Pub Date : 2023-11-04DOI: 10.1142/s1793993323500266
Emmanuel Uche, Nicholas Ngepah
This study provides updated modalities for ensuring equitable income distributions in developing countries. This was achieved through the lens of self-employment, information and communication technologies (ICT), and remittances. To circumvent the dark spots in prior studies, this study harnesses annual panel series for 52 African countries. The study engaged both the system generalized method of moments (sGMM) and the panel quantile regression with nonadditive fixed effects (QRPD) techniques to elicit updated insights. Meanwhile, three metrics of income inequality, the Gini coefficient, the Atkinson index, and the Palma ratio, were explored for robust insights. A key discovery from both panel computations is the self-exacerbating inclinations of income disparities in the continent. Furthermore, it was discovered that both self-employment and ICT are significant income equalization factors. However, their influence is most effective at the upper quantiles of inequality. The influence of remittance inflows is predominantly unfavorable for equitable income distribution. Both financial inclusion and government effectiveness provided varying inequality-reducing effects. Notably, their influence is more formidable at the upper quantiles. Human capital development provides some noticeable income equalization effects, particularly at the lower quantiles. Policy insights for minifying income inequality in the continent are highlighted herein.
{"title":"Income Redistributive Propensities of Self-Employment, ICT and Remittances: Panel Quantile Regression with Nonadditive Fixed Effects Perspective","authors":"Emmanuel Uche, Nicholas Ngepah","doi":"10.1142/s1793993323500266","DOIUrl":"https://doi.org/10.1142/s1793993323500266","url":null,"abstract":"This study provides updated modalities for ensuring equitable income distributions in developing countries. This was achieved through the lens of self-employment, information and communication technologies (ICT), and remittances. To circumvent the dark spots in prior studies, this study harnesses annual panel series for 52 African countries. The study engaged both the system generalized method of moments (sGMM) and the panel quantile regression with nonadditive fixed effects (QRPD) techniques to elicit updated insights. Meanwhile, three metrics of income inequality, the Gini coefficient, the Atkinson index, and the Palma ratio, were explored for robust insights. A key discovery from both panel computations is the self-exacerbating inclinations of income disparities in the continent. Furthermore, it was discovered that both self-employment and ICT are significant income equalization factors. However, their influence is most effective at the upper quantiles of inequality. The influence of remittance inflows is predominantly unfavorable for equitable income distribution. Both financial inclusion and government effectiveness provided varying inequality-reducing effects. Notably, their influence is more formidable at the upper quantiles. Human capital development provides some noticeable income equalization effects, particularly at the lower quantiles. Policy insights for minifying income inequality in the continent are highlighted herein.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"56 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-04DOI: 10.1142/s1793993323500278
Alexander Correa
In this research paper, we address the challenge of predicting business bankruptcy in small and medium-sized enterprises (SMEs) in Colombia. We analyze various financial and non-financial factors that influence the likelihood of bankruptcy and employ machine learning techniques to improve prediction accuracy. We construct a database of 62,500 SMEs for the period 2017–2021 and compare two estimation methods: logistic regression and the eXtreme Gradient Boosting (XGBoost) algorithm. The findings demonstrate that the XGBoost algorithm outperforms in bankruptcy prediction. Key financial variables such as profitability and access to working capital, as well as non-financial variables such as geographic location, are identified as influencing bankruptcy risk. These findings provide valuable insights for stakeholders such as managers, financial intermediaries, and governmental decision-makers in their efforts to support and finance SMEs in Colombia, aiming to reduce bankruptcy rates and promote their economic success.
{"title":"Predicting Business Bankruptcy in Colombian SMEs: A Machine Learning Approach","authors":"Alexander Correa","doi":"10.1142/s1793993323500278","DOIUrl":"https://doi.org/10.1142/s1793993323500278","url":null,"abstract":"In this research paper, we address the challenge of predicting business bankruptcy in small and medium-sized enterprises (SMEs) in Colombia. We analyze various financial and non-financial factors that influence the likelihood of bankruptcy and employ machine learning techniques to improve prediction accuracy. We construct a database of 62,500 SMEs for the period 2017–2021 and compare two estimation methods: logistic regression and the eXtreme Gradient Boosting (XGBoost) algorithm. The findings demonstrate that the XGBoost algorithm outperforms in bankruptcy prediction. Key financial variables such as profitability and access to working capital, as well as non-financial variables such as geographic location, are identified as influencing bankruptcy risk. These findings provide valuable insights for stakeholders such as managers, financial intermediaries, and governmental decision-makers in their efforts to support and finance SMEs in Colombia, aiming to reduce bankruptcy rates and promote their economic success.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"56 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135774826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1142/s1793993323500242
Can Dinh Ngoc, Tam Phan Huy, Tu Ta Thi Cam, Tam Luong Thi My, Hien Nguyen Thi Thuy, Minh Ngo Hai
This paper aims to cluster politically affiliated groups using machine learning. The sample used in the study is enterprises listed on the stock exchanges of Ho Chi Minh City and Hanoi, research data during the period from 2015 to 2020. Data used in the study include state ownership ratio, the degree of political connection of business leaders and financial indicators in the listed financial statements of enterprises. The author’s study measures political connection by K-means algorithm and then compares the results of the K-means clustering with the traditional method of manual measurement of political connection including two values of 0 and 1, where 0 is no political affiliation and 1 is political affiliation. At the same time, the author runs three clusters to have in-depth insight. The authors conclude that machine learning clustering using the k-means model can replace the traditional method. Politically connected businesses listed on HOSE and HNX with political connections bring many benefits to businesses in investment activities, in accessing resources as well as capital; however, that businesses have a negative impact on business performance. The authors recommend that a moderate degree of political affiliation will help businesses achieve better performance.
{"title":"Political Affiliate Clustering with Machine Learning in Vietnam Stock Exchange Market","authors":"Can Dinh Ngoc, Tam Phan Huy, Tu Ta Thi Cam, Tam Luong Thi My, Hien Nguyen Thi Thuy, Minh Ngo Hai","doi":"10.1142/s1793993323500242","DOIUrl":"https://doi.org/10.1142/s1793993323500242","url":null,"abstract":"This paper aims to cluster politically affiliated groups using machine learning. The sample used in the study is enterprises listed on the stock exchanges of Ho Chi Minh City and Hanoi, research data during the period from 2015 to 2020. Data used in the study include state ownership ratio, the degree of political connection of business leaders and financial indicators in the listed financial statements of enterprises. The author’s study measures political connection by K-means algorithm and then compares the results of the K-means clustering with the traditional method of manual measurement of political connection including two values of 0 and 1, where 0 is no political affiliation and 1 is political affiliation. At the same time, the author runs three clusters to have in-depth insight. The authors conclude that machine learning clustering using the k-means model can replace the traditional method. Politically connected businesses listed on HOSE and HNX with political connections bring many benefits to businesses in investment activities, in accessing resources as well as capital; however, that businesses have a negative impact on business performance. The authors recommend that a moderate degree of political affiliation will help businesses achieve better performance.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135592604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.1142/s1793993323500230
Asma Salman, Muthanna G. Abdul Razzaq, Bisharat Hussain Chang, Wing-Keung Wong, Mohammed Ahmar Uddin
Previous research has investigated the connections between foreign direct investment (FDI), carbon emissions (CO 2 ), and foreign trade openness. However, these past studies did not specifically focus on industrial sectors in China and their carbon emissions, thus leaving a gap in understanding this relationship. In our study, we aim to contribute to the existing body of knowledge by employing a threshold regression model with a threshold variable. This model calculates how strongly carbon emissions are produced to assess the impact of the industrial sector on carbon emissions. Our findings reveal that foreign trade openness and FDI have a threefold threshold impact on industrial carbon emissions. The effect of FDI on carbon emissions in the industrial sector shows a pattern of initially lowering and then increasing the emissions, indicating potential harm. Conversely, the impact of foreign trade openness on carbon emissions exhibits both positive and negative effects. While foreign trade openness exacerbates carbon emissions in economic sectors with lower carbon intensity, it helps mitigate emissions in sectors with high- carbon emission levels. Furthermore, our study identifies that the intensity of economic activity, per capita GDP, and the number of employees all significantly influence the industrial sector’s carbon emissions. By employing the latest cutting-edge methodology, our research opens the door for extrapolating these findings to other nations for a comprehensive analysis.
{"title":"Carbon Emissions and Its Relationship with Foreign Trade Openness and Foreign Direct Investment","authors":"Asma Salman, Muthanna G. Abdul Razzaq, Bisharat Hussain Chang, Wing-Keung Wong, Mohammed Ahmar Uddin","doi":"10.1142/s1793993323500230","DOIUrl":"https://doi.org/10.1142/s1793993323500230","url":null,"abstract":"Previous research has investigated the connections between foreign direct investment (FDI), carbon emissions (CO 2 ), and foreign trade openness. However, these past studies did not specifically focus on industrial sectors in China and their carbon emissions, thus leaving a gap in understanding this relationship. In our study, we aim to contribute to the existing body of knowledge by employing a threshold regression model with a threshold variable. This model calculates how strongly carbon emissions are produced to assess the impact of the industrial sector on carbon emissions. Our findings reveal that foreign trade openness and FDI have a threefold threshold impact on industrial carbon emissions. The effect of FDI on carbon emissions in the industrial sector shows a pattern of initially lowering and then increasing the emissions, indicating potential harm. Conversely, the impact of foreign trade openness on carbon emissions exhibits both positive and negative effects. While foreign trade openness exacerbates carbon emissions in economic sectors with lower carbon intensity, it helps mitigate emissions in sectors with high- carbon emission levels. Furthermore, our study identifies that the intensity of economic activity, per capita GDP, and the number of employees all significantly influence the industrial sector’s carbon emissions. By employing the latest cutting-edge methodology, our research opens the door for extrapolating these findings to other nations for a comprehensive analysis.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136341551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.1142/s1793993323500254
Shilpy Verma
This study examines the role of human capital accumulation in order to escape the poverty-land degradation trap. Moreover, we explore whether the human capital accumulation could lead to reduction in land degradation and poverty. To test this, we have used data of 26 Indian states covering time period 1993–2011 and have employed System-GMM method of estimation to account for the joint endogeneity between the dependent and the explanatory variables. Due to the non-availability of state level poverty data, we have restricted our study to year 2011. To measure poverty, we have used head count ratio, total land degradation as percentage of geographical area is used as a proxy for land degradation, and enrolment in primary classes and 6th to 12th classes is used to measure human capital accumulation. The results suggest that land degradation reduces poverty and increase in poverty increases land degradation. This could be due to the fact that increase in income or reduction in poverty of individual requires the intensification of agriculture production, which contributed to land degradation. We also find that higher educational attainment will reduce poverty. The role of human capital accumulation on land degradation remains unclear.
{"title":"Role of Human Capital Accumulation in Reducing Poverty and Land Degradation","authors":"Shilpy Verma","doi":"10.1142/s1793993323500254","DOIUrl":"https://doi.org/10.1142/s1793993323500254","url":null,"abstract":"This study examines the role of human capital accumulation in order to escape the poverty-land degradation trap. Moreover, we explore whether the human capital accumulation could lead to reduction in land degradation and poverty. To test this, we have used data of 26 Indian states covering time period 1993–2011 and have employed System-GMM method of estimation to account for the joint endogeneity between the dependent and the explanatory variables. Due to the non-availability of state level poverty data, we have restricted our study to year 2011. To measure poverty, we have used head count ratio, total land degradation as percentage of geographical area is used as a proxy for land degradation, and enrolment in primary classes and 6th to 12th classes is used to measure human capital accumulation. The results suggest that land degradation reduces poverty and increase in poverty increases land degradation. This could be due to the fact that increase in income or reduction in poverty of individual requires the intensification of agriculture production, which contributed to land degradation. We also find that higher educational attainment will reduce poverty. The role of human capital accumulation on land degradation remains unclear.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.1142/s1793993323500217
Victor Krasnobayev, Alina Yanko, Alina Hlushko
Research directed at strengthening the security of the national economy of the state in the information sphere is based on ensuring operational (fast-acting) reliability, confidentiality, integrity and availability of state information resources, information with limited access, in particular, circulating at economic information infrastructure facilities in the context of information and hybrid wars. The essence of scientific research is to increase the speed (performance) and reliability of computer systems of processing economic data due to the development and implementation of methods of control, diagnosis and correction of errors of the non-positional number system, the so-called system of residual classes (SRC). Prospects for further research are aimed at formulating the concept of development of reliable computer systems for real-time data processing in SRC used in the modern economy.
{"title":"Information Security of the National Economy Based on an Effective Data Control Method","authors":"Victor Krasnobayev, Alina Yanko, Alina Hlushko","doi":"10.1142/s1793993323500217","DOIUrl":"https://doi.org/10.1142/s1793993323500217","url":null,"abstract":"Research directed at strengthening the security of the national economy of the state in the information sphere is based on ensuring operational (fast-acting) reliability, confidentiality, integrity and availability of state information resources, information with limited access, in particular, circulating at economic information infrastructure facilities in the context of information and hybrid wars. The essence of scientific research is to increase the speed (performance) and reliability of computer systems of processing economic data due to the development and implementation of methods of control, diagnosis and correction of errors of the non-positional number system, the so-called system of residual classes (SRC). Prospects for further research are aimed at formulating the concept of development of reliable computer systems for real-time data processing in SRC used in the modern economy.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135011562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1142/s1793993323500205
Ha Quynh Hoa, N. Hung, Leavitt Ha, Luu Thi Phuong, Truong Nhu Hieu, Tran Anh Ngoc
In this paper, we employ the quantile vector autoregression (QVAR) technique to determine the degree of connectedness between seven variables from 1985 to 2019 for the purpose of examining the relationships between the Trade market and Green energy consumption. Based on our findings, dynamic connectedness, which is 24.18% in the short term and 9% in the long term, is influenced by both long-term and short-term periods. Based on the dynamic net total connectedness of a quantile, a quantile of 50% describes the period’s overall connectedness, which is associated both with highly positive changes (above the 80% quantile) and with highly volatile variables (below the 20% quantile) of export, import, and green energy consumption. In both durations, export and import values turn into a net shock transmitter, and green energy consumption acts like a net shock receiver since the last half of the period. In 2008, uncertain events were correlated with dynamic net pairwise directional connectedness over a quantile, such as the Global Financial crisis, have an influence on the trade market and green energy consumption’s volatility.
{"title":"An Exploration of Interlinkages between International Trades and Green Energy Volatility over Quantiles","authors":"Ha Quynh Hoa, N. Hung, Leavitt Ha, Luu Thi Phuong, Truong Nhu Hieu, Tran Anh Ngoc","doi":"10.1142/s1793993323500205","DOIUrl":"https://doi.org/10.1142/s1793993323500205","url":null,"abstract":"In this paper, we employ the quantile vector autoregression (QVAR) technique to determine the degree of connectedness between seven variables from 1985 to 2019 for the purpose of examining the relationships between the Trade market and Green energy consumption. Based on our findings, dynamic connectedness, which is 24.18% in the short term and 9% in the long term, is influenced by both long-term and short-term periods. Based on the dynamic net total connectedness of a quantile, a quantile of 50% describes the period’s overall connectedness, which is associated both with highly positive changes (above the 80% quantile) and with highly volatile variables (below the 20% quantile) of export, import, and green energy consumption. In both durations, export and import values turn into a net shock transmitter, and green energy consumption acts like a net shock receiver since the last half of the period. In 2008, uncertain events were correlated with dynamic net pairwise directional connectedness over a quantile, such as the Global Financial crisis, have an influence on the trade market and green energy consumption’s volatility.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"65 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86575314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.1142/s1793993323500199
Shahid Mahmood Waqar, M. Abdu
This study explores the productivity growth effects of horizontal, backward, and forward FDI spillovers in the Türkiye manufacturing sector using industry-level data for the period 2008–2018. While controlling for capital intensity and human capital as proxies for the absorption capacity, we apply system GMM and bootstrapped LSDV estimator to estimate the models. Our findings reveal that backward linkages significantly hamper industrial productivity due to the rudimentary nature of the products in the downstream sector or lack of absorption capacity. While horizontal spillovers retard the productivity growth; forward linkages enhance the growth, though all insignificant. The results depict that all the interactions with capital intensity strongly promote industrial productivity growth.
{"title":"Productivity Growth Effects of FDI Spillovers: Evidence from the Türkiye Manufacturing Industries","authors":"Shahid Mahmood Waqar, M. Abdu","doi":"10.1142/s1793993323500199","DOIUrl":"https://doi.org/10.1142/s1793993323500199","url":null,"abstract":"This study explores the productivity growth effects of horizontal, backward, and forward FDI spillovers in the Türkiye manufacturing sector using industry-level data for the period 2008–2018. While controlling for capital intensity and human capital as proxies for the absorption capacity, we apply system GMM and bootstrapped LSDV estimator to estimate the models. Our findings reveal that backward linkages significantly hamper industrial productivity due to the rudimentary nature of the products in the downstream sector or lack of absorption capacity. While horizontal spillovers retard the productivity growth; forward linkages enhance the growth, though all insignificant. The results depict that all the interactions with capital intensity strongly promote industrial productivity growth.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"25 35","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72489448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-18DOI: 10.1142/s1793993323500163
Saransh Royal, Kamaljit Singh, Ramesh Chander
The study aims to ascertain the impact of micro, small and medium enterprises (MSMEs) growth on wealth creation and its distribution in India concerning macroeconomic variables such as GDP (Gross Domestic Product) per capita, unemployment, Foreign direct investment (FDI), human development index (HDI) and the urban population (URP). The research has examined the underlying short-term association using ECM, FMOLS, DOLS and CCR to estimate the long-run association between the identified variables. It documents a positive relationship between the share of the B[Formula: see text] populace and the FDI. On the other hand, per capita GDP, in the long run, had a negative association with MSME share, URP and HDI. Similarly, for the top 10 percentile (T[Formula: see text]) share, there was a positive relationship between MSME share and URP. Therefore, the results document a decentralized wealth creation for an MSME-focused development strategy in the short run to address skewed wealth creation in emerging societies.
{"title":"MSME Promotion, Inequality and Decentralized Wealth Creation: A Strategic Policy Perspective","authors":"Saransh Royal, Kamaljit Singh, Ramesh Chander","doi":"10.1142/s1793993323500163","DOIUrl":"https://doi.org/10.1142/s1793993323500163","url":null,"abstract":"The study aims to ascertain the impact of micro, small and medium enterprises (MSMEs) growth on wealth creation and its distribution in India concerning macroeconomic variables such as GDP (Gross Domestic Product) per capita, unemployment, Foreign direct investment (FDI), human development index (HDI) and the urban population (URP). The research has examined the underlying short-term association using ECM, FMOLS, DOLS and CCR to estimate the long-run association between the identified variables. It documents a positive relationship between the share of the B[Formula: see text] populace and the FDI. On the other hand, per capita GDP, in the long run, had a negative association with MSME share, URP and HDI. Similarly, for the top 10 percentile (T[Formula: see text]) share, there was a positive relationship between MSME share and URP. Therefore, the results document a decentralized wealth creation for an MSME-focused development strategy in the short run to address skewed wealth creation in emerging societies.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"4 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89532911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-18DOI: 10.1142/s1793993323500187
Feriel Nasser, Feryel Ouerghi
The COVID-19 pandemic has raised concerns about the vulnerabilities of global value chains (GVCs), leading to discussions on how to enhance their resilience, security, and sustainability through adjustments to Industry 4.0 roadmaps. While some argue that digitization under Industry 4.0 could be a potential solution to make GVCs more resilient, others suggest that it could potentially reverse the trend toward GVCs and favor near-shoring or reshoring. However, empirical research on the impact of digital technologies on GVCs proliferation is lacking. This study addresses this gap by using a panel data set covering 27 African countries from 2005 to 2018 to examine how digitalization under Industry 4.0 affects the participation of African countries in GVCs. The findings reveal that digital infrastructure and skills positively and significantly impact GVCs participation. However, based on the Hansen threshold model, we find that when digital skills are below a certain threshold, digital infrastructure negatively affects both forward and backward linkages to GVCs. Conversely, when digital skills are above the threshold, digital infrastructure has a positive impact only on backward linkages. Nonetheless, digital skills consistently and significantly impact the participation of African countries in GVCs, irrespective of the level of digital infrastructure. As a conclusion, this study highlights the importance of digital infrastructure and skills in shaping the participation of African countries in GVCs, and underscores the need for further research in this area.
{"title":"Global Value Chains and Digitalization under Industry 4.0: The Hansen Threshold Regression Model in the Case of Africa","authors":"Feriel Nasser, Feryel Ouerghi","doi":"10.1142/s1793993323500187","DOIUrl":"https://doi.org/10.1142/s1793993323500187","url":null,"abstract":"The COVID-19 pandemic has raised concerns about the vulnerabilities of global value chains (GVCs), leading to discussions on how to enhance their resilience, security, and sustainability through adjustments to Industry 4.0 roadmaps. While some argue that digitization under Industry 4.0 could be a potential solution to make GVCs more resilient, others suggest that it could potentially reverse the trend toward GVCs and favor near-shoring or reshoring. However, empirical research on the impact of digital technologies on GVCs proliferation is lacking. This study addresses this gap by using a panel data set covering 27 African countries from 2005 to 2018 to examine how digitalization under Industry 4.0 affects the participation of African countries in GVCs. The findings reveal that digital infrastructure and skills positively and significantly impact GVCs participation. However, based on the Hansen threshold model, we find that when digital skills are below a certain threshold, digital infrastructure negatively affects both forward and backward linkages to GVCs. Conversely, when digital skills are above the threshold, digital infrastructure has a positive impact only on backward linkages. Nonetheless, digital skills consistently and significantly impact the participation of African countries in GVCs, irrespective of the level of digital infrastructure. As a conclusion, this study highlights the importance of digital infrastructure and skills in shaping the participation of African countries in GVCs, and underscores the need for further research in this area.","PeriodicalId":44073,"journal":{"name":"Journal of International Commerce Economics and Policy","volume":"10 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91122638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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