Panel Data Research Articles

Friendshoring: how geopolitical tensions affect foreign sourcing, supply base complexity, and sub-tier supplier sharing

PurposeThis paper examines the influence of geopolitical tensions—operationalized as political divergence between governments—on firms’ foreign supply bases and the resulting effects on supply base complexity and sub-tier supplier sharing.Design/methodology/approachThe authors conduct panel data regression analyses over the period 2003–2019 to investigate whether political divergence affects foreign supply bases for 2,858 US firms sourcing from 99 countries and to examine how political divergence exposure impacts the supply network structures of 853 US firms.FindingsFirms reduce their supply bases in countries exposed to heightened geopolitical tensions. These supply chain adjustments are associated with increased supply base complexity and greater sub-tier supplier sharing.Originality/valueThis study highlights the importance of state relations in global supply chain reconfiguration. Political divergence between governments provides a dual-view of political risk (i.e. buyer–supplier countries), which can help firms anticipate geopolitical disruptions. While reducing supply bases in foreign countries facing heightened geopolitical tensions is intended to mitigate disruptions, these supply base adjustments are linked to increased supply base complexity and sub-tier supplier sharing, thereby exposing firms to other types of supply disruptions. Additionally, this research contributes to understanding the effects of geopolitical tensions on supply base complexity through the lenses of transaction cost economics and resource dependence theory.

Institutions as a determinant of Foreign Direct Investment inflows into the Southern African Development Community

Foreign Direct Investment (FDI) in Southern Africa has been one of the drivers of infrastructure development and economic growth especially in sectors such as mining, agriculture, energy, information, and communications technology (ICT). However, although important economic and institutional reforms have been undertaken by some SADC countries to encourage the inflow of FDI--particularly in low-income countries in the region, the flow of FDI to SADC member states remains low and concentrated in few countries and sectors and is still largely attracted to natural resources sectors. This paper examines the institutions and infrastructure development in the promotion of FDI inflows into the SADC region. Institutions and infrastructure development typically have a positive effect on FDI inflows through their impact on the investment climate. The paper uses panel data econometric analysis with OLS and PCSE to ascertain the impact of governance institutions on FDI inflows into the region. The results obtained reveal that the quality of governance, together with the level of economic development, market size, and openness to trade with the external world play a critical role in attracting FDI into SADC countries. There is however a need to control rampant corruption and reduce the political instability common in some of the countries of the region.

The macroeconomic determinants of trade openness in Latin American countries: A panel data analysis

Background Trade openness shows a positive impact on economic growth, supported by economic theory, and export diversification and economic complexity show a positive dynamic in trade openness in the world; however, a specificity is generated in South American countries. Therefore, the objective of the research is to analyse the macroeconomic determinants of trade openness in Latin American countries. Methods The research approach was quantitative and explanatory using panel data methodology from the databases of the World Bank, Harvard University and the Economic Commission for Latin America and the Caribbean for the period 2000-2020. Results The fixed effects panel data model showed that the variables that had a negative impact on trade openness were GDP, the economic complexity index and the logistic performance index, while the variables that had a positive impact were exports of high-tech products (a proxy for innovation), exports, imports, research and development expenditure and interregional trade in goods. Conclusions Therefore, during the analysis period of 2000-2020 in South America, based on the panel data analysis under fixed effects, a total of 8 countries had a negative impact on trade openness, and only the economies of Chile, French Guiana, and Brazil had a positive impact on trade openness; these economies are characterized by their better performance in the economic complexity index, their higher percentage of budget for research and development expenses, and their trade policies oriented towards the industrialization of their value-added products.

Donor country official development assistance in health R&D: domestic economic burden vs. medical disseminative capacity

Abstract This study examines domestic determinants of donor country official development assistance (ODA) in health research and development (R&D). It argues that health R&D ODA is negatively related to domestic economic burden, i.e. pressures that donor governments face because of economic issues in their own country, while also positively influenced by long-standing capabilities in medicine and medical research that are projected globally. Using panel data on forty-four donor countries over a 6-year period, the study finds support for a negative relationship between domestic economic burden and donor country health R&D ODA. It also finds a positive relationship between medical disseminative capacity (MDC) and donor country health R&D ODA, as well as with the ratio of health R&D ODA to overall ODA. While domestic economic burden dampens the overall appetite for health R&D ODA, MDC helps to reverse this and ensures that the proportion of ODA that goes to health R&D in developing countries is increased.

Has the Anti-Corruption Campaign Decreased Environmental Pollution? Evidence from China

Whether anti-corruption efforts help reduce environmental pollution is a hot topic in academia. This paper analyzes the impact of anti-corruption on the emissions of environmental pollutants using panel data from 31 provinces (municipalities) in China from 2015 to 2022. By using the 2018 supervision system reform as an exogenous policy shock, a Difference-in-Differences (DID) model is employed to examine the impact of the anti-corruption campaign on environmental pollutant emissions. The results show that the effectiveness of anti-corruption measures has strengthened over time, especially after the 2018 system reform, although these reforms exhibit a lag effect before significantly reducing pollution levels. Furthermore, heterogeneity analysis indicates that due to the high-pollution, high-energy-consumption industrial structure, the pollution reduction effect of anti-corruption measures is more pronounced in resource-based provinces than in non-resource-based provinces. Our findings emphasize the importance of strengthening anti-corruption measures and establishing a sound legal framework to effectively curb corruption and enhance environmental protection.

Climate policy uncertainty and economic growth, a moderating role of crude oil price changes: evidence from the Asian economies

Purpose This study aims to inspect the impact of US climate policy uncertainty (CPU) on the economic growth of Asian countries with the moderating role of crude oil price (COP) changes. Design/methodology/approach The Im-Pesaran Sin and Fisher-type tests are used for stationarity check, while Kao and Pedroni tests are used for cointegration analysis. The Hausman test is applied for model selection, where pooled mean group autoregressive distributed lag (PMG/ARDL) has been selected and applied. Besides, the fully modified ordinary least squares is also used for robustness analysis. Additionally, the literature review and descriptive statistics have been used. Findings The main findings disclosed that US CPU negatively impacted the economic growth of Asian economies with high significance in the long run whereas insignificant in the short run. The results further concluded that COP positively affected economic growth both in the short and long run. Furthermore, the results also revealed that COP significantly and positively moderates the relationship between CPU and COP in the long and short run. Originality/value The study is the first of its kind to examine the impact of the US CPU on the economic growth of Asian economies. Second, it further revealed the moderating role of COP between US CPU and economic growth. Third, a large panel of data from Asian countries has been considered. Fourth, the study adds to the current literature by using the PMG/ARDL model to determine the impact of US CPU on economic growth. Additionally, this study focuses on the US CPU because it is a developed country playing a significant role in energy and climate issues, and has been very uncertain.

The influence of economic determinants on CO2 emissions in Belt and Road Initiative (BRI) countries.

CO2 emissions in Belt and Road Initiative (BRI) countries are precisely influenced by economic determinants, requiring a comprehensive perspective. The BRI can augment its prospects for sustainable development by acknowledging the obstacles it faces and promoting global collaboration. Examining the CO2 emission (CO2e) in BRI countries in response to economic determinants such as financial development (FD), income distribution (ID), foreign direct investment (FDI), economic complexity index (ECI), and economic growth (EG) will determine the study's long-term and short-term impacts. This study introduces a novel concept of CO2es by employing panel data from 1991 to 2020. Thus, the CD, Kao, Pedroni, FMOLS, and pooled mean group-autoregressive distributed lag (PMG-ARDL) tests are utilized to assess cointegration. According to empirical findings, economic determinants (ECI, EG, FDI, and ID) have a statistically significant short-run and long-run impact on CO2e in BRI countries. Policymakers in BRI countries should integrate monetary development, FDI, and CO2es to foster EG, attract FDI, and promote sustainable development through regulatory frameworks.

Impact of Green Finance on Carbon Emissions: Empirical Analysis Based on Chinese Provincial Panel Data

Impact of Green Finance on Carbon Emissions: Empirical Analysis Based on Chinese Provincial Panel Data

Does Rigorous Government Regulation on Nonprofits Improve Their Outputs? Evidence from China

Abstract This study mainly takes China as an example to explore the logic between government regulation and outputs of nonprofit organizations in the context of authoritarian countries. Based on the theory of embeddedness and organizational legitimacy, using the panel data of 29 mainland provinces from 2010 to 2019, and applying the fixed effect model, it is found that government regulation has a positive effect on outputs of non-profit organizations. However, it is also found that there exists a single threshold, only government regulation intensity keeps in a certain range, the positive effect is made. Further research finds that government regulation positively impacts nonprofit outputs through encouraging social donations. Our findings fill the gap of exploring the logic between government regulation and nonprofits outputs, giving some enlightenment to regulators of similar regimes countries. We also have improved the current government regulation theory based on legitimacy and embeddedness theory empirically, extended and enriched embeddedness theory.

The Influence Of Economic Value Added (EVA), Return On Assets (ROA) On Stock Prices With Market Value Added (MVA) As A Moderating Variable

The aim of this research is to ascertain the influence of Economic Value Added (EVA), Return on Assets (ROA) on stock prices with Market Value Added (MVA) as a moderating variable in retail sector companies on the Indonesian Stock Exchange for the 2017-2022 period. The research methodology used is a quantitative method. The research population and sample consisted of 30 data. In this research, the data collection techniques used in this research were documentation and library research techniques. Data were analyzed using panel data regression, Microsoft Excel 2010 and Eviews Version 12 were used to process the data. Findings: The results of the t test (partial) on the Economic Value Added (EVA) variable (X1) obtained a calculated t value of 0.434167 < t table, namely 2.048407142 and a sig value. 0.6676 > 0.05, then H1 is rejected. The results of the t test (partial) on the Return on Assets (ROA) variable obtained a calculated t value of 12.77570 > t table, namely 2.048407142 and a sig value. 0.0000 < 0.05, then H2 is accepted. The results of the t test (partial) on the moderating variable Market Value Added (MVA) are able to moderate Economic Value Added (EVA) and obtain a sig level value. is 1.288399 > 0.05 and the sig.prob value is 0.2094 < 0.05, then H3 is accepted. The results of the t test (partial) on the Market Value Added (MVA) moderating variable are able to moderate the Return on Assets (ROA) to obtain a sig level value. is -0.916624 < 0.05 and the sig.prob value is 0.3681 > 0.05, then H4 is rejected.

Factors Influencing Water Resource Levels under the Water Resource Carrying Capacity Framework: A Dynamic Qualitative Comparative Analysis Based on Provincial Panel Data

Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management.

More ESG Practices, Higher Financial Performance? The U‐Shaped Pattern in China's Agricultural and Food Firms

ABSTRACTESG (environmental, social, and governance) practices, an internationally recognized concept of a firm's sustainability, can serve as a bridge to enhance effective communication between firms and various stakeholders. It is also a new tool for measuring firms' value. This study employs a balanced panel data set of 114 publicly traded agricultural and food firms in China from 2016 to 2022. It empirically investigates the relationship between ESG and financial performance based on shareholder primacy theory and stakeholder theory. Employing a two‐way fixed effects (FE) model, our findings reveal a U‐shaped nonlinear pattern in how ESG impacts financial performance. It differs from previous studies that found predominantly positive relationships: Specifically, the average ESG score for firms is 0.396, the median is 0.390, and the inflection point of the U‐shape occurs at 0.53. When firms' ESG investments are less than 0.53, the high initial ESG cost makes it difficult to transform ESG into financial improvement. However, once this threshold is surpassed, good ESG can convey an excellent reputation to the public and increase anti‐risk ability—which, in turn, significantly improves firms' financial performance and facilitates long‐term development. Also, our study demonstrates that firms' ownership and different positions in the supply chain differentially affect the relationship between ESG and financial performance. This paper also offers insights into promoting the sustainable development of Chinese agri‐food firms.

Elucidating the Non-Performing Assets in Indian Banking Sector: Does Macroeconomic Factor Matter?*

Using the system generalized methods of moments on panel data set of 45 selected Indian commercial banks from 2005–2006 to 2019–2020, the study investigates the determinants of non-performing assets (NPAs), taking into account macroeconomic and bank-specific factors. The study finds evidence of a persistent effect in stressed assets. The profitability ratio, operational capacity, cost efficiency and aggressive lending negatively and significantly affect the NPAs. The negative impact of the profitability ratio implies that less efficient banks are more exposed to bad loans. While cost efficiency discourages the NPAs, on the other hand, higher credit deposit ratio (operational capacity) suggests that a well-diversified portfolio leads to lesser probability of loan defaults. The probability of loan default is high when more advances are released to the economy’s weaker and vulnerable sectors (high-priority sector lending). Small-sized banks are more efficient in NPAs management than large-sized banks. Various macroeconomic variables, such as lending rates and credit growth in the banking industry, significantly affect the NPAs. The higher lending rate adversely affects borrowers’ repayment capacity, leading to more stressed assets. Therefore, to maintain bad assets within a bearable limit, policymakers should take macroeconomic determinants into consideration.

Urban housing prices and consumption structure upgrading: Different relationships in urban and rural China

The dynamics of housing prices can play a pivotal role in shaping household behavior. Motivated by the limited research on the impact of housing prices on consumption structure upgrading in China, this paper presents a series of analyses that deploy panel data from 276 Chinese cities between 2005 and 2019 to scrutinize this impact. Firstly, fixed effect models were used to investigate the relationship between urban housing price and the consumption structure upgrading, and it was found that urban housing price has an inverted U-shaped effect on the consumption structure upgrading of Chinese urban residents, while it has an inhibitory effect on the consumption structure upgrading of Chinese rural residents. Then, we conducted multiple robustness tests, all of which corroborated the benchmark results’ reliability. Finally, deeper than existing research, the mechanism of the impact of urban housing prices on the consumption structure upgrading was further explored and it was found that increasing urban housing prices can affect consumption structure upgrading by affecting residents’ marginal propensity to consume in development and enjoyment. Our findings provide key alternatives for China’s government to promote residents’ consumption structure upgrading.

Analysis of Spatiotemporal Evolution of Coordinated Development Between Transportation Infrastructure and Ecological Environment in the Yangtze River Economic Belt

The coupling and coordinated development of transportation infrastructure and ecological environment is an important way to achieve win-win economic, social, and ecological benefits. This study analyzes the coupling and coordinated development between transportation infrastructure and ecological environment in the Yangtze River Economic Belt. Based on panel data from 11 provinces in the Yangtze River Economic Belt from 2007 to 2022, establish their respective indicator systems and use entropy method to measure the comprehensive level of the two. Through the perspective of spatiotemporal differentiation, this study analyzes the changes in the coupling and coordinated development level of transportation infrastructure and ecological environment in 11 provinces. It is found that the overall coupling and coordinated development level of each province has significantly improved, but there are obvious regional differences. In the future, each province should formulate more precise and effective policy measures based on its own actual situation, strengthen regional cooperation and communication, and jointly promote the coupling and coordinated development of transportation infrastructure and ecological environment protection in the Yangtze River Economic Belt.

How Does AI Affect the Pay Gap Within Firms: Mechanism Analysis Based on Personnel Structure and Corporate Investment

ABSTRACTThis study examines how AI impacts the internal pay gap within enterprises. Using data from listed companies in China and a panel data two‐way fixed effect model, findings reveal that AI widens pay gap, with executives in AI‐applied companies earning 0.327 times more than average employees. AI increases executive pay while hindering employee salary growth, especially in nonmanufacturing and private firms. Labor substitution AI reduces employee compensation growth, whereas labor enhancement AI boosts executive pay without affecting employee compensation. AI also influences personnel structure and enterprise investment in fixed assets and R&D, highlighting its “job substitution effect” and “productivity effect”.

Nexus between Financial Inclusion and Poverty: Does the Country's Education matter? Evidence from Lower-Middle-Income Countries

There are special relations between financial inclusion and social inclusion with the latter being one of the best addressed when people have access to financial services. This paper explores effects of financial access on poverty, while incorporating moderation effects by years of schooling. Therefore, this study utilizes unbalanced panel data of 17 lower-middle-income countries itself and both the above mentioned static and dynamic panel model to conduct a strict panel data analyse. The analysis of data, employing the Composite Financial Inclusion Index (CFII) as an instrument to assess financial inclusion, shows that the level of financial inclusion and poverty in these countries are negatively related and sharply influenced. Also, the study discovers that there is a positive correlation between the financial inclusion, and Poverty reduction after controlling the effects of education attainment. They provide useful recommendations for policymakers, institutions dealing with money, and governments. First, financial services must be brought nearer to the poor populations which can reduce poverty level in the society. Second, a subsequent improvement of the education level is required to achieve the best results for financial inclusion on poverty reduction.

Wrapping input–output multipliers in confidence intervals

Input–output multipliers are typically calculated as point estimates of the Leontief quantity model. From the previous literature, they can also be estimated (and their confidence intervals) directly from establishments’/industries’ inputs and outputs data by running an appropriate econometric regression. However, previous contributions relied on analyses carried out for 1 single year, one country/region and a reduced number of degrees of freedom. This paper tests the robustness of the previous literature by using instead a time series of large-scale inter-country supply, use and input–output database with more than one country and more than 1 year, as well as panel data econometrics.

The Non-Linear Impact of Industry 4.0 on Carbon Emissions in China’s Logistics Sector

This study investigates the impact of Industry 4.0 on carbon emissions within China’s logistics sector, focusing on its potential to support global carbon reduction goals. Utilizing panel data from 30 Chinese provinces between 2011 and 2019, this research employed an Industry 4.0 index alongside IPCC guidelines to estimate logistics emissions. Through fixed effects and dynamic panel models, this study indicated an inverted U-shaped relationship among the development of Industry 4.0 and carbon emission management. Industries move to emitting more pollution to provide their required needs to all but once technologies advance, drastic decreases in combustion and emissions take place as the industries move more towards conservation and the integration of information continues to improve. This study investigates the non-linear impact of Industry 4.0 on carbon emissions in China’s logistics sector. Utilizing panel data from 30 Chinese provinces between 2011 and 2019, the research employs a dynamic panel model to quantify the relationship between Industry 4.0 adoption and carbon emissions. The findings reveal an inverted U-shaped relationship, with emissions initially increasing by 10% at lower levels of technology adoption before decreasing by 15% as the Industry 4.0 index reached higher levels. This study provides empirical evidence supporting the strategic deployment of Industry 4.0 technologies to achieve sustainable logistics growth. Key policy implications and future research directions are discussed.

Inequality of Opportunity and the Probability of Being Very Rich or Very Poor

This paper models the effects of individuals' background variables on the chances they end up in the extremes of the income distribution. Taking high‐quality Australian panel data, we show that factors like the education of one's father have a much stronger impact on belonging to the top 1 per cent than they have on the conditional mean. Similarly, individuals from immigrant families are more likely to belong to both the left and the right tails of income distribution. Identifying the drivers of extreme incomes is important as individuals with very high incomes exert disproportionate political power, while those with very low incomes may drive prejudice and perceptions of disadvantage.