The Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience

The Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience | 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 The Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience SALISU, Temitope Quadri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5437681/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 The study examines the impact of trade openness on economic growth and development in Nigeria from 1980 to 2021. The variables used in the study include the proxy of capital and labour, trade openness, exchange rate, and import and foreign reserves. A different diagnostic test was carried out which included correlation, unit root test and Autoregressive Distributed Lag. Descriptive statistics was used to examine if the explanatory variables and the dependent variable exhibit time-varying volatility and leptokurtosis characteristics. The Augmented Dickey-Fuller (ADF) unit root test was also carried out to check the long-run and short-run relationship of the variables while Аutоrеgrеssіvе dіstrіbutеd lаg (АRDL) bоunds tеstіng рrосеdurе and standardised beta was used to achieve the two specific objectives that were set. The АRDL bоunds tеstіng рrосеdurе revealed that the proxy of capital and labour is the only variables that determine economic growth and development in Nigeria, but trade openness has a positive insignificant effect on economic growth and development in Nigeria. Also, in the short run, the variables that significantly determine economic growth and development are the proxy of capital and labour, exchange rate and import. International Economics Trade Openness Economic Growth Economic Development Autoregressive Distributed Lag Figures Figure 1 Figure 2 INTRODUCTION Nigeria has undergone significant transformations in its trade policies, economic expansion, and financial advancement in recent years, positioning it as a leading African economy. The economic landscape of Nigeria has prominently featured trade openness, characterised by the adoption of liberalized trade policies and increased involvement in international trade (Moyo, Kolisi, & Khobai 2017). Concurrently, the nation has experienced phases of substantial economic expansion driven by diverse industries, including oil, agriculture, and services. These advancements have spurred efforts to enhance the financial industry and streamline its progress. However, trade has been an area of interest to policymakers as well as economists. It enables nations to sell their domestically produced goods to other countries of the world. It has been regarded as an engine of growth which leads to steady improvement in human status by expanding the range of people's standard of living and preferences (Adewuyi, 2002). The pivotal roles financial development and trade openness play in bolstering economic growth across countries cannot be overemphasised. International trade theories posit that differences in technology, factor endowments, and economies of scale, among others, across countries are the main sources of comparative advantage and determinants of trade patterns. Moreover, it has been argued that financial development is a potential source of comparative advantage to an economy, thus it can facilitate trade (Ijirshar, 2019; Baldwin, 1989). Intuitively, a country with a relatively well-regulated, well-developed and efficient financial sector has a comparative advantage in sectors that depend on external financing. Hence, countries with well-developed financial sectors should experience greater volumes of international trade (Ajayi & Araoye 2019; Keho 2017; Omoke & Opuala–Charles 2021). This accounts for the great volume of trade witnessed in China, Germany, the United States, and the United Kingdom, among other developed countries of the world. Thus, to experience greater volumes of international trade, it is expedient that each country especially developing economies aim at having a well-regulated and competitive financial sector. Structural barriers, such as infrastructural deficiencies, regulatory bottlenecks, and institutional limitations, may impede the effective utilisation of trade opportunities. Understanding how these factors interact with trade openness is crucial for developing targeted interventions that promote economic development (Ohwofasa & Ekaruwe 2023). Persistent trade imbalances and a reliance on a restricted array of export commodities pose substantial threats to Nigeria's sustainable economic growth. It is imperative to delve into the intricacies of how trade openness influences economic diversification and aids in ameliorating trade imbalances for enduring stability. The vulnerability arising from an overdependence on a limited set of exports necessitates a nuanced exploproxyn of policies that can foster a more diversified and resilient economic landscape (Atoyebi et al., 2024). Additionally, Nwadike et al., (2020) reveal that the impact of heightened trade openness on domestic industries requires meticulous scrutiny. The dynamics of competition, the transfer of technology, and shifts in employment patterns demand a comprehensive examination to ascertain the potential ramifications for local businesses. Crafting policies that strike a delicate balance between openness and safeguarding domestic interests becomes indispensable in navigating the complexities of globalization, ensuring that increased trade benefits local industries without compromising employment or technological advancement (Khobai et al., 2018). This multifaceted analysis is critical for policymakers striving to create an economic environment that is both open to global trade and protective of domestic economic interests (Omoke & Opuala–Charles 2021). The relationship between trade openness and economic growth has been the subject of extensive research and debate in economic literature (Oppong-Baah et al., 2022). The Nigerian government has made several efforts toward developing its financial sector as reflected in the different reforms in the sector over time even though there has been inconsistency in implementing the policies (Afolabi 2022; Yakubu & Akanegbu 2018). These policy reforms were aimed at maintaining a stable, well-regulated, and competitive financial sector. 1.1 OBJECTIVE OF THE STUDY The objective of this study is to examine the impact of trade openness on economic growth and development. The specific objectives are to examine the causal relationship between trade openness and economic growth in Nigeria. Also, to determine the long-run relationship between trade openness and economic growth and development in Nigeria LITERATURE REVIEW 2.1 Rationale for Trade Openness in Nigeria Nigeria is a member of several bilateral and multilateral organisations, which has aided her global integration efforts and facilitated foreign capital inflows into the domestic economy. Because of this, the economy has put in place several incentives and regulations to promote trade openness as a prelude to luring in much-needed FDI inflows for economic development (Dauda, 2007). According to World Bank Development Indicators (WDI) (2021), Nigeria attracted approximately $89,570.52 million in FDI inflows with an average of 1.41 per cent from 1996 to 2020. It is expected that these capital inflows will boost socio-economic activities; however, taking the trade as a percentage of GDP as an example, the average is 36.63 per cent, which is far below expectations, especially when compared to countries such as South Africa, which has traded as a percentage of GDP at 51.59 per cent, Egypt at 46.37 per cent, Kenya at 48.89 per cent, and Rwanda at 38.73 per cent. In terms of economic performance, GDP growth averaged 4.87 per cent, which is still below the level that can generate significant economic performance indicators and is one of the reasons why unemployment (percentage of the total labour force) and inflation averaged 5.00 per cent and 12.21 per cent, respectively. 2.1.1 Trend of Trade Openness in Nigeria The trend of trade openness in Nigeria values exhibit fluctuations over time, with periods of increase followed by periods of decline. From 1980 to the mid-1980s, trade values remained relatively low, with fluctuations but no clear trend. A notable increase in trade is observed in the late 1980s, particularly in 1987 and 1989, suggesting a period of economic expansion or increased international trade activity (Ajayi & Araoye 2019). Trade values experienced a downturn in the early 1990s, followed by a gradual recovery and subsequent fluctuations throughout the decade. The late 1990s and early 2000s witnessed another period of growth in trade values, peaking around 2001. However, subsequent years saw fluctuations in trade values, with no clear long-term trend evident. Towards the end of the time series (2015-2021), trade values appear to stabilise at lower levels compared to the peak years. 2.2 Trade Openness and Economic Growth Recent studies have investigated both regional and individual country experiences, incorporating other institutional, social, economic, and technological factors. The analysis of the growth of exports and imports indicates the extent of the openness of an economy (Keho 2017). However, trade flow analysis provides the basis of a robust empirical investigation of the openness of an economy. Empirically, openness can be measured by the share of trade (import plus export) in total output, measured by the Gross Domestic Product (GDP). This is a broad concept of openness; in the narrow context, the proxy of imports or exports to GDP can represent the degree of openness of an economy. The statistics show that the Nigerian economy has been relatively more open since 1986, as a result of policy measures applied under the structural adjustment programme. The broad measure of openness, total trade to GDP (TT/GDP) increased from 0.21 in 1986 to 0.64 in 1987 as a result of the consistent implementation of adjustment measures (Huchet‐Bourdon et al., 2018). 2.2.1 Trend of Trade Openness and Growth of Gross Domestic Product The relationship between trade and economic growth indicates a consistent positive correlation, where fluctuations in trade values tend to correspond with changes in Gross Domestic Product (GDP) growth rates. During periods of heightened trade activity, evidenced by higher trade values, there is typically a concurrent increase in GDP growth rates. Conversely, when trade values decrease, as observed during certain periods such as the early 1980s, mid-1990s, and mid-2010s, there is often a subdued growth rate of GDP. The impact of trade fluctuations on GDP growth is evident in historical trends. Declines in trade values, particularly during the early 1980s and mid-1990s, were accompanied by decreases in GDP growth rates. Conversely, periods of increased trade values, such as in the late 1990s and early 2000s, coincided with upsurges in GDP growth rates. 2.3 THEORETICAL REVIEW Heckscher-Ohlin (H-O) Theory According to Heckscher and Ohlin's 1993 theory, a country should export those employing more factors with which it is better endowed, in that it has comparative advantages in both production and exports. The theory is mainly composed of two significant theories, namely: the Heckscher-Ohlin theory and the factor price equalisation theorem (Bajona & Kehoe 2010). The Heckscher-Ohlin theorem, one which explains the various determinants of comparative cost differences in production, says a country enjoys a comparative advantage in producing a certain commodity if its relatively abundant factor is used more intensively. On the contrary, the theory of factor price equalisation discusses the effects of international trade on the prices of factors and states that it completely and relatively equalises factor prices across countries and thus replaces the requirement of global factor mobility (Brondino 2023). Heckscher-Ohlin's theory postulates that "A country will export those goods whose production requires abundant factors of its endowments and import those goods whose production requires scarce factors of its endowment." "A capital-abundant country will export the capital-intensive good while the labour-abundant country will export the labour-intensive good," is how the two-factor case is stated. RESEARCH METHOD The study utilised Heckscher and Ohlin's theory. Heckscher-Ohlin's theory states that a country will export goods that use its abundant factor intensively and import goods that use its scarce factors intensively. In the two-factor case, it states “A capital-abundant country will export the capital-intensive good while the labour-abundant country will export the labour-intensive good”. Hecksher and Ohlin have explained the basis of international trade terms of factor endowment. Factor abundance = f(KLR) …………………….……………………………….…………. (1) Where KLR is the capital-labour proxy, hence, since factor abundance= (KLR) the model will be rewritten as: Following the theoretical framework and that of Abinabo and Abubarkar (2023), Umar et al., (2021) and Atoyebi et al., (2024) the model can be specified as: GGDP = f (KLR, TRAD, EXCH & INT) …………………………………………… (2) The growth of gross domestic product is a function of the proxy of capital to labour, trade openness, exchange rate and interest. Where GGDP is the growth of the gross domestic product, TRAD is trade openness, EXCH is the exchange rate and INT is the interest rate. In other to make the model different from past studies and make it more robust, therefore the study will include import and export as part of the explanatory variables and remove interest rate from the explanatory variable. Thus, the model will be specified as: GGDP = f (KLR, TRAD, EXCH, IMP & FRV) ……………………..………..…… (3) The growth of gross domestic product is a function of the proxy of capital to labour, trade openness, exchange rate, import and export. Where GGDP = Growth of Gross Domestic Product (constant 2005 US$) KLR = Proxied by capital-labour proxy TRAD = Trade Openness (% of GDP) EXCH = Exchange rate (LCU per US$, period average) IMP = Import FRV = Total reserves (includes gold, current US$) The linear function of equation (3.4) will be given below: GGDP = β 0 + β 1 KLR + β 2 TRAD + β 3 EXCH + β 4 IMP + β 5 FRV ………………….……..… (4) In other to capture other variables that could affect the growth of gross domestic product (GGDP), the linear function above in equation 3.4 will be transformed into an econometrics equation by adding stochastic or error terms with all the standard attributes. GGDP = β 0 + β 1 KLR + β 2 TRAD + β 3 EXCH + β 4 IMP + β 5 FRV + u t ……………………..… (5) The variables will be transformed to their natural logarithms to eliminate any serial correlation and to normalize the variables. LN(GGDP) = β 0 + β 1 LN(KLR) + β 2 LN(TRAD) + β 3 LN(EXCH) + β 4 LN(IMP) + β 5 LN(FRV)+ u t ………………………………………………………………………...……………..….… (6) 4.1 Estimation Technique In this paper, the Auto-regressive Distributive Lag (ARDL) is adopted. The study will consider both the long-run and short-run simultaneously by using the co-integrating ARDL approach and the Error correction ARDL approach. EMPIRICAL ANALYSIS AND DISCUSSION 5.1 Correlation Analysis Result The study makes use of correlation analysis in other to show the relationship between the growth of gross domestic product on macroeconomic variables and to also see if there is multicollinearity among the variables. GGDP KLR TRAD EXCH IMP FRV GGDP 1.000000 KLR 0.781 1.000000 TRAD 0.235 0.381951 1.000000 EXCH -0.822 0.849603 0.056695 1.000000 IMP -0.756 0.392392 -0.288544 0.522480 1.000000 FRV 0.837 0.907476 0.388658 0.789445 0.523280 1.000000 Source: Author’s Computation from E-view 12 The table above presents the correlation analysis carried out between the growth of gross domestic product and select macroeconomic variables. The correlation coefficient is 0.781242, indicating a strong positive correlation. This implies that there is a linear positive relationship between the growth of gross domestic product and the proxy of capital and labour. Specifically, the correlation coefficient between the two is 0.781. Since the coefficient of the relationship between the two is greater than +0.5, there exists a “strong positive correlation” between the growth of gross domestic product and the proxy of capital and labour. This shows that as the proxy of capital and labour increases, the growth of gross domestic product also increases. Also, the correlation analysis between the growth of gross domestic product and trade openness is positively related. This implies that there is a linear negative relationship between the growth of gross domestic product and trade openness. Specifically, the correlation coefficient between the two is 0.235. Since the coefficient of the relationship between the two is less than +0.5, there exists a “weak positive correlation” between the growth of gross domestic product and trade openness. This shows that as the trade openness increases, the growth of gross domestic product also decreases. In the same vein, the correlation analysis of the growth of gross domestic product and the exchange rate is negatively related. This implies that there is a linear negative relationship between the growth of gross domestic product and the exchange rate. Specifically, the correlation coefficient between the two is -0.822. Since the coefficient of the relationship between the two is greater than -0.5, there exists a “strong negative correlation” between the growth of gross domestic product and the exchange rate. This shows that as the exchange rate increases, the growth of gross domestic product also decreases. More so, the correlation analysis of the growth of gross domestic product and import (IMP) is negatively related. This implies that there is a linear negative relationship between the growth of gross domestic product and import (IMP). Specifically, the correlation coefficient between the two is -0.756. Since the coefficient of the relationship between the two is greater than +0.5, there exists a “strong negative correlation” between the growth of gross domestic and imports. This shows that as importation increases, the growth of gross domestic product in Nigeria also decreases. Lastly, the correlation analysis of the growth of gross domestic product and foreign reserve (FRV) is positively related. This implies that there is a linear positive relationship between the growth of gross domestic product and foreign reserve. Specifically, the correlation coefficient between the two is 0.837. Since the coefficient of the relationship between the two is greater than +0.5, there exists a “strong positive correlation” between the growth of gross domestic product and foreign reserve. This shows that as Nigeria's foreign reserve increases, the growth of gross domestic product also increases. 5.2 Unit Root Test The study tests for unit roots on growth of gross domestic product (GGDP), proxy of capital-labour (KLR), trade openness (TRAD), exchange rate (EXCH) import (IMP) and foreign reserve (FRV). In other to test for the unit root of the variables, the Augmented Dickey-Fuller (ADF) unit Root Test was employed. The study makes use of unit roots to guarantee that our inference regarding the important issue of stationarity is unlikely driven by the choice of testing procedures used. Variable Level First Difference Status ADF Critical Value t* ADF Critical Value t* GGDP -2.935 -0.517 -2.936 -8.433* I(1) KLR -2.938 -0.847 -2.939 -3.605** I(1) TRAD -2.935 -2.792** - - I(0) EXCH -2.935 0.592 -2.936 -4.343* I(1) IMP -2.935 -0.558* -2.936 -4.968 I(1) FRV -2.935 -0.815067 -2.938 -5.504* I(1) Source: Author’s Computation from E-view 12 Notes: * Statistical significance at 1% level; ** Statistical significance at 5% level; *** Statistical significance at 10% level. The above results in Table 2 above showed that one of the variables is stationary at levels. The unit root tests applied to the variables at levels reject the null hypothesis of stationarity of all the variables used. The variables are therefore differenced once to perform stationarity tests on different variables. After differencing the variables once, all the variables were confirmed to be stationary except inflation and labour which are stationary at level. The ADF test applied to the first difference of the data series accepts the null hypothesis of stationarity for all the variables used. It is, therefore, worth concluding that the variables are integrated of order zero and one which is the combination of I(0) and I(1). Therefore, the variables will be co-integrated to ascertain the existence of the long-run relationship of the variables. Table 3 Serial Correlation Test Breusch-Godfrey Serial Correlation LM Test: Null hypothesis: No serial correlation at up to 1 lag F-statistic 0.555377 Prob. F(1,33) 0.3274 Obs*R-squared 0.824587 Prob. Chi-Square(1) 0.2944 Source: Author’s Computation from E-View12 The table presents the results of a Breusch-Godfrey Serial Correlation LM Test, which is used to check for the presence of serial correlation in the residuals of a regression model. The null hypothesis of this test is that there is no serial correlation up to one lag. The results of the Breusch-Godfrey Serial Correlation LM Test suggest that there is no significant serial correlation in the residuals of the regression model at up to 1 lag. Both the F-statistic and the Obs*R-squared statistic have p-values greater than 0.05, indicating that the study fails to reject the null hypothesis of no serial correlation. This implies that the residuals are independent over time, which is a desirable property in regression analysis as it validates the assumption of no autocorrelation in the residuals. Table 4 Bound Test F-Bounds Test Null Hypothesis: No levels relationship Test Statistic Value Signif. I(0) I(1) F-statistic 5.278318 10% 2.08 3 k 5 5% 2.39 3.38 2.5% 2.7 3.73 1% 3.06 4.15 Source: Author’s Computation from E-View12 The table provides the results of the F-Bounds test, which is used in the context of an Autoregressive Distributed Lag (ARDL) model to test for the presence of a long-run (levels) relationship between variables. The null hypothesis of the F-Bounds test is that there is no level of relationship (no cointegration) among the variables. However, the F-Bounds test results indicate that the F-statistic (5.278318) is greater than the upper bound critical values at all common significance levels (10%, 5%, 2.5%, and 1%). Therefore, the study rejects the null hypothesis of no levels relationship and concludes that there is a significant long-run relationship among the variables in the model. This suggests that the variables are cointegrated and there is a long-term equilibrium relationship between them. 5.3 Short-Run and Long-Run Effect of Trade Openness on Growth of Gross Domestic Product from 1980 – 2021 Table 5: Parsimonious Long-run and Short-run ARDL-ECM Results Dependent Variable: Manufacturing output (GGDP) Variables Long-run Short-run KLR 4.165 (0.031) * 5.263 (0.005) * TRAD 0.004 (0.564) 0.008 (0.128) EXCH -0.005 (0.075) -0.006 (0.039)* IMP -0.071 (0.528) 6.455 (0.000) * FRV 0.022 (0.8527) 0.189 (0.1089) ECT(-1) - -0.354 (0.001) * CONS -2.528 (0.131) - R-Square 0.954 Adj R-Square 0.939 F-Statistics 62.812 (0.000) * Akaike info criterion (AIC) 0.339 Schwarz criterion (SIC) 0.799 Durbin-Watson Stat. 2.161 Hannan-Quinn (HIC) 0.507 Source: Author’s Computation from E-View12 Note: *, ** and *** imply 1%, 5% and 10% level of significance The short-run and long-run ARDL results for the impact of trade openness on economic growth and development are presented in Table 5. Since the unit root test confirmed the combination of order zero and one that I(0) and I(1) and the ARDL bounds test for cointegration shows evidence of a long-run relationship between the dependent variable and the independent variable, the short-run and long-run effect of the variables were examined. Table 5 above reveals the long-run and short-run results of the ARDL-ECM result. From the results above, it was revealed that in the long run, one variable which is the proxy of capital and labour is the only variable out of five variables considered as the explanatory variables that can only determine economic growth and development in Nigeria. However, in the short run, only three of the explanatory variables from the table are significant. The proxy of capital and labour, exchange rate and import are the significant variables that determine economic growth and development in Nigeria. It was also revealed that the proxy of capital and labour, exchange rate and import are all significant at a 5% level of significance. Also, in the short run, all the explanatory variables are positively related to the growth of gross domestic product except the exchange rate which is negatively related. However, in the long run, the proxy of capital and labour, trade openness and foreign reserve are positively related to the growth of gross domestic product while exchange rate and import are negatively related to gross domestic product. Meanwhile, a percentage increase in the positive variables in the short run which are the proxy and capital and labour, trade openness, and import and foreign reserve will increase the growth of gross domestic product by 5.263, 0.008, 6.455 and 0.189 respectively while a percentage increase in exchange in the short run will decrease the growth of gross domestic product by -0.006. In the same vein, a percentage increase in the positive variables in the long run which are the proxy of capital and labour, trade openness and foreign reserve will increase the growth of gross domestic product by 4.165, 0.004 and 0.022 respectively. Meanwhile, a percentage increase in the exchange rate and import in the long run will decrease the growth of the exchange rate by -0.005 and -0.071 respectively. The benchmark for error correction term (ECT) is that it must be negative and significant at any level of significance and it will be used to examine how the variables will converge to equilibrium. Therefore, the coefficient of the error correction term (ECT) indicated a 35% deviation from the long-run equilibrium in the growth of gross domestic product which is corrected annually. Moreover, the diagnostic tests confirm the correctness of the estimated model. Also, the R squared variable of 0.954 shows that the explanatory variables of electricity consumption, inflation, interest rate, labour, gross fixed capital formation, exchange rate and electricity production explained about 95.4% of the variation in Nigerian economic growth and development. The adjusted R-square of 0.939 indicated that about 93.9% of the total variation in Nigerian economic growth and development can be explained by all the explanatory variables and the F-statistic of 62.812 with the probability value of 0.000 implied that the overall model is statistically significant at 1% level of significant while the Durbin-Watson statistic of 2.161 means that there is no serious autocorrelation in the model. 5.4 DISCUSSION OF FINDINGS The findings of this study reveal a nuanced relationship between trade openness and economic growth in Nigeria, corroborating and diverging from prior research in significant ways. This research established that while proxy of capital and labour, exchange rates, and imports significantly influence Nigeria's economic growth and development in the short run. However, this result aligns with Khobai et al. (2018) and Yakubu & Akanegbu (2018), who found that trade openness has a mixed impact on economic growth, depending on the country and specific conditions analysed. Khobai et al. highlighted a positive impact in Ghana but a negative, though insignificant, effect in Nigeria. Similarly, Yakubu & Akanegbu noted that trade openness positively influenced economic growth but was dependent on the degree of openness and other economic factors. Moreover, this study supports the findings of Nduka (2013), who identified a positive impact of trade openness on economic growth but emphasised the significant roles of investment and government expenditure in driving this growth. However, it contrasts with the findings of Abinabo & Abubarkar (2023), who demonstrated a positive and statistically significant impact of trade openness on economic growth in Nigeria, suggesting that import dynamics might adversely affect economic growth if not managed properly. Hwofasa & Ekaruwe's (2023) research also contributes to this dialogue by showing that while agricultural and crude oil exports positively impact economic growth, solid mineral exports negatively affect it. This highlights the sector-specific effects of trade openness, reinforcing the complexity observed in this study where general trade openness did not show a significant impact. CONCLUSION AND RECOMMENDATION This study examines the impact of trade openness on economic growth and development in Nigeria from 1980 to 2021 using different diagnostic tests which include descriptive statistics, correlation analysis, unit root test, and autoregressive distributed lag. This study concludes that: There is a weak positive correlation between trade openness and Nigerian economy growth and development which signifies that as trade openness increases, the growth of gross domestic product also decreases. The proxy of capital and labour, exchange rates, and imports have a significant influence on the growth of gross domestic product in the short run, whereas trade openness, does not significantly impact economic growth both in the short run and in the long run. While trade openness is a critical component of economic policy, its impact on growth is complex and multifaceted. This study highlights the need for targeted and comprehensive economic strategies that consider the interplay between trade openness and other key economic variables to effectively promote economic development in Nigeria. 6.1 Recommendation The following recommendations are made based on the findings of the study. Optimise Capital and Labour Utilisation: Given that the proxy of capital to labour significantly influences economic growth in both the short and long run, it is essential to implement policies that enhance the efficiency of capital and labour deployment. This involves investing in comprehensive education and training programs to boost labour productivity and foster skill development. Additionally, promoting technological advancements and innovation can lead to more effective use of capital resources. Address Exchange Rate Fluctuations: The observed negative impact of exchange rate fluctuations on GDP growth highlights the urgent need for stable exchange rate policies in Nigeria. To mitigate these adverse effects, the monetary authorities must implement measures such as maintaining adequate foreign exchange reserves and engaging in targeted currency stabilisation interventions in Nigeria. These actions can help reduce volatility and provide a more predictable economic environment, ultimately fostering a more stable and conducive atmosphere for sustained economic growth and development. Promote Trade Openness: Trade openness has a positive relationship with GDP growth over the long term and the short run. To harness these benefits, the Nigerian government needs to implement policies that enhance trade liberalisation, reduce trade barriers, and refine trade agreements. Supporting export-oriented industries through targeted incentives and improving trade facilitation processes can further amplify the advantages of trade openness. Declarations Data Availability Upon request, the corresponding author will provide the datasets gathered and/or analysed for this study. All of the study's data are fully accessible to the corresponding author, who also bears full responsibility for the accuracy of the data analysis and the data's integrity. References Abinabo, P., Munir, S. M., & Abubakar, A. (2023). Workplace Diversity Management and Organizational Performance of Deposit Money Banks in Katsina State. UBS Journal of Business and Economic Policy , 1 (3), 213-229. Afolabi, J. (2022). Financial Development, Trade Openness, and Economic Growth in Nigeria. Iranian Economic Review , 26 (1), 237-254. Ajayi, E. O., & Araoye, F. E. (2019). Trade openness and economic growth in Nigeria. International Journal of Economics and Financial Management , 4 (2), 50-63. Atoyebi, E. O., Oseni, I. O., Ogede, J. S., & Adegboyega, S. B. (2024). Unraveling the relationship between trade openness, economic growth, and financial development in Nigeria. Journal of Enterprise and Development (JED) , 6 (1), 1-11. Bajona, C., & Kehoe, T. J. (2010). Trade, growth, and convergence in a dynamic Heckscher–Ohlin model. Review of Economic Dynamics , 13 (3), 487-513. Baldwin, R. E. (2008). The development and testing of Heckscher-Ohlin trade models: a review. Brondino, G. (2023). Fragmentation of production, comparative advantage, and the Heckscher-Ohlin theory. Review of Political Economy , 35 (3), 803-822. Dauda, R. O. S. (2007). The impact of FDI on Nigeria’s economic growth: trade policy matters. Journal of Business and Policy Research , 3 (2), 11-26 Elijah, S., & Musa, A. B. (2019). The dynamic impact of trade openness on the economic growth in Nigeria. International Journal of Engineering and Advanced Technology , 8 (5), 609-616. Huchet‐Bourdon, M., Le Mouël, C., & Vijil, M. (2018). The relationship between trade openness and economic growth: Some new insights on the openness measurement issue. The World Economy , 41 (1), 59-76 Ijirshar, V. U. (2019). Impact of trade openness on economic growth among ECOWAS Countries: 1975-2017. CBN Journal of Applied Statistics (JAS) , 10 (1), 4. Keho, Y. (2017). The impact of trade openness on economic growth: The case of Cote d’Ivoire. Cogent Economics & Finance , 5 (1), 1332820. Khobai, H., & Chitauro, M. (2018). The impact of trade liberalisation on economic growth in Switzerland. Moyo, C., Kolisi, N., & Khobai, H. (2017). The relationship between trade openness and economic growth: The case of Ghana and Nigeria. Nduka, E. K. (2013). Openness and economic growth in Nigeria. Journal of Education and Practice , 4 (1), 68-73. Nwadike, G. C., Johnmary, A. K., & Alamba, C. S. (2020). Impact of trade openness on Nigerian economic growth: an empirical investigation, 1970–2011. Foreign Trade Review , 55 (2), 239-247. Ohwofasa, B. O., & Ekaruwe, M. (2023). Trade Openness and Economic Growth in Nigeria. LAFIA JOURNAL OF ECONOMICS AND MANAGEMENT SCIENCES , 8 , 23-47. Omoke, P. C., & Opuala–Charles, S. (2021). Trade openness and economic growth nexus: Exploring the role of institutional quality in Nigeria. Cogent Economics & Finance , 9 (1), 1868686. Oppong-Baah, T., Bo, Y., Twi-Brempong, C., Amoah, E. O., Prempeh, N. A., & Addai, M. (2022). The Impact of trade openness on economic growth: The case of Ghana and Nigeria. Journal of Human Resource and Sustainability Studies , 10 (1), 142-160. Solomon, O. I., & Tukur, M. U. (2019). Trade openness and economic growth in the developing countries: evidence from Nigeria. International Journal of Academic Research in Economics and Management Sciences , 8 (3), 30-42. Umar, M., Chaudhry, I. S., Faheem, M., & Farooq, F. (2021). Do Governance, Foreign Direct Investment and Human Capital Matter to Bolster Trade Liberalization? Fresh Insight from Developing Countries. Review of Economics and Development Studies , 7 (3), 325-341. Yakubu, M. M., & Akanegbu, B. N. (2018). Trade openness and economic growth: Evidence from Nigeria. European Journal of Business, Economics and Accountancy , 6 (4), 30-44. Additional Declarations The authors declare no competing interests. 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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-5437681","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":377089173,"identity":"a8574741-344f-4c6b-ad05-f8833b630afb","order_by":0,"name":"SALISU, Temitope Quadri","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0000-0051-6726","institution":"University of Ibadan","correspondingAuthor":true,"prefix":"","firstName":"Temitope","middleName":"Quadri","lastName":"SALISU","suffix":""}],"badges":[],"createdAt":"2024-11-12 08:32:38","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5437681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5437681/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68900091,"identity":"9f97b308-a1cf-450a-a4cd-0271447481ca","added_by":"auto","created_at":"2024-11-13 09:35:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69493,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2.1 Trend of Trade Openness in Nigeria from 1980 – 2021\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource: \u003c/strong\u003eAuthor’s Computation from World Development Indicator (WDI, 2021)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5437681/v1/6fdcb14829d3c7c50729065f.png"},{"id":68900092,"identity":"40e10104-d21b-4d2a-b89a-d55501557c57","added_by":"auto","created_at":"2024-11-13 09:35:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":419181,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2.2: Trend of Trade Openness and Growth of Gross Domestic Product\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource: \u003c/strong\u003eAuthor’s Computation from World Development Indicator (WDI, 2021)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5437681/v1/b19de8aa82bb7a8ae700f914.png"},{"id":68901055,"identity":"ef93c9a3-f635-4488-b96a-110fc5ec6e9c","added_by":"auto","created_at":"2024-11-13 09:43:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1106406,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5437681/v1/996b2595-75d7-4a97-b737-1f43201aa94b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eThe Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eNigeria has undergone significant transformations in its trade policies, economic expansion, and financial advancement in recent years, positioning it as a leading African economy. The economic landscape of Nigeria has prominently featured trade openness, characterised by the adoption of liberalized trade policies and increased involvement in international trade (Moyo, Kolisi, \u0026amp; Khobai 2017). Concurrently, the nation has experienced phases of substantial economic expansion driven by diverse industries, including oil, agriculture, and services. These advancements have spurred efforts to enhance the financial industry and streamline its progress. However, trade has been an area of interest to policymakers as well as economists. It enables nations to sell their domestically produced goods to other countries of the world. It has been regarded as an engine of growth which leads to steady improvement in human status by expanding the range of people\u0026apos;s standard of living and preferences (Adewuyi, 2002).\u003c/p\u003e\n\u003cp\u003eThe pivotal roles financial development and trade openness play in bolstering economic growth across countries cannot be overemphasised. International trade theories posit that differences in technology, factor endowments, and economies of scale, among others, across countries are the main sources of comparative advantage and determinants of trade patterns. Moreover, it has been argued that financial development is a potential source of comparative advantage to an economy, thus it can facilitate trade (Ijirshar, 2019; Baldwin, 1989). Intuitively, a country with a relatively well-regulated, well-developed and efficient financial sector has a comparative advantage in sectors that depend on external financing. Hence, countries with well-developed financial sectors should experience greater volumes of international trade (Ajayi \u0026amp; Araoye 2019; Keho 2017; Omoke \u0026amp; Opuala\u0026ndash;Charles 2021). This accounts for the great volume of trade witnessed in China, Germany, the United States, and the United Kingdom, among other developed countries of the world. Thus, to experience greater volumes of international trade, it is expedient that each country especially developing economies aim at having a well-regulated and competitive financial sector.\u003c/p\u003e\n\u003cp\u003eStructural barriers, such as infrastructural deficiencies, regulatory bottlenecks, and institutional limitations, may impede the effective utilisation of trade opportunities. Understanding how these factors interact with trade openness is crucial for developing targeted interventions that promote economic development (Ohwofasa \u0026amp; Ekaruwe 2023). Persistent trade imbalances and a reliance on a restricted array of export commodities pose substantial threats to Nigeria\u0026apos;s sustainable economic growth. It is imperative to delve into the intricacies of how trade openness influences economic diversification and aids in ameliorating trade imbalances for enduring stability. The vulnerability arising from an overdependence on a limited set of exports necessitates a nuanced exploproxyn of policies that can foster a more diversified and resilient economic landscape (Atoyebi et al., 2024).\u003c/p\u003e\n\u003cp\u003eAdditionally, Nwadike et al., (2020) reveal that the impact of heightened trade openness on domestic industries requires meticulous scrutiny. The dynamics of competition, the transfer of technology, and shifts in employment patterns demand a comprehensive examination to ascertain the potential ramifications for local businesses. Crafting policies that strike a delicate balance between openness and safeguarding domestic interests becomes indispensable in navigating the complexities of globalization, ensuring that increased trade benefits local industries without compromising employment or technological advancement (Khobai et al., 2018). This multifaceted analysis is critical for policymakers striving to create an economic environment that is both open to global trade and protective of domestic economic interests (Omoke \u0026amp; Opuala\u0026ndash;Charles 2021). The relationship between trade openness and economic growth has been the subject of extensive research and debate in economic literature (Oppong-Baah et al., 2022). The Nigerian government has made several efforts toward developing its financial sector as reflected in the different reforms in the sector over time even though there has been inconsistency in implementing the policies (Afolabi 2022; Yakubu \u0026amp; Akanegbu 2018). These policy reforms were aimed at maintaining a stable, well-regulated, and competitive financial sector.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;OBJECTIVE OF THE STUDY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe objective of this study is to examine the impact of trade openness on economic growth and development. The specific objectives are to examine the causal relationship between trade openness and economic growth in Nigeria. Also, to determine the long-run relationship between trade openness and economic growth and development in Nigeria\u003c/p\u003e"},{"header":"LITERATURE REVIEW","content":"\u003cp\u003e\u003cstrong\u003e2.1 \u0026nbsp; \u0026nbsp; \u0026nbsp; Rationale for Trade Openness in Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNigeria is a member of several bilateral and multilateral organisations, which has aided her global integration efforts and facilitated foreign capital inflows into the domestic economy. Because of this, the economy has put in place several incentives and regulations to promote trade openness as a prelude to luring in much-needed FDI inflows for economic development (Dauda, 2007). According to World Bank Development Indicators (WDI) (2021), Nigeria attracted approximately $89,570.52 million in FDI inflows with an average of 1.41 per cent from 1996 to 2020. It is expected that these capital inflows will boost socio-economic activities; however, taking the trade as a percentage of GDP as an example, the average is 36.63 per cent, which is far below expectations, especially when compared to countries such as South Africa, which has traded as a percentage of GDP at 51.59 per cent, Egypt at 46.37 per cent, Kenya at 48.89 per cent, and Rwanda at 38.73 per cent. In terms of economic performance, GDP growth averaged 4.87 per cent, which is still below the level that can generate significant economic performance indicators and is one of the reasons why unemployment (percentage of the total labour force) and inflation averaged 5.00 per cent and 12.21 per cent, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.1 \u0026nbsp; \u0026nbsp;Trend of Trade Openness in Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe trend of trade openness in Nigeria values exhibit fluctuations over time, with periods of increase followed by periods of decline. From 1980 to the mid-1980s, trade values remained relatively low, with fluctuations but no clear trend. A notable increase in trade is observed in the late 1980s, particularly in 1987 and 1989, suggesting a period of economic expansion or increased international trade activity (Ajayi \u0026amp; Araoye 2019). Trade values experienced a downturn in the early 1990s, followed by a gradual recovery and subsequent fluctuations throughout the decade. The late 1990s and early 2000s witnessed another period of growth in trade values, peaking around 2001. However, subsequent years saw fluctuations in trade values, with no clear long-term trend evident. Towards the end of the time series (2015-2021), trade values appear to stabilise at lower levels compared to the peak years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 \u0026nbsp; \u0026nbsp; \u0026nbsp; Trade Openness and Economic Growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRecent studies have investigated both regional and individual country experiences, incorporating other institutional, social, economic, and technological factors. The analysis of the growth of exports and imports indicates the extent of the openness of an economy (Keho 2017). However, trade flow analysis provides the basis of a robust empirical investigation of the openness of an economy. Empirically, openness can be measured by the share of trade (import plus export) in total output, measured by the Gross Domestic Product (GDP). This is a broad concept of openness; in the narrow context, the proxy of imports or exports to GDP can represent the degree of openness of an economy. The statistics show that the Nigerian economy has been relatively more open since 1986, as a result of policy measures applied under the structural adjustment programme. The broad measure of openness, total trade to GDP (TT/GDP) increased from 0.21 in 1986 to 0.64 in 1987 as a result of the consistent implementation of adjustment measures (Huchet‐Bourdon et al., 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1 \u0026nbsp; \u0026nbsp;Trend of Trade Openness and Growth of Gross Domestic Product\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relationship between trade and economic growth indicates a consistent positive correlation, where fluctuations in trade values tend to correspond with changes in Gross Domestic Product (GDP) growth rates. During periods of heightened trade activity, evidenced by higher trade values, there is typically a concurrent increase in GDP growth rates. Conversely, when trade values decrease, as observed during certain periods such as the early 1980s, mid-1990s, and mid-2010s, there is often a subdued growth rate of GDP.\u003c/p\u003e\n\u003cp\u003eThe impact of trade fluctuations on GDP growth is evident in historical trends. Declines in trade values, particularly during the early 1980s and mid-1990s, were accompanied by decreases in GDP growth rates. Conversely, periods of increased trade values, such as in the late 1990s and early 2000s, coincided with upsurges in GDP growth rates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 \u0026nbsp; \u0026nbsp; \u0026nbsp; THEORETICAL REVIEW\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHeckscher-Ohlin (H-O) Theory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to Heckscher and Ohlin\u0026apos;s 1993 theory, a country should export those employing more factors with which it is better endowed, in that it has comparative advantages in both production and exports. \u0026nbsp;The theory is mainly composed of two significant theories, namely: the Heckscher-Ohlin theory and the factor price equalisation theorem (Bajona \u0026amp; Kehoe 2010). The Heckscher-Ohlin theorem, one which explains the various determinants of comparative cost differences in production, says a country enjoys a comparative advantage in producing a certain commodity if its relatively abundant factor is used more intensively. On the contrary, the theory of factor price equalisation discusses the effects of international trade on the prices of factors and states that it completely and relatively equalises factor prices across countries and thus replaces the requirement of global factor mobility (Brondino 2023). Heckscher-Ohlin\u0026apos;s theory postulates that \u0026quot;A country will export those goods whose production requires abundant factors of its endowments and import those goods whose production requires scarce factors of its endowment.\u0026quot; \u0026quot;A capital-abundant country will export the capital-intensive good while the labour-abundant country will export the labour-intensive good,\u0026quot; is how the two-factor case is stated.\u003c/p\u003e"},{"header":"RESEARCH METHOD","content":"\u003cp\u003eThe study utilised Heckscher and Ohlin\u0026apos;s theory. Heckscher-Ohlin\u0026apos;s theory states that a country will export goods that use its abundant factor intensively and import goods that use its scarce factors intensively. In the two-factor case, it states \u0026ldquo;A capital-abundant country will export the capital-intensive good while the labour-abundant country will export the labour-intensive good\u0026rdquo;. Hecksher and Ohlin have explained the basis of international trade terms of factor endowment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactor abundance = f(KLR) \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;. (1)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhere KLR is the capital-labour proxy, hence, since factor abundance= (KLR) the model will be rewritten as:\u003c/p\u003e\n\u003cp\u003eFollowing the theoretical framework and\u0026nbsp;that of Abinabo and Abubarkar (2023), Umar et al., (2021) and Atoyebi et al., (2024) the model can be specified as:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGGDP = f (KLR, TRAD, EXCH \u0026amp; INT) \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip; (2)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe growth of gross domestic product is a function of the proxy of capital to labour, trade openness, exchange rate and interest. Where GGDP is the growth of the gross domestic product, TRAD is trade openness, EXCH is the exchange rate and INT is the interest rate.\u003c/p\u003e\n\u003cp\u003eIn other to make the model different from past studies and make it more robust, therefore the study will include import and export as part of the explanatory variables and remove interest rate from the explanatory variable. Thus, the model will be specified as:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGGDP = f (KLR, TRAD, EXCH, IMP \u0026amp; FRV) \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;\u0026hellip; (3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe growth of gross domestic product is a function of the proxy of capital to labour, trade openness, exchange rate, import and export.\u003c/p\u003e\n\u003cp\u003eWhere\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGGDP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Growth of Gross Domestic Product (constant 2005 US$)\u003c/p\u003e\n\u003cp\u003eKLR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Proxied by capital-labour proxy\u003c/p\u003e\n\u003cp\u003eTRAD\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Trade Openness (% of GDP)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEXCH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Exchange rate (LCU per US$, period average)\u003c/p\u003e\n\u003cp\u003eIMP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Import\u003c/p\u003e\n\u003cp\u003eFRV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;=\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Total reserves (includes gold, current US$)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe linear function of equation (3.4) will be given below:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGGDP = \u0026beta;\u003csub\u003e0\u003c/sub\u003e + \u0026beta;\u003csub\u003e1\u003c/sub\u003eKLR + \u0026beta;\u003csub\u003e2\u003c/sub\u003eTRAD + \u0026beta;\u003csub\u003e3\u003c/sub\u003eEXCH + \u0026beta;\u003csub\u003e4\u003c/sub\u003eIMP + \u0026beta;\u003csub\u003e5\u003c/sub\u003eFRV \u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;.\u0026hellip;\u0026hellip;..\u0026hellip; (4)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn other to capture other variables that could affect the growth of gross domestic product (GGDP), the linear function above in equation 3.4 will be transformed into an econometrics equation by adding stochastic or error terms with all the standard attributes.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGGDP = \u0026beta;\u003csub\u003e0\u003c/sub\u003e + \u0026beta;\u003csub\u003e1\u003c/sub\u003eKLR + \u0026beta;\u003csub\u003e2\u003c/sub\u003eTRAD + \u0026beta;\u003csub\u003e3\u003c/sub\u003eEXCH + \u0026beta;\u003csub\u003e4\u003c/sub\u003eIMP + \u0026beta;\u003csub\u003e5\u003c/sub\u003eFRV +\u003cem\u003e\u0026nbsp;u\u003c/em\u003e\u003csub\u003et\u003c/sub\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip; (5)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe variables will be transformed to their natural logarithms to eliminate any serial correlation and to normalize the variables.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLN(GGDP) = \u0026beta;\u003csub\u003e0\u003c/sub\u003e + \u0026beta;\u003csub\u003e1\u003c/sub\u003eLN(KLR) + \u0026beta;\u003csub\u003e2\u003c/sub\u003eLN(TRAD) + \u0026beta;\u003csub\u003e3\u003c/sub\u003eLN(EXCH) + \u0026beta;\u003csub\u003e4\u003c/sub\u003eLN(IMP) + \u0026beta;\u003csub\u003e5\u003c/sub\u003eLN(FRV)+\u003cem\u003e\u0026nbsp;u\u003c/em\u003e\u003csub\u003et\u003c/sub\u003e\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;...\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;\u0026hellip;..\u0026hellip;.\u0026hellip; (6)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Estimation Technique\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this paper, the Auto-regressive Distributive Lag (ARDL) is adopted. The study will consider both the long-run and short-run simultaneously by using the co-integrating ARDL approach and the Error correction ARDL approach.\u003c/p\u003e"},{"header":"EMPIRICAL ANALYSIS AND DISCUSSION","content":"\u003cp\u003e\u003cstrong\u003e5.1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Correlation Analysis Result\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study makes use of correlation analysis in other to show the relationship between the growth of gross domestic product on macroeconomic variables and to also see if there is multicollinearity among the variables.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eGGDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eKLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eTRAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eEXCH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eIMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003eFRV\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eGGDP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eKLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eTRAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.381951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eEXCH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;-0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.849603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.056695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eIMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e-0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.392392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e-0.288544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.522480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 9.76%;\"\u003e\n \u003cp\u003eFRV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.837\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.907476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.388658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.789445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;0.523280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.04%;\"\u003e\n \u003cp\u003e\u0026nbsp;1.000000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eAuthor\u0026rsquo;s Computation from E-view 12\u003c/p\u003e\n\u003cp\u003eThe table above presents the correlation analysis carried out between the growth of gross domestic product and select macroeconomic variables.\u003c/p\u003e\n\u003cp\u003eThe correlation coefficient is 0.781242, indicating a strong positive correlation. This implies that there is a linear positive relationship between the growth of gross domestic product and the proxy of capital and labour. Specifically, the correlation coefficient between the two is 0.781. Since the coefficient of the relationship between the two is greater than +0.5, there exists a \u0026ldquo;strong positive correlation\u0026rdquo; between the growth of gross domestic product and the proxy of capital and labour. This shows that as the proxy of capital and labour increases, the growth of gross domestic product also increases.\u003c/p\u003e\n\u003cp\u003eAlso, the correlation analysis between the growth of gross domestic product and trade openness is positively related. This implies that there is a linear negative relationship between the growth of gross domestic product and trade openness. Specifically, the correlation coefficient between the two is 0.235. Since the coefficient of the relationship between the two is less than +0.5, there exists a \u0026ldquo;weak positive correlation\u0026rdquo; between the growth of gross domestic product and trade openness. This shows that as the trade openness increases, the growth of gross domestic product also decreases.\u003c/p\u003e\n\u003cp\u003eIn the same vein, the correlation analysis of the growth of gross domestic product and the exchange rate is negatively related. This implies that there is a linear negative relationship between the growth of gross domestic product and the exchange rate. Specifically, the correlation coefficient between the two is -0.822. Since the coefficient of the relationship between the two is greater than -0.5, there exists a \u0026ldquo;strong negative correlation\u0026rdquo; between the growth of gross domestic product and the exchange rate. This shows that as the exchange rate increases, the growth of gross domestic product also decreases.\u003c/p\u003e\n\u003cp\u003eMore so, the correlation analysis of the growth of gross domestic product and import (IMP) is negatively related. This implies that there is a linear negative relationship between the growth of gross domestic product and import (IMP). Specifically, the correlation coefficient between the two is -0.756. Since the coefficient of the relationship between the two is greater than +0.5, there exists a \u0026ldquo;strong negative correlation\u0026rdquo; between the growth of gross domestic and imports. This shows that as importation increases, the growth of gross domestic product in Nigeria also decreases.\u003c/p\u003e\n\u003cp\u003eLastly, the correlation analysis of the growth of gross domestic product and foreign reserve (FRV) is positively related. This implies that there is a linear positive relationship between the growth of gross domestic product and foreign reserve. Specifically, the correlation coefficient between the two is 0.837. Since the coefficient of the relationship between the two is greater than +0.5, there exists a \u0026ldquo;strong positive correlation\u0026rdquo; between the growth of gross domestic product and foreign reserve. This shows that as Nigeria\u0026apos;s foreign reserve increases, the growth of gross domestic product also increases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Unit Root Test\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study tests for unit roots on growth of gross domestic product (GGDP), proxy of capital-labour (KLR), trade openness (TRAD), exchange rate (EXCH) import (IMP) and foreign reserve (FRV). In other to test for the unit root of the variables, the Augmented Dickey-Fuller (ADF) unit Root Test was employed. The study makes use of unit roots to guarantee that our inference regarding the important issue of stationarity is unlikely driven by the choice of testing procedures used.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"640\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003eADF Critical Value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003et*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eADF Critical Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003et*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGGDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-8.433*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-3.605**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTRAD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-2.792**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEXCH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-4.343*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIMP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.558*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-4.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFRV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e-2.935\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e-0.815067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-2.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-5.504*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eAuthor\u0026rsquo;s Computation from E-view 12\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNotes:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e* Statistical significance at 1% level; ** Statistical significance at 5% level; *** Statistical significance at 10% level.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe above results in Table 2 above showed that one of the variables is stationary at levels. The unit root tests applied to the variables at levels reject the null hypothesis of stationarity of all the variables used. The variables are therefore differenced once to perform stationarity tests on different variables. After differencing the variables once, all the variables were confirmed to be stationary except inflation and labour which are stationary at level. The ADF test applied to the first difference of the data series accepts the null hypothesis of stationarity for all the variables used. It is, therefore, worth concluding that the variables are integrated of order zero and one which is the combination of I(0) and I(1). Therefore, the variables will be co-integrated to ascertain the existence of the long-run relationship of the variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Serial Correlation Test\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 630px;\"\u003e\n \u003cp\u003eBreusch-Godfrey Serial Correlation LM Test:\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 630px;\"\u003e\n \u003cp\u003eNull hypothesis: No serial correlation at up to 1 lag\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.555377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Prob. F(1,33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.3274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003eObs*R-squared\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e0.824587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Prob. Chi-Square(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.2944\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eAuthor\u0026rsquo;s Computation from E-View12\u003c/p\u003e\n\u003cp\u003eThe table presents the results of a Breusch-Godfrey Serial Correlation LM Test, which is used to check for the presence of serial correlation in the residuals of a regression model. The null hypothesis of this test is that there is no serial correlation up to one lag. The results of the Breusch-Godfrey Serial Correlation LM Test suggest that there is no significant serial correlation in the residuals of the regression model at up to 1 lag. Both the F-statistic and the Obs*R-squared statistic have p-values greater than 0.05, indicating that the study fails to reject the null hypothesis of no serial correlation. This implies that the residuals are independent over time, which is a desirable property in regression analysis as it validates the assumption of no autocorrelation in the residuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Bound Test\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 293px;\"\u003e\n \u003cp\u003eF-Bounds Test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 301px;\"\u003e\n \u003cp\u003eNull Hypothesis: No levels relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003eTest Statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003eSignif.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003eI(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003eI(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003eF-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;5.278318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e10% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003ek\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e5% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.5% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e1% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eAuthor\u0026rsquo;s Computation from E-View12\u003c/p\u003e\n\u003cp\u003eThe table provides the results of the F-Bounds test, which is used in the context of an Autoregressive Distributed Lag (ARDL) model to test for the presence of a long-run (levels) relationship between variables. The null hypothesis of the F-Bounds test is that there is no level of relationship (no cointegration) among the variables. However, the F-Bounds test results indicate that the F-statistic (5.278318) is greater than the upper bound critical values at all common significance levels (10%, 5%, 2.5%, and 1%). Therefore, the study rejects the null hypothesis of no levels relationship and concludes that there is a significant long-run relationship among the variables in the model. This suggests that the variables are cointegrated and there is a long-term equilibrium relationship between them.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Short-Run and Long-Run Effect of Trade Openness on Growth of Gross Domestic Product from 1980 \u0026ndash; 2021\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eParsimonious Long-run and Short-run ARDL-ECM Results\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003eDependent Variable: Manufacturing output (GGDP)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003eLong-run\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003eShort-run\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eKLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;4.165\u0026nbsp;(0.031) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e5.263\u0026nbsp;(0.005) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eTRAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e0.004\u0026nbsp;(0.564)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.008\u0026nbsp;(0.128)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eEXCH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e-0.005\u0026nbsp;(0.075)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-0.006\u0026nbsp;(0.039)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eIMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e-0.071\u0026nbsp;(0.528)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e6.455 (0.000) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eFRV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e0.022\u0026nbsp;(0.8527)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e0.189\u0026nbsp;(0.1089)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eECT(-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-0.354 (0.001) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eCONS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 32.0513%;\"\u003e\n \u003cp\u003e-2.528\u0026nbsp;(0.131)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.3333%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eR-Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eAdj R-Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eF-Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e62.812\u0026nbsp;(0.000) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eAkaike info criterion (AIC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eSchwarz criterion (SIC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eDurbin-Watson Stat.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e2.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 34.6154%;\"\u003e\n \u003cp\u003eHannan-Quinn (HIC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 65.3846%;\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSource:\u0026nbsp;\u003c/strong\u003eAuthor\u0026rsquo;s Computation from E-View12\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: *, ** and *** imply 1%, 5% and 10% level of significance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe short-run and long-run ARDL results for the impact of trade openness on economic growth and development are presented in Table 5. Since the unit root test confirmed the combination of order zero and one that I(0) and I(1) and the ARDL bounds test for cointegration shows evidence of a long-run relationship between the dependent variable and the independent variable, the short-run and long-run effect of the variables were examined.\u003c/p\u003e\n\u003cp\u003eTable 5 above reveals the long-run and short-run results of the ARDL-ECM result. From the results above, it was revealed that in the long run, one variable which is the proxy of capital and labour is the only variable out of five variables considered as the explanatory variables that can only determine economic growth and development in Nigeria. However, in the short run, only three of the explanatory variables from the table are significant. The proxy of capital and labour, exchange rate and import are the significant variables that determine economic growth and development in Nigeria. It was also revealed that the proxy of capital and labour, exchange rate and import are all significant at a 5% level of significance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlso, in the short run, all the explanatory variables are positively related to the growth of gross domestic product except the exchange rate which is negatively related. However, in the long run, the proxy of capital and labour, trade openness and foreign reserve are positively related to the growth of gross domestic product while exchange rate and import are negatively related to gross domestic product. Meanwhile, a percentage increase in the positive variables in the short run which are the proxy and capital and labour, trade openness, and import and foreign reserve will increase the growth of gross domestic product by 5.263, 0.008, 6.455 and 0.189 respectively while a percentage increase in exchange in the short run will decrease the growth of gross domestic product by -0.006. In the same vein, a percentage increase in the positive variables in the long run which are the proxy of capital and labour, trade openness and foreign reserve will increase the growth of gross domestic product by 4.165, 0.004 and 0.022 respectively. Meanwhile, a percentage increase in the exchange rate and import in the long run will decrease the growth of the exchange rate by -0.005 and -0.071 respectively.\u003c/p\u003e\n\u003cp\u003eThe benchmark for error correction term (ECT) is that it must be negative and significant at any level of significance and it will be used to examine how the variables will converge to equilibrium. Therefore, the coefficient of the error correction term (ECT) indicated a 35% deviation from the long-run equilibrium in the growth of gross domestic product which is corrected annually. Moreover, the diagnostic tests confirm the correctness of the estimated model. Also, the R squared variable of 0.954 shows that the explanatory variables of electricity consumption, inflation, interest rate, labour, gross fixed capital formation, exchange rate and electricity production explained about 95.4% of the variation in Nigerian economic growth and development. The adjusted R-square of 0.939 indicated that about 93.9% of the total variation in Nigerian economic growth and development can be explained by all the explanatory variables and the F-statistic of 62.812\u0026nbsp;with the probability value of 0.000 implied that the overall model is statistically significant at 1% level of significant while the Durbin-Watson statistic of 2.161 means that there is no serious autocorrelation in the model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DISCUSSION OF FINDINGS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings of this study reveal a nuanced relationship between trade openness and economic growth in Nigeria, corroborating and diverging from prior research in significant ways. This research established that while proxy of capital and labour, exchange rates, and imports significantly influence Nigeria\u0026apos;s economic growth and development in the short run. However, this result aligns with Khobai et al. (2018) and Yakubu \u0026amp; Akanegbu (2018), who found that trade openness has a mixed impact on economic growth, depending on the country and specific conditions analysed. Khobai et al. highlighted a positive impact in Ghana but a negative, though insignificant, effect in Nigeria. Similarly, Yakubu \u0026amp; Akanegbu noted that trade openness positively influenced economic growth but was dependent on the degree of openness and other economic factors.\u003c/p\u003e\n\u003cp\u003eMoreover, this study supports the findings of Nduka (2013), who identified a positive impact of trade openness on economic growth but emphasised the significant roles of investment and government expenditure in driving this growth. However, it contrasts with the findings of Abinabo \u0026amp; Abubarkar (2023), who demonstrated a positive and statistically significant impact of trade openness on economic growth in Nigeria, suggesting that import dynamics might adversely affect economic growth if not managed properly. Hwofasa \u0026amp; Ekaruwe\u0026apos;s (2023) research also contributes to this dialogue by showing that while agricultural and crude oil exports positively impact economic growth, solid mineral exports negatively affect it. This highlights the sector-specific effects of trade openness, reinforcing the complexity observed in this study where general trade openness did not show a significant impact.\u003c/p\u003e"},{"header":"CONCLUSION AND RECOMMENDATION","content":"\u003cp\u003eThis study\u0026nbsp;examines the impact of trade openness on economic growth and development in Nigeria from 1980 to 2021\u0026nbsp;using different diagnostic tests which include descriptive statistics, correlation analysis, unit root test, and autoregressive distributed lag.\u0026nbsp;This study concludes that:\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eThere is a weak positive correlation between trade openness and Nigerian economy growth and development which signifies that as trade openness increases, the growth of gross domestic product also decreases.\u003c/li\u003e\n \u003cli\u003eThe\u0026nbsp;proxy of capital and labour, exchange rates, and imports have a significant influence on the growth of gross domestic product in the short run, whereas trade openness, does not significantly impact economic growth both in the short run and in the long run. While trade openness is a critical component of economic policy, its impact on growth is complex and multifaceted.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis study highlights the need for targeted and comprehensive economic strategies that consider the interplay between trade openness and other key economic variables to effectively promote economic development in Nigeria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6.1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Recommendation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following recommendations are made based on the findings of the study.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eOptimise Capital and Labour Utilisation:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eGiven that the proxy of capital to labour significantly influences economic growth in both the short and long run, it is essential to implement policies that enhance the efficiency of capital and labour deployment. This involves investing in comprehensive education and training programs to boost labour productivity and foster skill development. Additionally, promoting technological advancements and innovation can lead to more effective use of capital resources.\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eAddress Exchange Rate Fluctuations:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe observed negative impact of exchange rate fluctuations on GDP growth highlights the urgent need for stable exchange rate policies in Nigeria. To mitigate these adverse effects, the monetary authorities must implement measures such as maintaining adequate foreign exchange reserves and engaging in targeted currency stabilisation interventions in Nigeria. These actions can help reduce volatility and provide a more predictable economic environment, ultimately fostering a more stable and conducive atmosphere for sustained economic growth and development.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003ePromote Trade Openness:\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eTrade openness has a positive relationship with GDP growth over the long term and the short run. To harness these benefits, the Nigerian government needs to implement policies that enhance trade liberalisation, reduce trade barriers, and refine trade agreements. Supporting export-oriented industries through targeted incentives and improving trade facilitation processes can further amplify the advantages of trade openness.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUpon request, the corresponding author will provide the datasets gathered and/or analysed for this study. All of the study\u0026apos;s data are fully accessible to the corresponding author, who also bears full responsibility for the accuracy of the data analysis and the data\u0026apos;s integrity.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbinabo, P., Munir, S. M., \u0026amp; Abubakar, A. (2023). Workplace Diversity Management and Organizational Performance of Deposit Money Banks in Katsina State.\u0026nbsp;\u003cem\u003eUBS Journal of Business and Economic Policy\u003c/em\u003e,\u0026nbsp;\u003cem\u003e1\u003c/em\u003e(3), 213-229.\u003c/li\u003e\n\u003cli\u003eAfolabi, J. (2022). Financial Development, Trade Openness, and Economic Growth in Nigeria.\u0026nbsp;\u003cem\u003eIranian Economic Review\u003c/em\u003e,\u0026nbsp;\u003cem\u003e26\u003c/em\u003e(1), 237-254.\u003c/li\u003e\n\u003cli\u003eAjayi, E. O., \u0026amp; Araoye, F. E. (2019). Trade openness and economic growth in Nigeria.\u0026nbsp;\u003cem\u003eInternational Journal of Economics and Financial Management\u003c/em\u003e,\u0026nbsp;\u003cem\u003e4\u003c/em\u003e(2), 50-63.\u003c/li\u003e\n\u003cli\u003eAtoyebi, E. O., Oseni, I. O., Ogede, J. S., \u0026amp; Adegboyega, S. B. (2024). Unraveling the relationship between trade openness, economic growth, and financial development in Nigeria.\u0026nbsp;\u003cem\u003eJournal of Enterprise and Development (JED)\u003c/em\u003e,\u0026nbsp;\u003cem\u003e6\u003c/em\u003e(1), 1-11.\u003c/li\u003e\n\u003cli\u003eBajona, C., \u0026amp; Kehoe, T. J. (2010). Trade, growth, and convergence in a dynamic Heckscher\u0026ndash;Ohlin model.\u0026nbsp;\u003cem\u003eReview of Economic Dynamics\u003c/em\u003e,\u0026nbsp;\u003cem\u003e13\u003c/em\u003e(3), 487-513.\u003c/li\u003e\n\u003cli\u003eBaldwin, R. E. (2008). The development and testing of Heckscher-Ohlin trade models: a review.\u003c/li\u003e\n\u003cli\u003eBrondino, G. (2023). Fragmentation of production, comparative advantage, and the Heckscher-Ohlin theory.\u0026nbsp;\u003cem\u003eReview of Political Economy\u003c/em\u003e,\u0026nbsp;\u003cem\u003e35\u003c/em\u003e(3), 803-822.\u003c/li\u003e\n\u003cli\u003eDauda, R. O. S. (2007). The impact of FDI on Nigeria\u0026rsquo;s economic growth: trade policy matters.\u0026nbsp;\u003cem\u003eJournal of Business and Policy Research\u003c/em\u003e,\u0026nbsp;\u003cem\u003e3\u003c/em\u003e(2), 11-26\u003c/li\u003e\n\u003cli\u003eElijah, S., \u0026amp; Musa, A. B. (2019). The dynamic impact of trade openness on the economic growth in Nigeria.\u0026nbsp;\u003cem\u003eInternational Journal of Engineering and Advanced Technology\u003c/em\u003e,\u0026nbsp;\u003cem\u003e8\u003c/em\u003e(5), 609-616.\u003c/li\u003e\n\u003cli\u003eHuchet‐Bourdon, M., Le Mou\u0026euml;l, C., \u0026amp; Vijil, M. (2018). The relationship between trade openness and economic growth: Some new insights on the openness measurement issue.\u0026nbsp;\u003cem\u003eThe World Economy\u003c/em\u003e,\u0026nbsp;\u003cem\u003e41\u003c/em\u003e(1), 59-76\u003c/li\u003e\n\u003cli\u003eIjirshar, V. U. (2019). Impact of trade openness on economic growth among ECOWAS Countries: 1975-2017.\u0026nbsp;\u003cem\u003eCBN Journal of Applied Statistics (JAS)\u003c/em\u003e,\u0026nbsp;\u003cem\u003e10\u003c/em\u003e(1), 4.\u003c/li\u003e\n\u003cli\u003eKeho, Y. (2017). The impact of trade openness on economic growth: The case of Cote d\u0026rsquo;Ivoire.\u0026nbsp;\u003cem\u003eCogent Economics \u0026amp; Finance\u003c/em\u003e,\u0026nbsp;\u003cem\u003e5\u003c/em\u003e(1), 1332820.\u003c/li\u003e\n\u003cli\u003eKhobai, H., \u0026amp; Chitauro, M. (2018). The impact of trade liberalisation on economic growth in Switzerland.\u003c/li\u003e\n\u003cli\u003eMoyo, C., Kolisi, N., \u0026amp; Khobai, H. (2017). The relationship between trade openness and economic growth: The case of Ghana and Nigeria.\u003c/li\u003e\n\u003cli\u003eNduka, E. K. (2013). Openness and economic growth in Nigeria.\u0026nbsp;\u003cem\u003eJournal of Education and Practice\u003c/em\u003e,\u0026nbsp;\u003cem\u003e4\u003c/em\u003e(1), 68-73.\u003c/li\u003e\n\u003cli\u003eNwadike, G. C., Johnmary, A. K., \u0026amp; Alamba, C. S. (2020). Impact of trade openness on Nigerian economic growth: an empirical investigation, 1970\u0026ndash;2011.\u0026nbsp;\u003cem\u003eForeign Trade Review\u003c/em\u003e,\u0026nbsp;\u003cem\u003e55\u003c/em\u003e(2), 239-247.\u003c/li\u003e\n\u003cli\u003eOhwofasa, B. O., \u0026amp; Ekaruwe, M. (2023). Trade Openness and Economic Growth in Nigeria.\u0026nbsp;\u003cem\u003eLAFIA JOURNAL OF ECONOMICS AND MANAGEMENT SCIENCES\u003c/em\u003e,\u0026nbsp;\u003cem\u003e8\u003c/em\u003e, 23-47.\u003c/li\u003e\n\u003cli\u003eOmoke, P. C., \u0026amp; Opuala\u0026ndash;Charles, S. (2021). Trade openness and economic growth nexus: Exploring the role of institutional quality in Nigeria.\u0026nbsp;\u003cem\u003eCogent Economics \u0026amp; Finance\u003c/em\u003e,\u0026nbsp;\u003cem\u003e9\u003c/em\u003e(1), 1868686.\u003c/li\u003e\n\u003cli\u003eOppong-Baah, T., Bo, Y., Twi-Brempong, C., Amoah, E. O., Prempeh, N. A., \u0026amp; Addai, M. (2022). The Impact of trade openness on economic growth: The case of Ghana and Nigeria.\u0026nbsp;\u003cem\u003eJournal of Human Resource and Sustainability Studies\u003c/em\u003e,\u0026nbsp;\u003cem\u003e10\u003c/em\u003e(1), 142-160.\u003c/li\u003e\n\u003cli\u003eSolomon, O. I., \u0026amp; Tukur, M. U. (2019). Trade openness and economic growth in the developing countries: evidence from Nigeria.\u0026nbsp;\u003cem\u003eInternational Journal of Academic Research in Economics and Management Sciences\u003c/em\u003e,\u0026nbsp;\u003cem\u003e8\u003c/em\u003e(3), 30-42.\u003c/li\u003e\n\u003cli\u003eUmar, M., Chaudhry, I. S., Faheem, M., \u0026amp; Farooq, F. (2021). Do Governance, Foreign Direct Investment and Human Capital Matter to Bolster Trade Liberalization? Fresh Insight from Developing Countries.\u0026nbsp;\u003cem\u003eReview of Economics and Development Studies\u003c/em\u003e,\u0026nbsp;\u003cem\u003e7\u003c/em\u003e(3), 325-341.\u003c/li\u003e\n\u003cli\u003eYakubu, M. M., \u0026amp; Akanegbu, B. N. (2018). Trade openness and economic growth: Evidence from Nigeria.\u0026nbsp;\u003cem\u003eEuropean Journal of Business, Economics and Accountancy\u003c/em\u003e,\u0026nbsp;\u003cem\u003e6\u003c/em\u003e(4), 30-44.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Ibadan","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":"Trade Openness, Economic Growth, Economic Development, Autoregressive Distributed Lag","lastPublishedDoi":"10.21203/rs.3.rs-5437681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5437681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eThe study examines the impact of trade openness on economic growth and development in Nigeria from 1980 to 2021. The variables used in the study include the proxy of capital and labour, trade openness, exchange rate, and import and foreign reserves. A different diagnostic test was carried out which included correlation, unit root test and Autoregressive Distributed Lag. Descriptive statistics was used to examine if the explanatory variables and the dependent variable exhibit time-varying volatility and leptokurtosis characteristics. The Augmented Dickey-Fuller (ADF) unit root test was also carried out to check the long-run and short-run relationship of the variables while Аutоrеgrеssіvе dіstrіbutеd lаg (АRDL) bоunds tеstіng рrосеdurе and standardised beta was used to achieve the two specific objectives that were set. The АRDL bоunds tеstіng рrосеdurе revealed that the proxy of capital and labour is the only variables that determine economic growth and development in Nigeria, but trade openness has a positive insignificant effect on economic growth and development in Nigeria. Also, in the short run, the variables that significantly determine economic growth and development are the proxy of capital and labour, exchange rate and import.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"The Impact of Trade Openness on Economic Growth and Development (1980 – 2021): The Nigerian Experience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-13 09:35:44","doi":"10.21203/rs.3.rs-5437681/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":"eeb3d460-b92e-4e1b-a67f-2db59b56e323","owner":[],"postedDate":"November 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":40199262,"name":"International Economics"}],"tags":[],"updatedAt":"2024-11-13T09:35:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-13 09:35:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5437681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5437681","identity":"rs-5437681","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}