Panel Data Estimation Methods Research Articles

The impact of institutions on economic growth in selected developing countries: An analysis based on Bayesian panel estimation

This paper presents an empirical analysis of the impact of institutions on the economic growth of 27 developing countries during the period 1990-2014. Many creative models of panel data allow variations in slope coefficients both across time and cross-sectional units. All models were established in a Bayesian structure and their performance was tested by using an interesting application of the effect of institution on GDP. Technical details of all these models are given and tools are presented to compare their performance in the Bayesian system. Besides, panel data models and posterior model pools are provided for an insight into the institution's relationship with economic development. The derivation of Bayesian panel data models is included. The previous data has been used in this study and normal gamma prior is used for the models of panel data. 2SLS estimation technique has been used to analyze the classical estimation of panel data models. In the paper, developing countries were viewed as a whole. The study's evaluated results have shown that panel data models are valid Bayesian methodology models. In the Bayesian approach, the results of all independent variables affect the dependent variable significantly and positively. Based on all model standard defects, it is necessary to say that the Fixed Effect Model is the best in Bayesian panel data estimation methods. It was also shown that in comparison to other models, the fixed-effect model has the lowest standard error value.

Macroeconomic Policies and Social Inclusion in the Developing World

Many in the developing world face social exclusion and discrimination, preventing them from actively participating in society itself. Sound macroeconomic policies with a focus on stabilizing the price level and social outcomes can help to achieve social justice for marginalized people. This study empirically examines the impact of macroeconomic policies on social inclusion, considering specifically the coordination among them in promoting that social inclusion. It deals primarily with pure non-income dimensions of social inclusion such as education, and health, etc. Using annual panel data of 51 developing countries for the period 1995-2017 this study employs state-of-the-art panel data estimation methods – pooled estimation, fixed-effect, and random-effect models. To check for robustness and to handle the problem of endogeneity, the 2SLS technique has also been used. This study argues that a well-designed macroeconomic policy framework can do much more than just achieve economic goals. Results suggest that fiscal and monetary policy, through resource mobilization, can play a significant and positive role in promoting social inclusion. However, these fiscal and monetary policy actions are not independent; thus, a policy mix is required to achieve the target of an inclusive society.

Remittances, Official Development Assistance, and Human Development in Africa: An Empirical Analysis

ABSTRACTRemittances are important sources of household income and foreign exchange in many developing countries. Official development assistance (ODA) also constitutes another major source of external finance for receiving countries, although it is on a relative decline. While the contributions of ODA and remittances to economic growth in developing countries have been a subject of numerous empirical studies, there is a paucity of comparable analysis on their implications for human development, especially in the context of Africa. This study assesses the relative contributions of ODA and remittances to human development outcomes in 35 African countries over three decades using panel-data estimation methods. The approach of the study includes exploring the factors that may condition the relationship between the two financial flows,on the one hand, and human development, on the other. The results of the study suggest that both ODA and remittances exerted modest favorable effects on human development in the typical country of study. The relationship between the two flows and human development index (HDI) remains positive when their coefficients are allowed to shift across different groups of the sample. However, differences are observed in their magnitude and statistical significance, suggesting the presence of factors that condition the said relationships. Accordingly, the HDI effect of ODA seems to be affected by the level of real GDP per capita, the quality of institutions, and the size and degree of instability of ODA flows. Official development assistance flows are found to exert at least as much marginal effect as remittances; and low but stable flows of ODA seem to have larger positive effect on human development than high but fluctuating ODA flows. The results of the study also suggest that recipients would benefit more from the inflows of remittances and ODA, among others, by improving the quality of their institutions.

Green innovations and patenting renewable energy technologies

We examine the impact of regulation and policies on green patent generation and evolution of renewable energy technologies in the OECD countries. Public and private investment, investment in education, research and development, and environmental regulation are considered. There is considerable variation in innovation systems and investments in renewable energy, and in outcomes. We assess the impact of environmental stringency and environmental taxes and regulations on renewable energy patents. The considerable heterogeneity requires emphasis on country effects and a separation of general from specific green innovation outcomes. We account for country-specific innovation factors. A balanced panel of 27 OECD countries is examined between 1990 and 2018. A renewable patent model is estimated by different panel data models and estimation methods. We find considerable sensitivity to model assumptions and inference techniques. The study is suggestive, however, of some renewable energy approaches for achievement of OECD environmental goals.

Determination of factors affecting the profitability variables by panel data analysis in the islamic banks: the case of Turkey

Islamic banks, which operate on the profit and loss sharing basis, have an important role in the financial system in terms of the collected funds bringing into the real economy. Therefore, for a strong economic structure, the market share of Islamic banks in the financial system needs to increase. The profitability level of banks is one of the most important financial performance indicators. Determining the factors that affect profitability indicates which issues are vital. The aim of this paper is to determine the factors that affect the profitability of participation banks operating in Turkey. In this context, panel data estimation methods were applied by using the data obtained from the financial statements (2006-2019) of three participation banks (Kuveyt Türk, Albaraka ve Türkiye Finans) and various macroeconomic indicators of the country. The most appropriate model was tried to be determined. In this study, the effect of capital adequacy ratio, bank size, credit risk, operational risk, operating effectiveness, inflation and GNP growth rate on return on assets (ROA) and return on equity (ROE) was analyzed. According to the results of the analysis, bank size, credit risk, operating effectiveness and inflation rates has an effect on ROA. Also, the effect of credit risk, operational risk, operating effectiveness and inflation rates on ROE is determined. Independent variables that do not have an impact on the profitability of banks are determined as capital adequacy ratio and growth. Also, according to the results of the analysis, it is possible to express that banks’ specific variables are more effective on the profitability of participation banks than macroeconomic indicators.

Does democracy help reduce environmental degradation?

The main purpose of this study is to examine the democracy-environmental degradation nexus in 26 Organization for Economic Cooperation and Development (OECD) countries from 1990 through 2015 by using panel data estimation methods, performing well under cross-sectional dependence. Empirical results are as follows: (i) Tests show that cross-section dependence exists among panel members, and slope coefficients are heterogeneous, respectively, and (ii) long-term coefficient estimation results with Augmented Mean Group estimator show that democracy, non-renewable energy consumption, and real income per capita have statistically significant negative effects on environmental quality, whereas renewable energy consumption has a positive effect. There is also no statistically significant relationship between urbanization and environmental quality. These findings show the poor functioning of democracy in addressing environmental issues among OECD countries; therefore, raising environmental quality conflicts with the Sustainable Development Goals (SDGs) of creating strong institutions and economic growth targets. Moreover, promoting renewable energy consumption may be an effective alternative in reducing environmental degradation; therefore, it can be said that promoting clean energy use and raising the SDG environmental quality targets are in harmony.

Revisiting the location of FDI in China: A panel data approach with heterogeneous shocks

Foreign Direct Investment (FDI) is viewed as a primary driving force in shaping the global economy and receives particular attention in empirical studies. In this paper, we argue that many of the existing studies ignore endogeneities that arise from shocks in source and destination countries. To address this endogeneity issue, we take the “controlling through estimating” idea from the econometric literature and propose using panel data models with heterogeneous shocks to deal with it. We consider the quasi maximum likelihood (QML) method to estimate our proposed model. We investigate the asymptotic properties of the QML estimator, including the consistency, the asymptotic representation, and the limiting distribution. We also propose new statistics to test the validity of the use of traditional dynamic and static panel data estimation methods. Applying it to the location determinants of inward FDI in China, we find that the endogeneity issue does exist, and that controlling for heterogeneous shocks helps to improve the estimation results.

Circular Economy Innovation and Environmental Sustainability Impact on Economic Growth: An Integrated Model for Sustainable Development

This study examines the link between selected indicators of a circular economy, including essential components of environmental and economic growth. Developed economies are continuously innovating to promote growth and giving governmental support to the producers to move from linear economies to circular ones. Hence, waste materials in industrial systems are recycled or re-used, improving the efficiency of using finite resources with the no-waste approach. The aim of this paper is the following: (1) to identify the main components of a circular economy, which are also supportive of sustainability and development; (2) to check the impact of these variables in the economic growth of European Union countries; (3) to find out if the three components of sustainable development adopted to circular economy (CE) indicators (environmental–social–economic) are significant to economic growth. We used a fixed effect panel data analysis to identify the circular economy’s impact on the economic growth of European countries. Additionally, to support the results of the regression analysis, we employed a second method—generalized methods of moments—computing the Arellano–Bond dynamic panel data estimation method. The model included five independent variables, such as environmental tax rate, a recycling rate of waste, private investment and jobs in a circular economy, patents related to recycling, and trade of recyclable raw materials. The identification of each variable was made based on a deep search through literature. The results of both econometric models showed a strong and positive correlation between a circular economy to economic growth, highlighting the crucial role of sustainability, innovation, and investment in no-waste initiatives to promote wealth.

Environmental Phillips curve: OECD and Asian NICs perspective.

This research aims to explore the existence of a new concept known as "environmental Phillips curve" (EPC) developed by the authors. Taking annual data of 30 countries for 26years, a panel data estimation method is applied. The invented function shows an inverse relationship between pollution and unemployment. In most of the cases, the industrialized countries show that the relationship is valid. The notion is proved effective in every format of investigation. It seems that curbing pollution in the world is only possible at the cost of human employment. Therefore, if countries want to curb environmental pollution without affecting the generation of employment and reducing poverty, they should contemplate both innovation and enforcement alternative technologies that would be less polluting but employment friendly. Moreover, this research also suggests that if a country can treat pollution efficiently, it can increase the national income without a deteriorating unemployment level.

Relationship between economic growth and CO2 emissions: does governance matter?

The environmental stress due to massive CO2 emissions is a critical issue for scholars and policymakers. Many studies have discussed various determinants of environmental pollution both from theoretical and empirical perspectives. However, how governance influences the nexus between economic growth and CO2 emissions israrely studied. Hence this study investigates the relationship between economic growth, governance and CO2 emissions within the framework of the Environmental Kuznets Curve for five high CO2 emission countries over 1996-2017. Empirical results from the panel data estimation methods reflect that measures of governance influence emission levels differently in high CO2 emission countries. Overall, political, economic and institutional governance enhance environmental quality. According to the results, provision of good governance needs to exercise effective measures to enhance and protect environmental quality.

Added-variable plots for panel-data estimation

In this article, I extend the theory of added-variable plots to three panel-data estimation methods: fixed effects, between effects, and random effects. An added-variable plot is an effective way to show the correlation between an independent variable and a dependent variable conditional on other independent variables. In a multivariate context, a simple scatterplot showing x versus y is not adequate to show the relationship of x with y, because it ignores the impact of the other covariates. Added-variable plots are also useful for spotting influential outliers in the data that affect the estimated regression parameters. Stata can display added-variable plots with the command avplot, but it can be used only after regress. My new command, xtavplot, is a postestimation command that creates added-variable plots after xtreg estimates. Unlike avplot, xtavplot can display a confidence interval around the fitted regression line.

Does information and communication technology affect CO2 mitigation under the pathway of sustainable development during the mode of globalization?

AbstractThe rapid developments of globalization promote interaction among countries and people around the globe through the fast mode of information and telecommunication technology (ICT). ICT development also contributes to economic growth through various channels, but it may influence the environment on the other hand. Considering this concern, the present study focuses on examining the relationship between ICT developments and carbon emissions through the globalization channel. The study employs robust panel data estimation methods, continuously updated fully modified, and continuously updated bias corrected estimators, for the data set of Brazil, Russia, India, China, and South Africa (BRICS) economies spanning from 1990 to 2015. Findings of the study are robust against heteroskedasticity, endogeneity, and cross‐sectional dependence issues. The robust panel data estimators reveal that ICT has a favourable effect on carbon emissions in BRICS countries. Also, globalization leads to environmental pollution by contributing to an increase in CO2 emissions. These findings provide new insights to the policymakers in combatting environmental challenges.

Information and Communication Technology (ICT) and Income Inequality in ASEAN-5 Countries

Digital transformation spreads across borders, globalization develops or transforms the economics growth of a nation. Information and communication technology (ICT) fosters the economy; however, it might trigger the income inequality of a country. On this note, income inequality in ASEAN country is relatively higher than other countries. The aim of this study is to examine the relationship between ICT and income inequality in ASEAN-5 countries over the study period of 2009 to 2017. Employing panel data estimation method, the results show volume of internet users is found to have the strongest effect on income inequality among the ICT indicators. The findings suggest countries to focus on the innovation of ICT especially on the internet users, mobile cellular subscription and fixed telephone subscription to achieve economic growth and hence reduce income inequality. Investments in ICT infrastructure promote ICT technology cooperation as well as the expansion of ICT especially on the network access to confront with the income inequality.

Impact of macroeconomic variables on Islamic and conventional stock market returns: a panel data approach

This study examines the impact of macroeconomic factors on returns in both conventional and Islamic stock market indices. It uses a multifactor model of five macroeconomic factors: the inflation rate, the money supply, industrial production, exchange rates and short-term interest rates. We employed panel data estimation methods of pooled ordinary least squares, fixed-effects estimations and the random-effects approach, in addition to panel co-integration and causality tests. Monthly data for ten countries were utilised for the sample period January 2009 to December 2016. The results show that real effective exchange rates and the money supply influence returns in conventional stock markets, while exchange rates alone influence returns on Islamic stock markets. The results of the co-integration and causality tests confirm the existence of short- and long-run relationships between the above-mentioned macroeconomic variables and returns to both conventional and Islamic stock markets. These results have important implications for investors and policy-makers as they add new insight on the different impacts of macroeconomic variables on returns in both conventional and Islamic stock markets.

Urbanisasi, Konsumsi Energi, dan Emisi CO2 : Adakah Perbedaan Korelasinya di Kawasan Barat Indonesia (KBI) dan Kawasan Timur Indonesia (KTI)?

Indonesia’s rapid urbanization has become one of the indicators of development that also continues to increase. It is undeniable, improving stage of development is often have an impact on environmental degradation such as excessive fossil energy consumption and CO2 emissions. However, not all regions in Indonesia are at the same stage of development. There are high economic and socio-demographic inequalities and differences between western Indonesia (KBI) and eastern Indonesia (KTI). This study aims to provide empirical evidence and analyze impact of urbanization on energy consumption and CO2 emissions in the country that has different stage of developments across the region. Taking regional heterogeneity in Indonesia, panel data estimation method was applied at the provincial level during the 2011-2015 period. The results of the study show that urbanization in KBI and KTI has different effects on per capita fossil energy consumption. Urbanization in KBI has a positive relationship to per capita energy consumption, whereas urbanization in the KTI has a negative correlation. Urbanization in KBI has a negative correlation with CO2 emissions. However, there was no difference effect of urbanization on CO2 emissions in both of region because the estimation results in KTI showed values that were not statistically significant. These findings not only help advance the existing literature, but also add insight to policy makers in the urban and regional planning.

Development level and the impact of technological factor on renewable energy production

This study provides a comprehensive analysis of the drivers of renewable energy production by employing variables of technological factors, economic factors, and environmental factors for two panels of developed and developing countries. Using GLS (Generalized Least Square) panel data estimation method, this paper finds that the determinants towards renewable sources vary in accordance with the level of income. The results reveal that renewable energy production is significantly determined by high technology export in developed countries, while high technology export is not statistically significant in explaining the use of RE sources in developing countries. Oil price has the smallest impact on renewable energy production in both groups. Although GDP per capita yields a positive impact on renewable energy production per capita in both groups, per capita CO2 emission shows considerably different impacts in developed and developing countries.

İklim Değişikliği ve Turizm Sektörü Arasındaki İlişkinin Dinamik Panel Veri Analizi ile İncelenmesi

Climate change is one of the serious global problems having a variety of impacts, including sea level rise, severe wind, rising temperatures, changing rainfall patterns and environmental changes. Therefore, climate change has become one of the obstacles in the tourism sector due to its environmental sensitivity and its climate-dependent characteristics. The aim of the study is to examine the possible impacts of the climate change on tourism sector within the green economy approach. The study examined the relations of variables using the dynamic panel data estimation methods with the Arellano and Bover/Blundell and Bond System Generalized Method of Moments (GMM). The research covers 21 countries with the highest number of tourist arrivals in 2017 on different continents. As a result of the analysis, the share of tourism in GDP was positively correlated with the number of tourists, Human Development Index, forest areas and renewable energy use. However, it has a negative and statistically significant relationship with CO2 emission and temperature level. The results indicate that within the green economy approach of tourism sector will contribute to economic growth and sustainable development in included countries. To increase the economic impact of the tourism strengthening the tourism sector and implementing environmental policies is presented as a research proposal.

Towards cross‐regional sustainable development: The nexus between information and communication technology, energy consumption, and CO2 emissions

AbstractThe environmental impact of information and communication technology (ICT) has drawn increasing attention for two decades. The behaviour of ICT is positive towards economic growth; however, its environmental implications cannot be ignored. This empirical research explores the roles of ICT, economic growth, and energy consumption in environmental pollution across different regions from 1990 to 2015. Robust long‐run panel data estimation methods fully modified ordinary least square and dynamic ordinary least square and Driscoll–Kraay regression are applied. To summarise the results, ICT reduces the level of CO2 emissions across high‐ and middle‐income countries; however, contrary to this, ICT increases CO2 emissions in low‐income countries. Also, energy consumption is responsible for the increase in CO2 emissions in all income groups as expected. Finally, the environmental Kuznets curve is proved in all income groups. It is inferred that high‐ and middle‐income regions of the world have achieved a level of environmental sustainability in the significance of ICT, but this is not the case in low‐income countries.

Analyzing the role of governance in CO2 emissions mitigation: The BRICS experience

The linkage between economic growth and carbon dioxide (CO2) emissions has been quantified from both a theoretical perspective and an empirical perspective. However, these studies did not address the role of governance in environmental quality explicitly. Therefore, the current study examines the behavior of governance in CO2 emissions within the framework of the Environmental Kuznets Curve hypothesis for panel data from 1996 to 2017 for BRICS countries. The study employs Westerlund panel cointegration for investigation of cointegration among study’s variables. The long-run panel data estimation methods those eliminate dependencies across countries, heteroscedasticity, and spatial and serial dependency issues are used. To summarize the finding, governance has negative and statistically significant effects on CO2 emissions, help to form the Environmental Kuznets Curve hypothesis and reduces CO2 emissions in the BRICS countries. The newly developed results recommend the importance of governance in the clean environment and suggestions are directed accordingly

Analisis Pengaruh Kinerja Perusahaan, Kebijakan Hutang, Ukuran Perusahaan, Dan Nilai Perusahaan Terhadap Tingkat Pengembalian Investasi Pada Perusahaan Property Dan Real Estate Yang Terdaftar Di Bei Periode 2014-2016

The purpose of this research is to examine empirically the influence of company performance, debt policy, firm size and firm value toward retun on investment. In this research, researcher used four independent variables and one dependent variabel. Company performance is proxied by Return On Equity (ROE), Debt policy is proxied by Debt to Equity Ratio (DER), firm size is proxied by Natural Logarithm of Total Asset (SIZE), firm value is proxied by Price Book Value (PBV), and return on investment is proxied by Stock Return (RETURN). The sample of the research consist of 36 property and real estate companies listed in Indonesia Stock Exchange in the period 2014-2016. This research used quantitative analysis with panel data estimation methods with time series and cross section data used 5% significance level. The result shows that company performance have a positive effect and insignificant toward stock return, debt policy have a negative effect and significant toward stock return, firm size has a negative effect and insignificant toward stock return and firm value have a positive effect and significant toward the stock return.