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

Baoline Chen and Peter A. Zadrozny ()
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Peter A. Zadrozny: U.S. Bureau of Labor Statistics

No 429, Working Papers from 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.

Keywords: Kalman; filter; estimation; of; latent; variables (search for similar items in EconPapers)
JEL-codes: C50 C81 D24 L60 (search for similar items in EconPapers)
Date: 2009-09

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Journal Article: Estimated U.S. manufacturing production capital and technology based on an estimated dynamic structural economic model (2009)
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