An Analysis of Gender Inequality in Professional Tennis

This paper examines the gender wage gap in professional sports using a pooled cross-section of professional tennis players across the years 2011-2017. The dependent variable is the prize money earned by the top fifty male and top fifty female ranked tennis players throughout the world. This prize money is measured in 2017 real dollar value. The independent variables include: number of tournaments played, age, rank differentiation, gender, country and WTA/ATP score. Gender inequality is measured by determining the wage gap shown through the mean prize money earned by the professional tennis players from 2011-2017. While prize money for men and women has recently become equal in the Grand Slam tournaments, there is evidence to show that women's prize money is considerably lower in the less-publicized tournaments. Results of the ordinary least squares (OLS) regressions suggest that there is evidence for a gender-related pay disparity in professional tennis due to a number of statistically significant variables including WTA/ATP score (+), age (+), country (+) and the gender (-) and year (+) dummies.

Socioeconomic Influences on Fertility Rate Fluctuations in Developed and Developing Economies

This study investigates what socioeconomic factors determine the varying fertility rates among developed and developing nations and the implications of this information. Social and economic variables are analyzed using a panel of 20 nations with annual data from 1991-2015 to determine the most sizable and significant variables that impact fertility rates. A one-way fixed effects model is utilized. This study includes an aggregate model as well as two models isolating the fertility rates of developed nations and of developing nations, in accordance with Chow-Test results. The results find that there is a divergence between the determinants of fertility rates, based upon the development level. It is clear from these results that fertility and population control issues are specific to the state of a nation's development; thus, blanket policies will not fully address the issue of excessive population growth.

The Convergence Behind the Curtain

This chapter extends applications of unconditional and conditional β-convergence and unconditional σ-convergence analysis to Part I crime rates in a panel data sample of Pennsylvania counties during the period 1990-2015. Temporal structural breaks at specific points in the business cycle during the time frame and spatial breakpoints between rural and urban counties in Pennsylvania are acknowledged in the analysis in order to avoid spurious inferences regarding convergence behavior. Unit-root testing is performed on measures of dispersion as well as directly on the underlying crime-rate series via panel-data tests for non-stationarity. The findings support the existence of both unconditional and conditional β-convergence in the pooled, urban, and rural samples during 1990-2015. Visual and statistical evidence reveals the presence of σ-convergence in the three samples across the time span as well. The comprehensive convergence analysis of appropriately disaggregated data performed in this study offers strong support for the predictions of modernization theory.

Oil Prices and Economic Growth in Major Emerging Economies

There is a strong correlation between energy prices and economic activity. The relationship particularly holds true for crude oil as changes in oil prices are associated with changes in production costs, and economic activity also generates significant demand for energy and crude oil. This chapter examines the relationship between economic activity and crude oil prices using causality tests in the frequency domain and taking into account the difference between positive and negative changes in both oil prices and economic activity as the relationship can be asymmetric. The authors present empirical results for major emerging economies including Brazil, Russia, India, China, South Africa, and Turkey. Empirical results indicate that for most countries there is bidirectional causality between crude oil prices and economic activity whereas only negative oil price shocks seem to negatively affect economic activity.

Macroeconomic Suprises and the Turkish Financial Market

In the study, the authors investigate the impacts of macroeconomic news originating from Turkey, US, Euro Zone, and China on the Turkish financial market. They consider Purchasing Managers Indices and Gross Domestic Product growth rates as macroeconomic news. The study covers the period from May 4, 2015 to January 1, 2019, and six sectoral indices are included into the analysis. The findings show that impacts of macroeconomic surprises on abnormal returns are significant for all the sectors except Holdings and Investments and Insurance. The authors also provide evidence that the impacts of macroeconomic surprises on volatilities are significant for only Holdings and Investments and Technology.

Does Regional Variation in Startup Concentration Predict Employment Growth in Rural Areas of Ohio, Pennsylvania, and West Virginia?

Measures of entrepreneurship, such as average establishment size and the prevalence of start-ups, correlate strongly with employment growth across and within urban areas. Is it possible for entrepreneurship to occur outside of urban areas and be active in rural areas such as Ohio, Pennsylvania, and West Virginia? There are causal links of entrepreneurial finance to industry or city growth but little link of the evidence of entrepreneurship outside of urban areas overall. This chapter examines the regional variation in startup concentration used to predict employment in the rural areas of Pennsylvania, Ohio, and West Virginia by metropolitan statistical area (MSA)/micropolitan areas for the year 2017. The authors find significant differences in new firm formation rates from industrial regions to technologically progressive regions using the generalized linear models (GLM). Variations in firm birth rates are explained by industrial size, population growth, the number of startups, human capital variables, and establishments.

Financial Determinants Affecting Leasing Policies

Airline companies have started to develop strategies to increase their market share and expand their network structure with the effect of globalization. In this process, one of the most important sources of airline companies to achieve competitive advantage is aircraft. Airline companies have to increase the number of aircraft in the fleet to expand their network structure. On the other hand, the high price of aircraft has led airline companies to adopt new financing strategies. Leasing is one of the financing methods used frequently by airline companies recently. Therefore, this study focuses on the leasing policies of airline companies. In this study, it is aimed to reveal the factors affecting the leasing policies of airline companies. In this context, 26 airlines operating in the period 2000-2017 were analyzed empirically. Panel data analysis was used as the method in the study. The empirical findings of the study indicate that return on assets, asset structure, tangibility, leverage ratio, and liquidity affects the leasing policies of airline companies.

Categorical Dependent Variables Estimations With Some Empirical Applications

Microeconomic datasets are usually large, mainly survey data. These data are samples of hundreds of respondents or group of respondents (e.g., households). The distributions of such data are mostly not normal because some responses/variables are discrete. Handling such datasets poses some problems of summarizing/reporting the important features of the data in estimations. This study concentrates on how to handle categorical variables in estimation/reporting based on theoretical and empirical knacks. This study used Ghana Demographic and Health Survey data for 2014 for illustration and elaborates on how to interpret results of binary and multinomial outcome regressions. Comparison is made on the different binary models, and binary logit is found to be weighted over the other binary models. Multinomial logistic model is best handled when the odds of one outcome versus the other outcome are independent of other outcome alternatives as verified by the Independent of Irrelevant Alternatives (IIA). Conclusions and suggestions for handling categorical models are discussed in the study.

Autoregressive Distributed Lag Approach to External Credit and Economic Growth in Nigeria

The need for increasing external credit flows to boost economic activity has exposed Nigeria to the negative effects of external structural changes. Therefore, an important question of concern in this study is, how does the Nigerian economy grow when there is a decline in external credit? This study attempted to answer this question by comparing the flow of external credit to economic activities. This is a distinction from previous studies that had compared stock of external credit to economic activities. Using annual data covering 36 years for the period 1980-2016, the study adopted the neoclassical growth model and estimated the model using the Autoregressive Distributed Lag (ARDL) approach. The study argued that, to the extent that expenditure is credit financed, GDP should be a function of credit flow, which is new borrowing.

Dynamics of the Relation Between Producer and Consumer Price Indices

The relation between the Producer Prices Index (PPI) and the Consumer Price Index (CPI) in the U.S. is analyzed for two sub-periods: one spanning from 1947 to 1982, the post-war period marked by demand-side economic policies, and the other one starting by 1983 when supply-side policies pioneered by the Reagan government came into effect. As the series in question are found to be cointegrated, a Vector Error Correction Model is employed for the analysis. Regarding the long-run equilibrium relationships, it is found that the loading for the PPI series are statistically significant for both periods, while the loading for the CPI is barely significant for the first period, and it is insignificant at any acceptable level for the second. Thus, the CPI represents the common trend in the system in both periods, but it does more clearly so in the second period.