This paper considers recent and historical changes in the three-point line distance at the NCAA and NBA levels as an example of policy change with highly-measurable outcome(s). The paper presents several empirical tests describing a point-maximizing basketball team's optimal allocation of two-point and three-point shots. It does so primarily in the context that the NCAA Men's Basketball three-point line was extended from 20′9″ to 21′9″ in advance of the 2019–20 season, and similar analysis for the NBA in the 1990s. We find that a three-point line extension significantly lowers three- and two-point shot proficiency, while decreasing (increasing) three-point (two-point) shot volume.
Background: In the wake of COVID-19, almost all major league sports have been either cancelled or postponed. The sports industry suffered a major blow with the uncertainty of sporting events being held in the near future. Various scenarios of how and when sports might recommence have been discussed. This paper examines various scenarios of how Major League Baseball team performance is going to be impacted by the presence of fans, or the lack thereof, in the context of physical distancing and other COVID-19 countermeasuresMethods: The paper simulates, using a neural network and a logit regression model, the win-loss probabilities for various scenarios under consideration and also estimates the home effect for each team using data for the 2017-2019 seasons.Results: The model demonstrates that individual team home effect is symmetric between home and away and teams will not necessarily have a win or loss of any additional games in neutral stadiums, as teams with a high home field effect will lose more neutral games that would have been at home but will win more neutral games that would have been away. However, the result of individual games will be different since home effect is asymmetric between teams. Our simulation demonstrates that these individual game differences may lead to a slight difference in Play-Off Berths between a full season, a half season, or a full season without fans.Conclusions: Without fans, any advantage (or disadvantage) from home field advantage is removed. Our models and simulation demonstrate that this will reduce the variance. This stabilizes the outcome based upon true team talent, which we estimate will cause a larger divide between the best and worst teams. This estimation helps decision makers understand how individual team performance will be impacted as they prepare for the 2020 season under the new circumstances.
This paper focuses on analyzing small-sample business survey data. We survey 129 businesses in Nepal, where a majority of businesses express an overwhelmingly positive perception towards microfinance institutions (MFIs). The survey focuses mainly on how businesses perceive the services provided by local MFIs. In order to address the bias in maximum likelihood estimation in the context of small sample size, we utilize Firth’s adjusted maximum likelihood estimation procedure in the application of logistic regression. The results show that it is the borrowing of a loan from an MFI, not the actual business performance, which influences a business owner’s perception towards the role of MFIs in various aspects of rural development. While there is no strong evidence of the MFI loans helping with the actual business performance, and thereby influencing the perceptions, we discuss the potential benefits of owning a business that may be contributing to the positive perceptions towards the institutions with which they are associated. These findings have important implications from the managerial perspective of both MFIs and governing institutions in developing countries.
This paper analyzes the effect of research and development expenditure (R&D) on innovation in the Organization for Economic Cooperation and Development (OECD) member countries over the period 1996-2015. Innovation, the dependent variable, is measured using two different proxies: patent applications by residents (PAR) and the patent applications by non-residents (PANR) in the host countries. R&D is the main variable of interest which is also interacted with foreign direct investment (FDI) to see how the entry of foreign competitors influence the role of R&D on innovation in the host country. The findings show that R&D alone promotes innovation by residents but impedes innovation by non-residents. However, when FDI interacts with the R&D in the host country, it produces opposite results. Specifically, increasing FDI in the presence of a certain level of R&D in host countries impacts PAR negatively and the PANR positively. These results have important policy implications.
The Pythagorean Expected Wins Percentage Model was developed by Bill James to estimate a baseball team expected wins percentage over the course of a season. As such, the model can be used to assess how lucky or unfortunate a team was over the course of a season. From a sports analytics perspective, such information is valuable in that it is important to understand how reproducible a given result may be in the next time period. In contest theoretic (game theoretic) parlance, the original model represents a (restricted) Tullock contest success function (CSF). We transform, estimate, and compare the original model and two alternative models from contest theory, the serial and difference form CSFs, using MLB team win data (2003 to 2015) and perform a cross-validation exercise to test the accuracy of the alternative models. The serial CSF estimator dramatically improves wins estimation (reduces root mean squared error) compared to the original model, an optimized version of the model, or an optimized difference form model. We conclude that the serial CSF model of wins estimation substantially improves estimates of team quality, on average. The work provides a real world test of alternative contest forms.
This study assesses the impact of globalization on female participation in the labor force (FPLF). The increased globalization in the last several decades has created various economic opportunities for enterprises and individuals worldwide at an unprecedented rate. As a result, it has helped improve the quality of life for many men and women. In this process, the issue of women’s economic participation has been a critical topic for discussion worldwide. In that context, the objective of the paper is to determine if FPLF is influenced by a country’s participation in foreign markets through foreign direct investment (FDI) – a proxy for globalization. The paper uses a panel dataset obtained from the World Bank’s World Development Indicators database for 99 countries from 2001 to 2018. We then use system Generalized Method of Moments (system GMM) to estimate a dynamic panel model with appropriate specification tests. The results show that the positive effects of FDI on FPLF are more robust for low- and middle-income countries than high-income countries. We also find that results may be sensitive to outlier observations. Our results explain the seemingly inconclusive results within existing literatures and suggest that low- and middle-income countries should particularly focus on sectors that generate FDI as they stand to yield the greatest benefits with regards to female economic empowerment.
This paper analyzes the impact of foreign direct investment (FDI) and technology on income levels in middle-income countries. These two factors are used as the measures of imitation and innovation of technology respectively. From micro perspectives, technology entails a great deal of incentive for individuals, firms, and industry. But, how innovation and imitation of technology lead a country as a whole to a higher level of economic performance is not as direct as microeconomic perspectives. The focus of this paper is to analyze the individual impacts of these two variables on the level of GDP per capita for two groups of countries: upper-middle-income (UMI) and the lower-middle-income (LMI) countries. The baseline results show a stronger effect of FDI (imitation) compared to technology (innovation) for both sets of countries. However, when we control for potential endogeneity using the instrumental variable approach, imitation favors the LMI countries while innovation favors the UMI countries. The findings can be applied in the context of “more developed” and “less developed” countries suggesting that the less developed countries may be better-off focusing on the imitation of technology instead of innovating new ones, leaving the role of innovation to the more developed countries.
Purpose The purpose of this paper is to analyze how the coronavirus disease 2019 (COVID-19) countermeasures will affect the financing of the North American leagues. In particular, we focus on the missed revenue from gate receipts for the Big Four leagues. Design/methodology/approach The authors forecast the 2020 revenue for each of the four major leagues under two scenarios: (1) expected revenue under the normal conditions of fans in attendance and (2) expected revenues in the absence of fans due to the countermeasures in place. Then, the authors calculate the loss in gate receipts as a difference in the revenue under fans and no-fans scenarios. Findings Based on the current estimates, the combined financial loss of the clubs from NFL, MLB, NBA and NHL is expected to be above 6.8bn dollars in gate receipts alone. Practical implications The findings are useful to the league management to prepare for the suboptimal financial situation. Originality/value To the best of our knowledge, this is the first study that explores the effect of the COVID-19 pandemic across the major league sports leagues in North America.
Abstract This study examines the influence of microfinance institutions’ (MFIs) financial innovation on structural transformation. For this purpose, we considered a household survey from Nepal. The survey collected data on various individual and household characteristics, borrowing patterns, and occupations over the years. The key question focused on occupations before and after borrowing, a categorical response variable indicating 1 for occupational change after borrowing and 0 otherwise. Therefore, we use logistic regression to estimate the probability of occupational change, given two measures of financial innovation: loan purpose and size. The results show that the number of households involved in agriculture significantly decreased, with the majority switching to businesses and convenience stores, indicating a shift to the manufacturing and service sectors. These findings suggest that MFIs contribute to local-level structural transformation by enabling borrowers to move away from traditional employment. This study has important implications for policymakers, development practitioners, and academics interested in promoting economic development through microfinancing in low-income countries.
Increasing levels of carbon emissions have been a growing concern worldwide because of their adverse environmental effects. In that context, this paper examines the association between different categories of trade and carbon dioxide emissions. In particular, we analyze whether total trade, commodity trade, and service trade affect the environment differently. The analysis is based on panel data for 147 developing countries for the period from 1960 to 2020. Methodologically, the fixed-effects model, as suggested by the Hausman test, is used to examine the relationships. We present two main conclusions: (1) overall trade increases CO2 emissions, and (2) commodity trade contributes to higher levels of CO2 emissions than service trade. These results have important policy implications—climate change policies should target commodity trade sectors to help reduce environmental carbon emissions.
