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On The Measurement Of Total Factor Productivity: A Latent Variable Approach

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  • Fuentes, J. Rodrigo
  • Morales, Marco

Abstract

Despite the important role that total factor productivity (TFP) has played in the growth literature, few attempts have been made to change the methodology to estimate it. This paper proposes a methodology based on a state-space model to estimate TFP and its determinants. With this methodology, it is possible to reduce the measurement of our ignorance. As a by-product, this estimate yields the capital share in output and the long-term growth rate. When applied to Chile, the estimation shows a capital share around 0.5 and long-term growth of TFP around 1%. Capital accumulation tends to explain the growth rate in the fast growth periods under the econometric estimation more than the traditional growth accounting methodology.

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  • Fuentes, J. Rodrigo & Morales, Marco, 2011. "On The Measurement Of Total Factor Productivity: A Latent Variable Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 15(2), pages 145-159, April.
  • Handle: RePEc:cup:macdyn:v:15:y:2011:i:02:p:145-159_99
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    Cited by:

    1. Sturla Furunes Kvamsdal, 2019. "Indexing of Technical Change in Aggregated Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 901-920, March.
    2. Fakhri J. Hasanov & Elchin Suleymanov & Heyran Aliyeva & Hezi Eynalov & Sa'd Shannak, 2022. "What Drives the Agricultural Growth in Azerbaijan? Insights from Autometrics with Super Saturation," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 70(3), pages 147-174.
    3. Ayesha Ashraf & Dierk Herzer & Peter Nunnenkamp, 2016. "The Effects of Greenfield FDI and Cross-border M&As on Total Factor Productivity," The World Economy, Wiley Blackwell, vol. 39(11), pages 1728-1755, November.
    4. Michael Donadelli & Vahid Mojtahed & Antonio Paradiso, 2015. "Technological Progress, Investment Frictions and Business Cycle: New Insights from a Neoclassical Growth Model," Working Papers LuissLab 15119, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    5. Aroca, Patricio & Garrido, Nicolás, 2017. "Sectoral breakdown of total factor productivity in Chile, 1996-2010," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    6. Donadelli, M. & Paradiso, A. & Livieri, G., 2019. "Adding cycles into the neoclassical growth model," Economic Modelling, Elsevier, vol. 78(C), pages 162-171.
    7. Sturla Furunes Kvamsdal, 2016. "Technical Change as a Stochastic Trend in a Fisheries Model," Marine Resource Economics, University of Chicago Press, vol. 31(4), pages 403-419.
    8. Deng, Zhongqi & Song, Shunfeng & Jiang, Nan & Pang, Ruizhi, 2023. "Sustainable development in China? A nonparametric decomposition of economic growth," China Economic Review, Elsevier, vol. 81(C).
    9. Mohammad Zeqi Yasin, 2020. "Productivity: The Growth Accounting and The Stochastic Frontier Approach," Economics Bulletin, AccessEcon, vol. 40(4), pages 3020-3032.

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