Showing papers on "Panel data published in 2020"
TL;DR: In this paper, the authors analyzed micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of ''superstar firms''.
Abstract: The fall of labor's share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments of trends in labor's share typically have relied on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of \superstar firms." If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labor in firm valueadded and sales. As the importance of superstar firms increases, the aggregate labor share will tend tofall. Our hypothesis offers several testable predictions: industry sales will increasingly concentrate in a small number of firms; industries where concentration rises most will have the largest declines in the labor share; the fall in the labor share will be driven largely by between-firm reallocation rather than (primarily) a fall in the unweighted mean labor share within firms; the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; and finally, such patterns will be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.
676 citations
TL;DR: In this article, the authors explored the relationship between renewable and non-renewable energy consumption and economic growth for a panel of five South Asian countries over the period of 1990-2014.
314 citations
TL;DR: In this article, the authors examined the effect of financial development on renewable energy consumption using a panel data of 28 countries in the European Union (EU) over the period 1990-2015.
270 citations
TL;DR: Wang et al. as discussed by the authors investigated the effect of environmental regulation on technological innovations based on the provincial panel data of industrial sectors in China during the years 2005-2015, and found that industries with a higher degree of market competition and higher human capital investment tend to have stronger technological innovation capabilities.
247 citations
TL;DR: The authors provided some preliminary estimates about the behavior of oil-stock nexus during the COVID-19 pandemic and found that stock markets may experience greater initial and prolonged impacts of own and cross shocks during the pandemic than the period before it.
210 citations
TL;DR: In this article, the authors investigated the impact of financial inclusion on reducing poverty and income inequality, and the determinants and conditional effects thereof in 116 developing countries using an unbalanced annual panel data for the period of 2004-2016.
Abstract: Financial inclusion is a key element of social inclusion, particularly useful in combating poverty and income inequality by opening blocked advancement opportunities for disadvantaged segments of the population. This study intends to investigate the impact of financial inclusion on reducing poverty and income inequality, and the determinants and conditional effects thereof in 116 developing countries. The analysis is carried out using an unbalanced annual panel data for the period of 2004–2016. For this purpose, we construct a novel index of financial inclusion using a broad set of financial sector outreach indicators, finding that per capita income, ratio of internet users, age dependency ratio, inflation, and income inequality significantly influence the level of financial inclusion in developing countries. Furthermore, the results provide robust evidence that financial inclusion significantly reduces poverty rates and income inequality in developing countries. The findings are in favor of further promoting access to and usage of formal financial services by marginalized segments of the population in order to maximize society’s overall welfare.
183 citations
TL;DR: The results showed an inverted U-shaped EKC behavior in ASEAN countries, hence a negative relation between tourism and natural resources with the ecological footprint, which implies that tourism andnatural resources help to improve the environmental quality in AseAN countries.
Abstract: This study examines the impacts of economic growth, energy consumption, tourism, and natural resources on the ecological footprint in the ASEAN countries for spanning from 1995 to 2016. For this purpose, the cross-sectional dependent test, the second-generation unit root test, and the Westerlund cointegration test have been applied. The Driscoll-Kraay panel regression model has been used to check the long-run relationship among the series. Also, the Dumitrescu-Hurlin panel causality test is used to determine the paths of causal interactions. These tests help to overcome the problem of cross-sectional dependence in panel data analysis. The results showed an inverted U-shaped EKC behavior in ASEAN countries, hence a negative relation between tourism and natural resources with the ecological footprint. This implies that tourism and natural resources help to improve the environmental quality in ASEAN countries.
155 citations
TL;DR: Li et al. as discussed by the authors utilized the provincial panel data of 30 provinces in China from 2005 to 2016 to investigate the relationship between misallocation, corruption and GTFEE by employing appropriate spatial econometric methods and panel threshold model.
153 citations
TL;DR: In this paper, the authors investigate whether there are relationships among corporate disclosure of environmental, social and governance (ESG) and firms' operational (ROA), financial (ROE) and market performance (Tobin's Q), and if these relationships are positives or negatives or even neutral.
Abstract: This paper aims to investigate whether there are relationships among corporate disclosure of environmental, social and governance (ESG) and firms’ operational (ROA), financial (ROE) and market performance (Tobin’s Q), and if these relationships are positives or negatives or even neutral.,The study sample covers US S&P 500-listed companies during the period 2009 to 2018. Panel regression analysis was used to examine the study hypotheses and achieve the study aims.,The results showed that ESG disclosure positively affects a firms’ performance measures. However, measuring ESG sub-components separately showed that environmental (EVN) and corporate social responsibility (CSR) disclosure is negatively associated with ROA and ROE. EVN and CSR disclosure is positively related to Tobin’s Q. Further, corporate governance (CG) disclosure is positively related to ROA and Tobin’s Q, and negatively related to ROE. More importantly, ESG, CSR, EVN and CG tend to be higher with firms that have high assets and high financial leverage. Furthermore, the higher level of ESG, EVN, CSR and CG disclosure, the higher the ROA and ROE.,The study limns a vision of the role of ESG on firm performance. This study tries to determine whether there are relationships among all ESG disclosure and FP, and if they are positive, negative or even neutral.
148 citations
TL;DR: The results indicate that the relationship between globalization and CO2 emissions are inverted U-sharped, which strongly support the Environmental Kuznets Curve hypothesis.
145 citations
TL;DR: In this article, the authors synthesize, compare, and extend methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework, which is the first paper in a series of two that synthesizes, compares, and extends methods.
Abstract: This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Start...
TL;DR: A critical discussion of 12 limitations of fixed-effects models for panel data, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions are provided.
Abstract: Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical di...
TL;DR: In this article, the authors employed 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.
Abstract: The 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.
TL;DR: In this paper, the impacts of different environmental regulatory instruments and relative stringency on total factor energy efficiency were investigated using China's provincial panel data during 2000-2017, and the results indicated a relatively low energy efficiency of industrial sector and significant difference between provinces in China.
TL;DR: In this paper, a large panel data set comprising 812 listed European firms was used to investigate whether sustainability disclosure and female representation on boards affect firm value, and they observed that the firms with higher female representation had significantly superior environmental, social, and governance performance.
Abstract: Using a large panel data set comprising 812 listed European firms, this study investigates whether sustainability disclosure environmental, social, and governance) and female representation on boards affect firm value. We observe a positive impact of sustainability disclosure and board gender diversity on firm value, suggesting that the best management practices, enhanced takeholder trust, and female representation on boards improve firm value. We observe that the firms in sensitive industries achieve superior social and governance performance. We also observe that the firms with higher female representation on their boards present significantly superior environmental, social, and governance performance. Our results are robust to different firm and country specific control variables and to year- and country-fixed effects.
TL;DR: It is found that east coast cities have stronger effects, with the largest for NYC in the pandemic’s early stages, and substantial spatial and temporal heterogeneity is found.
TL;DR: This work focuses on 2 concerns, that is: (a) the concern about random effects versus fixed effects, which is central in the (micro)econometrics/sociology literature; and (b) the concerns about grand mean versus group (or person) mean centering, which are central inThe multilevel literature associated with disciplines like psychology and educational sciences.
Abstract: In many disciplines researchers use longitudinal panel data to investigate the potentially causal relationship between 2 variables. However, the conventions and concerns vary widely across disciplines. Here we focus on 2 concerns, that is: (a) the concern about random effects versus fixed effects, which is central in the (micro)econometrics/sociology literature; and (b) the concern about grand mean versus group (or person) mean centering, which is central in the multilevel literature associated with disciplines like psychology and educational sciences. We show that these 2 concerns are actually addressing the same underlying issue. We discuss diverse modeling methods based on either multilevel regression modeling with the data in long format, or structural equation modeling with the data in wide format, and compare these approaches with simulated data. We extend the multilevel model with random slopes and discuss the consequences of this. Subsequently, we provide guidelines on how to choose between the diverse modeling options. We illustrate the use of these guidelines with an empirical example based on intensive longitudinal data, in which we consider both a time-varying and a time-invariant covariate. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
TL;DR: In this article, the authors empirically analyze the compatibility of national trade liberalization policies with regards to promoting widespread use of renewable energy resources across 71 low, lower-middle and upper-middle income countries from South Asia, East Asia, Pacific, Central Asia, Latin America, Caribbean islands and Sub-Saharan Africa.
TL;DR: In this article, the authors explore firm-level moderators that may contribute to disentangling the relationship between corporate social responsibility and firm value, and they find that the relationship is moderated by firm size and age so that it is negatively impacted when small or young companies are considered.
Abstract: Although the current empirical literature has focused predominantly on the direct relationship between corporate social responsibility (CSR) and firm value, in this paper, we aim to explore firm‐level moderators that may contribute to disentangling this relationship. On the basis of a dataset of Western European listed companies, we use a moderation analysis of panel data to examine whether firm size and age drive the impact of CSR on firm value. Our estimations show that the relationship between CSR and firm value is moderated by firm size and age so that it is negatively impacted when small and/or young companies are considered. This finding seems to be consistent with the view that CSR initiatives could be ineffective in smaller and younger companies due to their lack of financial resources, experience, reputation, and so forth. Implications for firms are also discussed.
TL;DR: In this paper, the authors present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales.
TL;DR: In this article, the authors explored the important contributors of energy efficiency in OECD countries, by taking the energy intensity and carbon intensity as a proxy for energy efficiency and investigated the role of institutional factors for energy intensity.
TL;DR: In this article, the authors analyzed panel data derived from 27 European countries for the period 2010 to 2018 and found that citizens' use of e-government services is influenced by supply-side egovernment evaluations, citizens' trust in governments and the digital divide associated to income and education.
TL;DR: The authors show that monetary interventions have large and significant effects using historical panel data since 1870 and that the causal effect of these interventions depends on whether the economy is above or below potential, inflation is low, and there is a credit boom in mortgage markets.
TL;DR: In this article, the authors address the question of whether disinforming news spread online possesses the power to change the prevailing political circumstances during an election campaign, and they highlight fact fact
Abstract: In this paper, we address the question of whether disinforming news spread online possesses the power to change the prevailing political circumstances during an election campaign. We highlight fact...
TL;DR: Zhang et al. as mentioned in this paper investigated the influence of land transfer marketization on green total factor productivity (green TFP) and its mechanisms and empirically estimated the impact of LTM, the rationalization and optimization of industrial structure and their interactions on green TFP further.
TL;DR: This paper provides a general framework that extends GGM modeling with latent variables, including relationships over time, from time-series data or panel data featuring at least three waves of measurement, and takes the form of a graphical vector-autoregression model between latent variables.
Abstract: Researchers in the field of network psychometrics often focus on the estimation of Gaussian graphical models (GGMs)—an undirected network model of partial correlations—between observed variables of cross-sectional data or single-subject time-series data. This assumes that all variables are measured without measurement error, which may be implausible. In addition, cross-sectional data cannot distinguish between within-subject and between-subject effects. This paper provides a general framework that extends GGM modeling with latent variables, including relationships over time. These relationships can be estimated from time-series data or panel data featuring at least three waves of measurement. The model takes the form of a graphical vector-autoregression model between latent variables and is termed the ts-lvgvar when estimated from time-series data and the panel-lvgvar when estimated from panel data. These methods have been implemented in the software package psychonetrics, which is exemplified in two empirical examples, one using time-series data and one using panel data, and evaluated in two large-scale simulation studies. The paper concludes with a discussion on ergodicity and generalizability. Although within-subject effects may in principle be separated from between-subject effects, the interpretation of these results rests on the intensity and the time interval of measurement and on the plausibility of the assumption of stationarity.
TL;DR: In this paper, the convergence of the per capita ecological footprint among the Association of Southeast Asian Nations (ASEAN-5) countries by using panel data for the period 1961 to 2016 was investigated.
TL;DR: In this article, the authors employ monthly provincial panel data and fixed-effects models to study how COVID-19 has impacted China's insurance market and find that the insurance market has been greatly impacted by the outbreak of the COVID19 pandemic.
Abstract: The insurance market has been greatly impacted by the outbreak of the COVID-19 pandemic. We employ monthly provincial panel data and fixed-effects models to study how COVID-19 has impacted China’s ...
TL;DR: The main findings of panel co-integration reveal a long-run relationship between urbanization, energy consumption, and CO 2 emissions, indicating that urban development and high energy consumptions are barriers to improve environmental quality in the long run.
Abstract: The developing world is facing pivotal challenges in recent times. Among these, global warming has ominous repercussions on every segment of society, thus tracing its underlying causes is imperative. This research attempts to investigate the impact of urbanization and energy consumption on carbon dioxide emissions (CO2) for a panel of 8 Asian countries (Bangladesh, China, India, Indonesia, Malaysia, Nepal, Pakistan, and Sri Lanka) over the period 1982 to 2017. The analyses are executed using panel co-integration and Granger causality techniques. The main findings of panel co-integration reveal a long-run relationship between urbanization, energy consumption, and CO2 emissions. Furthermore, the results indicate a positive and significant impact of urbanization and energy consumption on CO2 emissions, indicating that urban development and high energy consumptions are barriers to improve environmental quality in the long run. The results also highlight bi-directional causality between energy consumption and urbanization, while unidirectional causality exists between energy consumption and CO2 emissions. Based on the obtained results, this study offers useful policy implications for plummeting carbon emissions.
TL;DR: In this paper, the link between economic growth, renewable energy, tourism arrivals, trade openness, and carbon dioxide emissions in the European Union (EU-28) was evaluated using panel data.
Abstract: This paper evaluates the link between economic growth, renewable energy, tourism arrivals, trade openness, and carbon dioxide emissions in the European Union (EU-28). As an econometric strategy, the research uses panel data. In the first step, we apply the unit root test, and the results demonstrated that the variables used in this study are integrated I (1) in the first difference. In the second step, we apply the Pedroni cointegration test, and Kao Residual cointegration test, and we observe that the variables are cointegrated in the long run. The panel fully modified least squares (FMOLS), panel dynamic least squares (DOLS), and generalized moments system (GMM-System) estimator are considered in this research. The econometric results proved that trade openness and renewable energy decreased climate change and environmental degradation. The empirical study also found a positive effect of economic growth on carbon dioxide emissions. Moreover, tourism arrivals are negatively correlated with carbon dioxide emissions, showing sustainability practices of the tourism sector on the environment. Furthermore, carbon dioxide emissions in the long run present a positive impact, indicating that climate change increases. In this study, we also consider the recent methodology of Dumitrescu–Hurlin to observe the causality and the relationship between renewable energy, trade openness, economic growth, tourism arrivals, and carbon dioxide emissions.