Untested assumptions and data slicing: a critical review of firm-level production function estimators
This paper surveys the most popular parametric and semi-parametric estimators for Cobb-Douglas production functions arising from the econometric literature of the past two decades. We focus on the different approaches dealing with 'transmission bias' in firm-level studies, which arises fro...
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| Format: | Working paper |
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University of Oxford
2010
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| _version_ | 1797052683217010688 |
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| author | Eberhardt, M Helmers, C |
| author_facet | Eberhardt, M Helmers, C |
| author_sort | Eberhardt, M |
| collection | OXFORD |
| description | This paper surveys the most popular parametric and semi-parametric estimators for Cobb-Douglas production functions arising from the econometric literature of the past two decades. We focus on the different approaches dealing with 'transmission bias' in firm-level studies, which arises from firms' reaction to unobservable productivity realisations when making input choices. The contribution of the paper is threefold: we provide applied economists with (i) an in-depth discussion of the estimation problem and the solutions suggested in the literature; (ii) a detailed empirical example using FAME data for UK high-tech firms, emphasising analytical tools to investigate data properties and the robustness of the empirical results; (iii) a powerful illustration of the impact of estimator choice on TFP estimates, using matched data on patents in 'TFP regressions'. Our discussion concludes that while from a theoretical point of view the different estimators are conceptually very similar, in practice, the choice of the preferred estimator is far from arbitrary and instead requires in-depth analysis of the data properties rather than blind belief in asymptotic consistency. |
| first_indexed | 2024-03-06T18:34:33Z |
| format | Working paper |
| id | oxford-uuid:0ac64b00-91f2-4b0c-b79a-ed50e5b2405c |
| institution | University of Oxford |
| last_indexed | 2024-03-06T18:34:33Z |
| publishDate | 2010 |
| publisher | University of Oxford |
| record_format | dspace |
| spelling | oxford-uuid:0ac64b00-91f2-4b0c-b79a-ed50e5b2405c2022-03-26T09:25:41ZUntested assumptions and data slicing: a critical review of firm-level production function estimatorsWorking paperhttp://purl.org/coar/resource_type/c_8042uuid:0ac64b00-91f2-4b0c-b79a-ed50e5b2405cBulk import via SwordSymplectic ElementsUniversity of Oxford2010Eberhardt, MHelmers, CThis paper surveys the most popular parametric and semi-parametric estimators for Cobb-Douglas production functions arising from the econometric literature of the past two decades. We focus on the different approaches dealing with 'transmission bias' in firm-level studies, which arises from firms' reaction to unobservable productivity realisations when making input choices. The contribution of the paper is threefold: we provide applied economists with (i) an in-depth discussion of the estimation problem and the solutions suggested in the literature; (ii) a detailed empirical example using FAME data for UK high-tech firms, emphasising analytical tools to investigate data properties and the robustness of the empirical results; (iii) a powerful illustration of the impact of estimator choice on TFP estimates, using matched data on patents in 'TFP regressions'. Our discussion concludes that while from a theoretical point of view the different estimators are conceptually very similar, in practice, the choice of the preferred estimator is far from arbitrary and instead requires in-depth analysis of the data properties rather than blind belief in asymptotic consistency. |
| spellingShingle | Eberhardt, M Helmers, C Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title | Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title_full | Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title_fullStr | Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title_full_unstemmed | Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title_short | Untested assumptions and data slicing: a critical review of firm-level production function estimators |
| title_sort | untested assumptions and data slicing a critical review of firm level production function estimators |
| work_keys_str_mv | AT eberhardtm untestedassumptionsanddataslicingacriticalreviewoffirmlevelproductionfunctionestimators AT helmersc untestedassumptionsanddataslicingacriticalreviewoffirmlevelproductionfunctionestimators |