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Full-Text Articles in Social and Behavioral Sciences

Economic Growth Before And After The Fiscal Stimulus Of 2008–2009: The Role Of Institutional Quality And Government Size, André Varella Mollick, Andre Coelho Vianna Oct 2023

Economic Growth Before And After The Fiscal Stimulus Of 2008–2009: The Role Of Institutional Quality And Government Size, André Varella Mollick, Andre Coelho Vianna

Economics and Finance Faculty Publications and Presentations

Governments implemented fiscal stimulus packages to alleviate the global financial crisis of 2007–2009. Using annual data from 1996 to 2019, we investigate economic growth in a large sample of countries for pre-and post-Global Financial Crisis years. Our approach analyzes the interaction between institutional quality and government size (government expenditures as share of GDP), reinforced by threshold estimations. We document that economies react to government size depending on the quality of the institutions in question. First, fixed effects models indicate higher institutional quality has positive effects on growth, while government size—and its interactions with institutional quality—has negative effects. Second, the coefficients …

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Natural Disasters’ Effect On Tourism Employment, Caterina Messina May 2022

Natural Disasters’ Effect On Tourism Employment, Caterina Messina

Honors College Theses

Not only do natural disasters cause immediate physical damage to an area, but they often have long-lasting social and economic effects as well. Tourism is a sector of the economy that is relatively fragile and relies heavily on a stable economy. This paper attempts to capture the effect of natural disasters on the tourism industry, specifically tourism employment. This research uses panel data and focuses specifically on 7 metropolitan statistical areas in the United States between 2002-2018. Data collected from the BEA as well as SHELDUS is used in order to quantify this effect. A fixed effects model with a …

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The Predictive Ability Of Stock Market Factors, Fatma Ahmed, Mohammed Elgammal Elgammal, David Gordon Mcmillan Jan 2022

The Predictive Ability Of Stock Market Factors, Fatma Ahmed, Mohammed Elgammal Elgammal, David Gordon Mcmillan

Economics

Purpose – This paper aims to ask whether a range of stock market factors contain information that is useful to investors by generating a trading rule based on one-step-ahead forecasts from rolling and recursive regressions. Design/methodology/approach – Using USA data across 3,256 firms, the authors estimate stock returns on a range of factors using both fixed-effects panel and individual regressions. The authors use rolling and recursive approaches to generate time-varying coefficients. Subsequently, the authors generate one-step-ahead forecasts for expected returns, simulate a trading strategy and compare its performance with realised returns. Findings – Results from the panel and individual firm …

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Causality Analysis Of Disaggregated Fdi Inflows On Sectorial Growth In Oecd Area, Lawrence Ogbeifun, Olatunji Abdul Shobande Dec 2020

Causality Analysis Of Disaggregated Fdi Inflows On Sectorial Growth In Oecd Area, Lawrence Ogbeifun, Olatunji Abdul Shobande

Faculty and Student Publications

This article revisits the link between disaggregated Foreign Direct Investment (FDI) inflows and sectorial growth using the panel dataset of 25 Organisation for Economic Co-operation and Development (OECD) countries for the period 1990 to 2017. It adopted the panel fixed effect and Feasible Generalized Least Squares Approach in its analysis. The findings show that disaggregated FDI inflows have the potential to improve growth in the OECD area with adverse effects on domestic investment and inflationary pressure. Additionally, the results further indicate that disaggregated FDI inflows have a positive and significant relationship on the service and manufacturing sector but with no …

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Temperature And Economic Activity: Evidence From India, Anuska Jain, Róisín O'Sullivan, Vis Taraz Feb 2020

Temperature And Economic Activity: Evidence From India, Anuska Jain, Róisín O'Sullivan, Vis Taraz

Economics: Faculty Publications

This paper investigates the impact of temperature on economic activity in India, using state-level data from 1980–2015. We estimate that a 1 ◦C increase in contemporaneous temperature (relative to our sample mean) reduces the economic growth rate that year by 2.5 percentage points. The adverse impact of higher temperatures is more severe in poorer states and in the primary sector. Our analysis of lagged temperatures suggests that our effects are driven by the contemporaneous effect of temperature on output; we do not find evidence of a permanent impact of contemporaneous temperatures on future growth rates.

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Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin Dec 2019

Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin

Research Collection School Of Economics

We propose a heterogeneous time-varying panel data model with a latent group structure that allows the coefficients to vary over both individuals and time. We assume that the coefficients change smoothly over time and form different unobserved groups. When treated as smooth functions of time, the individual functional coefficients are heterogeneous across groups but homogeneous within a group. We propose a penalized-sieve-estimation-based classifier-Lasso (C-Lasso) procedure to identify the individuals’ membership and to estimate the group-specific functional coefficients in a single step. The classification exhibits the desirable property of uniform consistency. The C-Lasso estimators and their post-Lasso versions achieve the oracle …

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Quantile Treatment Effects In Difference In Differences Models With Panel Data, Brantly Callaway, Tong Li Nov 2019

Quantile Treatment Effects In Difference In Differences Models With Panel Data, Brantly Callaway, Tong Li

Faculty and Student Publications

Copyright © 2019 The Authors. This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT). Identification of the QTT is more complicated than the ATT though because it depends on the unknown dependence (or copula) between the change in untreated potential outcomes and the initial level of untreated potential outcomes for the treated group. To address this issue, we introduce a new Copula Stability Assumption that says that the …

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'Follow The Data' — What Data Says About Real-World Behavior In Commons Problems, Caleb M. Koch, Heinrich H. Nax Nov 2019

'Follow The Data' — What Data Says About Real-World Behavior In Commons Problems, Caleb M. Koch, Heinrich H. Nax

Cowles Foundation Discussion Papers

We test the game-theoretic foundations of common-pool resources using an individual-level dataset of groundwater usage that accounts for 3% of US irrigated agriculture. Using necessary and sufficient revealed preference tests for dynamic games, we find: (i) a rejection of the standard game-theoretic arguments based on strategic substitutes, and instead (ii) support for models building on reciprocity-like behavior and strategic complements. By estimating strategic interactions directly, we find that reciprocity-like interactions drive behavior more than market and climate trends. Taken together, we take a step toward developing more realistic models to understand groundwater usage, and related issues pertaining to tragedy of …

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A Time-Varying True Individual Effects Model With Endogenous Regressors, Levent Kutlu, Kien C. Tran, Mike G. Tsionas Aug 2019

A Time-Varying True Individual Effects Model With Endogenous Regressors, Levent Kutlu, Kien C. Tran, Mike G. Tsionas

Economics and Finance Faculty Publications and Presentations

We propose a fairly general individual effects stochastic frontier model, which allows both heterogeneity and inefficiency to change over time. Moreover, our model handles the endogeneity problems if either at least one of the regressors or one-sided error term is correlated with the two-sided error term. Our Monte Carlo experiments show that our estimator performs well. We employed our methodology to the US banking data and found a negative relationship between return on revenue and cost efficiency. Estimators ignoring time-varying heterogeneity or endogeneity did not perform well and gave very different estimates compared to our estimator.

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Functional Coefficient Panel Modeling With Communal Smoothing Covariates, Peter C.B. Phillips, Ying Wang May 2019

Functional Coefficient Panel Modeling With Communal Smoothing Covariates, Peter C.B. Phillips, Ying Wang

Cowles Foundation Discussion Papers

Behavior at the individual level in panels or at the station level in spatial models is often influenced by aspects of the system in aggregate. In particular, the nature of the interaction between individual-specific explanatory variables and an individual dependent variable may be affected by `global’ variables that are relevant in decision making and shared communally by all individuals in the sample. To capture such behavioral features, we employ a functional coefficient panel model in which certain communal covariates may jointly influence panel interactions by means of their impact on the model coefficients. Two classes of estimation procedures are proposed, …

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Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin Apr 2019

Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin

Research Collection School Of Economics

We propose a heterogeneous time-varying panel data model with a latent group structure that allows the coefficients to vary over both individuals and time. We assume that the coefficients change smoothly over time and form different unobserved groups. When treated as smooth functions of time, the individual functional coefficients are heterogeneous across groups but homogeneous within a group. We propose a penalized-sieve-estimation-based classifier-Lasso (C-Lasso) procedure to identify the individuals’ membership and to estimate the group-specific functional coefficients in a single step. The classification exhibits the desirable property of uniform consistency. The C-Lasso estimators and their post-Lasso versions achieve the oracle …

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Currency Unions And Trade: A Ppml Re-Assessment With High-Dimensional Fixed Effects, Mario Larch, Joschka Wanner, Yoto V. Yotov, Thomas Zylkin Jan 2019

Currency Unions And Trade: A Ppml Re-Assessment With High-Dimensional Fixed Effects, Mario Larch, Joschka Wanner, Yoto V. Yotov, Thomas Zylkin

Economics Faculty Publications

Recent work on the effects of currency unions (CUs) on trade stresses the importance of using many countries and years in order to obtain reliable estimates. However, for large samples, computational issues associated with the three-way (exporter-time, importer-time, and country-pair) fixed effects currently recommended in the gravity literature have heretofore limited the choice of estimator, leaving an important methodological gap. To address this gap, we introduce an iterative Poisson Pseudo-Maximum Likelihood (PPML) estimation procedure that facilitates the inclusion of these fixed effects for large data sets and also allows for correlated errors across countries and time. When applied to a …

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Monthly Spending Dynamics Of The Elderly Following A Health Shock: Evidence From Singapore, Terence C. Cheng, Jing Li, Rhema Vaithianathan Jan 2019

Monthly Spending Dynamics Of The Elderly Following A Health Shock: Evidence From Singapore, Terence C. Cheng, Jing Li, Rhema Vaithianathan

Research Collection School Of Economics

We use novel longitudinal data from 19 monthly waves of the Singapore Life Panel to examine the short-term dynamics of the effects health shocks have on household health and non-health spending and income by the elderly. The health shocks we study are the occurrence of new major conditions such as cancer, heart problems, and minor conditions (e.g. diabetes, and hypertension). Our empirical strategy exploits unanticipated changes in health status through the diagnosis of new health conditions, combined with an individual fixed effect framework. We find that major shocks have large and persistent effects while minor shocks have small and mainly …

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The Impact Of Foreign Remittances On Poverty In Nepal: A Panel Study Of Household Survey Data, 1996-2011, Udaya R. Wagle, Satis Devkota Oct 2018

The Impact Of Foreign Remittances On Poverty In Nepal: A Panel Study Of Household Survey Data, 1996-2011, Udaya R. Wagle, Satis Devkota

Economics & Management Publications

Using data from the longitudinal panel surveys of 1996, 2004, and 2011, this paper examines the dynamics of foreign remittances and their impact on poverty in Nepal. The intent is to explore how foreign remittances have evolved and impacted poverty and economic well-being of households. Focusing on a consistent set of households across the three survey rounds in a balanced panel format helps examine the effect of foreign remittances with appropriate controls. Results from methodologically consistent, random-effects regressions that correct for potential attrition and heterogeneity bias support significant poverty-reducing and, more accurately, economic well-being-enhancing effects of foreign remittances especially when …

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Convergence In Income Inequality: Further Evidence From The Club Clustering Methodology Across States In The U.S., Nicholas Apergis, Christina Christou, Rangan Gupta, Stephen M. Miller Mar 2018

Convergence In Income Inequality: Further Evidence From The Club Clustering Methodology Across States In The U.S., Nicholas Apergis, Christina Christou, Rangan Gupta, Stephen M. Miller

Economics Faculty Publications

This paper contributes to the sparse literature on inequality convergence by empirically testing convergence across states in the U.S. This sample period encompasses a series of different periods that the existing literature discusses -- the Great Depression (1929–1944), the Great Compression (1945–1979), the Great Divergence (1980-present), the Great Moderation (1982–2007), and the Great Recession (2007–2009). This paper implements the relatively new method of panel convergence testing, recommended by Phillips and Sul (2007). This method examines the club convergence hypothesis, which argues that certain countries, states, sectors, or regions belong to a club that moves from disequilibrium positions to their club-specific …

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A Distribution-Free Stochastic Frontier Model With Endogenous Regressors, Levent Kutlu Feb 2018

A Distribution-Free Stochastic Frontier Model With Endogenous Regressors, Levent Kutlu

Economics and Finance Faculty Publications and Presentations

We provide a guideline for estimating a distribution-free panel data stochastic frontier model in the presence of endogenous variables. In particular, we consider variations of the within estimator of Cornwell et al. (1990) to allow endogenous regressors.

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Bank Net Interest Margins, The Yield Curve, And The 2007–2009 Financial Crisis, Peter V. Egly, David W. Johnk, Andre V. Mollick Jan 2018

Bank Net Interest Margins, The Yield Curve, And The 2007–2009 Financial Crisis, Peter V. Egly, David W. Johnk, Andre V. Mollick

Economics and Finance Faculty Publications and Presentations

Using quarterly call report data from 2000 to 2016, we reexamine the relationship between net interest margins (NIM) and the yield curve for more than 5,500 U.S. commercial banks. In the full sample, yield curve and RGDP growth have positive effects on NIM, while inflation and deposit‐to‐loan ratios (D/L) have negative effects. Splitting the sample around the 2007–2009 crisis, we show the impact of yield curve and RGDP growth on NIM increasing during the “recovery” (2009Q3 to 2016Q4), and inflation and D/L changing signs. Positive effects of yield curve on profits vary with bank size and change over time.

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Endogeneity In Panel Stochastic Frontier Models: An Application To The Japanese Cotton Spinning Industry, Mustafa U. Karakaplan, Levent Kutlu Aug 2017

Endogeneity In Panel Stochastic Frontier Models: An Application To The Japanese Cotton Spinning Industry, Mustafa U. Karakaplan, Levent Kutlu

Economics and Finance Faculty Publications and Presentations

We present a panel stochastic frontier model that handles the endogeneity problem. This model can treat the endogeneity of both frontier and inefficiency variables. We apply our method to examine the technical efficiency of Japanese cotton spinning industry. Our results indicate that market concentration is endogenous, and when its endogeneity is properly handled, it has a larger negative impact on the technical efficiency of cotton spinning plants. We find that the exogenous model substantially overestimates efficiency in concentrated markets.

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Granger Causality And Structural Causality In Cross-Section And Panel Data, Xun Lu, Liangjun Su, Halbert White Apr 2017

Granger Causality And Structural Causality In Cross-Section And Panel Data, Xun Lu, Liangjun Su, Halbert White

Research Collection School Of Economics

Granger noncausality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger (G-) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well defined and identifiable, G-non-causality follows from structural noncausality, and with suitable conditions (e.g., separability or monotonicity), structural causality also implies G-causality. This justifies using tests of G-non-causality to test …

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Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su Dec 2016

Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su

Research Collection School Of Economics

In this article, we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furthermore, we estimate the regression coefficients through the post-LASSO method and establish the asymptotic distribution theory for the resulting estimators. The developed methodology and theory are applicable to …

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A Practical Test For Strict Exogeneity In Linear Panel Data Models With Fixed Effects, Liangjun Su, Yonghui Zhang, Jie Wei Oct 2016

A Practical Test For Strict Exogeneity In Linear Panel Data Models With Fixed Effects, Liangjun Su, Yonghui Zhang, Jie Wei

Research Collection School Of Economics

This paper provides a practical test for strict exogeneity in linear panel data models with fixed effects when the number of individuals N goes to infinity while the number of time periods T is fixed. The test is based on the supremum of a sequence of Wald test statistics. Under suitable conditions, we establish the asymptotic distribution of the test statistic and consistency of the test. A bootstrap procedure is proposed to improve the finite sample performance and the validity of the procedure is justified. We investigate the finite sample performance of the test via a small set of Monte …

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Us Airport Ownership, Efficiency, And Heterogeneity, Levent Kutlu, Patrick Mccarthy May 2016

Us Airport Ownership, Efficiency, And Heterogeneity, Levent Kutlu, Patrick Mccarthy

Economics and Finance Faculty Publications and Presentations

All US commercial airports are in the public sector yet not all have the same ownership type. For medium and large hub US airports we use stochastic frontier analysis to analyze the efficiency differences for alternative airport ownership types. We find that while form of ownership may matter for cost efficiency, in general its effect is relatively small. Yet type of public sector ownership does have cost efficiency implications in certain environments. Further, when heterogeneity is not controlled, the results change substantially so that type of ownership matters much more which demonstrates the importance of controlling for cross section heterogeneity.

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Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su Mar 2016

Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su

Research Collection School Of Economics

In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused Lasso. We consider two approaches—penalized least squares (PLS) for first-differenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one, both methods can correctly determine the unknown number of breaks and estimate the common break dates consistently. We establish the asymptotic distributions of the Lasso estimators of the regression coefficients and their post Lasso versions. We also propose and validate a data-driven method to determine the tuning parameter used in …

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Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshino Mar 2016

Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshino

Research Collection School Of Economics

In this paper we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We estimate the functional coefficients by the sieve-IVQR technique and establish the uniform consistency and asymptotic normality of the estimators. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients and study its asymptotic. We conduct simulations to evaluate the finite sample behavior of our estimator and test statistic, and apply our method to study the estimation of quantile Engel curves.

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Granger Causality And Structural Causality In Cross-Section And Panel Data, Xun Lu, Liangjun Su, Halbert White Feb 2016

Granger Causality And Structural Causality In Cross-Section And Panel Data, Xun Lu, Liangjun Su, Halbert White

Research Collection School Of Economics

Granger non-causality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger (G-) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well defined and identifiable, G- non-causality follows from structural non-causality, and with suitable conditions (e.g., separability or monotonicity), structural causality also implies G-causality. This justifies using tests of G- non-causality …

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Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su Nov 2015

Panel Data Models With Interactive Fixed Effects And Multiple Structural Breaks, Degui Li, Junhui Qian, Liangjun Su

Research Collection School Of Economics

In this paper we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furthermore, we estimate the regression coefficients through the post-LASSO method and establish the asymptotic distribution theory for the resulting estimators. The developed methodology and theory are applicable to …

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Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin Apr 2015

Sieve Estimation Of Time-Varying Panel Data Models With Latent Structures, Liangjun Su, Xia Wang, Sainan Jin

Research Collection School Of Economics

We consider the problem of determining the number of factors and selecting the proper regressors in linear dynamic panel data models with interactive fixed effects. Based on the preliminary estimates of the slope parameters and factors a la Bai and Ng (2009) and Moon andWeidner (2014a), we propose a method for simultaneous selection of regressors and factors and estimation through the method of adaptive group Lasso (least absolute shrinkage and selection operator). We show that with probability approaching one, our method can correctly select all relevant regressors and factors and shrink the coefficients of irrelevant regressors and redundant factors to …

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Fertility And Rural Electrification In Bangladesh, Tomoki Fujii, Abu S. Shonchoy Mar 2015

Fertility And Rural Electrification In Bangladesh, Tomoki Fujii, Abu S. Shonchoy

Research Collection School Of Economics

We use a panel dataset from Bangladesh to examine the relationship between fertility and the adoption of electricity with the latter instrumented by infrastructure development and the quality of service delivery. We find that the adoption of electricity reduces fertility, and this impact is more pronounced when the household already has two or more children. This observation can be explained by a simple household model of time use, in which adoption of electricity affects only the optimal number of children but not necessarily current fertility behavior if the optimal number has not yet been reached.

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Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshina Feb 2015

Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshina

Research Collection School Of Economics

In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis functions and estimate them by the IVQR technique. We establish the uniform consistency and asymptotic normality of the estimators of the functional coefficients. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients, study its asymptotic properties under the null hypothesis, a sequence of local alternatives and global alternatives, and propose a wild-bootstrap procedure …

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Do Expected Marginal Revenue Products For National Hockey League Players Equal Their Price In Daily Fantasy Games?, Benjamin Goldman Jun 2014

Do Expected Marginal Revenue Products For National Hockey League Players Equal Their Price In Daily Fantasy Games?, Benjamin Goldman

Award Winning Economics Papers

The equality between wages and marginal revenue products is a backbone of competitive labor markets. This study will seek to test the congruity between the two in the market for players in daily fantasy hockey games. Any observed and statistically significant incongruity would lead to the conclusion that an individual can earn long run profit playing daily fantasy games. Both fixed effects and pooled regressions are employed to isolate inequalities between prices and expected marginal revenue products for players in daily fantasy hockey games. Any deviation of such could potentially be explained by utility maximizing gamblers or incomplete information. Robust …

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