Quantitative Economics May 2021, Volume 12, Issue 2 is now online
Quantitative Economics
TABLE OF CONTENTS, May 2021, Volume 12, Issue 2
Full Issue
Articles
Abstracts follow the listing of articles.
Dealing with misspecification in structural macroeconometric models
Fabio Canova, Christian Matthes
Identification of counterfactuals in dynamic discrete choice models
Myrto Kalouptsidi, Paul T. Scott, Eduardo Souza‐Rodrigues
Linear regression with many controls of limited explanatory power
Chenchuan (Mark) Li, Ulrich K. Müller
Decentralization estimators for instrumental variable quantile regression models
Hiroaki Kaido, Kaspar Wüthrich
Making summer matter: The impact of youth employment on academic performance
Amy Ellen Schwartz, Jacob Leos‐Urbel, Joel McMurry, Matthew Wiswall
Where did it go wrong? Marriage and divorce in Malawi
Laurens Cherchye, Bram De Rock, Frederic Vermeulen, Selma Walther
From dual to unified employment protection: Transition and steady state
Juan J. Dolado, Etienne Lalé, Nawid Siassi
Uncertainty‐driven business cycles: Assessing the markup channel
Benjamin Born, Johannes Pfeifer
Is idiosyncratic risk conditionally priced?
Rajnish Mehra, Sunil Wahal, Daruo Xie
Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk
Torben G. Andersen, Martin Thyrsgaard, Viktor Todorov
Dealing with misspecification in structural macroeconometric models
Fabio Canova, Christian Matthes
Abstract
We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. In a Monte Carlo study, composite estimators dominate likelihood‐based estimators in mean squared error and composite models are superior to individual models in the Kullback–Leibler sense. We describe Bayesian quasi‐posterior computations and compare our approach to Bayesian model averaging, finite mixture, and robust control procedures. We robustify inference using the composite posterior distribution of the parameters and the pool of models. We provide estimates of the marginal propensity to consume and evaluate the role of technology shocks for output fluctuations.
Model misspecification composite likelihood Bayesian model averaging finite mixture C13 C51 E17
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Identification of counterfactuals in dynamic discrete choice models
Myrto Kalouptsidi, Paul T. Scott, Eduardo Souza‐Rodrigues
Abstract
Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non‐identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non‐additive changes in payoffs or changes to agents' choice sets. In doing so, we propose a general framework that allows the investigation of the identification of a broad class of counterfactuals (covering virtually any counterfactual encountered in applied work). To illustrate the results, we consider a firm entry/exit problem numerically, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and nonidentified counterfactuals of interest.
Identification dynamic discrete choice counterfactual welfare C14 C23 C25 C50 C61 L00 Q15
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Linear regression with many controls of limited explanatory power
Chenchuan (Mark) Li, Ulrich K. Müller
Abstract
We consider inference about a scalar coefficient in a linear regression model. One previously considered approach to dealing with many controls imposes sparsity, that is, it is assumed known that nearly all control coefficients are (very nearly) zero. We instead impose a bound on the quadratic mean of the controls' effect on the dependent variable, which also has an interpretation as an R2‐type bound on the explanatory power of the controls. We develop a simple inference procedure that exploits this additional information in general heteroskedastic models. We study its asymptotic efficiency properties and compare it to a sparsity‐based approach in a Monte Carlo study. The method is illustrated in three empirical applications.
High dimensional linear regression L2 bound invariance to linear reparameterizations C12 C21
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Decentralization estimators for instrumental variable quantile regression models
Hiroaki Kaido, Kaspar Wüthrich
Abstract
The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen (2005)) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of conventional quantile regression subproblems which are convex and can be solved efficiently. This reformulation leads to new identification results and to fast, easy to implement, and tuning‐free estimators that do not require the availability of high‐level “black box” optimization routines.
Instrumental variables quantile regression contraction mapping fixed‐point estimator bootstrap C21 C26
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Making summer matter: The impact of youth employment on academic performance
Amy Ellen Schwartz, Jacob Leos‐Urbel, Joel McMurry, Matthew Wiswall
Abstract
This paper examines New York City's Summer Youth Employment Program (SYEP). SYEP provides jobs to youth ages 14–24, and due to high demand for summer jobs, allocates slots through a random lottery system. We match student‐level data from the SYEP program with educational records from the NYC Department of Education and use the random lottery to estimate the effects of SYEP participation on a number of academic outcomes, including test taking and performance. We find that SYEP participation has positive impacts on student academic outcomes, and these effects are particularly large for students who participate in SYEP multiple times.
Summer employment youth employment I24 J13 J24
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Where did it go wrong? Marriage and divorce in Malawi
Laurens Cherchye, Bram De Rock, Frederic Vermeulen, Selma Walther
Abstract
Do individuals marry and divorce for economic reasons? Can we measure the economic attractiveness of a person's marriage market? We answer these questions using a structural model of consumer‐producer households that is applied to rich data from Malawi. Using revealed preference conditions for a stable marriage market, we define the economic attractiveness of a potential match as the difference between the potential value of consumption and leisure with the new partner and the value of consumption and leisure in the current marriage. We estimate this marital instability measure for every possible pair in geographically defined marriage markets in 2010. We find that the marital instability measure is predictive of future divorces, particularly for women. We further show that this estimated effect on divorce is mitigated by the woman's age, and by a lack of men, relative to women, in the marriage market, showing that these factors interact with the economic attractiveness of the remarriage market. These findings provide out‐of‐sample validation of our model and evidence that the economic value of the marriage market matters for divorce decisions.
Marriage market divorce Malawi agricultural production revealed preference D11 D12 D13 J12
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From dual to unified employment protection: Transition and steady state
Juan J. Dolado, Etienne Lalé, Nawid Siassi
Abstract
Three features of real‐life reforms of dual employment protection legislation (EPL) systems are particularly hard to study through the lens of standard labor‐market search models: (i) the excess job turnover implied by dual EPL, (ii) the nonretroactive nature of EPL reforms, and (iii) the transition dynamics from dual to a unified EPL system. In this paper, we develop a computationally tractable model addressing these issues. Our main finding is that the welfare gains of reforming a dual EPL system are sizeable and achieved mostly through a decrease in turnover at short job tenures. This conclusion continues to hold in more general settings featuring wage rigidities, heterogeneity in productivity upon matching, and human capital accumulation. We also find substantial cross‐sectional heterogeneity in welfare effects along the transition to a unified EPL scheme. Given that the model is calibrated to data from Spain, often considered as the epitome of a labor market with dual EPL, our results should provide guidance for a wide range of reforms of dual EPL systems.
Employment protection dualism labor market reform E24 J63 J65
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Uncertainty‐driven business cycles: Assessing the markup channel
Benjamin Born, Johannes Pfeifer
Abstract
Precautionary pricing and increasing markups in representative‐agent DSGE models with nominal rigidities are commonly used to generate negative output effects of uncertainty shocks. We assess whether this theoretical model channel is consistent with the data. Three things stand out. First, consistent with precautionary wage setting, we find that wage markups increase after uncertainty shocks. Second, the impulse responses of price markups are largely inconsistent with the standard model, both at the aggregate as well as the industry level. Finally, and in contrast to times‐series evidence, our theoretical model robustly predicts that uncertainty shocks have a quantitatively small impact on the economy.
Uncertainty shocks precautionary pricing markup channel price markup wage markup E01 E24 E32
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Is idiosyncratic risk conditionally priced?
Rajnish Mehra, Sunil Wahal, Daruo Xie
Abstract
In Merton (1987), idiosyncratic risk is priced in equilibrium as a consequence of incomplete diversification. We modify his model to allow the degree of diversification to vary with average idiosyncratic volatility. This simple recognition results in a state‐dependent idiosyncratic risk premium that is higher when average idiosyncratic volatility is low, and vice versa. The data appear to be consistent a positive state‐dependent premium for idiosyncratic risk both in the US and other developed markets.
Idiosyncratic risk factor models risk premium asset pricing G11 G12
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Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk
Torben G. Andersen, Martin Thyrsgaard, Viktor Todorov
Abstract
We study the temporal behavior of the cross‐sectional distribution of assets' market exposure, or betas, using a large panel of high‐frequency returns. The asymptotic setup has the sampling frequency of returns increasing to infinity, while the time span of the data remains fixed, and the cross‐sectional dimension of the panel is either fixed or increasing. We derive functional limit results for the cross‐sectional distribution of betas evolving over time. We demonstrate, for constituents of the S&P 500 market index, that the dispersion in betas is elevated at the market open and gradually declines over the trading day. This intraday pattern varies significantly over time and reacts to information shocks such as clustered earning announcements and releases of macroeconomic news. We find that earnings news increase beta dispersion while FOMC announcements have the opposite effect on market betas.
Asset pricing cross‐sectional dispersion functional convergence high‐frequency data intraday variation market beta nonparametric inference systematic risk C51 C52 G12
