A Sufficient Statistics Approach for Aggregating Firm-Level Experiments

92 Pages Posted: 12 Jan 2018 Last revised: 24 Apr 2019

See all articles by David Alexandre Sraer

David Alexandre Sraer

University of California, Berkeley; Princeton University

David Thesmar

Massachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA)

Multiple version iconThere are 3 versions of this paper

Date Written: April 22, 2019

Abstract

We consider a dynamic economy populated by heterogeneous firms subject to generic capital frictions: adjustment costs, taxes and financing constraints. A random subset of firms in this economy receives an empirical "treatment", which modifies the parameters governing these frictions. An econometrician observes the firm-level response to this treatment, and wishes to calculate how macroeconomic outcomes would change if all firms in the economy were treated. Our paper proposes a simple methodology to estimate this aggregate counterfactual using firm-level evidence only. Our approach takes general equilibrium effects into account, requires neither a structural estimation nor a precise knowledge on the exact nature of the experiment and can be implemented using simple moments of the distribution of revenue-to-capital ratios. We provide a set of sufficient conditions under which these formulas are valid and investigate the robustness of our approach to multiple variations in the aggregation framework.

Keywords: firm-level experriments; aggregation; misallocation; distorsions

JEL Classification: D24; O47

Suggested Citation

Sraer, David Alexandre and Thesmar, David, A Sufficient Statistics Approach for Aggregating Firm-Level Experiments (April 22, 2019). Available at SSRN: https://ssrn.com/abstract=3099007 or http://dx.doi.org/10.2139/ssrn.3099007

David Alexandre Sraer

University of California, Berkeley ( email )

310 Barrows Hall
Berkeley, CA 94720
United States

Princeton University ( email )

22 Chambers Street
Princeton, NJ 08544-0708
United States

David Thesmar (Contact Author)

Massachusetts Institute of Technology (MIT) - Economics, Finance, Accounting (EFA) ( email )

77 Massachusetts Avenue
Cambridge, MA 02139-4307
United States
16172259767 (Phone)

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