A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax

Ioannis Bournakis and Mike Tsionas

Oxford Bulletin of Economics and Statistics, 2024, vol. 86, issue 3, 641-671

Abstract: We develop a non‐parametric technique framework for estimating firm‐level Total Factor Productivity (TFP). Our paper has two major novelties: first, we propose a modelling of productivity with both firm‐idiosyncratic factors and aggregate shocks. Second, we apply the Bayesian Markov Chain Monte Carlo (MCMC) technique that offers a numerical integration of productivity outside the posterior overcoming the restrictive assumptions about the relationship between productivity and variable production inputs. We implement our methodology in a group of 4,286 manufacturing firms from France, Germany, Italy, and the UK (2001–14). The results show that: (i) aggregate shocks matter for firm TFP evolution. The global financial crisis of 2008 caused severe, albeit short, adverse effects on TFP; (ii) there is substantial heterogeneity across countries in the way firms react to changes in R&D and taxation. German and UK firms are more sensitive to fiscal changes than R&D, while the opposite is true for Italian firms. R&D and taxation effects are symmetrical for French firms; (iii) the UK productivity handicap continues for years after the financial crisis; and (iv) there are substantial knowledge spillovers among German and Italian firms.

Date: 2024
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https://doi.org/10.1111/obes.12594

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Working Paper: A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax (2023)
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