Bayesian Estimation of Capital Stock and Depreciation in the Production Function Framework

Jakub Boratyński () and Jacek Osiewalski
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Jakub Boratyński: University of Łódź

Central European Journal of Economic Modelling and Econometrics, 2021, vol. 13, issue 4, 455-486

Abstract: We propose a Bayesian approach to estimating productive capital stocks and depreciation rates within the production function framework, using annual data on output, employment and investment only. Productive capital stock is a concept related to the input of capital services to production, in contrast to the more common net capital stock estimates, representing market value of fixed assets. We formulate a full Bayesian model and employ it in a series of illustrative empirical examples. We find that parameters of our model, from which the time-path of capital is derived, are weakly identified with the data at hand. Nevertheless, estimation is feasible with the use of prior information on the production function parameters and the characteristics of productivity growth. We show how precision of the estimates can be improved by augmenting the model with an equation for the rate of return.

Keywords: productive capital stock; depreciation rate; aggregate production function; Bayesian analysis (search for similar items in EconPapers)
JEL-codes: C51 D24 E01 E22 E23 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:13:y:2021:i:4:p:455-486

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