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Estimated U.S. Manufacturing Production Capital and Technology Based on an Estimated Dynamic Structural Economic Model

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  • Baoline Chen

    ()
    (U.S. Bureau of Economic Analysis)

  • Peter A. Zadrozny

    ()
    (U.S. Bureau of Labor Statistics)

Abstract

Production capital and total factor productivity or technology are fundamental to understanding output and productivity growth, but are unobserved except at disaggregated levels and must be estimated before being used in empirical analysis. In this paper, we develop estimates of production capital and technology for U.S. total manufacturing based on an estimated dynamic structural economic model. First, using annual U.S. total manufacturing data for 1947-1997, we estimate by maximum likelihood a dynamic structural economic model of a representative production firm. In the estimation, capital and technology are completely unobserved or latent variables. Then, we apply the Kalman filter to the estimated model and the data to compute estimates of model-based capital and technology for the sample. Finally, we describe and evaluate similarities and differences between the model-based and standard estimates of capital and technology reported by the Bureau of Labor Statistics.

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Bibliographic Info

Paper provided by U.S. Bureau of Labor Statistics in its series Working Papers with number 429.

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Length: 43 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:bls:wpaper:ec090070

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Keywords: Kalman filter estimation of latent variables;

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