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

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Author Info
Baoline Chen () (U.S. Bureau of Economic Analysis)
Peter A. Zadrozny () (U.S. Bureau of Labor Statistics)

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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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Publisher 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
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Handle: RePEc:bls:wpaper:ec090070

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Related research
Keywords: Kalman filter estimation of latent variables;

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Find related papers by JEL classification:
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data
D24 - Microeconomics - - Production and Organizations - - - Production; Capital and Total Factor Productivity; Capacity
L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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This page was last updated on 2009-11-22.


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