How Does International Financial Integration Really Affect Post-Transition Countries' Growth? Empirical evidence from the CEE-10 countries

This paper seeks to empirically explore how an international financial integration influences a country’s GDP growth. The long run relationship is tested by PMG estimator for the sample of ten EU countries from Central, Eastern and Southeastern Europe (CEE-10 countries) between 1995 and 2017. Prior to the conducting of dynamic panel analysis based on PMG estimators, several panel unit root tests were conducted, as well as panel co integration tests. The findings offer mixed impact financial integration on growth. Among the measures of financial integration, growth of the CEE-10 countries is mostly driven in the long run by FDI inflows as well as remittances and financial openness. On the contrary, the study suggests a reversal relationship between growth and financial integration measured by Gross Foreign Assets and Liabilities in percentages of GDP. It might be explained with a fact that CEE-10 countries have not yet reached a certain level of financial development in order to benefit from financial integration. The study concludes that international financial integration does not per se enhance economic growth and country’s growth in the CEE-10 countries can be reached at a higher level of financial integration, further increase their financial openness and financial development.

Technological Innovation and Green Growth: Evidence from South Asia

Green growth means promote economic development and growth, while certify that natural assets continue to provide the resources and ecological. This research analyzes that how green growth is affected by technological innovation for South Asia (Bangladesh, Pakistan, India, Sri Lanka, and Nepal) economies during 1990 to 2019. Basic econometric tests such as Cross-section dependence test, Panel unit root tests and Wester Lund co-integration test is applied. Furthermore, we use the FMOLS and DOLS models for estimating the impact of CO2 emissions on patent by resident, renewable energy consumption, foreign direct investment, and GDP per capita. The results of all panel unit root tests reveal that all the variables are stationary at a 1st difference. Westerlund panel co-integration test confirmed the long-run relationship. In both the FMOLS and DOLS models, the findings show that patent application by residents and renewable energy consumption have negative and statistically significant impacts on CO2 emissions. While GDP has positive and statistically significant effect on CO2 emissions and FDI has no effect on CO2 emissions in both the long run and short run. The results recommend that government needs to take sustainable energy related source, for instance, renewable energy consumption which are beneficial to ecosystem as it increases green economy.

The efficiency of emerging markets: Evidence from nonlinear panel unit tests

In this study, we investigate market efficiency considering nonlinearities by testing the weak-form market efficiency of the stock markets of Brazil, China, Russia, Turkey, and South Africa using recently proposed nonlinear panel unit root tests. The stock markets of these emerging countries are deliberately selected for their market capitalization to form a homogenous panel. The results of nonlinear models indicate that the stock market indexes are stationary and weak-form inefficient. This finding contributes to the contradictory results of the prior research using linear and nonlinear models about the efficiency of emerging stock markets in favor of nonlinear ones. Furthermore, we propose that studies using financial variables consider such nonlinearity in order to achieve more accuracy in findings related to such studies.

Validity of Okun’s Law in a spatially dependent and cyclical asymmetric context

The current article analyzes the validity of Okun?s Law and sizable distortions that can occur in the estimation when spatial dependence and cyclical asymmetric impacts are not considered, which is a concern commonly ignored by the existing literature. Primarily spatial panel regressions (SDM, SAR, and SEM) and nonparametric regressions along with specification tests are adopted in terms of the methodology (such as panel unit root tests, panel cointegration, Moran?s I and Geary?s C tests of global spatial dependence, spatial LM, and Hausman tests). Additionally, spatial heterogeneity and cross-regional variation in Okun?s Law are investigated by adopting geographically weighted regression, LISA (local indicators for spatial association), and local Geary?s C analysis. A panel of 26 Turkish NUTS-2 regions from 2004 to 2018 was analyzed. The results clearly revealed that failing to incorporate spatial proximity and asymmetric cycle impacts leads to the biased estimation of Okun?s coefficient, such that during the downswing years of the national economy, Okun?s Law holds robustly: unemployment increases quickly in response to a decline in output. In contrast, during upswing years, the size of Okun?s coefficient is relatively much lower. Moreover, spatial dependence and heterogeneity are sizably evident. Okun?s coefficient is demonstrated to vary significantly across regions that have different industrial and labor market characteristics. As a policy implication, it has been understood that the reduction of unemployment is more difficult than initially understood, as economic growth itself does not provide a solution during upswing periods. The necessary special and region-specific policies are discussed throughout the text.

Causal Relationship Between the Spread of the COVID-19 and Geopolitical Risks in Emerging Economies

This study investigates the causality between the spread of the COVID-19 pandemic (measured by new cases per million and new deaths per million) and geopolitical risks (measured by the index of geopolitical risks). We use the balanced panel data framework in 18 emerging economies from January 2020 to August 2020. We run the initial tests of cross-sectional dependence and the panel unit root tests with capturing cross-sectional dependence. Then, we utilize the panel Granger non-causality tests for heterogeneous stationary panel datasets. According to the findings, there is a significant causality from both measures of spreading the COVID-19 pandemic to geopolitical risks. Further tests are performed, and potential implications are also discussed.

Considering nonlinearity and structural changes in the convergence of clean energy consumption: the case of OECD countries

PurposeIn this study, we aim to test the stochastic convergence of per capita clean energy use in 30 OECD (Organization for Economic Co-operation and Development) countries for the period of 1965–2017.Design/methodology/approachThis study employed both linear and nonlinear panel unit root tests, and unlike other studies, this study allowed fractional values in addition to integer values for frequencies in the Fourier functions. Integer values of frequency indicate temporary breaks, while fractional values show permanent breaks.FindingsThe results of the linear panel unit root test indicate that clean energy use does not converge to group average for almost all OECD countries. However, the results of nonlinear panel unit root tests provide evidence that the stochastic convergence hypothesis of clean energy consumption cannot be rejected for most countries. This study does not find any evidence for stochastic convergence of clean energy use in Australia, Canada, Denmark, Ireland, Norway or Sweden. Therefore, the policies regarding clean energy are mandatory in these countries due to their effectiveness. This study also reveals that there are permanent structural breaks in the convergence process of clean energy consumption in approximately half of OECD countries.Originality/valueThis study considers temporary and permanent smooth structural shifts in addition to nonlinearity when testing the stationarity of clean energy consumption in a country i relative to the group average. This new method eliminates deficiencies of the previous panel data techniques. Thus, it provides more reliable results compared to existing literature.

A Framework for Classifying Causal Factors of Tourism Demand Seasonality: An Interseason and Intraseason Approach

This study proposes a framework for classifying the causal effects of tourism demand seasonality, linking between season effects (interseason) with within season effects (intraseason). The literature has typically investigated the causes of tourism demand seasonality as isolated static factors, mostly ignoring the possibility of interseason and intraseason impacts. This study contributes to the literature by providing a system of categorizing the drivers of tourism demand seasonality, by introducing additional causal factors, and by using an alternative seasonal smoothing technique. The methodology includes data decomposition, panel unit root tests, and instrumental variable regression, distinguishing between peak and shoulder seasons. The findings, based on a case study, identify vigorous–irregular and moderate–irregular factors being the most prominent drivers of U.S. tourism demand seasonality, which could assist in specific policy recommendations for more sustainable management of tourism demand seasonality.

Validity of Purchasing Power Parity (PPP) Hypothesis in the Ecowas (1980–2017)

This study investigates the validity of a purchasing power parity (PPP) hypothesis in the ECOWAS. Secondary data on real exchange rates, domestic inflation rates, and foreign inflation rates were sourced from the World Development Indicators of the World Bank (2018). Unit root tests, Panel unit root tests, and panel cointegration tests were used to investigate the validity of the PPP hypothesis in the ECOWAS. The study found that the PPP hypothesis is valid individually in all the ECOWAS member countries. The results from the panel unit root tests also confirm the validity of the PPP hypothesis in the ECOWAS. Specifically, the LLC with individual intercept ( t = −5.97117, p < 0.0000), IPS with individual intercept ( t = −3.30564; p < 0.0000), Fisher ADF with individual intercept ( t = −3.43996; p < 0.0003), and Fisher PP with individual intercept ( t = −5.91557; p < 0.0000) while the panel cointegration test rejects the validity of the PPP hypothesis. Therefore, the study suggests that the ECOWAS can cautiously forge ahead with the implementation of their economic integration policies and programs in the sub-region.

An Empirical Inquiry into Per Capita Convergence of Indian States

The topic of growth convergence (or the lack of it) has always been one of the most important economic phenomena for Indian states. This study undertakes more than 3 decades of data for Indian states from the 1980s and traces convergence of state-level per capita income; breaking the data down into the subperiods based on time and levels of income using panel unit root tests. The results show no discernible evidence of convergence across the states, especially after post-liberalization. However, taking into account control variables for capital expenditure, development expenditure, and fiscal deficit, we find significant evidence for convergence of state-level per capita GDP. This indicates that the nature of inequality across states is not structural in nature and can be reduced through active policy interventions.