Research 

This paper examines how expansions of the EITC affect job match quality. I develop a simple job search model with wage subsidies, which predicts that higher subsidies reduce match quality. To test this, I construct a multidimensional measure of mismatch, defined as the gap between the skills required in an occupation and the worker’s ability to learn those skills.

Using a simulated instrument and data from the 1979 National Longitudinal Survey of Youth linked to O*NET, I find that the EITC increases skill mismatch in initial jobs, primarily because workers are overqualified relative to their positions. The effects are concentrated among single women with some college education. Moreover, mismatch lowers workers’ starting wages. These findings suggest that while the EITC boosts labor force participation, it may also raise the marginal cost of public funds by inducing distortions in job matching.

The number one challenge facing Household Enterprises (HEs) in Ghana is limited access to loans. Many of these entrepreneurs are considered not creditworthy by formal financial institutions because of information asymmetry, hence leaving them with limited options of borrowing from costly informal sources. The purpose of this study is to identify the factors that influence HEs’ access to formal and informal loans, and whether demand for formal and informal loans are substitutes or complements. 

Using Ghana’s 2013 informal enterprise survey of 729 household enterprises and ordinary probit and bivariate probit models, our results for the formal financial market show that an entrepreneur’s experience, enterprise age, enterprise size, and possession of assets are significant determinants of access to formal loans. Whereas access informal loans are determined by an entrepreneur’s gender and household size. We use a bivariate probit regression to estimate the relationship between demand for formal and informal loans. Our findings indicate that formal and informal loans are imperfect substitutes, with the probability of substituting formal and informal loans being 19.5%.

The findings from our paper provide empirical evidence that outlines the determinants of loan accessibility by HEs across both the formal and informal credit markets and the link between credit demand across both formal and informal financial sectors.

Most recently, machine learning methods have demonstrated accurate performance in different domains, including economics. Current methods for forecasting macroeconomic indicators are dominated by statistical methods that require a large amount of data and some prior knowledge of the data-generating process, which may not be available. In this study, I explore machine learning methods to predict  U.S. civilian unemployment across four forecast horizons using models built on three neural network architectures- Long Short-Term Memory (LSTM), Encoder Decoder, and Multi-Layer Perceptron (MLP). Using various performance metrics, results show that all the models perform well in predicting the unemployment rate at short-term horizons. However, only the Encoder-Decoder model performs well at the medium-term horizon. The predictiveness of the models suggests that the models were able to learn the economic relationship between the past and future values of the unemployment rate. The findings in this study imply that models built using machine learning methods, such as deep neural networks may have predictive powers as those built using statistical methods.

In this paper, I explore whether the apparent declines in match quality due to the Earned Income Tax Credit (EITC) mask a compensating benefit: increased access to workplace flexibility. I follow Goldin(2014) and measure workplace flexibility using occupation characteristics that reflect several aspects of a job, such as the time pressure associated with the job, the need for workers to be around at particular times, the flexibility of the occupation with regard to scheduling, the groups, and workers the employee must regularly keep in touch with, and the degree to which the worker has close substitutes. This measure of flexibility is referred to as temporal flexibility. Using the public version of the National Longitudinal Survey of Youth 1979 cohort (NLSY79) and the O*NET database, I find evidence that greater EITC generosity is positively associated with workers’ demand for flexible job arrangements.

In this follow-up study, I first investigate whether there is any relationship between the EITC and job satisfaction. The benefit incentives from the EITC may affect the quality of job matches workers form in the labor market, the flexibility workers demand in their jobs, and the wages workers earn on a job. Evidence from the literature shows that these factors are associated with the satisfaction workers report on their jobs. I exploit the EITC expansions in the 1980s and 1990s to provide evidence on whether the increasing generosity of the EITC has affected the job satisfaction of non-college-educated single women, using the 1980 to 2006 waves of the NLYS79 cohort to obtain individual-level information on measures of job satisfaction and detailed labor market information, and estimating an ordered logit model. Preliminary results using the federal variations in the EITC show that increases in the EITC increase the probability of reporting being dissatisfied with one's job but reduce the probability of reporting being very satisfied. Second, I examine whether the generosity of the EITC affects the relationship between job satisfaction and job quits. Among the EITC population, quitting a job could potentially mean exiting the labor market since intermittent labor force participation is often observed among women. The wage subsidy from the EITC implies that when a worker quits a job, she does not only lose the wage income from the job but the subsidy benefit. The increased opportunity cost of exiting the labor market may discourage quitting a job to exit the labor market for a given level of job satisfaction. Moreover, the EITC may increase the probability of quitting a job by encouraging job-to-job transitions if the credit benefit affects match quality and match quality is associated with job-to-job transitions. I examine whether the generosity of the EITC affects the relationship between job satisfaction and job quits using a logit model, exploring the federal and state-level variation in the EITC from expansions in the EITC over more than two decades. Results from  preliminary analysis using the federal variation in the EITC show that increases in the EITC generosity reduce the probability of quitting one's job, even among workers who report being dissatisfied with their jobs.