Did Gary Johnson and Jill Stein Cost Hillary Clinton the Presidency? A Counterfactual Analysis of Minor Party Voting in the 2016 US Presidential Election

Hillary Clinton won the national popular vote for president in 2016, but lost to Donald Trump in the Electoral College. Trump’s margin of victory in several decisive battleground states was smaller than the combined vote for the two leading minor party candidates: Gary Johnson, of the Libertarian Party, and Jill Stein, of the Green Party. The perception that Johnson and Stein “stole” the 2016 presidential election from Clinton is widespread, and potentially consequential for future minor party candidacies, but it has not yet been rigorously tested. In this article, we extend the analysis of minor party voting in the 1992 election from Lacy, D., and B. C. Burden. 1999. “The Vote-Stealing and Turnout Effects of Ross Perot in the 1992 U.S. Presidential Election.” American Journal of Political Science 43 (1): 233–55, by using data from the 2016 Cooperative Congressional Election Study to estimate a multinomial probit model of voting behavior—including outcomes for vote choice and abstention—and calculate the predicted probabilities that Johnson and Stein voters would have voted for another candidate or abstained from voting, had one or both of these candidates been excluded from the ballot. We then reallocate Johnson’s and Stein’s votes accordingly, to estimate Clinton’s and Trump’s counterfactual vote shares nationally and within key battleground states. Our analysis indicates that Johnson and Stein did not deprive Clinton of an Electoral College majority, nor Trump the legitimacy of winning the national popular vote. We estimate that most Johnson and Stein voters would have abstained from voting if denied the choice to vote for their preferred candidate, and that most of Johnson’s remaining voters would have supported Trump.

Champions during Crises Scenarios: High Growth and Persistent High Growth Firms

Our paper aims to participate to the growing policy discussion on high-growth firms (HGFs) by analyzing persistence of high growth patterns over crisis. During downturn periods, such as post pandemic one, policy makers seek sources to maintain competitiveness and accelerate growth. Being dynamic players in economic growth and job creation, persistent high-growth firms are notable candidates for assuming that role under such circumstances. Therefore, in this study we explore the determinants and characteristics of HGFs and persistent high-growth firms (PHGF) in a crisis scenario.We use a sample of 190,247 firms from 2007 to 2014. We estimate a multinomial probit model with independent idiosyncratic components across the different categories (i.e. HGFs, PHGFs and other firms) using full maximum likelihood. In a second phase we explore which characteristics of HGFs affect the probability of being a PHGFs.HGFs are characterized by higher productivity and leverage, and PHGFs systematically differ from other HGFs only in what regards degree of international involvement. HGFs probability of maintaining high growth rates is very low.HGFs are essentially one-hit wonders and it is debatable whether policymakers can enhance economic results by targeting them. Policy makers should be directed towards those firms which have in principal the potential to be winners, but only through policy intervention these aided firms can realize their great potential (i.e. pick and build winner).

EMPIRICAL INVESTIGATION OF TAX COMPLIANCE DETERMINANTS IN KATSINA STATE, NIGERIA

Tax compliance is determined by many factors, which are categorized into social, economic, institutional, demographic and individual factors. In this regard, the main objective of this study is to empirically evaluate and understand tax compliance determinants usingdata generated from agro-allied industries in some selected local government areas of Katsina state, Nigeria. As such, primary source of data was employed through the use of structured questionnaire to collect relevant information from all the 133 agro-allied industries in the study area and multinomial probit model was adopted for estimation. Basically, the findings from this study indicate that tax rate, level of income, perception on government spending, change in government policy, simplicity of tax system and efficiency of the tax authority are significant determinants of tax compliance among agro-allied industries in the study area; whereas perception on equity and peer influence are insignificant determinants. In this connection therefore, the study recommends that government should ensure efficient allocation of public funds, in order to fiscally motivate taxpayers to develop compliance attitude. Also, policy formulation and implementation should physically be centered towards improving the quality of life of citizens, so as to improve taxpayers’ belief in policy makers thereby increasing the level of compliance. And finally, the tax authorities should be transparent and accountable in tax collection, which may result to positive compliance as well as increase in tax revenue yield for national development.

Does Education Produce Identical Labour Market Outcomes for All? A Study on India

According to the neoclassical economists, discrimination exists in the labour market if employers treat two equally qualified and skilled persons differently based on gender, race, age, disability, religion, caste, etc. In this article, we attempt to look at discrimination in the Indian labour market by applying the multinomial probit model of regression to the National Sample Survey Office data set. By taking years of schooling (as an indicator of skill and ability) as an independent variable in the model, we find that identically educated persons from different caste and gender groups are not equally likely to achieve similar occupational status, indicating the existence of discrimination in the Indian labour market. JEL Classifications: I31, C31

Investigation of Alcohol Consumption Determinants in Turkey With Multinomial Probit Model

The main objective of this study is to determine key factors that may have a significant effect on alcohol consumption in Turkey. For this purpose, the cross-sectional data obtained from the Turkish Health Survey conducted in 2010 and 2012 by the Turkish Statistical Institute were analyzed through the multinomial probit model. Results revealed that several key variables were found to be a significant determinant of alcohol consumption, such as gender, age, education, marital status, income, general health status, tooth brushing frequency, situation of violence, fruit consumption frequency, tobacco use, exposure to tobacco smoke, and survey year. It is apparent that alcoholics need help to get rid of an addiction. Therefore, it would be inevitable for governments to intervene through national and international public health authorities. In particular, the ability of governments to design and implement comprehensive prevention strategies that combine the strengths of different policy approaches is critical to success.

Exploration of Contributing Factors Related to Driver Errors on Highway Segments

A significant portion of crashes occurred on highway segments, with more than 90% of crashes associated with driving errors. To avoid a crash, a driver needs to detect a hazard, decide the safest driving maneuvers, and execute them properly. Driver errors at any of these sequential phases may lead to a crash; therefore, it is necessary to identify the contributing factors and assess their influence on driver behavior. To assist this investigation, a multinomial probit model was employed to study driver errors reported in crashes in rural and urban areas. The modeling results identified many highway geometric features, traffic conditions, roadway events, and driver characteristics as statistically correlated to different types of driver error. Following the extensive list, the impacts of error-contributing factors were discussed within each error category. This exercise helps to gain a better understanding of similar or varying effects of explanatory variables across different error categories. The broad and insightful information will help researchers and safety professionals to better understand when, where, and how the driver error may lead to a crash and to develop cost-effective preventive countermeasures.

Minimum Wages, Employment, and College Enrollment

Most studies of the effects of minimum wage laws look exclusively at the labor market. This article investigates the less-researched topic of the effects of a minimum wage increase on enrollment in undergraduate higher education institutions in the United States. With a higher opportunity cost of pursuing an education given a higher minimum wage, potential students may opt to work instead of attend college. Conversely, if an increase in the minimum wage raises the unemployment rate for young workers, more people may enroll in college, as they are unable to find employment. Using restricted geocode variables and panel data from National Longitudinal Survey of Youth (NLSY97) over a period of time in which every state saw an increase in its effective minimum wage, we find that higher minimum wages do correspond to lower levels of college enrollment. We use a multinomial probit model to examine how tradeoffs are made between employment and college enrollment. Finally, we examine the transition path between college enrollment and employment. JEL Classification: I23, J24, and E24.