Browsing by Author "Collard-Wexler, A"

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    (Mis)Allocation, Market Power, and Global Oil Extraction
    (American Economic Review, 2019-04-01) Asker, J; Collard-Wexler, A; De Loecker, J
    © 2019 American Economic Association. All Rights Reserved. We propose an approach to measuring the misallocation of production in a market that compares actual industry cost curves to undistorted (counterfactual) supply curves. As compared to traditional, TFPR- based, misallocation measures, this approach leverages cost data, such that results are readily mapped to welfare metrics. As an application, we analyze global crude oil extraction and quantify the extent of misallocation therein, together with the proportion attributable to market power. From 1970 to 2014, we find substantial misallocation, in the order of US$744 billion, 14.1 percent to 21.9 percent of which is attributable to market power.
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    “Nash-in-Nash” Bargaining: A Microfoundation for Applied Work
    (2019-02-01) Collard-Wexler, A; Gowrisankaran, G; Lee, RS
    © 2019 by The University of Chicago. All rights reserved. A “Nash equilibrium in Nash bargains” has become a workhorse bargaining model in applied analyses of bilateral oligopoly. This paper proposes a noncooperative foundation for “Nash-in-Nash” bargaining that extends Rubinstein’s alternating offers model to multiple upstream and downstream firms. We provide conditions on firms’ marginal contributions under which there exists, for sufficiently short time between offers, an equilibrium with agreement among all firms at prices arbitrarily close to Nash-in-Nash prices, that is, each pair’s Nash bargaining solution given agreement by all other pairs. Conditioning on equilibria without delayed agreement, limiting prices are unique. Unconditionally, they are unique under stronger assumptions.
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    Production Function Estimation with Measurement Error in Inputs
    (2016-08-16) Collard-Wexler, A; Loecker, J
    Production functions are a central component in a variety of economic analyses. However, these production functions often first need to be estimated using data on individual production units. There is reason to believe that, more than any other input in the production process, there are severe errors in the recording of capital stock. Thus, when estimating production functions, we need to account for the ubiquity of measurement error in capital stock. This paper shows that commonly used estimation techniques in the productivity literature fail in the presence of plausible amounts of measurement error in capital. We propose an estimator that addresses this measurement error, while controlling for unobserved productivity shocks. Our main insight is that investment expenditures are informative about a producer’s capital stock, and we propose a hybrid IV-Control function approach that instruments capital with (lagged) investment, while relying on standard intermediate input demand equations to offset the simultaneity bias. We rely on a series of Monte Carlo simulations and find that standard approaches yield downward-biased capital coefficients, while our estimator does not. We apply our estimator to two standard datasets, the census of manufacturing firms in India and Slovenia, and find capital coefficients that are, on average, twice as large.