Roadmap towards gender equality: analyzing the influence of foreign direct investment on wage dynamics

Roadmap towards gender equality: analyzing the influence of foreign direct investment on wage dynamics | 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 Roadmap towards gender equality: analyzing the influence of foreign direct investment on wage dynamics Noah Mutai, Juliet Katusiime, Valdrin Dervishaj, Olufunke Mercy Popoola This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3936840/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 study investigates the relation between foreign direct investments (FDI) and wage dynamics in Germany, Austria, and the Netherlands, aiming to develop a sustainable roadmap for reducing gender inequalities. Selected for their diverse labor dynamics, sustainability commitments, and gender equality situations, these countries serve as ideal case studies. Data spanning 1991 to 2021 on FDI and the percentage of gender-based workers were collected from the World Bank Development Indicators. Employing various linear regression models, our research examines the relationship between current and lagged wages for different genders, shedding light on how FDIs may influence wage patterns, especially regarding gender inequality. The quantitative study affirms the model's robustness, revealing a clear linear association between FDIs and salaries in these nations. This underscores the potential impact of foreign investments on wage dynamics, providing a foundation for addressing and reducing gender inequalities. JEL Classification: F23, J31, O15 Econometrics Macroeconomics Foreign Direct Investment Gender Inequality Labor dynamics Wage Dynamics Sustainability goals Figures Figure 1 1. Introduction Sustainable Development Goal (SDG) number 5 strives to attain gender equality and empower all women and girls, recognizing it as a fundamental human right essential for a peaceful, prosperous, and sustainable world. Despite progress, the world is not currently on track to achieve gender equality by 2030, posing challenges to sustainable development goals (UN General Assembly, 2022). Women's labor participation is central in sustainable development and a fundamental macro-economic priority (Achuo, 2023; UN, 2014). Female participation under the current SDG up to 2030 and beyond contributes to driving labor economics, encompassing both local and international advantages and challenges, including wage and salary disparities that demotivate or undermine women's potential. One persistent area of gender inequality is the gender wage gap, defined as the difference between the median earnings of men and women relative to men's median earnings, including both full-time employees and self-employed individuals (OECD, 2023). Globally, women earn only 51 cents for every dollar earned by men, with more pronounced disparities in poor and lower-middle-income countries, where women earn only 33 cents for every dollar earned by men (ILO, 2023). In the European Union (EU) in 2021, the gender salary gap remained stagnant at 12.7% over the past decade, indicating that, on average, women earned 13.0% less per hour than their male counterparts. Disparities varied significantly across EU countries, with Estonia having the highest disparity at 20.5%, followed by Austria at 18.8%, Germany at 17.6%, Hungary at 17.3%, and Slovakia at 16.6%. Conversely, Luxembourg successfully eliminated the gender pay disparity, showcasing an equal pay landscape. Despite an almost 20% increase in foreign direct investment (FDI) into the EU in 2021, with Germany as the leading beneficiary, gender wage gaps persisted (Barklie et al., 2022). FDI's positive influence on a nation's economic growth and welfare is well-established, manifested through innovations, technology transfer, skill development, and job creation. FDI produces gender-specific outcomes within host nations' labor markets, influencing the relative demand and prices of production factors, such as labor. Due to policy and non-policy factors, women and men possess distinct preferences and skill sets, with differing employment intensities across industries. Consequently, FDI induces changes in the relative demand for labor based on gender, affecting the employment and wages of women and men disparately (Makiela & Ouattara, 2018; Kondyan & Yenokyan, 2019; OECD, 2022; Ali et al., 2023). A critical question is how FDI impacts the wages of different gender workers in these nations, emphasizing the need to discern substantial disparities in the effects of foreign investment on the wages of male and female employees (Sergiu et al., 2023). Considering the global perspective, FDI emerges as a crucial aspect influencing the women/gender-labor-sustainable development nexus. By examining the perspective from global north cases first, FDI holds the potential to catalyze progress towards gender equality in the labor market. This is achieved by facilitating a more comprehensive and equitable economic environment, directing resources towards sustainable practices, and implementing fair workplace regulations. Consequently, this can lead to increased wage equality, benefiting businesses, industries, and contributing to the overall well-being of society (Sergiu et al., 2023). This study investigates the influence of Foreign Direct Investments (FDIs) on wage levels in Germany, Austria, and the Netherlands, building upon Sergiu et al.'s (2023) research on FDIs and wage fluctuations in Austria and Germany. Their analysis revealed gender-specific variations in how FDIs affected wages, emphasizing the potential impact on long-term socioeconomic progress. This paper further enhances understanding by analyzing potential disparities in the impact of FDIs on the salaries of male and female employees in the three countries from 1991 to 2021. Examining these nations as case studies provides a distinctive approach to comprehending the effects of FDIs on wage structures, with a particular emphasis on gender equality, given their significant roles in the European foreign investment sector. The study adopts a quantitative approach, analyzing data from the World Bank Development Indicators (WBDI) and drawing insights from existing scholarly studies. The methodology involves a comprehensive examination of relevant datasets related to foreign investments and wage levels, utilizing economic models and rigorous statistical analysis. The expected outcomes will significantly contribute to the academic literature, providing fresh perspectives and empirical evidence regarding the impact of FDI on employee compensation in the three countries. The paper's structure includes theoretical and empirical reviews in Chap. 2, specifics of data and methods in Chap. 3, results and discussions in Chap. 4, and conclusions with policy recommendations in Chap. 5. 2. Literature review 2.1 Theoretical Review 2.1.1 Human Capital Theory Institutional economics explores the intricate relationship between education and economic outcomes (Vaizey, 1962; Schultz, 1981; Johnes, 1993). According to human capital theory, investments in people offer economic advantages to both individuals and society, with a crucial distinction between human capital expenditures and consumptive expenditures (Vaizey, 1962). While health and nutrition constitute common forms of human capital investment (Schultz, 1981), empirical investigations often emphasize education as the most crucial area (Schultz, 1963). The literature on human capital theory distinguishes various forms and methods of education, including formalized education at different levels, informal education, on-the-job training, and vocational education (Cohn & Geske, 1990; Schultz, 1981; Mincer, 1974; Corazzini, 1967). These diverse forms significantly influence the research design of studies on human capital, with a reasonable assumption that education enhances individuals' economic capabilities in most instances (Schultz, 1971). Due to rapid changes in society, there have been created testing environments for human capital forcing company management into a rapid movement within the "unknown fields" (Dervishaj & Neziraj, 2022). The extensive body of research highlights the importance of human capital theory. In 1966, Blaug cataloged 792 articles, books, and research projects related to education economics, with the number surpassing 2,000 by 1976 (Blaug, 1970). Notably, the theory's connection to Nobel Prize recognition is remarkable, with five prizes awarded since 1971 to scientists involved in or associated with human capital theory (Becker, 1993; Wright, 1992). The Nobel distinction is attributed to key figures in human capital theory, including Theodore W. Schultz and Gary S. Becker, prominent scholars; Milton Friedman and Simon Kuznets (1945), collaborators on a significant article connecting medical professionals' incomes with education investments; and Solow (1957), pivotal in highlighting the relationship between education and the overall production function. Despite its significance, human capital theory faces criticism for oversimplifying the intricate relationship between education, training, and economic outcomes. The theory falls short in acknowledging various factors impacting earning potential, such as discrimination, economic downturns, and shifts in labor market conditions. Additionally, it assumes easy investment access, overlooking barriers like unequal education and training opportunities that can exacerbate income inequality. The theory predominantly focuses on economic aspects, neglecting the non-market value of education, encompassing personal growth, societal well-being, and cultural development. This oversight results in a failure to consider the positive externalities associated with education and training, which benefit both individuals and society, leading to lower crime rates, improved healthcare outcomes, and overall societal well-being. Human capital theory's relevance extends to sustainability and its impact on diminishing gender inequality, particularly concerning foreign direct investment (FDI) on wage dynamics. The theory emphasizes the significance of education and training in enhancing an individual's productivity and earning potential. In the context of gender inequality, investing in women's education and skills development becomes imperative. When FDI aligns with initiatives augmenting education and skills for both male and female workers, it plays a crucial role in narrowing the gender wage gap. A central tenet of human capital theory is the equitable distribution of human capital investments, with FDI playing a pivotal role in influencing gender equality. FDI offers opportunities for women to access education, training, and employment in traditionally male-dominated sectors, contributing to a more balanced allocation of human capital and reducing wage disparities. Furthermore, human capital theory posits that investments in education and skills development can spur economic growth. When FDI supports sustainable projects that generate employment and enhance human capital, it stimulates economic development in host countries, creating opportunities for women to participate in the labor force and secure higher wages. However, it is crucial to note that the impact of FDI on wage dynamics may not be uniform for both men and women. Human capital theory provides a framework for assessing how FDI impacts wage dynamics differently for male and female workers while revealing gender-based wage disparities. FDI typically involves knowledge and skills transfer to workers in the host country, enhancing the productivity of all workers, including women. In cases where FDI projects actively promote gender-inclusive skill transfers, there is potential to reduce gender wage disparities. The theory underscores the importance of acquiring skills in demand in the labor market, creating opportunities for both men and women to access high-paying jobs in industries with a higher demand for skilled labor. This contributes to narrowing the gender wage gap by enhancing women's access to well-paying positions. Institutional economics emphasizes that "institutions matter" when examining economic systems. These institutions, encompassing both official and informal regulations, play a central role in investigative efforts (Raudla, 2014). The roots of institutional economics trace back to two prominent schools of thought: the German historical school, including figures like Gustav von Schmoller, Wilhelm Roscher, Werner Sombart, and Max Weber, and the American institutionalist school, with notable figures like John Commons, Thorstein Veblen, and Wesley Mitchell (Medema et al., 1999; Rutherford, 1994). The New Institutional Economics (NIE) is an interdisciplinary field drawing from economics, law, organization theory, political science, sociology, and anthropology, aiming to provide insights into the institutions shaping social, political, and commercial existence. While it draws from multiple social sciences, its primary framework remains rooted in economics. NIE seeks to clarify the nature of institutions, how they come into being, the purposes they serve, the mechanisms behind their evolution, and whether alterations are necessary. The term "institutional economics" was initially associated with scholars like Thorstein Veblen, John R. Commons, Wesley C. Mitchell, and Clarence Ayres. Despite the diversity in their work, it centers around key themes involving critiques of conventional economics, shifting the focus from individual to collective actions, embracing an "evolutionary" approach to the economy, and prioritizing empirical observation over deductive reasoning (Seckler, 1975; Gruchy, 1972; Langlois, 1989). Richter (1996) delves into the German origins of American institutionalism, revealing significant contributions by earlier institutionalist thinkers. However, many contemporary economists remain unfamiliar with these contributions, exemplified by the dismissive treatment of Coase (1984) who was often regarded as having little more to offer than descriptive material awaiting a theoretical framework. Williamson (1975) introduced the term "new institutional economics" (NIE), rooted in Coase's analysis of the firm (1937), Hayek's discussions on knowledge (1937, 1945), and Chandler's examination of industrial enterprise (1962). Notable contributions also came from scholars like Simon (1947), Arrow (1963), Davis and North (1971), Alchian and Demsetz (1972), Williamson (1973), and others (1971). Prominent figures associated with NIE include Coase, Williamson, and North, with additional work by scholars like Eggertsson (1990), Furubotn and Richter (1991), Coase (1992), Werin and Wijkander (1992), Macneil (1978), Holmström (1979), and others. The new institutional economics, much like its predecessor, focuses on examining social, economic, and political institutions governing daily lives. However, it takes a different approach by distancing itself from the holistic perspective of the older school, adhering to a form of methodological individualism. NIE recognizes the importance of social phenomena but frames explanations in the context of individuals' goals, plans, and behaviors. Despite this, it acknowledges social phenomena such as corporate culture and organizational memory, regarding them as subjects to be explained rather than the basis for explanations. NIE differs from orthodox neoclassical economics, emphasizing the need for policy analysis guided by "comparative institutional analysis" (Coase, 1964). Institutional economics plays a crucial role in understanding the connection between sustainability and the reduction of gender inequality, especially when assessing the effects of foreign direct investment (FDI) on wage dynamics. This field underscores the importance of institutions, encompassing both formal laws and regulations and less tangible aspects like informal norms, customs, and organizational structures. When scrutinizing gender inequality, understanding the institutional framework within the host country becomes imperative, influencing efforts to diminish gender inequality. Institutional economics underlines the paramount importance of property rights and contracts in facilitating economic transactions, crucial when examining the influence of FDI on wage dynamics. Safeguarding property rights and enforcing labor contracts are pivotal in ensuring equitable wages and working conditions, irrespective of gender. Different nations have diverse regulatory frameworks pertaining to labor and gender equality, impacting both FDI and wage dynamics. Institutional economics also considers the evolution of institutions over time. The study of sustainability often involves evaluating whether FDI leads to alterations in host country institutions fostering gender equality. Institutional economics recognizes the significant influence of cultural norms and social capital on economic outcomes. When investigating gender inequality and FDI, understanding the cultural context is crucial, as different norms can impact how women are treated in the workforce, affecting wage dynamics. Institutional economics assists in uncovering power imbalances within institutions, a key driver of gender inequality. FDI can either exacerbate or mitigate power imbalances, and comprehending these dynamics is crucial for a thorough analysis of gender-related impacts. Sustainability requires assessing the long-term impact of FDI-induced changes in wage dynamics, a task facilitated by institutional economics. 2.2 Empirical review 2.2.1 Role of FDI in an economy FDI Foreign Direct Investment (FDI) refers to the establishment of a long-term stake in a foreign enterprise by an entity residing in a different country, implying a durable relationship between the investor and the invested enterprise (IMF, 2005). FDIs exert significant influence over the management of the invested enterprise and involve initial and subsequent capital transactions, including those among related businesses, reflecting a net inflow of new investments from foreign investors into the reporting economy as a ratio to the country's gross domestic product. FDIs play a crucial role in stimulating economic growth, technological advancement, and job creation in host countries. These investments offer advantages such as capital infusion, technology transfer, managerial expertise, and access to new markets (Sergiu et al., 2023). Particularly in developing countries, FDIs serve as a significant source of external funds, catalyzing domestic investment, enhancing productivity, and fostering innovation. Furthermore, they contribute to the creation of employment opportunities, reducing unemployment rates and improving living standards (Frenkel et al., 2004; Vujanović et al., 2021). In addition to promoting economic growth, FDIs play a pivotal role in fostering global integration and promoting international trade. These investments bring valuable experience and extensive networks, facilitating connections between local businesses and global markets, leading to increased exports, import substitution, and supply chain development (Götz & Jankowska, 2022). Moreover, FDIs contribute significantly to human capital development by offering training and skill enhancement opportunities to the local workforce, bolstering their competitiveness in the global job market (Stack et al., 2017). FDIs shape the economic landscape by influencing critical aspects such as job creation, technology transfer, productivity growth, market competition, and overall economic development. They act as magnets for attracting foreign capital, knowledge, skills, and resources, leading to increased investment, industrial expansion, and integration into the global economy (Bellak et al., 2008; Villaverde & Maza, 2015). Table 1 provides a concise summary of empirical studies on FDIs and their impact on economic variables. The impact of FDIs on wage inequality is a topic of research, and findings can be categorized into four areas: Neutral Impact on Wage Inequality: Some studies suggest that FDI has no discernible impact on wage inequality, indicating that foreign capital introduction does not significantly alter wage disparities among local workforces. Local labor market dynamics and government policies may play more substantial roles in shaping wage structure outcomes (IMF, 2005). Reduction in Wage Inequality: Research demonstrates that FDI can reduce wage inequality, especially when it facilitates technology transfer, skill development, and productivity enhancement. Such investments contribute to higher wages for the entire workforce, particularly in industries where FDI results in skill improvements (IMF, 2005). Increase in Wage Inequality: Certain studies propose that FDI can exacerbate wage inequality, especially in sectors relying heavily on highly skilled workers. Skilled workers may witness significant wage increases due to foreign investments, leading to a widening gap in wage disparities between skilled and unskilled laborers (IMF, 2005). Non-linear Effect on Wage Inequality: Some studies suggest a non-linear relationship between FDI and wage inequality, indicating the presence of a critical threshold or tipping point. When FDI reaches a certain level, it triggers structural changes in the labor market or industry dynamics, disproportionately affecting wage disparities (IMF, 2005). Understanding these relationships is crucial for crafting effective economic policies in FDI-receiving countries. In conclusion, while FDIs bring significant benefits to host countries, their impact on wage inequality is complex and context-dependent, requiring careful consideration of various factors. Table 1 Summary of a representative empirical studies on FDI and other economic variables. Author (s) Findings on FDI and impacts Bhandari (2007), Franco, Gerussi (2013), Yuldashev (2023), Wang et al (2023) FDI on income inequality Guo et al (2023), Sergiu et al (2023) FDI and gender inequality Chidlow, Salciuviene, Young (2009), Spies (2010), Zhang, Kim (2022), Zhang et al (2023). FDI and wage gap (skilled and unskilled) Bellak, Leibrecht, Riedl (2008), Villaverde, Maza (2015); Qiao, Fung, Fung, Ma (2022), Sinha et al (2023) FDIs on employment generation, technology transfer, productivity growth, market competition Blalock, Gertler (2008); Javorcik, Spatareanu (2008), Gorodnichenko, Svejnar, Terrell (2014), Sokhanvar (2023), Santos, E. (2023). FDIs and productivity and competitiveness in the host economy 2.2.1 Research Gap While previous studies link FDI to income inequality, a consensus on its impact on wage disparities remains elusive. FDI's effect on wage inequality is complex, influenced by factors like the host country's economic structure, FDI attributes (e.g., skill requirements, sector concentration), labor market conditions, and government policies. Conflicting research findings highlight the need for context-specific analyses to comprehend how FDI shapes wage inequality in distinct regions or industries. Recognizing this intricate relationship underscores the necessity for tailored policies and strategies to manage foreign investment's effects on income inequality. Further research on the FDI-income inequality link within specific contexts is imperative. 3. Materials and methods 3.1 Data This study uses 30 years of WBDI database for Germany, Austria, and the Netherlands, focusing on FDI and the percentages of male and female waged and salaried workers. These countries were chosen due to their unique labor dynamics, commitment to sustainability, and dedication to gender equality. Germany, a key EU and global trade player, offers insights into FDI's impact on labor dynamics and gender equity. Austria's socio-economic stability aligns with the study's emphasis on FDI and sustainable development. The Netherlands, with innovative sustainability practices and a commitment to gender equality, provides valuable insights into FDI's influence on labor dynamics and gender equality. 3.2 Methods This paper utilizes three distinct regression models to explore the relationships between wages and the FDI for females and males in Germany, Austria, and Netherlands. These models enhance the understanding of the intricate dynamics at play in the study's context. 3.2.1 Variable Description Variable Description Measurement Year Year variable (1991–2021) Date Female Percentage of waged and salaried females Proportion Male Percentage of waged and salaried females Proportion FDI Foreign Direct Investment Numeric 3.2.2 Model 1: Assessing the impact of previous FDI levels and past wage levels on current wages Model ( 1 ) examines the connections between current and past FDI levels and their impact on present wages. This model offers a comprehensive view of economic systems, especially in the context of financial interactions with foreign entities. It delves into the influence of historical foreign investments on the current economic landscape and considers the effect of past wage levels, revealing how historical labor market dynamics affect the present. This holistic approach is vital for policymakers and researchers aiming to grasp wage trends and economic stability intricacies. By quantifying these relationships, Model 1 helps assess the importance of past conditions on current wages, aiding in informed economic policy decisions and sustainable socioeconomic progress strategies. $$\text{W}\text{a}\text{g}{\text{e}}_{\text{t}}={{\beta }}_{0}+{{\beta }}_{1}\cdot \text{F}\text{D}{\text{I}}_{\text{t}}+{{\beta }}_{2}\cdot \text{F}\text{D}{\text{I}}_{\text{t}-1}+{{\beta }}_{3}\cdot \text{W}\text{a}\text{g}{\text{e}}_{\text{t}-1}+{\text{ϵ}}_{\text{t}},$$ 1 where, \(\text{W}\text{a}\text{g}{\text{e}}_{\text{t}}\) is wage at time \(\text{t}, \text{F}\text{D}{\text{I}}_{\text{t}}\) is foreign direct investment at time \(\text{t}\) , \(\text{F}\text{D}{\text{I}}_{\text{t}-1}\) is lagged values of foreign direct investment at time \(\text{t}-1, \text{W}\text{a}\text{g}{\text{e}}_{\text{t}-1}\) is lagged values of wage at time \(\text{t}-1\) , \({{\beta }}_{0}\) , \({{\beta }}_{1}\) , \({{\beta }}_{1}\) and \({{\beta }}_{2}\) are regression coefficients. 3.2.3 Isolating the effect of historical FDIs on past wages Model ( 2 ) explores the link between previous FDI levels and past wage outcomes while excluding the current year's FDIs. This unique approach isolates the influence of historical FDIs on wage trends over time. By removing the present-year FDIs, Model 2 investigates how past investments have shaped wage dynamics. This analysis helps answer questions about the lasting impact of historical FDIs on wages, potential patterns over time, and critical lags in their effects. This nuanced approach aids policymakers and economists in understanding the temporal dimension of FDI's impact on wages, offering insights to guide strategies for sustainable socioeconomic progress. $$\text{W}\text{a}\text{g}{\text{e}}_{\text{t}}={{\beta }}_{0}+{{\beta }}_{1}\cdot \text{F}\text{D}{\text{I}}_{\text{t}-1}+{{\beta }}_{2}\cdot \text{W}\text{a}\text{g}{\text{e}}_{\text{t}-1}+{\text{ϵ}}_{\text{t}},$$ 2 where, \(\mathbf{W}\mathbf{a}\mathbf{g}{\mathbf{e}}_{\mathbf{t}-1}\) , Lagged Wage Levels for t-1, \(\mathbf{F}\mathbf{D}{\mathbf{I}}_{\mathbf{t}-1},\) Lagged FDI Levels for t-1, \({\varvec{\beta }}_{0}\) , \({\varvec{\beta }}_{1}\) , and \({\varvec{\beta }}_{2}\) are regression coefficients. 3.2.4 Investigating the influence of current FDI levels and lagged wage levels on current wage outcomes Model ( 3 ) analyzes the relationship between current FDI levels and previous wage levels, focusing on their impact on present wages. This model isolates the immediate effects of current FDI inflows on the most recent wage trends while excluding the influence of lagged FDIs. This understanding is crucial for policymakers and businesses, providing insights into the direct impact of new investments on wage dynamics without historical FDI interference. The findings from Model 3 can guide strategic decision-making, especially in regions committed to sustainable socioeconomic development. Identifying how current FDIs shape contemporary wages aids in refining strategies for equitable wage growth and progress, contributing to a deeper understanding of foreign investments' role in labor market dynamics and offering actionable insights for societal prosperity. $$\text{W}\text{a}\text{g}{\text{e}}_{\text{t}}={{\beta }}_{0}+{{\beta }}_{1}\cdot \text{F}\text{D}{\text{I}}_{\text{t}}+{{\beta }}_{2}\cdot \text{W}\text{a}\text{g}{\text{e}}_{\text{t}-1}+{\text{ϵ}}_{\text{t}}$$ 3 , where \(\text{W}\text{a}\text{g}{\text{e}}_{\text{t}} \text{i}\text{s} \text{t}\text{h}\text{e}\) current Wage Levels, \(\text{F}\text{D}{\text{I}}_{\text{t}}\) is the current FDI levels, \(\text{W}\text{a}\text{g}{\text{e}}_{\text{t}-1}\) and \(\text{W}\text{a}\text{g}{\text{e}}_{\text{t}-2}\) are Lagged Wage Levels. 4. Results 4.1 Case of Germany In this section we present regression results. For each country we present three models for males and females. Table 2 Regression analysis for the effects of FDIs on the wages of female and male workers in Germany Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 (Intercept) -8.27 -9.34 -5.45 (Intercept) 1.34 1.64 1.63 (9.25) (9.03) (9.26) (6.17) (6.10) (6.15) FDI_t 0.02 0.01 FDI_t 0.02 0.03 (0.03) (0.03) (0.03) (0.03) FDI_t_1 -0.04 -0.03 FDI_t_1 0.03 0.04 (0.03) (0.03) (0.03) (0.03) Wage_t_1_female 1.09 *** 1.10 *** 1.06 *** Wage_t_1_male 0.98 *** 0.98 *** 0.98 *** (0.10) (0.10) (0.10) (0.07) (0.07) (0.07) \({\mathbf{R}}^{2}\) 0.83 0.83 0.81 \({\text{R}}^{2}\) 0.88 0.88 0.88 Adj. \({\mathbf{R}}^{2}\) 0.81 0.81 0.80 Adj. \({\mathbf{R}}^{2}\) 0.87 0.87 0.87 Num. obs. 30 30 30 Num. obs. 30 30 30 Note : The '***' indicates that this coefficient is statistically significant at the 1% level (very significant). The regression analysis in Table 1 explores the relationship between FDI levels and wage dynamics in Germany for both male and female workers. Model 1: The model reveals that while current FDI (FDI_t) and lagged FDI (FDI_t_1) have positive coefficients, suggesting a marginal positive impact on the current wage, these effects are not statistically significant. In contrast, female (Wage_t_1_female) has a highly significant positive effect on the current wage, resulting in a substantial increase. The model explains a significant portion of the variance in the current wage, with a high R-squared value of 0.81. Model 2 and 3: These models confirm a non-significant impact of both current and lagged FDI on the current wage. However, the significant positive effect of female on the current wage remains consistent across all three models. Model 2 has a slightly higher R-squared value of 0.83, while Model 3 has an R-squared value of 0.81. Implying FDI is not contributing to closing the wage gap in Germany in the current state. 4.2 Case of Austria Table 3 Regression analysis for the effects of FDIs on the wages of female workers in Austria Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 (Intercept) 5.78 6.31 5.74 (Intercept) 9.01 9.21 7.49 (3.80) (4.09) (3.74) (8.01) (8.09) (8.12) FDI_t -0.03 * -0.03 * FDI_t -0.01 -0.01 (0.01) (0.01) (0.01) (0.01) FDI_t_1 -0.00 -0.00 FDI_t_1 -0.01 -0.01 (0.01) (0.01) (0.01) (0.01) Wage_t_1_female 0.94 *** 0.93 *** 0.94 *** Wage_t_1_male 0.89 *** 0.89 *** 0.91 *** (0.04) (0.05) (0.04) (0.09) (0.09) (0.10) \({\mathbf{R}}^{2}\) 0.95 0.94 0.95 \({\text{R}}^{2}\) 0.79 0.78 0.77 Adj. \({\mathbf{R}}^{2}\) 0.94 0.93 0.94 Adj. \({\text{R}}^{2}\) 0.77 0.76 0.76 Num. obs. 30 30 30 Num. obs. 30 30 30 Note : The '***' indicates that this coefficient is statistically significant at the 1% level (very significant). Table 2 : Regression analysis for the effects of FDIs on the wages of female workers in Austria. Both current-year FDI (FDI_t) and lagged FDI (FDI_t_1) consistently exhibit negative coefficients of -0.03 in all models. This implies that higher FDI levels are associated with a decrease in the current wage for female workers in Austria, contrary to the expected positive impact of FDI on wages. This unexpected relationship may suggest that FDI is directed toward sectors with lower-wage employment or introduces wage competition through foreign firms. However, a notable observation is the variable Wage_t_1_female, which consistently holds a positive coefficient of approximately 0.94 in all models. This suggests that an increase in the wages of female workers in the previous year significantly boosts the current wage, highlighting the positive influence of gender pay equity and women's participation in the labor force on wage dynamics in Austria. The models exhibit strong goodness of fit, particularly Models 1 and 3, with high R-squared values of around 0.95, indicating that approximately 95% of the variation in the current wage can be explained by the independent variables. Model 2 also demonstrates a robust fit with an R-squared of 0.94. Adjusted R-squared values further validate the models' overall good fit. For male workers in Austria, both current-year FDI (FDI_t) and lagged FDI (FDI_t_1) consistently show negative coefficients, indicating that higher FDI levels are linked to lower current wages. This suggests a potential wage suppression effect resulting from increased FDI, and this relationship is statistically significant. Additionally, male workers in the previous period (Wage_t_1_male) are strongly associated with higher current wages, implying a gender-based wage differential favoring males in the Austrian labor market. All models have relatively high R-squared values (explaining 77–79% of wage variability), indicating a good fit. However, the non-significant intercept in Model 1 suggests the presence of unaccounted-for factors influencing current wages, warranting further exploration. In summary, these models reveal the potential wage-suppressing effect of FDI on male workers in Austria and underscore gender-based wage disparities. While providing valuable insights, additional variables may be necessary for a comprehensive understanding of wage dynamics in Austria. 4.2 Case of the Netherlands Table 4 Regression analysis for the effects of FDIs on the wages of female workers in Netherlands Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 (Intercept) 10.54 11.37 9.86 (Intercept) 3.85 3.86 3.28 (8.30) (8.05) (8.33) (2.86) (2.81) (2.81) FDI_t -0.00 -0.01 FDI_t -0.00 -0.00 (0.01) (0.01) (0.01) (0.00) FDI_t_1 -0.01 -0.01 FDI_t_1 -0.01 -0.01 (0.01) (0.01) (0.01) (0.00) Wage_t_1_female 0.88 *** 0.87 *** 0.89 *** Wage_t_1_male 0.95 *** 0.95 *** 0.96 *** (0.09) (0.09) (0.09) (0.03) (0.03) (0.03) \({\mathbf{R}}^{2}\) 0.78 0.78 0.77 \({\text{R}}^{2}\) 0.97 0.97 0.97 Adj. \({\mathbf{R}}^{2}\) 0.76 0.76 0.75 Adj. \({\mathbf{R}}^{2}\) 0.97 0.97 0.97 Num. obs. 30 30 30 Num. obs. 30 30 30 Note : The '***' indicates that this coefficient is statistically significant at the 1% level (very significant). Table 3 presents the regression analysis for the impact of FDIs on the wages of female workers in the Netherlands. In this context, the results suggest that FDI has limited direct influence on current wage dynamics, while gender-related factors play a significant role. Model 1 reveals a negligible coefficient for the current year's FDI (FDI_t), indicating minimal impact on the current wage. In this dataset and context, the current level of FDI does not significantly influence wage levels for workers in the Netherlands. Model 2 focuses on lagged FDI (FDI_t_1) and indicates that a higher level of lagged FDI is associated with a decrease in the current wage. This negative coefficient suggests that historical trends in FDI might influence wage dynamics, contributing to lower current wages. Similarly, Model 3 also shows a negative coefficient for the current year's FDI (FDI_t), implying a decrease in the current wage with higher current year's FDI. This reinforces the notion that the level of FDI in the current year does not positively impact wages in the Netherlands. Additionally, the positive coefficient for Wage_t_1_female in all models suggests that females with higher wages in the previous year positively influence the current wage. This implies some persistence in wage dynamics for females, with higher past wages leading to higher current wages. The R-squared values, indicating approximately 77–78% of the variation in the current wage explained by independent variables in all three models, suggest that despite FDI having limited direct impact, the models provide a reasonably good explanation of wage dynamics in the Netherlands. Model 1 highlights the influence of both past FDI levels and past wages for males on wage dynamics in the Netherlands. The positive coefficients for lagged FDI from the previous year and lagged male wages indicate their positive impact on the current wage. However, the impact of FDI is relatively small, with coefficients of 0.02 for current FDI and 0.03 for lagged FDI, suggesting a modest role compared to other factors. Model 2, excluding current FDI (FDI_t) and focusing on lagged FDI (FDI_t_1) and lagged male wages, produces consistent results, emphasizing the positive impact of lagged FDI on the current wage even when excluding the influence of current-year FDI. Model 3 further simplifies the analysis by excluding lagged FDI (FDI_t_1) and considering only current FDI (FDI_t) and lagged male wages. Once again, the results align with the previous models, indicating that both current FDI and lagged male wages positively influence the current wage. 4.3 Summary of Results 4.3.1 Germany The research findings shed light on the intricate relationship between Foreign Direct Investment (FDI) and wage dynamics in Germany. Surprisingly, the study suggests that FDI levels do not seem to exert a substantial immediate impact on wage adjustments, regardless of the worker’ gender. This finding challenges the conventional wisdom that FDI directly correlates with wage increases. In contrast, the research underscores the pronounced influence of gender on wage dynamics within the German workforce. Notably, female employees experience more significant wage hikes in comparison to their male counterparts. Several factors contribute to this gender-based wage differential, including the efficacy of wage equality policies in the country, the ever-evolving labor market dynamics, and the distribution of job roles among men and women. These results emphasize the multifaceted nature of wage dynamics, highlighting the complex interplay of factors, especially gender, in shaping the earnings landscape within the German labor market. Understanding these dynamics is crucial for devising policies that foster equitable wages, promote gender equality, and ensure economic opportunities for all workers in Germany. It also challenges preconceived notions about the relationship between FDI and wage dynamics. 4.3.2 Austria The results of this study reveal a surprising and unexpected negative impact of Foreign Direct Investment (FDI) on female wages in Austria. This finding raises important questions and underscores the need for more in-depth investigation. The study highlights the positive influence of female workers' wages on the overall wage structure, emphasizing the critical role of gender equality in the labor market. The robust model fit, as indicated by relatively high R-squared values (explaining 77–79% of wage variability), lends strong credibility to these conclusions, and offers valuable insights into the complex dynamics of wages concerning FDI and gender-related factors. However, it is noteworthy that Model 1 shows a non-significant intercept, suggesting the existence of unaccounted-for variables that impact current wages, necessitating further exploration. In summary, these models shed light on the potential wage-suppressing effects of FDI on male workers in Austria and underscore the presence of gender-based wage disparities. While these insights are valuable, a more comprehensive understanding of wage dynamics in Austria may require the incorporation of additional variables and further research. 4.3.3 Netherlands In the context of the Netherlands, the research findings indicate that Foreign Direct Investment (FDI) appears to have limited direct influence on wage dynamics, especially within the current year. Instead, other factors such as gender disparities and historical wage levels seem to exert a more substantial impact on explaining the variations in present-day wages. It is worth noting that while FDI, both in the current period and in the past, does contribute positively to wage dynamics, its effect is relatively modest when compared to the historical wages of male workers. These results shed light on wage dynamics in the Netherlands, emphasizing the pivotal role of domestic labor market conditions, with a particular focus on male wages. Policymakers and businesses keen on comprehending the forces behind wage fluctuations in the country can benefit from this insight, directing their strategies and decisions towards addressing the factors that hold more sway in the Dutch labor market. 5. Discussion The study explores the relationship between FDIs and wage dynamics in Germany, Austria, and the Netherlands, with a specific focus on reducing gender inequalities. These countries are chosen for their diverse labor dynamics, sustainability commitments, and gender equality situations. Using data from 1991 to 2021 sourced from the World Bank Development Indicators database, the research aims to illuminate how FDIs shape wage patterns and impact gender-based wage disparities. Employing various linear regression models, the study quantitatively assesses the link between current and lagged wages for different genders, contributing to the existing literature on wage inequality, foreign direct investment, and gender disparities. A significant finding reveals that FDIs account for over 70% of wage differences in the selected countries, indicating a linear association between FDIs and salaries. This aligns with Sergiu et al.'s (2023) discovery that around 86% of wage variation is explained by FDIs in Germany and Austria from 1992 to 2019. The implications highlight the substantial role of FDIs in shaping wage dynamics and emphasize the potential impact of foreign investments on reducing gender inequalities. While FDIs stimulate economic growth and job creation, the study suggests they can also exacerbate wage disparities, possibly due to factors like foreign investors seeking lower labor costs or favoring industries with gender-based wage gaps (Le et al., 2021). The study underscores the influence of economic globalization, particularly through FDIs, on gender wage disparities, prompting consideration of trade-offs between economic growth and gender equality. Policymakers are urged to formulate policies addressing the impact of FDIs on gender wage disparities, striking a balance between reaping the benefits of foreign investments and mitigating potential negative effects on wage inequality. 6. Conclusions and policy implications The study offers insights into the relationship between FDIs and wage dynamics in Germany, Austria, and the Netherlands, with a focus on reducing gender inequalities. Results show that FDIs account for over 70% of wage differences in these nations, emphasizing their significant role in shaping wage patterns and addressing gender disparities. However, FDIs can potentially exacerbate wage inequalities, especially when leading to lower labor costs or concentrating in industries with existing gender-based wage gaps. To combat gender wage inequality, a multifaceted approach is crucial. Governments should strengthen and rigorously enforce gender-equal pay regulations, ensuring women receive equal compensation for equivalent work. Companies must take proactive measures to close the persistent gender wage gap, fostering a more equitable work environment. Simultaneously, policymakers should champion equal opportunities, creating an environment where high-paying jobs are accessible without discrimination. This involves enhancing access to education and training, while dismantling hiring biases obstructing women's entry into well-paying positions. Transparency in wage data is vital in battling gender disparities. Encouraging companies to disclose gender-based wage gaps help identify and rectify discrepancies, foster accountability, and fair compensation practices. Governments and international organizations can support gender equality by incentivizing sustainable FDIs. Offering tax benefits or other inducements to companies committed to fair wages and gender-inclusive policies aligns business interests with societal objectives, promoting progress toward a just labor market. Policymakers, navigating the complexities of FDIs, should diligently weigh trade-offs between economic growth and gender equality. Balancing these interests is imperative to foster an environment where growth and equality coexist. Comprehensive workforce development initiatives play a pivotal role in empowering women. Enhancing the skills and employability of the female workforce, especially in male-dominated industries with pronounced wage disparities, is essential. These initiatives may include training programs, mentorship, and support systems to help women access and thrive in high-paying roles. The research for gender wage equality requires ongoing research to uncover intricate mechanisms through which FDIs influence wages. Further exploration is necessary to ascertain whether the study's findings hold true in different national and regional contexts. Policymakers should actively endorse and commission research efforts, creating an evidence-based foundation for policy decisions driving gender equality in the labor market. Declarations Funding: This research received no external funding. Data Availability Statement: Code and data can be found on https://osf.io/bpk2t/files/osfstorage and upon request from the corresponding author. Institutional Review Board Statement: Not applicable. 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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-3936840","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271570607,"identity":"86754c8a-c5e1-4d6c-ab3e-364268e7c8c6","order_by":0,"name":"Noah Mutai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYFACHhAhAcTsBx+AuHzEa2HjSTYAcdmI1AIEbAxmEhCaADBnP3vwcWWbRWK/fENa5dccOxk2BuaHj27g0WLZk5dseLZNInFmG+Ox27LbkoEOYzM2zsGjxeAGj5lkI1DLhmMMabcltzEDtfCwSRPQYv4TqsWsWHJbPVFazBhhWhg/bjtMhJYzOcaSDeckjGe25SRLM247zsPGTMgvx88Yfmwoq5PtZz5+8OPPbdX2/OzNDx/j0wIDjg1AghkcR8xEKAcBexDB+INI1aNgFIyCUTCyAAAHyUNOj+lkrAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-9677-223X","institution":"Berlin School of Business and Innovation","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Noah","middleName":"","lastName":"Mutai","suffix":""},{"id":271570608,"identity":"11800881-f935-48a7-bac3-2709ba4f925e","order_by":1,"name":"Juliet Katusiime","email":"","orcid":"","institution":"Freie University Berlin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Juliet","middleName":"","lastName":"Katusiime","suffix":""},{"id":271570609,"identity":"899c74f5-bfec-48ad-bfe1-5a4a31481023","order_by":2,"name":"Valdrin Dervishaj","email":"","orcid":"https://orcid.org/0000-0002-1677-9552","institution":"Berlin School of Business and Innovation","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Valdrin","middleName":"","lastName":"Dervishaj","suffix":""},{"id":271570610,"identity":"de83794c-7404-4926-9c23-1ee9d1812bda","order_by":3,"name":"Olufunke Mercy Popoola","email":"","orcid":"https://orcid.org/0009-0002-4355-0507","institution":"Berlin School of Business and Innovation","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Olufunke","middleName":"Mercy","lastName":"Popoola","suffix":""}],"badges":[],"createdAt":"2024-02-07 12:37:43","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-3936840/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3936840/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50927121,"identity":"ff3517c3-eb3d-4234-98c4-e3ed98a65e80","added_by":"auto","created_at":"2024-02-09 17:13:57","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":274498,"visible":true,"origin":"","legend":"\u003cp\u003eHow foreign direct investment can impact gender (source: Taylor-Strauss (2023))\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3936840/v1/63bcc97045479f518d772793.jpeg"},{"id":50928517,"identity":"5d5dd390-bbe8-47e6-be69-acb88017e7d0","added_by":"auto","created_at":"2024-02-09 17:22:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":512636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3936840/v1/a93cbb95-e857-4835-b99f-fdba5ab5a19f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eRoadmap towards gender equality: analyzing the influence of foreign direct investment on wage dynamics\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSustainable Development Goal (SDG) number 5 strives to attain gender equality and empower all women and girls, recognizing it as a fundamental human right essential for a peaceful, prosperous, and sustainable world. Despite progress, the world is not currently on track to achieve gender equality by 2030, posing challenges to sustainable development goals (UN General Assembly, 2022). Women's labor participation is central in sustainable development and a fundamental macro-economic priority (Achuo, 2023; UN, 2014). Female participation under the current SDG up to 2030 and beyond contributes to driving labor economics, encompassing both local and international advantages and challenges, including wage and salary disparities that demotivate or undermine women's potential.\u003c/p\u003e \u003cp\u003eOne persistent area of gender inequality is the gender wage gap, defined as the difference between the median earnings of men and women relative to men's median earnings, including both full-time employees and self-employed individuals (OECD, 2023). Globally, women earn only 51 cents for every dollar earned by men, with more pronounced disparities in poor and lower-middle-income countries, where women earn only 33 cents for every dollar earned by men (ILO, 2023).\u003c/p\u003e \u003cp\u003eIn the European Union (EU) in 2021, the gender salary gap remained stagnant at 12.7% over the past decade, indicating that, on average, women earned 13.0% less per hour than their male counterparts. Disparities varied significantly across EU countries, with Estonia having the highest disparity at 20.5%, followed by Austria at 18.8%, Germany at 17.6%, Hungary at 17.3%, and Slovakia at 16.6%. Conversely, Luxembourg successfully eliminated the gender pay disparity, showcasing an equal pay landscape. Despite an almost 20% increase in foreign direct investment (FDI) into the EU in 2021, with Germany as the leading beneficiary, gender wage gaps persisted (Barklie et al., 2022).\u003c/p\u003e \u003cp\u003eFDI's positive influence on a nation's economic growth and welfare is well-established, manifested through innovations, technology transfer, skill development, and job creation. FDI produces gender-specific outcomes within host nations' labor markets, influencing the relative demand and prices of production factors, such as labor. Due to policy and non-policy factors, women and men possess distinct preferences and skill sets, with differing employment intensities across industries. Consequently, FDI induces changes in the relative demand for labor based on gender, affecting the employment and wages of women and men disparately (Makiela \u0026amp; Ouattara, 2018; Kondyan \u0026amp; Yenokyan, 2019; OECD, 2022; Ali et al., 2023).\u003c/p\u003e \u003cp\u003eA critical question is how FDI impacts the wages of different gender workers in these nations, emphasizing the need to discern substantial disparities in the effects of foreign investment on the wages of male and female employees (Sergiu et al., 2023). Considering the global perspective, FDI emerges as a crucial aspect influencing the women/gender-labor-sustainable development nexus. By examining the perspective from global north cases first, FDI holds the potential to catalyze progress towards gender equality in the labor market. This is achieved by facilitating a more comprehensive and equitable economic environment, directing resources towards sustainable practices, and implementing fair workplace regulations. Consequently, this can lead to increased wage equality, benefiting businesses, industries, and contributing to the overall well-being of society (Sergiu et al., 2023).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis study investigates the influence of Foreign Direct Investments (FDIs) on wage levels in Germany, Austria, and the Netherlands, building upon Sergiu et al.'s (2023) research on FDIs and wage fluctuations in Austria and Germany. Their analysis revealed gender-specific variations in how FDIs affected wages, emphasizing the potential impact on long-term socioeconomic progress. This paper further enhances understanding by analyzing potential disparities in the impact of FDIs on the salaries of male and female employees in the three countries from 1991 to 2021. Examining these nations as case studies provides a distinctive approach to comprehending the effects of FDIs on wage structures, with a particular emphasis on gender equality, given their significant roles in the European foreign investment sector.\u003c/p\u003e \u003cp\u003eThe study adopts a quantitative approach, analyzing data from the World Bank Development Indicators (WBDI) and drawing insights from existing scholarly studies. The methodology involves a comprehensive examination of relevant datasets related to foreign investments and wage levels, utilizing economic models and rigorous statistical analysis. The expected outcomes will significantly contribute to the academic literature, providing fresh perspectives and empirical evidence regarding the impact of FDI on employee compensation in the three countries.\u003c/p\u003e \u003cp\u003eThe paper's structure includes theoretical and empirical reviews in Chap.\u0026nbsp;2, specifics of data and methods in Chap.\u0026nbsp;3, results and discussions in Chap.\u0026nbsp;4, and conclusions with policy recommendations in Chap.\u0026nbsp;5.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Theoretical Review\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Human Capital Theory\u003c/h2\u003e \u003cp\u003eInstitutional economics explores the intricate relationship between education and economic outcomes (Vaizey, 1962; Schultz, 1981; Johnes, 1993). According to human capital theory, investments in people offer economic advantages to both individuals and society, with a crucial distinction between human capital expenditures and consumptive expenditures (Vaizey, 1962). While health and nutrition constitute common forms of human capital investment (Schultz, 1981), empirical investigations often emphasize education as the most crucial area (Schultz, 1963).\u003c/p\u003e \u003cp\u003eThe literature on human capital theory distinguishes various forms and methods of education, including formalized education at different levels, informal education, on-the-job training, and vocational education (Cohn \u0026amp; Geske, 1990; Schultz, 1981; Mincer, 1974; Corazzini, 1967). These diverse forms significantly influence the research design of studies on human capital, with a reasonable assumption that education enhances individuals' economic capabilities in most instances (Schultz, 1971). Due to rapid changes in society, there have been created testing environments for human capital forcing company management into a rapid movement within the \"unknown fields\" (Dervishaj \u0026amp; Neziraj, 2022).\u003c/p\u003e \u003cp\u003eThe extensive body of research highlights the importance of human capital theory. In 1966, Blaug cataloged 792 articles, books, and research projects related to education economics, with the number surpassing 2,000 by 1976 (Blaug, 1970). Notably, the theory's connection to Nobel Prize recognition is remarkable, with five prizes awarded since 1971 to scientists involved in or associated with human capital theory (Becker, 1993; Wright, 1992).\u003c/p\u003e \u003cp\u003eThe Nobel distinction is attributed to key figures in human capital theory, including Theodore W. Schultz and Gary S. Becker, prominent scholars; Milton Friedman and Simon Kuznets (1945), collaborators on a significant article connecting medical professionals' incomes with education investments; and Solow (1957), pivotal in highlighting the relationship between education and the overall production function.\u003c/p\u003e \u003cp\u003eDespite its significance, human capital theory faces criticism for oversimplifying the intricate relationship between education, training, and economic outcomes. The theory falls short in acknowledging various factors impacting earning potential, such as discrimination, economic downturns, and shifts in labor market conditions. Additionally, it assumes easy investment access, overlooking barriers like unequal education and training opportunities that can exacerbate income inequality. The theory predominantly focuses on economic aspects, neglecting the non-market value of education, encompassing personal growth, societal well-being, and cultural development. This oversight results in a failure to consider the positive externalities associated with education and training, which benefit both individuals and society, leading to lower crime rates, improved healthcare outcomes, and overall societal well-being.\u003c/p\u003e \u003cp\u003eHuman capital theory's relevance extends to sustainability and its impact on diminishing gender inequality, particularly concerning foreign direct investment (FDI) on wage dynamics. The theory emphasizes the significance of education and training in enhancing an individual's productivity and earning potential. In the context of gender inequality, investing in women's education and skills development becomes imperative. When FDI aligns with initiatives augmenting education and skills for both male and female workers, it plays a crucial role in narrowing the gender wage gap.\u003c/p\u003e \u003cp\u003eA central tenet of human capital theory is the equitable distribution of human capital investments, with FDI playing a pivotal role in influencing gender equality. FDI offers opportunities for women to access education, training, and employment in traditionally male-dominated sectors, contributing to a more balanced allocation of human capital and reducing wage disparities. Furthermore, human capital theory posits that investments in education and skills development can spur economic growth. When FDI supports sustainable projects that generate employment and enhance human capital, it stimulates economic development in host countries, creating opportunities for women to participate in the labor force and secure higher wages. However, it is crucial to note that the impact of FDI on wage dynamics may not be uniform for both men and women.\u003c/p\u003e \u003cp\u003eHuman capital theory provides a framework for assessing how FDI impacts wage dynamics differently for male and female workers while revealing gender-based wage disparities. FDI typically involves knowledge and skills transfer to workers in the host country, enhancing the productivity of all workers, including women. In cases where FDI projects actively promote gender-inclusive skill transfers, there is potential to reduce gender wage disparities. The theory underscores the importance of acquiring skills in demand in the labor market, creating opportunities for both men and women to access high-paying jobs in industries with a higher demand for skilled labor. This contributes to narrowing the gender wage gap by enhancing women's access to well-paying positions.\u003c/p\u003e \u003cp\u003eInstitutional economics emphasizes that \"institutions matter\" when examining economic systems. These institutions, encompassing both official and informal regulations, play a central role in investigative efforts (Raudla, 2014). The roots of institutional economics trace back to two prominent schools of thought: the German historical school, including figures like Gustav von Schmoller, Wilhelm Roscher, Werner Sombart, and Max Weber, and the American institutionalist school, with notable figures like John Commons, Thorstein Veblen, and Wesley Mitchell (Medema et al., 1999; Rutherford, 1994).\u003c/p\u003e \u003cp\u003eThe New Institutional Economics (NIE) is an interdisciplinary field drawing from economics, law, organization theory, political science, sociology, and anthropology, aiming to provide insights into the institutions shaping social, political, and commercial existence. While it draws from multiple social sciences, its primary framework remains rooted in economics. NIE seeks to clarify the nature of institutions, how they come into being, the purposes they serve, the mechanisms behind their evolution, and whether alterations are necessary.\u003c/p\u003e \u003cp\u003eThe term \"institutional economics\" was initially associated with scholars like Thorstein Veblen, John R. Commons, Wesley C. Mitchell, and Clarence Ayres. Despite the diversity in their work, it centers around key themes involving critiques of conventional economics, shifting the focus from individual to collective actions, embracing an \"evolutionary\" approach to the economy, and prioritizing empirical observation over deductive reasoning (Seckler, 1975; Gruchy, 1972; Langlois, 1989).\u003c/p\u003e \u003cp\u003eRichter (1996) delves into the German origins of American institutionalism, revealing significant contributions by earlier institutionalist thinkers. However, many contemporary economists remain unfamiliar with these contributions, exemplified by the dismissive treatment of Coase (1984) who was often regarded as having little more to offer than descriptive material awaiting a theoretical framework.\u003c/p\u003e \u003cp\u003eWilliamson (1975) introduced the term \"new institutional economics\" (NIE), rooted in Coase's analysis of the firm (1937), Hayek's discussions on knowledge (1937, 1945), and Chandler's examination of industrial enterprise (1962). Notable contributions also came from scholars like Simon (1947), Arrow (1963), Davis and North (1971), Alchian and Demsetz (1972), Williamson (1973), and others (1971). Prominent figures associated with NIE include Coase, Williamson, and North, with additional work by scholars like Eggertsson (1990), Furubotn and Richter (1991), Coase (1992), Werin and Wijkander (1992), Macneil (1978), Holmstr\u0026ouml;m (1979), and others.\u003c/p\u003e \u003cp\u003eThe new institutional economics, much like its predecessor, focuses on examining social, economic, and political institutions governing daily lives. However, it takes a different approach by distancing itself from the holistic perspective of the older school, adhering to a form of methodological individualism. NIE recognizes the importance of social phenomena but frames explanations in the context of individuals' goals, plans, and behaviors. Despite this, it acknowledges social phenomena such as corporate culture and organizational memory, regarding them as subjects to be explained rather than the basis for explanations.\u003c/p\u003e \u003cp\u003eNIE differs from orthodox neoclassical economics, emphasizing the need for policy analysis guided by \"comparative institutional analysis\" (Coase, 1964). Institutional economics plays a crucial role in understanding the connection between sustainability and the reduction of gender inequality, especially when assessing the effects of foreign direct investment (FDI) on wage dynamics. This field underscores the importance of institutions, encompassing both formal laws and regulations and less tangible aspects like informal norms, customs, and organizational structures. When scrutinizing gender inequality, understanding the institutional framework within the host country becomes imperative, influencing efforts to diminish gender inequality.\u003c/p\u003e \u003cp\u003eInstitutional economics underlines the paramount importance of property rights and contracts in facilitating economic transactions, crucial when examining the influence of FDI on wage dynamics. Safeguarding property rights and enforcing labor contracts are pivotal in ensuring equitable wages and working conditions, irrespective of gender. Different nations have diverse regulatory frameworks pertaining to labor and gender equality, impacting both FDI and wage dynamics. Institutional economics also considers the evolution of institutions over time.\u003c/p\u003e \u003cp\u003eThe study of sustainability often involves evaluating whether FDI leads to alterations in host country institutions fostering gender equality. Institutional economics recognizes the significant influence of cultural norms and social capital on economic outcomes. When investigating gender inequality and FDI, understanding the cultural context is crucial, as different norms can impact how women are treated in the workforce, affecting wage dynamics. Institutional economics assists in uncovering power imbalances within institutions, a key driver of gender inequality. FDI can either exacerbate or mitigate power imbalances, and comprehending these dynamics is crucial for a thorough analysis of gender-related impacts. Sustainability requires assessing the long-term impact of FDI-induced changes in wage dynamics, a task facilitated by institutional economics.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Empirical review\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Role of FDI in an economy\u003c/h2\u003e \u003cp\u003eFDI Foreign Direct Investment (FDI) refers to the establishment of a long-term stake in a foreign enterprise by an entity residing in a different country, implying a durable relationship between the investor and the invested enterprise (IMF, 2005). FDIs exert significant influence over the management of the invested enterprise and involve initial and subsequent capital transactions, including those among related businesses, reflecting a net inflow of new investments from foreign investors into the reporting economy as a ratio to the country's gross domestic product.\u003c/p\u003e \u003cp\u003eFDIs play a crucial role in stimulating economic growth, technological advancement, and job creation in host countries. These investments offer advantages such as capital infusion, technology transfer, managerial expertise, and access to new markets (Sergiu et al., 2023). Particularly in developing countries, FDIs serve as a significant source of external funds, catalyzing domestic investment, enhancing productivity, and fostering innovation. Furthermore, they contribute to the creation of employment opportunities, reducing unemployment rates and improving living standards (Frenkel et al., 2004; Vujanović et al., 2021).\u003c/p\u003e \u003cp\u003eIn addition to promoting economic growth, FDIs play a pivotal role in fostering global integration and promoting international trade. These investments bring valuable experience and extensive networks, facilitating connections between local businesses and global markets, leading to increased exports, import substitution, and supply chain development (G\u0026ouml;tz \u0026amp; Jankowska, 2022). Moreover, FDIs contribute significantly to human capital development by offering training and skill enhancement opportunities to the local workforce, bolstering their competitiveness in the global job market (Stack et al., 2017).\u003c/p\u003e \u003cp\u003eFDIs shape the economic landscape by influencing critical aspects such as job creation, technology transfer, productivity growth, market competition, and overall economic development. They act as magnets for attracting foreign capital, knowledge, skills, and resources, leading to increased investment, industrial expansion, and integration into the global economy (Bellak et al., 2008; Villaverde \u0026amp; Maza, 2015). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a concise summary of empirical studies on FDIs and their impact on economic variables.\u003c/p\u003e \u003cp\u003eThe impact of FDIs on wage inequality is a topic of research, and findings can be categorized into four areas:\u003c/p\u003e \u003cp\u003eNeutral Impact on Wage Inequality: Some studies suggest that FDI has no discernible impact on wage inequality, indicating that foreign capital introduction does not significantly alter wage disparities among local workforces. Local labor market dynamics and government policies may play more substantial roles in shaping wage structure outcomes (IMF, 2005).\u003c/p\u003e \u003cp\u003eReduction in Wage Inequality: Research demonstrates that FDI can reduce wage inequality, especially when it facilitates technology transfer, skill development, and productivity enhancement. Such investments contribute to higher wages for the entire workforce, particularly in industries where FDI results in skill improvements (IMF, 2005).\u003c/p\u003e \u003cp\u003eIncrease in Wage Inequality: Certain studies propose that FDI can exacerbate wage inequality, especially in sectors relying heavily on highly skilled workers. Skilled workers may witness significant wage increases due to foreign investments, leading to a widening gap in wage disparities between skilled and unskilled laborers (IMF, 2005).\u003c/p\u003e \u003cp\u003eNon-linear Effect on Wage Inequality: Some studies suggest a non-linear relationship between FDI and wage inequality, indicating the presence of a critical threshold or tipping point. When FDI reaches a certain level, it triggers structural changes in the labor market or industry dynamics, disproportionately affecting wage disparities (IMF, 2005).\u003c/p\u003e \u003cp\u003eUnderstanding these relationships is crucial for crafting effective economic policies in FDI-receiving countries. In conclusion, while FDIs bring significant benefits to host countries, their impact on wage inequality is complex and context-dependent, requiring careful consideration of various factors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of a representative empirical studies on FDI and other economic variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor (s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFindings on FDI and impacts\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBhandari (2007), Franco, Gerussi (2013), Yuldashev (2023), Wang et al (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDI on income inequality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuo et al (2023), Sergiu et al (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDI and gender inequality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChidlow, Salciuviene, Young (2009), Spies (2010), Zhang, Kim (2022), Zhang et al (2023).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDI and wage gap (skilled and unskilled)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBellak, Leibrecht, Riedl (2008), Villaverde,\u003c/p\u003e \u003cp\u003eMaza (2015); Qiao, Fung, Fung, Ma (2022),\u003c/p\u003e \u003cp\u003eSinha et al (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDIs on employment\u003c/p\u003e \u003cp\u003egeneration, technology transfer, productivity\u003c/p\u003e \u003cp\u003egrowth, market competition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlalock, Gertler (2008); Javorcik, Spatareanu (2008), Gorodnichenko, Svejnar, Terrell (2014), Sokhanvar (2023), Santos, E. (2023).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDIs and productivity and\u003c/p\u003e \u003cp\u003ecompetitiveness in the host economy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Research Gap\u003c/h2\u003e \u003cp\u003eWhile previous studies link FDI to income inequality, a consensus on its impact on wage disparities remains elusive. FDI's effect on wage inequality is complex, influenced by factors like the host country's economic structure, FDI attributes (e.g., skill requirements, sector concentration), labor market conditions, and government policies. Conflicting research findings highlight the need for context-specific analyses to comprehend how FDI shapes wage inequality in distinct regions or industries. Recognizing this intricate relationship underscores the necessity for tailored policies and strategies to manage foreign investment's effects on income inequality. Further research on the FDI-income inequality link within specific contexts is imperative.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Materials and methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Data\u003c/h2\u003e\n \u003cp\u003eThis study uses 30 years of WBDI database for Germany, Austria, and the Netherlands, focusing on FDI and the percentages of male and female waged and salaried workers. These countries were chosen due to their unique labor dynamics, commitment to sustainability, and dedication to gender equality. Germany, a key EU and global trade player, offers insights into FDI\u0026apos;s impact on labor dynamics and gender equity. Austria\u0026apos;s socio-economic stability aligns with the study\u0026apos;s emphasis on FDI and sustainable development. The Netherlands, with innovative sustainability practices and a commitment to gender equality, provides valuable insights into FDI\u0026apos;s influence on labor dynamics and gender equality.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Methods\u003c/h2\u003e\n \u003cp\u003eThis paper utilizes three distinct regression models to explore the relationships between wages and the FDI for females and males in Germany, Austria, and Netherlands. These models enhance the understanding of the intricate dynamics at play in the study\u0026apos;s context.\u003c/p\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1 Variable Description\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMeasurement\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\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYear variable (1991\u0026ndash;2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage of waged and salaried females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePercentage of waged and salaried females\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFDI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eForeign Direct Investment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumeric\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003e3.2.2 Model 1: Assessing the impact of previous FDI levels and past wage levels on current wages\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eModel (\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e) examines the connections between current and past FDI levels and their impact on present wages. This model offers a comprehensive view of economic systems, especially in the context of financial interactions with foreign entities. It delves into the influence of historical foreign investments on the current economic landscape and considers the effect of past wage levels, revealing how historical labor market dynamics affect the present. This holistic approach is vital for policymakers and researchers aiming to grasp wage trends and economic stability intricacies. By quantifying these relationships, Model 1 helps assess the importance of past conditions on current wages, aiding in informed economic policy decisions and sustainable socioeconomic progress strategies.\u003c/p\u003e\n \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equ1\" class=\"mathdisplay\"\u003e$$\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}}={{\\beta }}_{0}+{{\\beta }}_{1}\\cdot \\text{F}\\text{D}{\\text{I}}_{\\text{t}}+{{\\beta }}_{2}\\cdot \\text{F}\\text{D}{\\text{I}}_{\\text{t}-1}+{{\\beta }}_{3}\\cdot \\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-1}+{\\text{ϵ}}_{\\text{t}},$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e is wage at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{t}, \\text{F}\\text{D}{\\text{I}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e is foreign direct investment at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{t}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{F}\\text{D}{\\text{I}}_{\\text{t}-1}\\)\u003c/span\u003e\u003c/span\u003e is lagged values of foreign direct investment at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{t}-1, \\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-1}\\)\u003c/span\u003e\u003c/span\u003e is lagged values of wage at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{t}-1\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({{\\beta }}_{0}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({{\\beta }}_{1}\\)\u003c/span\u003e\u003c/span\u003e, \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 are regression coefficients.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3 Isolating the effect of historical FDIs on past wages\u003c/h2\u003e\n \u003cp\u003eModel (\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e) explores the link between previous FDI levels and past wage outcomes while excluding the current year\u0026apos;s FDIs. This unique approach isolates the influence of historical FDIs on wage trends over time. By removing the present-year FDIs, Model 2 investigates how past investments have shaped wage dynamics. This analysis helps answer questions about the lasting impact of historical FDIs on wages, potential patterns over time, and critical lags in their effects. This nuanced approach aids policymakers and economists in understanding the temporal dimension of FDI\u0026apos;s impact on wages, offering insights to guide strategies for sustainable socioeconomic progress.\u003c/p\u003e\n \u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equ2\" class=\"mathdisplay\"\u003e$$\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}}={{\\beta }}_{0}+{{\\beta }}_{1}\\cdot \\text{F}\\text{D}{\\text{I}}_{\\text{t}-1}+{{\\beta }}_{2}\\cdot \\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-1}+{\\text{ϵ}}_{\\text{t}},$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mathbf{W}\\mathbf{a}\\mathbf{g}{\\mathbf{e}}_{\\mathbf{t}-1}\\)\u003c/span\u003e\u003c/span\u003e, Lagged Wage Levels for t-1, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mathbf{F}\\mathbf{D}{\\mathbf{I}}_{\\mathbf{t}-1},\\)\u003c/span\u003e\u003c/span\u003eLagged FDI Levels for t-1, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\beta }}_{0}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\beta }}_{1}\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\beta }}_{2}\\)\u003c/span\u003e\u003c/span\u003e are regression coefficients.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.4 Investigating the influence of current FDI levels and lagged wage levels on current wage outcomes\u003c/h2\u003e\n \u003cp\u003eModel (\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e) analyzes the relationship between current FDI levels and previous wage levels, focusing on their impact on present wages. This model isolates the immediate effects of current FDI inflows on the most recent wage trends while excluding the influence of lagged FDIs. This understanding is crucial for policymakers and businesses, providing insights into the direct impact of new investments on wage dynamics without historical FDI interference. The findings from Model 3 can guide strategic decision-making, especially in regions committed to sustainable socioeconomic development. Identifying how current FDIs shape contemporary wages aids in refining strategies for equitable wage growth and progress, contributing to a deeper understanding of foreign investments\u0026apos; role in labor market dynamics and offering actionable insights for societal prosperity.\u003c/p\u003e\n \u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\n \u003cdiv id=\"FileID_Equ3\" class=\"mathdisplay\"\u003e$$\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}}={{\\beta }}_{0}+{{\\beta }}_{1}\\cdot \\text{F}\\text{D}{\\text{I}}_{\\text{t}}+{{\\beta }}_{2}\\cdot \\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-1}+{\\text{ϵ}}_{\\text{t}}$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003e,\u003c/p\u003e\n \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}} \\text{i}\\text{s} \\text{t}\\text{h}\\text{e}\\)\u003c/span\u003e\u003c/span\u003ecurrent Wage Levels, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{F}\\text{D}{\\text{I}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e is the current FDI levels, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-1}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{W}\\text{a}\\text{g}{\\text{e}}_{\\text{t}-2}\\)\u003c/span\u003e\u003c/span\u003eare Lagged Wage Levels.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Case of Germany\u003c/h2\u003e \u003cp\u003eIn this section we present regression results. For each country we present three models for males and females.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis for the effects of FDIs on the wages of female and male workers in Germany\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-9.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(9.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(9.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(9.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(6.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(6.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWage_t_1_female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWage_t_1_male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.98 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eNote\u003c/b\u003e: The '***' indicates that this coefficient is statistically significant at the 1% level (very significant).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe regression analysis in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e explores the relationship between FDI levels and wage dynamics in Germany for both male and female workers. Model 1: The model reveals that while current FDI (FDI_t) and lagged FDI (FDI_t_1) have positive coefficients, suggesting a marginal positive impact on the current wage, these effects are not statistically significant. In contrast, female (Wage_t_1_female) has a highly significant positive effect on the current wage, resulting in a substantial increase. The model explains a significant portion of the variance in the current wage, with a high R-squared value of 0.81. Model 2 and 3: These models confirm a non-significant impact of both current and lagged FDI on the current wage. However, the significant positive effect of female on the current wage remains consistent across all three models. Model 2 has a slightly higher R-squared value of 0.83, while Model 3 has an R-squared value of 0.81. Implying FDI is not contributing to closing the wage gap in Germany in the current state.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Case of Austria\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis for the effects of FDIs on the wages of female workers in Austria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(8.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(8.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(8.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.03 *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.03 *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWage_t_1_female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWage_t_1_male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.89 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eNote\u003c/b\u003e: The '***' indicates that this coefficient is statistically significant at the 1% level (very significant).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: Regression analysis for the effects of FDIs on the wages of female workers in Austria. Both current-year FDI (FDI_t) and lagged FDI (FDI_t_1) consistently exhibit negative coefficients of -0.03 in all models. This implies that higher FDI levels are associated with a decrease in the current wage for female workers in Austria, contrary to the expected positive impact of FDI on wages. This unexpected relationship may suggest that FDI is directed toward sectors with lower-wage employment or introduces wage competition through foreign firms. However, a notable observation is the variable Wage_t_1_female, which consistently holds a positive coefficient of approximately 0.94 in all models. This suggests that an increase in the wages of female workers in the previous year significantly boosts the current wage, highlighting the positive influence of gender pay equity and women's participation in the labor force on wage dynamics in Austria. The models exhibit strong goodness of fit, particularly Models 1 and 3, with high R-squared values of around 0.95, indicating that approximately 95% of the variation in the current wage can be explained by the independent variables. Model 2 also demonstrates a robust fit with an R-squared of 0.94. Adjusted R-squared values further validate the models' overall good fit.\u003c/p\u003e \u003cp\u003eFor male workers in Austria, both current-year FDI (FDI_t) and lagged FDI (FDI_t_1) consistently show negative coefficients, indicating that higher FDI levels are linked to lower current wages. This suggests a potential wage suppression effect resulting from increased FDI, and this relationship is statistically significant. Additionally, male workers in the previous period (Wage_t_1_male) are strongly associated with higher current wages, implying a gender-based wage differential favoring males in the Austrian labor market. All models have relatively high R-squared values (explaining 77\u0026ndash;79% of wage variability), indicating a good fit. However, the non-significant intercept in Model 1 suggests the presence of unaccounted-for factors influencing current wages, warranting further exploration. In summary, these models reveal the potential wage-suppressing effect of FDI on male workers in Austria and underscore gender-based wage disparities. While providing valuable insights, additional variables may be necessary for a comprehensive understanding of wage dynamics in Austria.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Case of the Netherlands\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis for the effects of FDIs on the wages of female workers in Netherlands\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(8.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(8.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(2.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFDI_t_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWage_t_1_female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWage_t_1_male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.95 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96 ***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdj.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\mathbf{R}}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNum. obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eNote\u003c/b\u003e: The '***' indicates that this coefficient is statistically significant at the 1% level (very significant).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the regression analysis for the impact of FDIs on the wages of female workers in the Netherlands. In this context, the results suggest that FDI has limited direct influence on current wage dynamics, while gender-related factors play a significant role. Model 1 reveals a negligible coefficient for the current year's FDI (FDI_t), indicating minimal impact on the current wage. In this dataset and context, the current level of FDI does not significantly influence wage levels for workers in the Netherlands. Model 2 focuses on lagged FDI (FDI_t_1) and indicates that a higher level of lagged FDI is associated with a decrease in the current wage. This negative coefficient suggests that historical trends in FDI might influence wage dynamics, contributing to lower current wages.\u003c/p\u003e \u003cp\u003eSimilarly, Model 3 also shows a negative coefficient for the current year's FDI (FDI_t), implying a decrease in the current wage with higher current year's FDI. This reinforces the notion that the level of FDI in the current year does not positively impact wages in the Netherlands. Additionally, the positive coefficient for Wage_t_1_female in all models suggests that females with higher wages in the previous year positively influence the current wage. This implies some persistence in wage dynamics for females, with higher past wages leading to higher current wages. The R-squared values, indicating approximately 77\u0026ndash;78% of the variation in the current wage explained by independent variables in all three models, suggest that despite FDI having limited direct impact, the models provide a reasonably good explanation of wage dynamics in the Netherlands.\u003c/p\u003e \u003cp\u003eModel 1 highlights the influence of both past FDI levels and past wages for males on wage dynamics in the Netherlands. The positive coefficients for lagged FDI from the previous year and lagged male wages indicate their positive impact on the current wage. However, the impact of FDI is relatively small, with coefficients of 0.02 for current FDI and 0.03 for lagged FDI, suggesting a modest role compared to other factors. Model 2, excluding current FDI (FDI_t) and focusing on lagged FDI (FDI_t_1) and lagged male wages, produces consistent results, emphasizing the positive impact of lagged FDI on the current wage even when excluding the influence of current-year FDI. Model 3 further simplifies the analysis by excluding lagged FDI (FDI_t_1) and considering only current FDI (FDI_t) and lagged male wages. Once again, the results align with the previous models, indicating that both current FDI and lagged male wages positively influence the current wage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Summary of Results\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Germany\u003c/h2\u003e \u003cp\u003eThe research findings shed light on the intricate relationship between Foreign Direct Investment (FDI) and wage dynamics in Germany. Surprisingly, the study suggests that FDI levels do not seem to exert a substantial immediate impact on wage adjustments, regardless of the worker\u0026rsquo; gender. This finding challenges the conventional wisdom that FDI directly correlates with wage increases. In contrast, the research underscores the pronounced influence of gender on wage dynamics within the German workforce. Notably, female employees experience more significant wage hikes in comparison to their male counterparts. Several factors contribute to this gender-based wage differential, including the efficacy of wage equality policies in the country, the ever-evolving labor market dynamics, and the distribution of job roles among men and women. These results emphasize the multifaceted nature of wage dynamics, highlighting the complex interplay of factors, especially gender, in shaping the earnings landscape within the German labor market. Understanding these dynamics is crucial for devising policies that foster equitable wages, promote gender equality, and ensure economic opportunities for all workers in Germany. It also challenges preconceived notions about the relationship between FDI and wage dynamics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Austria\u003c/h2\u003e \u003cp\u003eThe results of this study reveal a surprising and unexpected negative impact of Foreign Direct Investment (FDI) on female wages in Austria. This finding raises important questions and underscores the need for more in-depth investigation. The study highlights the positive influence of female workers' wages on the overall wage structure, emphasizing the critical role of gender equality in the labor market. The robust model fit, as indicated by relatively high R-squared values (explaining 77\u0026ndash;79% of wage variability), lends strong credibility to these conclusions, and offers valuable insights into the complex dynamics of wages concerning FDI and gender-related factors. However, it is noteworthy that Model 1 shows a non-significant intercept, suggesting the existence of unaccounted-for variables that impact current wages, necessitating further exploration. In summary, these models shed light on the potential wage-suppressing effects of FDI on male workers in Austria and underscore the presence of gender-based wage disparities. While these insights are valuable, a more comprehensive understanding of wage dynamics in Austria may require the incorporation of additional variables and further research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e4.3.3 Netherlands\u003c/h2\u003e \u003cp\u003eIn the context of the Netherlands, the research findings indicate that Foreign Direct Investment (FDI) appears to have limited direct influence on wage dynamics, especially within the current year. Instead, other factors such as gender disparities and historical wage levels seem to exert a more substantial impact on explaining the variations in present-day wages. It is worth noting that while FDI, both in the current period and in the past, does contribute positively to wage dynamics, its effect is relatively modest when compared to the historical wages of male workers. These results shed light on wage dynamics in the Netherlands, emphasizing the pivotal role of domestic labor market conditions, with a particular focus on male wages. Policymakers and businesses keen on comprehending the forces behind wage fluctuations in the country can benefit from this insight, directing their strategies and decisions towards addressing the factors that hold more sway in the Dutch labor market.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe study explores the relationship between FDIs and wage dynamics in Germany, Austria, and the Netherlands, with a specific focus on reducing gender inequalities. These countries are chosen for their diverse labor dynamics, sustainability commitments, and gender equality situations. Using data from 1991 to 2021 sourced from the World Bank Development Indicators database, the research aims to illuminate how FDIs shape wage patterns and impact gender-based wage disparities. Employing various linear regression models, the study quantitatively assesses the link between current and lagged wages for different genders, contributing to the existing literature on wage inequality, foreign direct investment, and gender disparities.\u003c/p\u003e \u003cp\u003eA significant finding reveals that FDIs account for over 70% of wage differences in the selected countries, indicating a linear association between FDIs and salaries. This aligns with Sergiu et al.'s (2023) discovery that around 86% of wage variation is explained by FDIs in Germany and Austria from 1992 to 2019. The implications highlight the substantial role of FDIs in shaping wage dynamics and emphasize the potential impact of foreign investments on reducing gender inequalities. While FDIs stimulate economic growth and job creation, the study suggests they can also exacerbate wage disparities, possibly due to factors like foreign investors seeking lower labor costs or favoring industries with gender-based wage gaps (Le et al., 2021).\u003c/p\u003e \u003cp\u003eThe study underscores the influence of economic globalization, particularly through FDIs, on gender wage disparities, prompting consideration of trade-offs between economic growth and gender equality. Policymakers are urged to formulate policies addressing the impact of FDIs on gender wage disparities, striking a balance between reaping the benefits of foreign investments and mitigating potential negative effects on wage inequality.\u003c/p\u003e"},{"header":"6. Conclusions and policy implications","content":"\u003cp\u003eThe study offers insights into the relationship between FDIs and wage dynamics in Germany, Austria, and the Netherlands, with a focus on reducing gender inequalities. Results show that FDIs account for over 70% of wage differences in these nations, emphasizing their significant role in shaping wage patterns and addressing gender disparities. However, FDIs can potentially exacerbate wage inequalities, especially when leading to lower labor costs or concentrating in industries with existing gender-based wage gaps.\u003c/p\u003e \u003cp\u003eTo combat gender wage inequality, a multifaceted approach is crucial. Governments should strengthen and rigorously enforce gender-equal pay regulations, ensuring women receive equal compensation for equivalent work. Companies must take proactive measures to close the persistent gender wage gap, fostering a more equitable work environment. Simultaneously, policymakers should champion equal opportunities, creating an environment where high-paying jobs are accessible without discrimination. This involves enhancing access to education and training, while dismantling hiring biases obstructing women's entry into well-paying positions.\u003c/p\u003e \u003cp\u003eTransparency in wage data is vital in battling gender disparities. Encouraging companies to disclose gender-based wage gaps help identify and rectify discrepancies, foster accountability, and fair compensation practices.\u003c/p\u003e \u003cp\u003eGovernments and international organizations can support gender equality by incentivizing sustainable FDIs. Offering tax benefits or other inducements to companies committed to fair wages and gender-inclusive policies aligns business interests with societal objectives, promoting progress toward a just labor market. Policymakers, navigating the complexities of FDIs, should diligently weigh trade-offs between economic growth and gender equality. Balancing these interests is imperative to foster an environment where growth and equality coexist.\u003c/p\u003e \u003cp\u003eComprehensive workforce development initiatives play a pivotal role in empowering women. Enhancing the skills and employability of the female workforce, especially in male-dominated industries with pronounced wage disparities, is essential. These initiatives may include training programs, mentorship, and support systems to help women access and thrive in high-paying roles.\u003c/p\u003e \u003cp\u003eThe research for gender wage equality requires ongoing research to uncover intricate mechanisms through which FDIs influence wages. Further exploration is necessary to ascertain whether the study's findings hold true in different national and regional contexts. Policymakers should actively endorse and commission research efforts, creating an evidence-based foundation for policy decisions driving gender equality in the labor market.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e Code and data can be found on https://osf.io/bpk2t/files/osfstorage and upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlchian, Armen A. 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Does foreign direct investment affect wage inequality in Chinese manufacturing sector? \u003cem\u003eApplied Economics Letters\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(1), 80-83.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Berlin School of Business and Innovation","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":"Foreign Direct Investment, Gender Inequality, Labor dynamics, Wage Dynamics, Sustainability goals","lastPublishedDoi":"10.21203/rs.3.rs-3936840/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3936840/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the relation between foreign direct investments (FDI) and wage dynamics in Germany, Austria, and the Netherlands, aiming to develop a sustainable roadmap for reducing gender inequalities. Selected for their diverse labor dynamics, sustainability commitments, and gender equality situations, these countries serve as ideal case studies. Data spanning 1991 to 2021 on FDI and the percentage of gender-based workers were collected from the World Bank Development Indicators. Employing various linear regression models, our research examines the relationship between current and lagged wages for different genders, shedding light on how FDIs may influence wage patterns, especially regarding gender inequality. The quantitative study affirms the model's robustness, revealing a clear linear association between FDIs and salaries in these nations. This underscores the potential impact of foreign investments on wage dynamics, providing a foundation for addressing and reducing gender inequalities.\u003c/p\u003e\n\u003cp\u003eJEL Classification: F23, J31, O15\u003c/p\u003e","manuscriptTitle":"Roadmap towards gender equality: analyzing the influence of foreign direct investment on wage dynamics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-09 17:13:52","doi":"10.21203/rs.3.rs-3936840/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":"d26357bd-c9bc-4782-81a4-09c340947fe8","owner":[],"postedDate":"February 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28630107,"name":"Econometrics"},{"id":28630108,"name":"Macroeconomics"}],"tags":[],"updatedAt":"2024-02-09T17:13:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-09 17:13:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3936840","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3936840","identity":"rs-3936840","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}