Open Access. Powered by Scholars. Published by Universities.®

Econometrics Commons

Open Access. Powered by Scholars. Published by Universities.®

2,568 Full-Text Articles 2,122 Authors 659,636 Downloads 114 Institutions

All Articles in Econometrics

Faceted Search

2,568 full-text articles. Page 1 of 91.

The Effect Of Low Skill Job Opportunities On Postsecondary Enrollment, Mallory Radesic 2021 The University of Akron

The Effect Of Low Skill Job Opportunities On Postsecondary Enrollment, Mallory Radesic

Williams Honors College, Honors Research Projects

This research examines the effect that low skill job opportunities have on the probability of enrollment in postsecondary institutions between men and women, namely the construction and manufacturing industries. The research is based on the human capital investment theory, which states that individuals will enroll in postsecondary institutions when the perceived benefits outweigh the costs. More job opportunity heightens the opportunity cost of enrollment, hence lowering the probability of enrollment. After running a probit model, there is evidence that enrollment is countercyclical and that enrollment decisions do not vary significantly between men and women. I find that a 1 percent ...


Essays In Macroeconomics Of Emerging Markets, Miguel Acosta Henao 2020 The Graduate Center, City University of New York

Essays In Macroeconomics Of Emerging Markets, Miguel Acosta Henao

All Dissertations, Theses, and Capstone Projects

Chapter 1. Law enforcement and the size of the informal sector.

I assemble new cross-country evidence showing that contrary to the standard view, the relationship between the size of the informal sector and tax rates is, at best, ambiguous. Law enforcement and informality also show no clear relation. Motivated by these findings, I augment a standard two-sector (formal and informal) small open economy model with endogenous law enforcement that depends on the size of the informal sector (measured by its assets) and government expenditure. I use a micro-dataset from Colombia to show that both taxes and law enforcement are necessary ...


Essays In Financial Economics And Applied Macroeconomics, Marius Mihai 2020 The Graduate Center, City University of New York

Essays In Financial Economics And Applied Macroeconomics, Marius Mihai

All Dissertations, Theses, and Capstone Projects

This dissertation consists of three chapters that cover topics in finance and macroeconomics.

Chapter 1 - Do Credit Booms Predict U.S. Recessions?

This paper investigates the role of bank credit in predicting U.S. recessions since the 1960s in the context of a bivariate probit model. A set of results emerge. First, credit booms are shown to have strong positive effects in predicting declines in the business cycle at horizons ranging from six to nine months. Second, by isolating the effect of credit booms, I identify their contributions to recession probabilities which range between three and four percentage points at ...


Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin HUANG, Sainan JIN, Liangjun SU 2020 Singapore Management University

Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su

Research Collection School Of Economics

We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips (2016, Econometrica 84(6), 2215-2264) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the stationary regressors to diverge with the sample size. We show that we can identify the individuals' group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties ...


Deviance Information Criterion For Latent Variable Models And Misspecified Models, Yong LI, Jun YU, Tao ZENG 2020 Singapore Management University

Deviance Information Criterion For Latent Variable Models And Misspecified Models, Yong Li, Jun Yu, Tao Zeng

Research Collection School Of Economics

Deviance information criterion (DIC) has been widely used for Bayesian model comparison, especially after Markov chain Monte Carlo (MCMC) is used to estimate candidate models. This paper first studies the problem of using DIC to compare latent variable models when DIC is calculated from the conditional likelihood. In particular, it is shown that the conditional likelihood approach undermines theoretical underpinnings of DIC. A new version of DIC, namely DICL, is proposed to compare latent variable models. The large sample properties of DICL are studied. A frequentist justification of DICL is provided. Like AIC, DICL provides an asymptotically unbiased estimator to ...


Sanctuary Cities And Their Respective Effect On Crime Rates, Adam R. Schutt 2020 Minnesota State University Moorhead

Sanctuary Cities And Their Respective Effect On Crime Rates, Adam R. Schutt

Undergraduate Economic Review

According to the U.S. Center for Immigration Studies (2017), cities or counties in twenty-four states declare themselves as a place of “sanctuary” for illegal immigrants. This study addresses the following question: Do sanctuary cities experience higher crime rates than those cities that are not? Using publicly available data, this regression analysis investigates the relationship between crime rates in selected cities and independent variables which the research literature or the media has linked to criminal activity. Results of this research reveal that sanctuary cities do not experience higher violent or property crime rates than those cities that are not sanctuary ...


Running On Fumes: The Long And Short-Run Effects Of British Columbia's Carbon Tax On Gasoline Consumption, Martin A. Long 2020 University of South Dakota

Running On Fumes: The Long And Short-Run Effects Of British Columbia's Carbon Tax On Gasoline Consumption, Martin A. Long

Honors Thesis

British Columbia (BC) implemented a carbon tax in 2008 at the rate of ten Canadian dollars (CAD) per metric ton of carbon dioxide equivalents (CO2e). In April of 2019, the tax was set at a rate of CAD 40 per metric ton of CO2e with a dual mandate to reduce fuel consumption while not contracting economic output. This paper attempts to estimate the effect of British Columbia’s carbon tax on per capita gasoline consumption using panel data regression. To assess the empirical evidence, provincial-level monthly data from ten Canadian provinces was collected and analyzed over the period 1991 to ...


Estimating Predictors Of Mental Well-Being Through Analysis Of Children’S Drawings: The Case Of Syrian Refugees, Stephanie Smith 2020 University of San Francisco

Estimating Predictors Of Mental Well-Being Through Analysis Of Children’S Drawings: The Case Of Syrian Refugees, Stephanie Smith

Master's Theses

There are currently over 65 million individuals that have been forcibly displaced globally. The cumulative trauma that comes from the refugee experience and exposure to violence has proven to have long-term negative psychological outcomes and thus negative impacts on human capital in the long run. Given that over 50% percent of the global refugee population are children, the ability to efficiently and accurately assess their mental well-being is of critical importance. Using data from over 2000 refugee children in Jordan, I use machine learning techniques to find key predictors of psychological distress, PTSD, and exposure to violence found in children ...


Mentoring Effects On Microbusiness Growth In Medellín, Colombia, Diana Herrera 2020 University of San Francisco

Mentoring Effects On Microbusiness Growth In Medellín, Colombia, Diana Herrera

Master's Theses

Microbusinesses are stagnant in growth across least developed countries due to their lack of managerial skills and limited access to the credit market. Current business methods aimed at increasing profitability for microentrepreneurs with limited capital in developing countries are only moderately successful in increasing growth. Having a mentor that has a localized business understanding can provide their mentee with the proper guidance on how to effectively manage their business to increase growth. This paper presents the results for a randomized controlled trial which identifies the average treatment effects of meeting with a mentor and observes the impact on business growth ...


Wellbeing And Marriage: Does Marriage Improve Mental Health?, Maranda L. (Kahl) Joyce 2020 Southwestern University

Wellbeing And Marriage: Does Marriage Improve Mental Health?, Maranda L. (Kahl) Joyce

Undergraduate Economic Review

With the decline in marriage rates and the rise in mental health issues, understanding the potential correlation between marital status and overall mental health is of economic importance. This research explores the potential effects of marital status on mental health in the U.S., using microdata from the 2016 Behavior Risk Factor Surveillance System. The role of marital status is examined on three different dependent variables. My results suggest that marriage is associated with a decrease in number of days of poor mental health, a decrease in the likelihood of a depressive disorder diagnosis, and an increase in overall life ...


Shutdown Policies And Worldwide Conflict, Nicolas Berman, Mathieu Couttenier, Nathalie Monnet, Rohit Ticku 2020 Aix-Marseille University

Shutdown Policies And Worldwide Conflict, Nicolas Berman, Mathieu Couttenier, Nathalie Monnet, Rohit Ticku

ESI Working Papers

We provide real-time evidence on the impact of Covid-19 restrictions policies on conflicts globally. We use daily information on conflict events and government policy responses to limit the spread of coronavirus to study how conflict levels vary following shutdown and lockdown policies. We use the staggered implementation of restriction policies across countries to identify their effect on conflict incidence and intensity. Our results show that imposing a nation-wide shutdown reduces the likelihood of daily conflict by around 9 percentage points. The reduction is driven by a drop in the incidence of battles, protests and violence against civilians. Across actors the ...


Comovement And Instability In Cryptocurrency Markets, Pierangelo De Pace, Jayant Rao 2020 Pomona College

Comovement And Instability In Cryptocurrency Markets, Pierangelo De Pace, Jayant Rao

Pomona Economics

We analyze the extent of comovement between daily price returns of nine major cryptocurrencies during the first three main phases of their development, from April 2013 to November 2018. We assess its evolution using bivariate and multivariate modelling approaches, and detect pronounced time variation. Generally, comovement is initially low and positive, but increases between early 2017 and late 2018. We then adopt a right-tail version of the Augmented Dickey-Fuller unit root test to identify periods of mildly explosive behavior (statistical instability) in the Network Value to Transactions (NVT) ratio (a measure of the dollar value of cryptocurrency transaction activity relative ...


Institutions, Opportunism And Prosocial Behavior: Some Experimental Evidence, Antonio Cabrales, Irma Clots-Figueras, Roberto Hernán-González, Praveen Kujal 2020 Universidad Carlos III de Madrid

Institutions, Opportunism And Prosocial Behavior: Some Experimental Evidence, Antonio Cabrales, Irma Clots-Figueras, Roberto Hernán-González, Praveen Kujal

ESI Working Papers

Formal or informal institutions have long been adopted by societies to protect against opportunistic behavior. However, we know very little about how these institutions are chosen and their impact on behavior. We experimentally investigate the demand for different levels of institutions that provide low to high levels of insurance and its subsequent impact on prosocial behavior. We conduct a large-scale online experiment where we add the possibility of purchasing insurance to safeguard against low reciprocity to the standard trust game. We compare two different mechanisms, the private (purchase) and the social (voting) choice of institutions. Whether voted or purchased, we ...


Information Aggregation And The Cognitive Make-Up Of Traders, Brice Corgnet, Mark DeSantis, David Porter 2020 Chapman University

Information Aggregation And The Cognitive Make-Up Of Traders, Brice Corgnet, Mark Desantis, David Porter

ESI Working Papers

We assess the effect of the cognitive make-up of traders on the informational efficiency of markets. We put forth that cognitive skills, such as cognitive reflection, are crucial for ensuring the informational efficiency of markets because they endow traders with the ability to infer others’ information from prices. Using laboratory experiments, we show that information aggregation is significantly enhanced when (i) all traders possess high levels of cognitive sophistication and (ii) this high level of cognitive sophistication is common information for all traders. Our findings shed light on the cognitive and informational constraints underlying the efficient market hypothesis.


Classical Versus Neoclassical Equilibrium Discovery Processes In Market Supply And Demand Theory, Sabiou M. Inoua, Vernon L. Smith 2020 Chapman University

Classical Versus Neoclassical Equilibrium Discovery Processes In Market Supply And Demand Theory, Sabiou M. Inoua, Vernon L. Smith

ESI Working Papers

"The 1870s marginal revolution in economics culminated a century later in a failure. The core utility maximization principle of this school of thought was shown to have no interesting implication for aggregate market behavior in general (Sonnenschein, 1972, 1973a, 1973b; Debreu, 1974; Mantel, 1974; Kirman, 1989; Shafer & Sonnenschein, 1993; Rizvi, 2006). We argue that neoclassical price theory was flawed from the beginning, owing to the more basic and more serious logical problem inherent to the axiom of price taking behavior, under which market price formation is left unexplained."


Identifying Latent Group Structures In Nonlinear Panels, Wuyi WANG, Liangjun SU 2020 Singapore Management University

Identifying Latent Group Structures In Nonlinear Panels, Wuyi Wang, Liangjun Su

Research Collection School Of Economics

We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify ...


Detecting Latent Communities In Network Formation Models, Shujie MA, Liangjun SU, Yichong ZHANG 2020 Singapore Management University

Detecting Latent Communities In Network Formation Models, Shujie Ma, Liangjun Su, Yichong Zhang

Research Collection School Of Economics

This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed effects. We model the coefficients of observed characteristics to have a latent community structure and the edge-wise fixed effects to be of low rank. We propose a multi-step estimation procedure involving nuclear norm regularization, sample splitting, iterative logistic regression and spectral clustering to detect the latent communities. We show that the latent communities can be exactly recovered when the expected degree of the network is of order log n or higher, where n is the number ...


Forecast Combinations In Machine Learning, Yue QIU, Tian XIE, Jun YU 2020 Singapore Management University

Forecast Combinations In Machine Learning, Yue Qiu, Tian Xie, Jun Yu

Research Collection School Of Economics

This paper introduces novel methods to combine forecasts made by machine learning techniques. Machine learning methods have found many successful applications in predicting the response variable. However, they ignore model uncertainty when the relationship between the response variable and the predictors is nonlinear. To further improve the forecasting performance, we propose a general framework to combine multiple forecasts from machine learning techniques. Simulation studies show that the proposed machine-learning-based forecast combinations work well. In empirical applications to forecast key macroeconomic and financial variables, we find that the proposed methods can produce more accurate forecasts than individual machine learning techniques and ...


Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang JIANG, Xiaobin LIU, Yichong ZHANG 2020 Singapore Management University

Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang Jiang, Xiaobin Liu, Yichong Zhang

Research Collection School Of Economics

This paper examines inference for quantile treatment effects (QTEs) in randomized experiments with matched-pairs designs (MPDs). We derive the limiting distribution of the QTE estimator under MPDs and highlight the difficulty of analytical inference due to parameter tuning. We show that a naive weighted bootstrap fails to approximate the limiting distribution of the QTE estimator under MPDs because it ignores the dependence structure within the matched pairs. We then propose two bootstrap methods that can consistently approximate that limiting distribution: the gradient bootstrap and the weighted bootstrap of the inverse propensity score weighted (IPW) estimator. The gradient bootstrap is free ...


Asymptotic Theory For Near Integrated Processes Driven By Tempered Linear Processes, Farzad SABZIKAR, Qiying WANG, Peter C. B. PHILLIPS 2020 Singapore Management University

Asymptotic Theory For Near Integrated Processes Driven By Tempered Linear Processes, Farzad Sabzikar, Qiying Wang, Peter C. B. Phillips

Research Collection School Of Economics

In an early article on near-unit root autoregression, Ahtola and Tiao (1984) studied the behavior of the score function in a stationary first order autoregression driven by independent Gaussian innovations as the autoregressive coefficient approached unity from below. The present paper develops asymptotic theory for near-integrated random processes and associated regressions including the score function in more general settings where the errors are tempered linear processes. Tempered processes are stationary time series that have a semi-long memory property in the sense that the autocovariogram of the process resembles that of a long memory model for moderate lags but eventually diminishes ...


Digital Commons powered by bepress