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Annual Review of Financial Economics

Volume 15, 2023

How to Use Microdata for Macro-Finance

Abstract

Financial frictions generate misallocation of resources across firms by restricting productive firms’ access to capital. This article reviews the literature that estimates the aggregate losses generated by such misallocation. The first approach relies on structural estimations: A model of firm dynamics with financial frictions is typically estimated and used to compare efficiency in the actual economy with a counterfactual with perfect financial markets. We argue that robustness is a central concern for this structural literature and discuss ways to analyze robustness in structural estimation (using well-identified moments and analyzing sensitivity to moments). The second approach relies on sufficient statistics, namely formulas that measure misallocation using simple empirical statistics and that are valid for a class of models. We discuss key contributions in that space, the generality of this approach, and the conditions under which it is valid. Sufficient statistic approaches are simpler and more robust, but they come at a cost: The range of counterfactual analyses that can be explored is more limited.

Keyword(s): aggregation, identification, JEL E10, JEL G10, JEL G30, microdata
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/content/journals/10.1146/annurev-financial-111021-103106
2023-11-01
2024-04-27
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/content/journals/10.1146/annurev-financial-111021-103106
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How to Use Microdata for Macro-Finance
Annual Review of Financial Economics 15, 387 (2023); https://doi.org/10.1146/annurev-financial-111021-103106
/content/journals/10.1146/annurev-financial-111021-103106
/content/journals/10.1146/annurev-financial-111021-103106
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