycle length and the degree of patent protection in the host country, to explain MNCs' inter-firm trade. The panel data of import trade for 208 types of products in 18 countries by U.S. MNCs from 2002 to 2013 strongly support the empirical results. The rate of unrelated-party outsourcing by MNCs in host countries, as a measure of changes in MNCs' corporate boundaries, can be explained by exploiting the interaction between patent law and product life cycle length. The research indicates that variations in the duration of the life cycle of products play a significant role in determining the sensitivity of MNCs to IPR protection in host countries. Additionally, it establishes a causal link between IPR protection and inter-firm trade of MNCs. The paper's heterogeneity analyses demonstrate that the sensitivity of the IPR protection mechanism is more effective in countries with a high degree of IPR protection. Additionally, the sensitivity to IPR protection in the host country is concentrated in products with a longer life cycle. The results derived from the theoretical model are consistent with reality. Finally, this paper's theoretical and empirical results support the notion that the length of a product's life cycle determines the degree of dependence of MNCs on IPR protection in host countries. It is crucial to note that the sophistication of IPR protection in host countries is particularly important for products with longer life cycles from a policy perspective. References Antràs, P. (2003). Firms, contracts, and trade structure. The Quarterly Journal of Economics , 118 (4), 1375–1418. Antras, P., & Helpman, E. (2004). Global sourcing. Journal of political Economy , 112 (3), 552–580. Antràs, P., & Helpman, E. (2006). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3877554","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269729167,"identity":"8636ca70-506e-4fa7-9441-0353c416860b","order_by":0,"name":"Yiming Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYDCCAwxsYJqNgbGBgaFCQk6eRC1nLIwNG4jVAgaMbRWJQBH8gO/28WcPfu6oTewTO9z28Os8iQTGBuaHj27g0SJ5LiHdsPfM8cQ26cR2Y9ltEnnsDGzGxjl4tBicYTgmwdt2DKSlTVpym0QxYwMPmzR+LYxtkn/hWuZIJDYcIKiFmU2at60GrEXyYwMRWiTPsLFJy7YdMAbbAnSksWEzAb/wnWF/Jvm2rU52/uz0Z5I/aurk5NmbHz7GpwUKDjs2AElmHhCbmbByEKizB5GMP4hTPQpGwSgYBSMMAAA0F0y7fDdH7QAAAABJRU5ErkJggg==","orcid":"","institution":"Southwest University of Finance and Economics: Southwestern University of Finance and Economics","correspondingAuthor":true,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Zhang","suffix":""},{"id":269729168,"identity":"d598a878-b415-4181-bb5b-ccfcb850483a","order_by":1,"name":"Zuoliang Ye","email":"","orcid":"","institution":"Southwest University of Finance and Economics: Southwestern University of Finance and Economics","correspondingAuthor":false,"prefix":"","firstName":"Zuoliang","middleName":"","lastName":"Ye","suffix":""},{"id":269729169,"identity":"62b9acbe-8ad1-4ef6-b599-485b30cef19e","order_by":2,"name":"Yunong Li","email":"","orcid":"","institution":"Southwest University of Finance and Economics: Southwestern University of Finance and Economics","correspondingAuthor":false,"prefix":"","firstName":"Yunong","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-01-19 03:57:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3877554/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3877554/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50424823,"identity":"181a179f-3fea-44ec-a757-d992044a7850","added_by":"auto","created_at":"2024-01-31 10:27:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17378,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLevels of Analysis in the Study of the Boundaries of the MNCs\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3877554/v1/3b4f397a46642d44866c7f40.png"},{"id":50424822,"identity":"c42d53dc-b92e-46db-b304-3034d0bf5560","added_by":"auto","created_at":"2024-01-31 10:27:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":160100,"visible":true,"origin":"","legend":"\u003cp\u003eProduct Lifecyele Lengths and Inter Firm Trade Ratio in the South\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3877554/v1/a175454e3e43ea766791892b.png"},{"id":50424820,"identity":"2d380a2c-969e-4366-b1e4-4c7971e0f663","added_by":"auto","created_at":"2024-01-31 10:27:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":11911,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProduct Life-cycle Lengths\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes:\u003c/em\u003e The bar chart illustrates the length of the product life-cycle for each of the 37 SIC 3-digit codes, measured in years and calculated using patent citation data.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3877554/v1/5613369122b9614bbabd0358.png"},{"id":50424821,"identity":"6e90e8cb-e1a3-4d95-b215-8333b7e5121d","added_by":"auto","created_at":"2024-01-31 10:27:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":18865,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProduct life-cycle lengths versus capital intensity across industries\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNotes:\u003c/em\u003e The scatterplot illustrates the correlation between the length of a product's life cycle and its capital intensity. The former is measured in years and determined using patent citation data.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3877554/v1/93eb948a2a1ff7b859cbe4fc.png"},{"id":55693718,"identity":"5b6b1be9-cb95-429f-b0e9-fd82b0c3186e","added_by":"auto","created_at":"2024-05-02 00:32:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1974312,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3877554/v1/afbf5d26-39df-4d18-b102-55f4d19b90e4.pdf"}],"financialInterests":"","formattedTitle":"Intellectual Property Protection, Product Life-cycle Lengths, and the Boundaries of Multinational Corporations","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe establishment and management of boundaries for multinational corporations (MNCs), as significant players in global commerce, have far-reaching implications for the global economic system. Deciding how to set the boundaries of MNCs is a crucial decision for operators in the international trading system. Economists and management scientists have extensively researched the factors that determine the boundaries of MNCs. Most explanations are based on transaction cost analysis or resource-based view. However, these two explanations are driven by different logics: cost minimisation and revenue maximisation, respectively (Cuervo-Cazurra et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This paper integrates transaction cost analysis and the resource base view to explain how intellectual property rights (IPR) protection and product life-cycle lengths affect the boundaries of MNCs. The model setup and derivation are presented based on a summary of existing literature. MNCs are significant players in US trade. The study uses US MNCs' trade data to validate the theory that U.S. overseas market penetration and sourcing are highly selective, and the main types of import sourcing (related-party and unrelated-party trade) vary by market (Co, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The paper examines the inter-firm trade ratio as a measure of the propensity of MNCs to cross corporate borders.\u003c/p\u003e \u003cp\u003eWhen reviewing theories on the study of firm boundaries, the most commonly used are transaction cost analysis and the resource-based view (Brouthers and Hennart, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These two different lines of thought have sparked a debate in academia as to whether the main driver behind a firm's competitive advantage is the minimization of transaction costs or the exploitation of resources to maximize revenues. The debate on the study of firm boundaries continues to pit cost minimization against revenue maximization. Several scholars are currently working on integrating transaction cost analysis and resource-based concepts (Silverman, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Foss and Foss, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Cuervo-Cazurra et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The challenge of integration arises from the assumptions made. The transaction cost analysis assumes that firms have developed their own sources of advantage and therefore need to focus on minimizing operating costs. On the other hand, the resource-based view assumes that the transaction problem can be solved and focuses on ensuring that advantages and revenues are maximized. This paper aims to integrate transaction cost analysis and the resource-based view to construct a theoretical model for MNCs\u0026rsquo; boundary choice.\u003c/p\u003e \u003cp\u003eTransaction cost analysis is a widely used theory in the study of international trade patterns. The transaction cost analysis framework assumes that decision making is influenced by three factors: asset specificity, uncertainty, and frequency (Williamson, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Most of these studies use asset specificity as the central explanatory variable. Some studies based on transaction cost analysis have found that high asset specificity is associated with high control patterns (Gatignon and Anderson, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Erramilli and Rao, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hennart and Larimo, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Makino and Neupert, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Brouthers and Brouthers, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Brouthers et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Integration is chosen for knowledge assets when asset specificity is high (Brouthers and Hennart, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, it has been found that the opposite conclusion is true in other studies (Delios and Beamish, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Palenzuela and Bobilo, 1999; Grossman and Helpman, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Some studies suggest that there is no significant relationship between asset specificity and the choice of international trade patterns (Hennart, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Kim and Hwang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Taylor et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The firm's R\u0026amp;D or advertising intensity (the sum of R\u0026amp;D and advertising expenditures divided by total sales) is a common measure of asset-specificity. Other studies have used perceived measures of asset-specific investments, including physical (service) asset specificity (Joskow, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Klein and Roth, 1990; Erramilli and Rao, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Klein et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Brouthers and Brouthers, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Brouthers et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e;Wang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), technology asset specificity (Taylor et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Palenzuela and Bobilom, 1999), human asset specificity (Dyer, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Handfield and Bechtel, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Brouthers and Brouthers, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Brouthers et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Shakir and Ahmed, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), site asset specificity (Handfield and Bechtel, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Williamson, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Parker et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and specialised asset specificity (Brouthers and Brouthers, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Brouthers et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). One innovation of this paper is the use of the product life cycle length as a measure of asset specificity.\u003c/p\u003e \u003cp\u003eThe second factor is uncertainty, which comprises of internal behaviour and external market idiosyncrasies. Internal uncertainty makes it difficult to verify performance ex post, while external uncertainty makes it difficult to specify all possible contingent events in the contract in advance. Previous research employs various measures to assess external uncertainty, including the Eurocurrency Country Risk Index (Delios and Beamish, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), Frost and Sullivan Country Risk Guide (Contractor and Kundu, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), industry growth (Kim and Hwang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Makino and Neupert, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Luo, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), industry concentration (Kim and Hwang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Makino and Neupert, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), market size (Gomes-Casseres, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Contractor and Kundu, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), perceived indicators of volatility and diversity in target markets (Klein et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Luo, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), political and economic stability (Kim and Hwang, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Luo, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Brouthers, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Brouthers and Brouthers, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Brouthers et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and perceived market potential (Brouthers, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). According to Williamson's model, uncertainty becomes problematic only when combined with asset specificity or higher switching costs. Uncertainty often leads to high levels of asset-specific integration (Leiblein and Miller, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The prevalence of offshoring has increased due to better contractual regimes in host countries (Antr\u0026agrave;s and Helpman, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).The patent law of the host country is used as an indicator for measuring external uncertainty, based on the length of the product life cycle as a measure of asset specificity. This is one of the innovations of this paper. This paper examines the impact of product life cycle length (asset specificity) and patent law (uncertainty) on changes in the boundaries of the MNCs.\u003c/p\u003e \u003cp\u003eResource-based view, including knowledge-based theory and organizational capability theory, suggest that firms develop unique resources that they can exploit in foreign markets or use foreign markets as a source for acquiring or developing new resource-based advantages (Madhok, 1997; Tsang, 2000; Luo, 2002). Firms can gain foundational advantages by developing or acquiring a set of firm-specific resources and capabilities that are valuable, rare, not fully imitable, and for which there are no universally available substitutes (Barney, 1991). Researchers have attempted to identify, measure, and test various resource-based advantages. For instance, Ekeledo and Sivakumar (2004) used multiple perceptual scales to measure firm-specific resources, including proprietary technology, tacit knowledge, corporate reputation, and international business experience.\u003c/p\u003e \u003cp\u003eIntegrating transaction cost analysis and resource-based view in the analysis of MNCs\u0026rsquo; boundaries refines and extends both approaches. The initial research argued that firm boundaries are driven by minimizing transaction costs, while later analyses proposed that firm boundaries are driven by developing and utilizing resources to maximize value creation and capture. To improve the discussion, we could consider (a) the link between asset specificity and uncertainty under transaction cost analysis, (b) the characteristics of relationships between headquarters and subsidiaries, as well as those between headquarters and unrelated-party outsourcing entities, from the perspective of the resource-based view, and (c) the differences in the institutional environments of home and host countries in the context of MNCs. The nature of economic systems is not independent of the environment, as they are based on certain social foundations that vary according to the local context (Meyer et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis paper analyses the influence of product life cycle length and patent law on the boundaries of MNCs. The study is based on transaction cost analysis and the resource-based view. The theoretical model is extrapolated and the results are validated using a real dataset. It is found that changes in the length of the product life cycle and patent law can account for the changes in the boundaries of MNCs between 2002 and 2013.\u003c/p\u003e \u003cp\u003eThe article is structured as follows: section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the derivation of the theoretical model, section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides the data and descriptive statistics, section \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e4\u003c/span\u003e outlines the empirical model, section \u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the empirical results, section \u003cspan refid=\"Sec16\" class=\"InternalRef\"\u003e6\u003c/span\u003e conducts the robustness test, and the last section presents the conclusion.\u003c/p\u003e"},{"header":"2 Theory Model","content":"\u003cdiv\u003e\n\u003ch2\u003e2.1 Setup\u003c/h2\u003e\n\u003cp\u003eThere are two countries in the world, South (\u003cem\u003eS\u003c/em\u003e) and North (\u003cem\u003eN\u003c/em\u003e) (Antras and Helpman, 2004; Bilir, 2014). According to transaction cost analysis and the resource base view, it is assumed that the R\u0026amp;D component of the MNCs are located in the home country, while the production component is established in the host country through both affiliates and unrelated-party firms. Time is continuous and products are continuously differentiated. Firms produce a variety of products continuously and sell them to consumers in the South and North countries, which are symmetric countries with a monopolistically competitive market of size 1. MNCs incur a one-time fixed cost that is specific to the product for its development and gain exclusive rights over the product until it is either imitated or eliminated. The rate of product obsolescence is determined by idiosyncratic technological developments and is exogenous to individual firms. Therefore, the length of the life cycle \u003cem\u003eT\u003c/em\u003e varies from product to product, but the length of the life cycle of a similar product i is the same. Once a product type reaches \u003cem\u003eT\u003c/em\u003e years of maturity, it becomes obsolete and loses economic value for consumers. The associated intellectual property rights also become obsolete.\u003c/p\u003e\n\u003cp\u003eThe rate of new product entry is constant and exogenous, equal to the rate of category obsolescence. This means that new products immediately replace obsolete ones, keeping the total number of products in each category constant. It is assumed that the total number of all products \u003cem\u003ei\u003c/em\u003e is 1. It is assumed that the distribution of the life cycle length of the product maturity at any point in time is uniform with a density \\({\\psi }_{i}\\left(t\\right)=1/{T}_{i}\\).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.2 Production\u003c/h2\u003e\n\u003cp\u003eMNCs typically have their headquarters located in the North, where they conduct R\u0026amp;D for specific product technologies. However, they may transfer production to subsidiaries in the South at no cost. MNCs carry out R\u0026amp;D in their home country and produce in the host country through subsidiaries or unrelated-party companies.The firm earns flow-through profits from production in the North \\({\\pi }^{N}\\) and the South \\({\\pi }^{S}\\) as a monopolist. It is assumed that economic conditions favour production in the South \\({\\pi }^{S}\u0026gt;{\\pi }^{N}\\). These conditions may include differences in regulatory costs, trade costs, and factor prices between the South and North. The objective of profit maximisation, where each firm earns revenue \\({r}^{c}=\\rho {\\pi }^{c}\\) when producing in country \u003cem\u003ec\u003c/em\u003e, \\(\\rho \u0026gt;1\\) is the elasticity of demand faced by all firms. Therefore, firms earn higher revenues when they produce in Southern countries \\({r}^{S}\u0026gt;{r}^{N}\\).\u003c/p\u003e\n\u003cp\u003eImitation can undermine the monopoly power of MNCs. To produce a product, imitators require access to specific information (Arora, 1996; Cohen, Nelson and Walsh, 2000). While MNCs conducting R\u0026amp;D protect proprietary information, they must disclose the information necessary for production (both proprietary and implicit) to their employees. This paper assumes that when production is outsourced to a unrelated party overseas, imitators gain access to undisclosed information about a particular product at a reduced cost. Additionally, the cost of trade secrets obtained across borders is high, which economically constrains imitators to produce locally.\u003c/p\u003e\n\u003cp\u003eWhen imitators enter a market, it can result in a loss of profits for the MNCs conducting the R\u0026amp;D; therefore, MNCs are cautious about their location. In the presence of imitators, MNCs conducting R\u0026amp;D will only receive a portion of the previously established per-period profits, which is dependent on the quality of local patent enforcement \\({\\lambda }_{c}\\). With reference to the Bilir (2014) setting, \\({\\lambda }_{c}\\) represents the probability or proportion of patents being enforced in country \u003cem\u003ec\u003c/em\u003e at any given point in time. Assume that patents are fully protected in the North \\({\\lambda }_{N}=1\\), but not in the South \\(0\u0026lt;{\\lambda }_{S}\u0026lt;1\\). Imitation products only appear in the South where patents are not fully protected. It is important to note that imitators are a direct result of inadequate patent protection.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.3 Imitation\u003c/h2\u003e\n\u003cp\u003eThere are potential imitators in the South, but it is uncertain how long it will take for them to successfully imitate \\(w=\\left[0,\\stackrel{-}{w}\\right]\\). The success rate follows a Poisson distribution and is constant, while \u003cem\u003ew\u003c/em\u003e is uniformly distributed (Grossman and Helpman, 1991; Glass and Saggi, 2002; Bilir, 2014). Imitation is a low-cost option, and outsourcing production to unrelated-party overseas companies immediately increases the risk of imitation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.4 The Product Cycle\u003c/h2\u003e\n\u003cp\u003eMNCs choose locations with the aim of maximising profits, considering the actions of imitators in the southern region. In particular, MNCs relocate production to the South to achieve their profit goals and determine the optimal product maturity \\({t}_{i}^{\\ast }\\in \\left[0,{T}_{i}\\right]\\) for industry \u003cem\u003ei\u003c/em\u003e to manufacture in the host country.\u003c/p\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${E}_{w}\\left[{\\varPi }_{i}\\left(t\\right)\\right]=2{\\pi }^{N}t+2{\\pi }^{S}{E}_{w}\\left[\\underset{}{\\text{min}}\\left\\{{T}_{i}-t,w\\right\\}\\right]+\\left(1+{\\lambda }_{S}\\right){\\pi }^{S}{E}_{w}\\left[\\underset{}{\\text{max}}\\left\\{0,{T}_{i}-t-w\\right\\}\\right]$$\u003c/div\u003e\n\u003cdiv\u003e1\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eOptimizing over the initial offshoring maturity \u003cem\u003et\u003c/em\u003e, it is apparent that\u003c/p\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\equiv {T}_{i}-{t}^{\\ast }=\\frac{{\\pi }^{S}-{\\pi }^{N}}{\\left(1-{\\lambda }_{S}\\right)}2\\stackrel{-}{w}$$\u003c/div\u003e\n\u003cdiv\u003e2\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003edepends on \\({\\lambda }_{S}\\),innovators\u0026rsquo; \\({\\pi }^{N}\\) and \\({\\pi }^{S}\\),and initators\u0026rsquo; \\(\\stackrel{-}{w}\\).Notice that firms manufacture in the South earlier in the product life cycle when Southern patents are better protected:\\(\\frac{\\partial {\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{\\partial {\\lambda }_{S}}\u0026gt;0\\).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProposition 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWhen the lifecycle length of product i,, the product is manufactured in the South. When the lifecycle length of product i,, the product is initially manufactured in the North, it gradually approaches the phase-out time, at which point it migrates to the South until it is phased out. The initial offshore production time cut-off increases with the degree of patent protection in the South: .\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProposition 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003estates that product \u003cem\u003ei\u003c/em\u003e is produced in the North at time and in the South at time. This means that the inter-firm trade ratio of products \u003cem\u003ei\u003c/em\u003e in the South at any give can be measured as:\u003c/p\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${S}_{i}\\left({\\lambda }_{S}\\right)\\equiv {\\int }_{{t}_{i}^{\\ast }\\left({\\lambda }_{S}\\right)}^{{T}_{i}}{\\psi }_{i}\\left(t\\right)dt=\\frac{{T}_{i}-{t}_{i}^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{i}}=\\underset{}{\\text{min}}\\left\\{1,\\frac{{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{i}}\\right\\}$$\u003c/div\u003e\n\u003cdiv\u003e3\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\\({T}_{i}\\) exhibits a weakly decreasing trend, with longer life cycle products being manufactured more in the North than in the South. The production quantity of product \u003cem\u003ei\u003c/em\u003e in the South decreases as the product life cycle lengthens: \\(\\partial {S}_{i}\\left({\\lambda }_{S}\\right)/\\partial {T}_{i}\\le 0\\).\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the inter-firm trade ratio of product \u003cem\u003ei\u003c/em\u003e in the South \\({S}_{i}\\left({\\lambda }_{S}\\right)\\) (vertical axis) plotted against its life-cycle length \\({T}_{i}\\) (horizontal axis) ranges between \\({T}_{min}\u0026lt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\u0026lt;{T}_{max}\\). Two different levels of patent protection in the South, \\({\\lambda }_{S}\\) (solid lines) and \\({\\lambda }_{S}^{{\\prime }}\\) (dashed lines).\u003c/p\u003e\n\u003cp\u003eThe distribution of revenues earned in the South across products \u003cem\u003ei\u003c/em\u003e is also determined by the initial offshoring maturity \\({\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\),\u003c/p\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${R}_{i}\\left({\\lambda }_{S}\\right)={\\int }_{\\underset{}{\\text{max}}\\left\\{0,{T}_{i}-{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\right\\}}^{{T}_{i}}\\left(2{r}^{S}\\left(1-p\\left(t\\right)\\right)+\\left(1+{\\lambda }_{S}\\right){r}^{S}p\\left(t\\right)\\right){\\psi }_{i}\\left(t\\right)dt$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eThe given formula calculates the revenues earned in the South, where \\({\\psi }_{i}\\left(t\\right)=1/{T}_{i}\\) is the density of product maturity and \\(p\\left(t\\right)\\) is the probability of a product with maturity \u003cem\u003et\u003c/em\u003e being imitated are the variables. It is important to note that a certain number of products are imitated at any given time, \\(p\\left(t\\right)=\\frac{t}{\\stackrel{-}{w}}\\). This means that the revenue of the product in the southern region is affected.\u003c/p\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${R}_{i}\\left({\\lambda }_{S}\\right)=2{r}^{S}\\left(1-\\frac{{T}_{i}}{2\\stackrel{-}{w}}\\right)+\\left(1+{\\lambda }_{S}\\right){r}^{S}\\frac{{T}_{i}}{2\\stackrel{-}{w}}, {T}_{i}\u0026lt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e$${R}_{i}\\left({\\lambda }_{S}\\right)=2{r}^{S}\\left(\\frac{{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{j}}-\\frac{{{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}^{2}}{2\\stackrel{-}{w}{T}_{j}}\\right)+\\left(1+{\\lambda }_{S}\\right){r}^{S}\\frac{{T}_{i}}{2\\stackrel{-}{w}}, {T}_{i}\\ge {\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)$$\u003c/div\u003e\n\u003cdiv\u003e4\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003ch2\u003e2.5 Cross-Product Response to IPR Protection\u003c/h2\u003e\n\u003cp\u003eSuppose that the South enacts a policy change that increases the level of patent protection from \\({\\lambda }_{S}\\) to \\({\\lambda }_{S}^{{\\prime }}\\), \\({\\lambda }_{S}^{{\\prime }}\u0026gt;{\\lambda }_{S}\\). According to Eq.\u0026nbsp;(2), this change would lead to firms offshoring production at an earlier stage of the product life cycle. Eq.\u0026nbsp;(3) implies that the inter-industry trade ratio in the South is based on the difference in the degree of patent protection in the country \\({\\lambda }_{S}\\), which is a segmented function based on \\({T}_{i}\\).\u003c/p\u003e\n\u003cp\u003e\\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)=0\\), \\({T}_{i}\u0026lt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\)\u003c/p\u003e\n\u003cp\u003e\\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)=\\frac{{T}_{i}-{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{i}}\\), \\({\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\le {T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\)\u003c/p\u003e\n\u003cp\u003e\\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)=\\frac{{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)-{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{i}}\\), \\({T}_{i}\u0026gt;{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\) (5)\u003c/p\u003e\n\u003cp\u003eThe generalised marginal effect \\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)\\) is plotted in the middle section of Fig.\u0026nbsp;2. It represents a change in the inter-firm trade ratio of product \u003cem\u003ei\u003c/em\u003e in the South immediately after the enhancement of patent protection. MNCs do not respond to enhanced patent protection if the life cycle of product \u003cem\u003ei\u003c/em\u003e is shorter than the initial unrelated-party sourcing date, \\({T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\). When the patent protection in the South is \\({\\lambda }_{S}\\), the entire life cycle of product \u003cem\u003ei\u003c/em\u003e is produced in the South, \\({T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\); if the intensity of patent protection in the South is high, \\({\\lambda }_{S}^{{\\prime }}\\), product \u003cem\u003ei\u003c/em\u003e continues to be produced there. However, for products with longer life cycles, \\({T}_{i}\u0026gt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\), the MNCs outsource the marginal production chain to a unrelated party in the South for the remaining years before obsolescence, \\({\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\le {T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\). \\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)\\) is a non-monotonic function depends on \\({T}_{i}\\). The inter-firm trade ratio in the South increases non-monotonically, \\({S}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{S}_{i}\\left({\\lambda }_{S}\\right)\\), with the degree of patent protection for product \u003cem\u003ei\u003c/em\u003e after the patent reform from \\({\\lambda }_{S}\\) to \\({\\lambda }_{S}^{{\\prime }}\\). The increase is zero for \\({T}_{i}\u0026lt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\), then increases for \\({\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\le {T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\), and finally decreases for \\({T}_{i}\u0026gt;{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\). The point of greatest impact is at \\({T}_{i}={\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\).\u003c/p\u003e\n\u003cp\u003eRevenues earned by MNCs are impacted by enhanced protection of intellectual property rights both because of newly shifted manufacturing and existing imitated varieties capture a larger share of Southern sales under the stronger patent regime. Based on equations (4) and (5), the change in product \u003cem\u003ei\u003c/em\u003e revenues earned offshore following a Southern enhanced protection of intellectual property rights from \\({\\lambda }_{S}\\) to \\({\\lambda }_{S}^{{\\prime }}\\) depends on \\({T}_{i}\\).\u003c/p\u003e\n\u003cp\u003eThe patent reform in South has impacted the revenues of MNCs. This is due to the shift of South production from subsidiaries to unrelated parties and the emergence of South imitations as unrelated-party outsourcing begins to take up a part of the MNCs' earnings. Equations\u0026nbsp;(4) and (5) indicate that the change in revenues affected by offshore production depends on \\({T}_{i}\\), which is affected by the change in patent protection in South from enhancement from \\({\\lambda }_{S}\\) to \\({\\lambda }_{S}^{{\\prime }}\\).\u003c/p\u003e\n\u003cp\u003e\\({R}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{R}_{i}\\left({\\lambda }_{S}\\right)={r}^{S}\\left({\\lambda }_{S}^{{\\prime }}-{\\lambda }_{S}\\right)\\frac{{T}_{i}}{2\\stackrel{-}{w}}\\), \\({T}_{i}\u0026lt;{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\)\u003c/p\u003e\n\u003cp\u003e\\({R}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{R}_{i}\\left({\\lambda }_{S}\\right)={r}^{S}\\left(2\\frac{{T}_{j}-{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{j}}+\\left({\\lambda }_{S}^{{\\prime }}-{\\lambda }_{S}\\right)\\frac{{\\left[{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\right]}^{2}}{2\\stackrel{-}{m}{T}_{i}}\\right)\\), \\({\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\le {T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\)\u003c/p\u003e\n\u003cp\u003e\\({R}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{R}_{i}\\left({\\lambda }_{S}\\right)={r}^{S}\\left(2\\frac{{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)-{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)}{{T}_{j}}+\\left({\\lambda }_{S}^{{\\prime }}-{\\lambda }_{S}\\right)\\frac{{\\left[{\\tau }^{\\ast }\\left({\\lambda }_{S}\\right)\\right]}^{2}}{2\\stackrel{-}{m}{T}_{i}}\\right)\\), \\({T}_{i}\u0026gt;{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\) (6)\u003c/p\u003e\n\u003cp\u003eThe function at the bottom of Fig.\u0026nbsp;2 is \\({R}_{i}\\left({\\lambda }_{S}^{{\\prime }}\\right)-{R}_{i}\\left({\\lambda }_{S}\\right)\\) a non-monotonic function based on \\({T}_{i}\\) that increases for \\({T}_{i}\\le {\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\) and decreases for \\({T}_{i}\u0026gt;{\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\), the point of greatest response to IPR protection reform at \\({T}_{i}={\\tau }^{\\ast }\\left({\\lambda }_{S}^{{\\prime }}\\right)\\).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Data and Descriptive Statistics","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Product Life-Cycle Lengths\u003c/h2\u003e\n\u003cp\u003eTo measure the length of a product's life cycle \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e, it is to associate the product with proprietary information such as patents and implicit intellectual property rights that are necessary for production but lose their economic value when the product becomes obsolete (Bilir, \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). The view implies that proprietary information must be separated across products, meaning that the information needed to create a new product must differ from that required for any previous product. Therefore, the main distinction between industries in the model is not the time lag between versions of a product that embody the same innovative idea, but rather the economic lifecycle of the innovative idea itself. This lifecycle may span consecutive versions of the product's lifecycle (Klepper, \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe length of a product's life cycle is determined by the economic durability of the embedded technology. This paper uses United States patent citation data from 1976 to 2006, which includes 6,832 products from 122 countries. The duration for which a patent is cited by subsequent patents is an indicator of the market longevity of the patented technology. A long average 'pre-citation lag', which is the time between the grant date of the cited patent and the subsequent citation, indicates that the technology has persistent relevance to future innovation. To construct the product life cycle length index \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\widehat{T}}_{i}\\)\u003c/span\u003e\u003c/span\u003e, we used the methodology of Hall et al. (\u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e) and Bilir (\u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e) and mapped from SIC 3-digit code to NAICS 6-digit code. The product life-cycle length index is constructed without any restrictions on the patent categories in which patents are cited. This allows patented technologies to be relevant not only to future innovations in their own category but also in other patent categories.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows a bar chart of the Product Life Cycle Length Index, highlighting the differences in life cycle length among various products. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the product name, life cycle length, and capital intensity for the top five, median, and bottom five product life cycle lengths. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows that products with shorter life cycles have higher capital intensity. This relationship is further supported by the scatter plot in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, which has a correlation coefficient of -0.072.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eProduct Life-cycle Lengths and Capital Intensity\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eName\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRank\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSIC 3-Digit Code\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eProduct Life-cycle Lengths\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCapital Intensity\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eShortest product life cycle\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElectronics machinery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e383\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.592\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWatches, clocks, clockwork operated devices\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e387\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.691\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eComputer and office equipment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e357\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.891\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAgricultural chemicals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e287\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.072\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElectronic components and accessories\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e367\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.566\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIntermediate-length product life cycles\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMiscellaneous industrial and commercial\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e359\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.275\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMiscellaneous chemical products\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e289\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.775\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSurgical, medical, dental instruments, and supplies\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e384\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.452\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFarm and garden machinery and equipment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e352\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.418\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold appliances\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.592\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLongest product life cycles\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFabricated structural metal products\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e344\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.182\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCutlery, handtools, and general hardware\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e342\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.787\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eScrew machine products, bolts, nuts, screws\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e345\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.718\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetal cans and shipping containers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e341\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.320\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeating equipment, except electric\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.187\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNotes: This table presents the top five, median, and bottom five product names, life cycle lengths, and capital intensities sorted by product life cycle length. Product life-cycle lengths were measured in years and calculated using patent citation data.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Intellectual Property Protection in Different Countries\u003c/h2\u003e\n\u003cp\u003eThis paper utilises Park's (2008) indicator to measure the strength of IPR protection across different countries. The indicator, which is comprehensive and widely applicable, assesses IPR protection in five dimensions: coverage, membership of international patent agreements, provisions for loss of patent, enforcement mechanisms, and duration of protection. Each dimension is scored between 0 and 1 based on objective criteria to determine whether the current patent law meets specific standards. The Patent Protection Index is the sum of these five dimensions, ranging from 0 to 5. Higher values indicate stronger IPR protection. These indices are available at five-year intervals for 122 countries from 1980 to 2005. In this paper, the year of each benchmarking survey is matched to the closest available index year.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Inter-firm Trade Ratio\u003c/h2\u003e\n\u003cp\u003eThis paper utilises US MNCs trade data from 2002\u0026ndash;2013 for 118 countries import data for 208 products based on the NAICS 6-digit classification. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents summary statistics for the aforementioned data.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSummary Statistics\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eS. D.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMin\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMax.\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIFR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.309\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.523\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.725\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.681\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.500\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.447\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.835\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.800\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCapital Intensity\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.172\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.636\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.989\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.929\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eGDP per capita\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18697.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17824.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e95012.67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Econometric Framework","content":"\u003cp\u003eBased on Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e in the second part of the theory, the safeguarding of host country IPR protection through offshore production activities of MNEs is a non-monotonic function of the product life cycle's length. This paper uses inter-firm trade ratios to characterise the corporate boundaries of MNCs (Antr\u0026agrave;s, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Antr\u0026agrave;s and Helpman, 2004; Antr\u0026agrave;s and Helpman, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Nunn and Trefler, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The baseline regression equation of this paper is based on the results of the theoretical derivation.\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$${IFR}_{cit}={\\beta }_{0}+{\\beta }_{1}\\bullet {IPR}_{ct}\\times {T}_{i}+{\\beta }_{2}\\bullet {IPR}_{ct}\\times {T}_{i}^{2}+{\\eta }_{ct}+{\\eta }_{i}+{ϵ}_{cit}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({IFR}_{cit}\\)\u003c/span\u003e\u003c/span\u003e is the inter-firm trade ratio of U.S. MNCs in country c for product \u003cem\u003ei\u003c/em\u003e in year \u003cem\u003et.\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({IPR}_{ct}\\)\u003c/span\u003e\u003c/span\u003e is an index of patent protection in country \u003cem\u003ec\u003c/em\u003e in year \u003cem\u003et.\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e denotes the life cycle length of product \u003cem\u003ei\u003c/em\u003e. The main coefficients of interest in this paper are \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{1}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{2}\\)\u003c/span\u003e\u003c/span\u003e, which shows the impact of different product life-cycle lengths and host country IPR protection on differences in MNCs' offshore production activities. In order to make the empirical model consistent with the theoretical model, the estimated coefficients of the empirical model must satisfy the following conditions: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{1}\u0026gt;0\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{2}\u0026lt;0\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{1}\\bullet {T}_{i}+{\\beta }_{2}\\bullet {T}_{i}^{2}\\ge 0\\)\u003c/span\u003e\u003c/span\u003e. The country-level control variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{ct}\\)\u003c/span\u003e\u003c/span\u003e controls for GDP, \u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e, while the product-level control variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{i}\\)\u003c/span\u003e\u003c/span\u003e controls for capital intensity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e. The error term includes any omitted factors that affect the offshore production patterns of MNCs. The results are clustered at the country level across all reports, which is robust due to the possibility of measurement error in the host country patent protection index.\u003c/p\u003e"},{"header":"5 Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003e5.1 Baseline Results\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents the main regression results, which provide favourable support for the above theoretical results. Column 1 shows that stronger IPR protection leads to a higher rate of MNCs choosing unrelated-party outsourcing in the production chain in host countries. Column 2 shows that host countries with stronger IPR protection have a higher rate of choosing unrelated-party outsourcing for products with longer life cycles. In column 3, the empirical model includes the interaction between \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({IPR}_{ct}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}^{2}\\)\u003c/span\u003e\u003c/span\u003e based on the results of the theoretical model. The empirical results show that the coefficient of \u003cem\u003eIPR\u0026times;T\u003c/em\u003e is 0.133\u0026thinsp;\u0026gt;\u0026thinsp;0, while the coefficient of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e is -0.129\u0026thinsp;\u0026lt;\u0026thinsp;0, consistent with the theoretical model. The impact of IPR protection in the host country follows a non-monotonic trend with respect to the length of the product life cycle. The effect is most pronounced in industries with moderately long product life cycles. Column 4 includes \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e in the model from column 3 to differentiate the impact of product life cycle length from that of product idiosyncrasies. Additionally, column 4 introduces \u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e to the model from column 3 to better distinguish the effect of IPR protection from that of overall economic development. Column 6 includes all control variables. The empirical regression results are consistent with the theoretical notation, indicating that the addition of control variables has a minimal impact on the main coefficients of interest \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{1}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{2}\\)\u003c/span\u003e\u003c/span\u003e in this paper.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMain Result\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eInter-firm Trade Ratio\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.108***\u003c/p\u003e\n\u003cp\u003e(0.017)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.029\u003c/p\u003e\n\u003cp\u003e(0.021)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.133***\u003c/p\u003e\n\u003cp\u003e(0.029)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.133***\u003c/p\u003e\n\u003cp\u003e(0.029)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.098***\u003c/p\u003e\n\u003cp\u003e(0.025)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.102***\u003c/p\u003e\n\u003cp\u003e(0.028)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.129***\u003c/p\u003e\n\u003cp\u003e(0.022)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.129***\u003c/p\u003e\n\u003cp\u003e(0.022)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.095***\u003c/p\u003e\n\u003cp\u003e(0.023)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.099***\u003c/p\u003e\n\u003cp\u003e(0.023)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eGDPpc\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028**\u003c/p\u003e\n\u003cp\u003e(0.011)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.019*\u003c/p\u003e\n\u003cp\u003e(0.011)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003cp\u003e(0.011)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.001*\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.001*\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndustry FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountry-year FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(Pesudo {R}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.204\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eNotes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003e5.2 Flexible Estimation\u003c/h2\u003e\nTo evaluate the influence of IPR protection in the host country on inter-firm trade ratio, we estimate coefficients that vary flexibly over the product life cycle's length \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e presents the estimates based on Eq.\u0026nbsp;(\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e), where the product life cycle length is divided into quartiles (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{1}^{T}\\)\u003c/span\u003e\u003c/span\u003e,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{2}^{T}\\)\u003c/span\u003e\u003c/span\u003e,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{3}^{T}\\)\u003c/span\u003e\u003c/span\u003e,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{4}^{T}\\)\u003c/span\u003e\u003c/span\u003e,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{5}^{T}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{6}^{T}\\)\u003c/span\u003e\u003c/span\u003e). Dummy variables corresponding to the last five quintiles intersect with the degree of IPR in the host country, with interactions as shown in Eq.\u0026nbsp;(\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003cbr /\u003e\n\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equ6\" class=\"mathdisplay\"\u003e$${{IF}R}_{{cit}}=\\beta +\\sum _{k=2}^{6}{\\beta }_{k}\\bullet {IPR}_{ct}\\times {1}_{{T}_{i}\\in {Q}_{k}^{T}}+{\\eta }_{ct}+{\\eta }_{i}+{ϵ}_{cit}$$\u003c/div\u003e\n\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\n\u003c/div\u003e\nso that \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e and fixed effects \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{ct}\\)\u003c/span\u003e\u003c/span\u003e capture the effect of \u003cem\u003eIPR\u003c/em\u003e on short-life-cycle sectors in the bottom fifth of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e distribution. An advantage of this approach is that the differential effect of IPR protection, as reflected by the coefficients \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{2}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{3}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{4}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{5}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{6}\\)\u003c/span\u003e\u003c/span\u003e, is unrestricted across fifths of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e distribution. A consistent pattern emerges from the estimates in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e: the fourth and fifth sextile coefficients tend to be negative and smaller than the second or third sextile coefficients. This pattern indicates that shrink in inter-firm trade ratio is concentrated within posterior-\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e industries. This pattern provides additional evidence consistent with the non-monotonicity implications of the theory.\u003cbr /\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThus, the combination of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e and fixed effects \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{ct}\\)\u003c/span\u003e\u003c/span\u003e explains that host country \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({IPR}_{ct}\\)\u003c/span\u003e\u003c/span\u003e impact on short life cycle lengths \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e in the bottom quartile of the distribution. This approach allows for coefficients \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{2}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{3}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{4}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{5}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\beta }_{6}\\)\u003c/span\u003e\u003c/span\u003e to reflect the differential impact of IPR protection in different quartiles of the product life cycle length \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{i}\\)\u003c/span\u003e\u003c/span\u003e distribution. The coefficients in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e tend to be positive for the fourth and fifth quintiles. The data indicates that inter-firm trade has increased in the middle and late products of the life-cycle length quartiles. Additionally, the expansion of unrelated-party outsourcing by MNCs in offshore production segments has been concentrated in products with medium- to long-term life-cycle lengths. These findings provide further evidence consistent with the non-monotonicity of the results of the theoretical model.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eHost-country IPR and Inter-firm Trade Ratio Flexible Estimation\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eInter-firm Trade Ratio\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}_{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}_{3}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003cp\u003e(0.004)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}_{4}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}_{5}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}_{6}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.011*\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.010**\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.004*\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.004\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000**\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000**\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003cp\u003e(0.012)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003cp\u003e(0.012)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001*\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001*\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndustry FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountry-year FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229,089\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNotes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"6 Robustness Checks and Heterogeneity Analysis","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003e6.1 Tobit Regression\u003c/h2\u003e\n\u003cp\u003eTo ensure the robustness of the regression results, the econometric model was replaced with Tobit regressions based on theoretical model extrapolation. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e reports the impact of host country IPR protection and product life-cycle length on inter-firm trade based on Tobit regressions. The results obtained through Tobit regressions are consistent with those obtained through OLS regression, indicating the robustness of the regression results.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eTobit Regression\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eInter-firm Trade Ratio\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.140***\u003c/p\u003e\n\u003cp\u003e(0.036)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.013\u003c/p\u003e\n\u003cp\u003e(0.013)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.111**\u003c/p\u003e\n\u003cp\u003e(0.044)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.204***\u003c/p\u003e\n\u003cp\u003e(0.062)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.080\u003c/p\u003e\n\u003cp\u003e(0.054)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.154**\u003c/p\u003e\n\u003cp\u003e(0.069)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.108**\u003c/p\u003e\n\u003cp\u003e(0.045)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.178***\u003c/p\u003e\n\u003cp\u003e(0.054)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.080\u003c/p\u003e\n\u003cp\u003e(0.056)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.136**\u003c/p\u003e\n\u003cp\u003e(0.064)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.010*\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.007\u003c/p\u003e\n\u003cp\u003e(0.005)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eGDPpc\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000**\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.091**\u003c/p\u003e\n\u003cp\u003e(0.038)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.077**\u003c/p\u003e\n\u003cp\u003e(0.039)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.004**\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.004**\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndustry FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountry-year FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136,918\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139,596\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139,596\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139,596\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136,918\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e136,918\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.231\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.231\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.231\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eNotes: Standard errors in brackets clustered at country level. ***Significant at the 1 percent level. **Significant at the 5 percent level. *Significant at the 10 percent level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003e6.2 Heterogeneity Analysis\u003c/h2\u003e\nTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e presents estimates based on whether the host country's IPR protection is above or below its mean (3.447). The results align with expectations, indicating that the IPR protection sensitivity mechanism is more effective in countries with high IP protection. Columns 1 to 5 pertain to the high IPR protection sample. The regression results indicate significantly positive coefficients for \u003cem\u003eIPR\u0026times;T\u003c/em\u003e and significantly negative coefficients for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e, which are consistent with the main regression results. However, in the low IPR protection sample, the direction of the coefficients of the regression results is not significant, although it is consistent with the main regression results. The data suggests that the mechanism for protecting intellectual property rights is more effective in countries with stronger IPR protection.\u003c/div\u003e\n\u003cdiv class=\"Section2\"\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e distinguishes between short, medium, and long product life cycle lengths based on the trichotomy of the product life cycle length. The results indicate that inter-firm trade ratio is more sensitive in samples with longer product life cycles. Specifically, the coefficients of \u003cem\u003eIPR\u0026times;T\u003c/em\u003e are significantly positive and those of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e are significantly negative for the sample with longer product life cycles in columns 7 to 10. This is consistent with the results of the main regression. The study shows that long life-cycle products tend to have a higher rate of unrelated-party outsourcing in the host country when they are far from the phase-out deadline. The rate of outsourcing decreases after reaching a peak and gradually approaches the phase-out date. However, for short and medium product life cycles, the coefficients show the opposite sign to that of long product life cycles and are not significant. The reason for the opposite sign may be that the risk of imitation for products with shorter and medium life cycles is relatively lower than that of products with longer life cycles. As a result, products with shorter and medium life cycles tend to outsource to unrelated parties at the initial stage, which is in line with the expected theoretical results. The results indicate that the rate of unrelated-party outsourcing in the host country is explained by both host country IPR protection and product life-cycle length. The relationship between these factors is non-linear, and the rate of host country unrelated-party outsourcing is more sensitive for products with long life-cycle lengths.\u003cbr /\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eHeterogeneity of IPR\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eHigh Patent Protection\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eLow Patent Protection\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(10)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.917**\u003c/p\u003e\n\u003cp\u003e(0.079)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.916\u003c/p\u003e\n\u003cp\u003e(0.593)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.377**\u003c/p\u003e\n\u003cp\u003e(0.599)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.202*\u003c/p\u003e\n\u003cp\u003e(0.670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.659**\u003c/p\u003e\n\u003cp\u003e(0.652)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.021\u003c/p\u003e\n\u003cp\u003e(0.041)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.625\u003c/p\u003e\n\u003cp\u003e(0.387)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.525\u003c/p\u003e\n\u003cp\u003e(0.400)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.673*\u003c/p\u003e\n\u003cp\u003e(0.397)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.565\u003c/p\u003e\n\u003cp\u003e(0.415)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.547*\u003c/p\u003e\n\u003cp\u003e(0.280)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.722**\u003c/p\u003e\n\u003cp\u003e(0.280)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.657**\u003c/p\u003e\n\u003cp\u003e(0.317)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.831***\u003c/p\u003e\n\u003cp\u003e(0.311)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.321*\u003c/p\u003e\n\u003cp\u003e(0.181)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.285\u003c/p\u003e\n\u003cp\u003e(0.185)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.335*\u003c/p\u003e\n\u003cp\u003e(0.184)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.296\u003c/p\u003e\n\u003cp\u003e(0.191)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.016**\u003c/p\u003e\n\u003cp\u003e(0.008)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.016*\u003c/p\u003e\n\u003cp\u003e(0.008)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001**\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001**\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.015\u003c/p\u003e\n\u003cp\u003e(0.010)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.015\u003c/p\u003e\n\u003cp\u003e(0.010)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.003\u003c/p\u003e\n\u003cp\u003e(0.008)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.002\u003c/p\u003e\n\u003cp\u003e(0.008)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndustry FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountry-year FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113,179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113,179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113,179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113,179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e113,179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115,910\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115,910\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115,910\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115,910\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e115,910\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.262\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"11\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Standard errors in brackets clustered at country level.***Significant at the 1 percent level; **Significant at the 5 percent level; *Significant at the 10 percent level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab7\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eHeterogeneity in Product Life Cycle Length\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eShort-length Product Life Cycle\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eIntermediate-length Product Life Cycle\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eLong-length Product Life Cycle\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eIPR\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.081\u003c/p\u003e\n\u003cp\u003e(0.060)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.083\u003c/p\u003e\n\u003cp\u003e(0.073)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.154*\u003c/p\u003e\n\u003cp\u003e(0.085)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.240\u003c/p\u003e\n\u003cp\u003e(0.227)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.191\u003c/p\u003e\n\u003cp\u003e(0.224)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.069\u003c/p\u003e\n\u003cp\u003e(0.248)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.222***\u003c/p\u003e\n\u003cp\u003e(0.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.212***\u003c/p\u003e\n\u003cp\u003e(0.035)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.186***\u003c/p\u003e\n\u003cp\u003e(0.037)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.088\u003c/p\u003e\n\u003cp\u003e(0.067)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.093\u003c/p\u003e\n\u003cp\u003e(0.076)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.173*\u003c/p\u003e\n\u003cp\u003e(0.089)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.250\u003c/p\u003e\n\u003cp\u003e(0.238)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.174\u003c/p\u003e\n\u003cp\u003e(0.227)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.047\u003c/p\u003e\n\u003cp\u003e(0.257)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.215***\u003c/p\u003e\n\u003cp\u003e(0.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.209***\u003c/p\u003e\n\u003cp\u003e(0.032)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.184***\u003c/p\u003e\n\u003cp\u003e(0.033)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times Capital intensity\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.003)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003cp\u003e(0.003)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.013\u003c/p\u003e\n\u003cp\u003e(0.011)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.012\u003c/p\u003e\n\u003cp\u003e(0.011)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003cp\u003e(0.006)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(IPR\\times {Capital intensity}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.000\u003c/p\u003e\n\u003cp\u003e(0.001)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eLog GDPpc\u0026times;T\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.019\u003c/p\u003e\n\u003cp\u003e(0.035)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;3.799\u003c/p\u003e\n\u003cp\u003e(1.783)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003cp\u003e(0.043)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(log GDPpc\\times {T}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003cp\u003e(0.093)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;0.001\u003c/p\u003e\n\u003cp\u003e(0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndustry FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCountry-year FE\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eObs.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76,363\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.322\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.323\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.323\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.343\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"10\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Standard errors in brackets clustered at country level.***Significant at the 1 percent level; **Significant at the 5 percent level; *Significant at the 10 percent level.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"7 Conclusions","content":"\u003cp\u003eThis paper explores the sensitivity of MNCs to host country IPR protection regimes from both theoretical and empirical perspectives. The firm's global production location decision model applies two dimensions, namely product life cycle length and the degree of patent protection in the host country, to explain MNCs' inter-firm trade.\u003c/p\u003e\n\u003cp\u003eThe panel data of import trade for 208 types of products in 18 countries by U.S. MNCs from 2002 to 2013 strongly support the empirical results. The rate of unrelated-party outsourcing by MNCs in host countries, as a measure of changes in MNCs' corporate boundaries, can be explained by exploiting the interaction between patent law and product life cycle length. The research indicates that variations in the duration of the life cycle of products play a significant role in determining the sensitivity of MNCs to IPR protection in host countries. Additionally, it establishes a causal link between IPR protection and inter-firm trade of MNCs.\u003c/p\u003e\n\u003cp\u003eThe paper's heterogeneity analyses demonstrate that the sensitivity of the IPR protection mechanism is more effective in countries with a high degree of IPR protection. Additionally, the sensitivity to IPR protection in the host country is concentrated in products with a longer life cycle. The results derived from the theoretical model are consistent with reality.\u003c/p\u003e\n\u003cp\u003eFinally, this paper's theoretical and empirical results support the notion that the length of a product's life cycle determines the degree of dependence of MNCs on IPR protection in host countries. It is crucial to note that the sophistication of IPR protection in host countries is particularly important for products with longer life cycles from a policy perspective.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAntr\u0026agrave;s, P. (2003). Firms, contracts, and trade structure. \u003cem\u003eThe Quarterly Journal of Economics\u003c/em\u003e, \u003cem\u003e118\u003c/em\u003e(4), 1375\u0026ndash;1418.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntras, P., \u0026amp; Helpman, E. (2004). Global sourcing. \u003cem\u003eJournal of political Economy\u003c/em\u003e, \u003cem\u003e112\u003c/em\u003e(3), 552\u0026ndash;580.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntr\u0026agrave;s, P., \u0026amp; Helpman, E. (2006). Contractual frictions and global sourcing.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArgyres, N. S., \u0026amp; Zenger, T. R. (2012). 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Free Press.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Boundaries of the multinational firm, Intellectual property protection, Product life-cycle lengths","lastPublishedDoi":"10.21203/rs.3.rs-3877554/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3877554/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper presents a theoretical model based on transaction cost analysis and the resource-based view. It establishes that the corporate boundaries of multinational corporations are determined by the length of the product life cycle and the level of intellectual property protection in the host country. The empirical results based on the panel data of U.S. multinational corporations' import trade of 208 types of products in 18 countries from 2002 to 2013 validate the extrapolation results of the theoretical model. The study finds that the most significant determinants of multinational corporations' boundaries are the length of the product life cycle and the level of IPR protection in the host country.\u003c/p\u003e","manuscriptTitle":"Intellectual Property Protection, Product Life-cycle Lengths, and the Boundaries of Multinational Corporations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-31 10:27:34","doi":"10.21203/rs.3.rs-3877554/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fd65b41a-05a8-4fb9-b0e2-6d873c0b976f","owner":[],"postedDate":"January 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-30T13:43:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-31 10:27:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3877554","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3877554","identity":"rs-3877554","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}