Heterogeneous Panel Research Articles

Predicting Multi-Scale Positive and Negative Stock Market Bubbles in a Panel of G7 Countries: The Role of Oil Price Uncertainty

While there is a large body of literature on oil uncertainty-equity prices and/or returns nexus, an associated important question of how oil market uncertainty affects stock market bubbles remains unanswered. In this paper, we first use the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to detect both positive and negative bubbles in the short-, medium- and long-term stock markets of the G7 countries. While detecting major crashes and booms in the seven stock markets over the monthly period of February 1973 to May 2020, we also observe similar timing of strong (positive and negative) LPPLS-CIs across the G7, suggesting synchronized boom-bust cycles. Given this, we next apply dynamic heterogeneous coefficients panel databased regressions to analyze the predictive impact of a model-free robust metric of oil price uncertainty on the bubbles indicators. After controlling for the impacts of output growth, inflation, and monetary policy, we find that oil price uncertainty predicts a decrease in all the time scales and countries of the positive bubbles and increases strongly in the medium term for five countries (and weakly the short-term) negative LPPLS-CIs. The aggregate findings continue to hold with the inclusion of investor sentiment indicators. Our results have important implications for both investors and policymakers, as the higher (lower) oil price uncertainty can lead to a crash (recovery) in a bullish (bearish) market.

Analysis of Heterogeneity of Carbon Trading Price Influencing Factors in China's Carbon Trading Pilots

This study analyzes the influencing factors and heterogeneity of carbon trading prices (CTPs) in China's seven major carbon trading pilot markets. With the intensification of climate change issues, carbon trading has received widespread attention as an important market mechanism. Through empirical analysis of monthly data from January 2014 to December 2023 in seven pilot markets: Shenzhen, Shanghai, Beijing, Tianjin, Guangdong, Hubei and Chongqing, a dynamic heterogeneous panel PMG model was used to explore the impact of factors such as energy prices, macroeconomic activity and environmental quality on CTPs. Based on these results, this paper puts forward targeted policy recommendations, including formulating differentiated carbon trading policies, strengthening environmental governance, and deepening research on the carbon trading market, in order to promote low-carbon transformation and the stable development of the market.

Unraveling the environmental Kuznets curve in IGAD countries: interplay between ecological footprint, economic growth, renewable energy, and globalization

Abstract Climate change has become a global phenomenon; hence, mitigating environmental pollution and degradation are crucial for addressing climate change consequences. A paradigm shift from fossil fuel to clean energy sources is suggested to reduce environmental pollution without compromising economic growth. This study assesses the validity of the environmental Kuznets curve (EKC) hypothesis by incorporating the impacts of renewable energy, population density, and globalization on ecological footprint in IGAD member nations. A battery of econometric techniques, such as Pedroni, Kao, and Johansen Fisher cointegration methods, heterogeneous panel methods, and Dumitrescu-Hurlin panel causality tests are utilized. Before the formal analysis, we performed a cross-sectional dependence test; and it was observed that the data are cross-sectional dependent. Hence, the second-generation unit root test is utilized which confirms that all the interested variables are stationary at the first difference I (1). The empirical results of cointegration methods indicate that explanatory variables are cointegrated into the ecological footprint in the long run. Moreover, the PMG – which provides consistent results as evidenced by the Hausman test – underscored that globalization, population density, and renewable energy mitigate ecological footprint in the long run even though renewable energy is insignificant. An increase in economic growth is associated with a deterioration of environmental pollution, while squared growth is linked to a reduction in pollution. This evidence supports the existence of the EKC theory, which posits an inverted U-shaped relationship between economic expansion and ecological footprint. Besides, unidirectional causalities are detected from ecological footprint to population density, renewable energy, economic growth, and squared economic growth but not the other way around. In light of the empirical results, several policy recommendations are proposed.

Institutions and Economic Growth: A Panel Granger Causality Analysis

This paper revisits the direction of causality between institutions and economic growth for a sample of 119 countries over the period 1999-2018, divided into four groups according to income level: high income, upper middle income, lower middle income and low income. The study uses two institutional datasets, the International Country Risk Guide (ICRG) for the main estimation and the World Governance Indicators (WGI) for check the robustness of the results. Using the non-causality Granger test in a heterogeneous panel model with fixed coefficients, developed by Dumitrescu and Hurlin (2012), the empirical results show a unidirectional relationship for all panels except for lower middle-income countries, where causality is bidirectional. The findings also suggest that causality patterns are heterogeneous and depend on the level of development of the countries. Based on these results, we propose some interesting recommendations. The types of reforms to prioritize must be determined according to the direction of causality between institutions and economic growth. Moreover, heterogeneous causality implies the implementation of different policies adapted to the level of development of each panel, rather than considering a common policy.

Impact of Innovation and Trade Participation on Economic Growth Among Selected African Countries

This study examines the impact of innovation and trade participation on economic growth among selected African countries from 1996 to 2021. This study applied nonstationary heterogeneous panel models utilizing pooled mean group estimators, mean group estimators and dynamic fixed effects estimators. Based on the results of the Hausman test, the PMG estimator was considered for the data analysis. The study revealed the significant role of industrial design, patents, trademarks, research and development, exports, and balanced trade policies in driving long-term economic growth in Africa. The synergies between innovation and trade participation are studied, emphasizing their amplified impact on economic growth. The study suggests practical policy recommendations for the selected African countries, urging governments to establish innovation ecosystems, encourage investments in design, strengthen intellectual property protection, prioritize infrastructure development, and develop balanced trade policies. Focusing on SMEs, offering incentives for research and development, and establishing trade promotion agencies are also recommended to create a conducive environment for innovation, trade, and sustained economic growth.

Handling Distinct Correlated Effects with CCE

AbstractThe common correlated effects (CCE) approach by Pesaran is a popular method for estimating panel data models with interactive effects. Due to its simplicity, i.e., unobserved common factors are approximated with cross‐section averages of the observables, the estimator is highly flexible and lends itself to a wide range of applications. Despite such flexibility, however, the properties of CCE estimators are typically only examined under the restrictive assumption that all the observed variables load on the same set of factors, which ensures joint identification of the factor space. In this article, we take a different perspective, and explore the empirically relevant case where the dependent and explanatory variables are driven by distinct but correlated factors. Hence, we consider the case of Distinct Correlated Effects. Such settings can be argued to be relevant for practice, for instance in studies linking economic growth to climatic variables. In so doing, we consider panel dimensions such that as , which is known to induce an asymptotic bias for the pooled CCE estimator even under the usual common factor assumption. We subsequently develop a robust bootstrap‐based toolbox that enables asymptotically valid inference in both homogeneous and heterogeneous panels, without requiring knowledge about whether factors are distinct or common.

Keynesian and post-Keynesian models on banks in Africa

In the present paper, we aim at filling the lacuna created by the lack of a multiplicity of empirical works on Keynesian and Post-Keynesian models on banks in Africa. Based on the case of banks and economic growth in 20 Sub-Sahara African countries for the 1990-2021periods, we employ the Granger causality tests in heterogeneous panels developed by Dumitrescu and Hurlin (2012), the Fixed Effect Ordinary Least Squares method, the Mean Group Method and the Generalized Method of Moments to conclude that, in the short and long run, economic growth precedes banks development as justified by Keynesian and Post-Keynesian bank models.

External Debt and Manufacturing Sector’s Performance in MINT Countries: Evidence from Dynamic Heterogeneous Panel Estimation Techniques

External Debt and Manufacturing Sector’s Performance in MINT Countries: Evidence from Dynamic Heterogeneous Panel Estimation Techniques

Selection of spillover channels in spatial dynamic panel models using heterogeneous shrinkage on spatial parameters

ABSTRACT This paper proposes a Bayesian approach to estimating heterogeneous spatial dynamic panel models, subject to possible shrinkage on spatial dependence parameters. This amounts to heterogeneous selection of candidate spatial weight matrices that represent different spillover channels. The shrinkage methods include both the traditional and more flexible ones that allow the shrinkage strength to vary across spatial parameters. Monte Carlo results indicate that when the true model has a relatively low proportion of nonzero spatial parameters, flexible shrinkage in general leads to lower average root mean squared errors in estimating these parameters. An empirical study using this approach shows that there exists substantial heterogeneity in spillover channels across counties that determine the correlation patterns of county COVID-19 vaccination rates in four states in the United States.

Dynamic linkages between element input structure, global value chain, and carbon emissions: evidence from a heterogeneous panel cointegration model

ABSTRACT Industrial CO2 constitutes a dominant component of global CO2 emissions. Therefore, modifications in industrial production processes are crucial. We analyse global cross-national panel datasets from 1995 to 2018 using the panel autoregressive distributed lag (ARDL) model to provide comprehensive evidence of the combined effects of input-side element structures and production-side global value chain (GVC) divisions on output-side CO2 emissions. The results show that: (i) Renewable energy and service elements in production factors can reduce CO2 emissions, though their abatement effects vary. Both can produce sustained carbon mitigation effects in the long term, but only renewable energy is effective in the short term. (ii) The GVC division pattern can induce a CO2 emission increase in both the short and long term, though these effects are heterogeneous depending on the differences in forward-backward GVC divisions. (iii) A path dependence analysis shows that input-side element structures can change production-side GVC divisions, thereby affecting output-side emissions. This study extends our understanding of the environmental effects of various production links and helps coordinate high-quality economic development and impending environmental constraints.

Driving Forces of the Consumer Price Index During the Crises in the Eurozone: Heterogeneous Panel Approach

This paper examines key driving forces of inflationary pressures, taking into account supply and demand side determinants and actions of policy makers, during the pandemic and geopolitical crises in the Eurozone. Using heterogeneous nonstationary macro-panel models, especially the Mean Group (MG) and Pooled Mean Group (PMG) methods in the period 2020q1–2024q4, it is concluded that the dominant determination of inflationary pressures comes from the supply side. There is a long-run positive equilibrium relationship between the growth of energy prices and the growth of the consumer price index (CPI), and between the index representing supply bottlenecks (SBI) and the growth of CPI, while the relationship with the unemployment rate is insignificant. Also, the existence of a long-run equilibrium between the interest rate and CPI is homogeneous due to the unique monetary policy on a sample, and negative, indicating the efficiency of that policy. However, the speed of adjustment of individual economies is heterogeneous, and in the case of Greece and Ireland, insignificant. The heterogeneous or insignificant response of Eurozone member states, especially related to core-periphery asymmetry, refers to the vulnerability and structural weakness of the Eurozone economies, and the need for deeper integration.

Unlocking the potential of natural resources, fintech and fiscal policy for carbon neutrality; evidence from N-11 nations

By controlling the quantity of greenhouse gases in the natural environment, carbon neutrality is designed to reduce the adverse impacts of climate change. The specific goal can be attained by enforcing carbon dioxide elimination approaches, fostering the growth of fintech, fiscal policy tools, and funding in human development, along with the lowering of emissions. The current research analyzes the influence of the human development index (HDI), natural resources (NR), fintech (FT), and fiscal policy (FP) on carbon neutrality within the parameters of a policy structure. This task is performed with the objective of fulfilling the goals stated above. The ongoing research applies the innovative " General Method of Moment Quantile-based Regression (GMMQR)" and “Panel Quantile ARDL" techniques on a sample of N-11 nations to accomplish the goal. The outcomes support the idea that NR and FP function as pivotal factors in diminishing carbon neutrality. On the other hand, FT and HDI improve carbon neutrality. Moreover, in accordance with the heterogeneous panel causality test developed by Dumitrescu and hurlin (2012), NR, FP, HDI, and FT have been determined to have a unidirectional link with carbon neutrality. In regard to these findings, the research outlines a strategy designed to attain SDG 13 for the chosen nations. Decision-makers in these nations need to focus on policies that encourage the efficient use of natural resources. In addition, the chosen nations need to enhance their level of fintech to combat environmental degradation and achieve the targets of carbon neutrality.

Analysis of the Relationship Between Military Expenditure and Investment in the Economic Community of West African States: A Heterogeneous Panel Data Approach

Abstract West Africa has been grappling with various security challenges prompting governments’ intervention via military expenditure both at the country and regional level. Given the sporadic surge in military expenditure in the region and the potential effect such expenditure may exert on investment which is a sin qua non to the development process of any economy or region, this study utilizes the augmented mean group (AMG) approach and the Granger non-causality test in investigating the impact and causal relationship between investment and military expenditure in the Economic Community of West African States (ECOWAS) between 1980 and 2020. With country-specific cross-dependence and heterogeneity adequately accounted for, the study found that military expenditure has a dampening impact on investment at both the panel and country levels; unemployment adversely impacts investment; whereas economic growth stimulates investment (catalytic effect) in the ECOWAS, although at differing levels of significance. The study also established a long-run relationship among the variables; with only economic growth Granger causing investment. The study thus recommends that country-specific and regional-based military policies be established to glean economic growth through viable investment.

Validity of Governance-Prosperity: Fresh Evidence Under Homogeneous and Heterogeneous Methods

The purpose of this study is to determine whether governance has an impact on per capita income. The governance-prosperity hypothesis was validated using data from 48 high-income countries. This study examines all governance indicators in sample countries rather than one that addresses specific effects. We find that good governance enhances prosperity, while FDI, exports, and urbanization positively impact effective governance outcomes using homogeneity and heterogeneity panel methodologies. In contrast, household expenditures exhibit a diverse relationship that requires a combination of saving policy and spending to increase per capita income. We found that effective governance attracts foreign direct investment, leading to high exports and urbanization trends. Therefore, countries should strengthen their governance apparatus to reap the benefits of sustainable economic growth.

How wealthy in natural resource leads environmental sustainability in developing economies? An empirical investigation

This study investigates the impact of income generated from natural resources on environmental sustainability and analyses the moderating role of institutional quality in carbon emissions function. An extensive dataset from 61 developing nations covering the years 2000–2018 has been taken, which uses a dynamic heterogeneous panel data model. Our study follows a rigorous methodology by applying the pooled mean group estimator. An extensive examination of the impacts over the short run and long run is possible using this method. This study reveals multifaceted findings: in the short run, the effect of institutional quality and natural resources revenues on carbon emissions is insignificant, implying that such factors have a relatively minor impact. The long-term examination reveals that income derived from natural resources causes a spike in carbon emissions, which causes environmental deterioration and climate change. Strong institutional quality can significantly mitigate the adverse effects of correlation between revenues from natural resources and carbon emissions, which have been observed. The study's moderating effect of natural resources richness, which gradually reduces institutional quality's ability to reduce carbon emissions, is a crucial finding. Our study significantly advances the field of environmental economics, especially when discussing sustainable development in emerging nations with abundant natural resources. It emphasizes the delicate balance that must be struck between preserving efficient environmental governance and maximizing the richness of natural resources. Our findings underscore the crucial need for developing nations to strengthen their institutional frameworks and capacities and have substantial policy implications. These steps are essential to ensuring that the use of natural resources is in line with environmental sustainability objectives, turning resource curses into blessings for long-term development and environmental preservation. This research opens the door to sector-specific impacts and personalized policy interventions in resource-rich developing economies.

Bringing economic freedom back to the study of global value chains: empirical evidences from heterogeneous panel data approach

Bringing economic freedom back to the study of global value chains: empirical evidences from heterogeneous panel data approach

Infant Mortality, Education and Financial Development: Evidence from World Level Data Using Heterogeneous Panel Granger Causality Analysis

Education and financial development are crucial factors in achieving better health, including the reduction of infant mortality. This article investigates the causal relationship between education, financial development and infant mortality rate using annual data for 81 countries for the period 1980–2015 and employing the Emirmahmutoglu and Rose (2011) Granger causality test procedure for heterogeneous mixed panels. The results show that, individually and jointly, education and financial development Granger cause infant mortality in some countries across the major regions of the world. This suggests that improved education and a developed financial system are likely to reduce the infant mortality rate. JEL Codes: C33; E25; I

On the impact of provincial digital economy on high-quality economic development in China from a regional heterogeneity perspective

Based on the data of 30 provinces in China from 2013 to 2021, this paper constructs indicators of the level of development of the digital economy, and explores the impact of the digital economy on the high-quality development of the economy based on the perspective of regional heterogeneity, using static and dynamic panel models. It is concluded that (1) the digital economy promotes high-quality development of the economy, and the eastern part of the country is particularly significant; and (2) the digital economy can promote high-quality development of the economy by promoting the innovation capacity of provinces and cities and reducing their carbon emissions. Finally, we put forward the recommendations of “vigorously developing the digital economy; improving the infrastructure construction and talent training in each region; establishing a regional coordination and linkage mechanism; and improving the development strategy of the digital economy”, so as to promote the high-quality development of the economy.

Renewable energy, regional tourism, and exports to tackle stagnant growth in developed economies

This study examines the effects of energy resources in the form of clean and unclean energy on the economic progress of 30 selected developed economies. This study used data from 1990 to 2020 and it employs the CS-ARDL method to obtain results. The results present that both clean and unclean energy significantly stimulate economic progress. The findings further expose that foreign investment resources in the form of inflow are significant factors that accelerate economic progress in developed economies. The results reveal that tourism development, capital accumulation, and exports are significant factors in boosting economic progress in the selected economies. Estimates from Dumitrescu and Hurlin's method for heterogeneous panels confirm the presence of the feedback-effect hypothesis for unclean energy, while the energy-conservation hypothesis holds for clean energy. This study suggests that targeting low-cost clean energy production is crucial for promoting economic growth and protecting the environment through carbon mitigation strategies. There is also a need to develop a policy framework that emphasizes the transformation of industry towards clean energy at a macro level. Furthermore, transitioning from unclean to clean energy may enhance economic progress by improving environmental quality norms in the selected developed economies. Finally, policies for tourism development, export improvement, and increased inflow of FDI should be directed towards fostering clean energy agreements and achieving environment-friendly economic progress in developed economies.

Fiscal multipliers in recession and expansion. An analysis for the Italian regions

This paper estimates the multipliers of two types of government spending in the 20 Italian administrative regions throughout 1960–2017, distinguishing between phases of expansion and recession. We derive regime- and region-specific multipliers through a nonlinear Bayesian heterogeneous panel threshold VAR model and provide a wide-ranging sensitivity analysis. We find that both government consumption and government investment multipliers are higher in recession than in expansion. In almost every region, government investment multipliers exceed unity in recession phases and are generally higher than their government consumption counterparts regardless of the business cycle. An exploratory analysis of the region-specific multipliers suggests that the difference between the region-specific multipliers in recession and expansion is positively associated with structural labour slack and negatively associated with trade openness. Factors related to the quality of local institutions, such as corruption and the relative size of the informal economy, also have a negative impact.