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The Dynamics of Productivity in the Telecommunications Equipment Industry

G. Steven Olley, +1 more
- 01 Nov 1996 - 
- Vol. 64, Iss: 6, pp 1263-1297
TLDR
In this paper, an empirical focus is on estimating the parameters of a production function for the equipment industry, and then using those estimates to analyze the evolution of plant-level productivity.
Abstract
Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. Our empirical focus is on estimating the parameters of a production function for the equipment industry, and then using those estimates to analyze the evolution of plant-level productivity. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Firms' choices on whether to liquidate, and on input quantities should they continue, depended on their productivity. This generates a selection and a simultaneity problem when estimating production functions. Our theoretical focus is on providing an estimation algorithm which takes explicit account of these issues. We find that our algorithm produces markedly different and more plausible estimates of production function coefficients than do traditional estimation procedures. Using our estimates we find increases in the rate of aggregate productivity growth after deregulation. Since we have plant-level data we can introduce indices which delve deeper into how this productivity growth occurred. These indices indicate that productivity increases were primarily a result of a reallocation of capital towards more productive establishments.

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Management practices across firms and nations

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References
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Paul R. Rosenbaum, +1 more
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TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
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Markov-Perfect Industry Dynamics: A Framework for Empirical Work

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Root-n-consistent semiparametric regression

Peter M. Robinson
- 01 Jul 1988 - 
TL;DR: In this article, a variable aleatoire (X,Z) dans #7B-R P ×#7b-R q is considered, and an estimateur generalisant l'estimateur des moindres carres ordinaires en inserant des estimateurs non parametriques de la regression dans la projection orthogonale non lineaire sur Z is constructed.
Journal ArticleDOI

Shadow prices, market wages, and labor supply

James J. Heckman
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