@inproceedings{ad17add4b2b743099874c792bc0958b1,
title = "An econometric approach to general equilibrium modeling",
abstract = "The first objective of this chapter is to present a new approach to econometric modeling of producer behavior. Our key contribution is to represent the rate and biases of technical change by unobservable or latent variables. We also divide the rate of technical change between components that are induced by changes in prices and those that are autonomous and not affected by prices. In our dataset, production is disaggregated into 35 separate commodities produced by one or more of the 35 industries making up the US economy. Our second objective is to present a new econometric model of aggregate consumer behavior. The model allocates full wealth among time periods for households distinguished by demographic characteristics, and determines the within-period demands for leisure, consumer goods and services. An important feature of our approach is the development of a closed-form representation of aggregate demand and labor supply that accounts for the heterogeneity in household behavior that is observed in micro-level data. Our model of producer behavior is the supply side of general equilibrium models of the US. The aggregate demand functions are important components of the demand side. These general equilibrium models are used to analyze the consequences of a broad spectrum of public policies. These applications are discussed in more detail in Chapter 8 of this Handbook. The third objective of the chapter is to demonstrate an important benefit of the econometric approach to parameterization. The parameter covariances obtained in the course of estimation can be used to construct confidence intervals for endogenous variables in general equilibrium models. Confidence intervals characterize the precision of modeling results more rigorously and systematically than traditional sensitivity analysis.",
keywords = "Aggregate demand, Confidence intervals, Kalman filter, Labor supply, Latent variables, Outcome variables, Rate and bias of technical change",
author = "Jorgenson, {Dale W.} and Hui Jin and Slesnick, {Daniel T.} and Wilcoxen, {Peter J.}",
note = "Funding Information: We are indebted to Jon Samuels for help with the data employed in this chapter. We are indebted to Yu Shi for assistance with the formulation of estimators of the covariance matrices in Section 17.4 . We are also indebted to Mun S. Ho and James H. Stock for valuable suggestions. Finally, we are indebted to seminar participants at the Copenhagen Business School, the Department of Economics of Harvard University, and the Department of Economics of the University of Oslo, and participants in the Summer Meeting of the Korean Econometric Society and the Annual Meeting of the European Association of Resources and Environmental Economists for useful comments and suggestions. Financial support was provided by the Climate Economics Division of the U.S. Environmental Protection Agency. Publisher Copyright: {\textcopyright} 2013 Elsevier B.V. All Rights Reserved.",
year = "2013",
doi = "10.1016/B978-0-444-59568-3.00017-1",
language = "English (US)",
isbn = "9780444595683",
series = "Handbook of Computable General Equilibrium Modeling",
publisher = "Elsevier",
pages = "1133--1212",
editor = "Dixon, {Peter B.} and Jorgenson, {Dale W.}",
booktitle = "Handbook of Computable General Equilibrium Modeling SET, Vols. 1A and 1B, 2013",
address = "Netherlands",
}