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Production Function Estimation without Invertibility: Imperfectly Competitive Environments and Demand Shocks

Ulrich Doraszelski, Lixiong Li

arXiv 16 Jun 2025 · Econometrics

arXiv:2506.13520 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We advance the proxy variable approach to production function estimation. We show that the invertibility assumption at its heart is testable. We characterize what goes wrong if invertibility fails and what can still be done. We show that rethinking how the estimation procedure is implemented either eliminates or mitigates the bias that arises if invertibility fails. In particular, a simple change to the first step of the estimation procedure provides a first-order bias correction for the GMM estimator in the second step. Furthermore, a modification of the moment condition in the second step ensures Neyman orthogonality and enhances efficiency and robustness by rendering the asymptotic distribution of the GMM estimator invariant to estimation noise from the first step.

Citation extraction

45
references
57
in-text mentions
45
distinct cited
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14,653
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Doraszelski \ Jaumandreu (2024) Reexamining the De Loecker & Warzynski (2012) method for estimating markups, Working paper, University of Pennsylvania, Philadel…0.8434475%
2Ackerberg, Caves \ Frazer (2015) `Identification properties of recent production function estimators', Econometrica 83(6), 2411–24510.64422100%
3Andrews, Gentzkow \ Shapiro (2017) `Measuring the sensitivity of parameter estimates to estimation moments', Quarterly Journal of Economics 132(4), 1553–15920.64422100%
4De Loecker \ Warzynski (2012) `Markups and firm-level export status', American Economic Review 102(6), 2437–24710.64422100%
5Neyman (1959) Optimal asymptotic tests of composite statistical hypotheses, in V. Grenander, ed., `Probability and Statistics', John Wiley & S…0.64422100%
6Brand (2020) Estimating productivity and markups under imperfect competition, Working paper, University of Texas, Austin0.51121100%
7Chernozhukov, Escanciano, Ichimura, Newey \ Robins (2022) `Locally robust semiparametric estimation', Econometrica 90(4), 1501–15350.51121100%
8Foster, Haltiwanger \ Syverson (2008) `Reallocation, firm turnover, and efficiency: Selection on productivity or profitability?', American Economic Review 98(1), 394–…0.51121100%
9Hu, Huang \ Sasaki (2020) `Estimating production functions with robustness against errors in the proxy variables', Journal of Econometrics 215(2), 375–3980.51121100%
10Ackerberg \ De Loecker (2024) Production function identification under imperfect competition, Working paper, University of Texas, Austin0.40511100%

Showing the top 10 of 45 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Automatic Debiased Machine Learning of Structural Parameters with General Conditional Moments0.64422
2Identification and Counterfactual Analysis in Incomplete Models with Support and Moment Restrictions0.40511
3Nonparametric Identification and Estimation of Production Functions Invariant to Productivity Dynamics0.40511