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The data presented here are manually encoded characteristics of research papers in the area of Energy-Economy Nexus (empirical investigation of Granger causality between energy consumption and economic growth) that describe the methods, samples, and other details related to the individual estimations done in the examined empirical papers. Data cover papers indexed by Scopus, published in economic journals, written in English, after year 2000. In addition, papers were manually filtered to only those that deal with Energy-Economy Nexus investigation and have at least 10 citations at (at the time of query – November 2015). This data are to be used to conduct meta-analysis – associated dataset was used in Hajko [1]. Early version of the dataset was used for multinomial logit estimation in Master thesis by Kociánová [2].

Purpose: The impact of financial inclusion on economic growth is a topic that is generating widespread interest among researchers and practitioners. In this paper, the authors review the existing literature to highlight the state of research in the literature and identify new opportunities for innovative research. Design/methodology/approach: The authors used a thematic literature review methodology which involves dividing the review along relevant themes. Findings: The authors find that significant research on the topic emerged in the post-2016 years. Most of the existing studies are from developing countries and from the Asian and African regions. Existing studies have not utilized relevant theories in explaining the impact of financial inclusion on economic growth. Most studies report a positive impact of financial inclusion on economic growth while very few studies show a negative impact. The most common channel through which financial inclusion affects economic growth is through greater access to financial products and services offered by financial institutions that increases financial intermediation and translates to positive economic growth. The common empirical methodology used in the literature are causality tests, cointegration and regression methods. Multiple proxies of financial inclusion and economic growth were used in the literature which partly explains the conflicting result among existing studies. The review paper concludes by identifying some directions for future research. Originality/value: This paper presents the first rigorous thematic review of the existing literature on the impact of financial inclusion on economic growth. It highlights the main approach that researchers have taken on this topic and identifies some important research areas for future investigation. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2022-0339. [ABSTRACT FROM AUTHOR]

In this paper, we aim to remark on the nine crucial economic factors that affect GDP (Gross Domestic Product) per capita as assess the importance, effect, or value of economic development for a sample of 31 years of economic data from Bangladesh for the period of 1992 to 2022. The research question is "What are the effects of these variables on GDP per capita?" To inquire into that business in detail we use multiple regression analysis in this paper as GDP (Gross Domestic Product) per capita is the regressand or dependent variable and the rest of the factors or variables are the regressors or independent variables. In this regard, we use nine independent variables in the regression analysis: Gross Domestic Product (GDP) in current billions of USD, GDP growth rate (latest) per annum, Inflation (on consumer price index), Gross Savings (%GDP), Literacy rate, Unemployment rate, Investment rate, Population growth rate, Poverty Rate. After the data analysis we found that among the nine independent variables, five have a significant impact on GDP per capita. For instance, Inflation (% of GDP), GDP (current USD), GDP growth rate, Gross Savings rate, and Poverty rate play a vital role in determining GDP per capita. Since we use time series data, to identify an accurate estimation as being present we test the stationarity of data, to conduct the time series has no unit root problem we use first difference and log difference such that the data and the estimation will become acceptable. An assortment of statistical tests, such as Normality Test, Multicollinearity, Heteroskedasticity, Autocorrelation, Goodness-of-Fit (GoF) Test, ANOVA (Analysis of Variance) Test, and Multiple Regression Analysis, were performed using GRETL (Gnu Regression, Econometrics and Time-series Library). We use CUSUM (cumulative sum) test and CUSUM (cumulative sum) square test to find out the stability of the coefficient or parameters. The research question is "What are the effects of these variables on GDP per capita?" [ABSTRACT FROM AUTHOR]

This paper asks the following question: can the macroeconomic fluctuations of Gross Domestic Product (GDP) explain the electoral success of political parties? Notwithstanding other important determinants such as the charisma of the leader of a popular political party or ideology, the economy may very well explain electoral successes. In this paper, I use a very simple variable to account for the economy: the rate of growth of GDP. It is claimed that years of relative higher growth are associated with the incumbent government retaining its power, while years of zero or negative growth rates are related with the fall of an incumbent government. The period between 1974-2023 shows evidence of Greek economic growth and the impact on elections and therefore the hypothesis cannot be rejected that the economy plays a central role in explaining electoral successes, and especially failures, of incumbent governments. [ABSTRACT FROM AUTHOR]

Gender and racial discrimination at work have gradually gained more attention from the public in the recent years. With social movements such as #MeToo and #BlackLivesMatter, people start to reach the consensus that there should be more equality in society; more perspectives from different genders and different races are beneficial to society. This paper focuses on employment in the general workforce and studies how race and gender diversity in different job positions affect the economy. This paper explores to empirically explain why race and gender diversity in the workforce can have an impact on the economy. Using data from the U.S. Equal Employment Opportunity Commission and from the Federal Reserve for the years of 1996 - 2018, this paper finds that race and gender diversity at work are positively associated with the economy. Also, this dataset supports the conjecture that race and gender diversity increases total employment, which further increases the economy. This dataset also supports the possibility that race and gender diversity may increase the capacity of different perspectives, which further increases the economy. Moreover, race and gender diversity both increased during these years: from 11.783% to 23.339% and from 31.683% to 38.735% in the executive and managerial positions. This study has significant contributions to current research and practice. [ABSTRACT FROM AUTHOR]