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Advances in Micro-Econometrics

Paper Session

Friday, Jan. 4, 2019 10:15 AM - 12:15 PM

Atlanta Marriott Marquis, M302
Hosted By: International Association of Applied Econometrics
  • Chair: Edward Vytlacil, Yale University

An Instrumental Variable Approach to Dynamic Models

Steven Berry
,
Yale University
Giovanni Compiani
,
Yale University

Abstract

We present a new class of methods for the identification and estimation of dynamic models with serially correlated unobservables, which typically imply that state variables are econometrically endogenous. In the context of Industrial Organization, these state variables often reflect econometrically endogenous market structure. We propose the use of Generalized Instrumental Variables methods to identify those dynamic policy functions that are consistent with instrumental variable restrictions on unobserved states. Extending popular ``two-step'' methods, these policy functions then identify the structural parameters of the dynamic model. We provide simulated examples as well as an illustrative empirical analysis.

Nonlinear Persistence and Partial Insurance: Innovations in the Panel Data Dynamics of Income and Consumption

Richard Blundell
,
University College London
Manuel Arellano
,
CEMFI
Stephane Bonhomme
,
University of Chicago

Abstract

The aim of this work is to examine the partial insurance approach to linking consumption and income dynamics. The leading applications we consider are to Norwegian population register data and the new PSID consumption and assets data. We develop a new framework to shed new light on the nonlinear transmission of income shocks to consumption and the nature of insurance to income shocks. This involves a Markovian permanent-transitory model of household income, which reveals asymmetric persistence of unusual shocks in the PSID and in large administrative registers. We develop a flexible age-dependent nonlinear consumption rule that is a function of assets, permanent income and transitory income. We provide conditions for nonparametric identification and explain how a simulation-based sequential QR method is feasible. This new framework is shown to lead to improved measures of the degree of partial insurance and the link between different measures of income and consumption inequality.

Identification of Causal Effects with Multiple Instruments: Problems and Some Solutions

Magne Mogstad
,
University of Chicago
Alexander Torgovitsky
,
University of Chicago
Christopher Walters
,
University of California-Berkeley

Abstract

Empirical researchers often combine multiple instruments for a single treatment using two stage least squares (2SLS). When treatment effects are heterogeneous, a common justification for combining instruments is that the 2SLS estimand can still be interpreted as a positively-weighted average of local average treatment effects (LATEs). This justification requires the well-known monotonicity condition. However, we show that with more than one instrument, the monotonicity condition is only satisfied if the rates of substitution between distinct instruments are the same for all individuals. Based on this finding, we consider the use of multiple instruments under a weaker, marginal monotonicity condition, which does not require choice behavior to be homogenous. First, we show that the 2SLS estimand can still be a positively-weighted average of LATEs. We characterize a simple sufficient and necessary condition that empirical researchers can check to ensure positive weights. Second, we develop a general method for using multiple instruments to identify a wide range of causal parameters other than LATEs. The method allows researchers to combine multiple instruments to obtain more informative empirical conclusions than one would obtain by using each instrument separately.

Optimal Contracting and Spatial Competition among Financial Service Providers

Robert Townsend
,
Massachusetts Institute of Technology
Gustavo Joaquim
,
Massachusetts Institute of Technology
Victor Zhorin
,
University of Chicago

Abstract


We present a contract-based model of industrial organization for markets characterized by information and other frictions (Moral Hazard, Adverse Selection, Limited Commitment etc.) and different market structures (Monopoly, Oligopoly, Competition), the latter driven by spatial costs, logit errors, and number of financial service providers. We show this method can be applied to understand and quantify the impact of spatial and technological changes in the banking sector in emerging market countries. We derive a likelihood estimator for the structural parameters that determine contracting frictions and market structure, but also establish methods, depending on counterfactuals of interest, that do not need to specify both. We illustrate our framework using simulated data, illustrating competition of local, relationship based banks versus less-informed national banks with a spatial cost advantage. Using real data from banks and entrepreneurs in the Townsend Thai Data, our results indicate that reducing spatial costs by 50% is equivalent to increasing consumption by 4.85%, which we compare to other policies. Our larger goal is to develop an operational, broadly applicable toolkit for empirical work.
JEL Classifications
  • C1 - Econometric and Statistical Methods and Methodology: General
  • C4 - Econometric and Statistical Methods: Special Topics