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A Latent Variable Model of Quality Determination

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  • Paul J. Gertler

Abstract

Despite substantial interest in the determination of quality, there has been little empirical work in the area. The problem, of course, is the general lack of data on quality. This paper overcomes the data problem by constructing a Multiple Indicator Multiple Cause (MIMIC) model of quality determination. We present a one-factor MIMIC model of quality which derives natural indicators out of the relationship between input demand and output determination. The indicators turn out to be input demands which have been filtered to remove variation due to all factors, except quality ana random disturbances. These indicators are measures of input investment in each unit of output or the volume (intensity) of service. The model is identified by defining input demand to be a function of quantity and "total effective output" (quantity times average quality), instead of quantity and average quality. The model is then applied to the determination of nursing home quality. The model appears to perform quite well, as the results generally conform with economic theory and restrictions implied by the MIMIC structure are accepted in hypothesis tests.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 1750.

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Date of creation: Oct 1985
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Publication status: published as Journal of Business and Economic Statistics, Vol. 6, pp.97-107, 1988.
Handle: RePEc:nbr:nberwo:1750

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  1. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
  2. Paul J. Gertler, 1985. "Subsidies, Quality, and Regulation in the Nursing Home Industry," NBER Working Papers 1691, National Bureau of Economic Research, Inc.
  3. Goldberger, Arthur S, 1972. "Structural Equation Methods in the Social Sciences," Econometrica, Econometric Society, Econometric Society, vol. 40(6), pages 979-1001, November.
  4. Goldberger, Arthur S, 1972. "Maximum-Likelihood Estimation of Regressions Containing Unobservable Independent Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(1), pages 1-15, February.
  5. Leffler, Keith B, 1982. "Ambiguous Changes in Product Quality," American Economic Review, American Economic Association, American Economic Association, vol. 72(5), pages 956-67, December.
  6. Aigner, Dennis J. & Hsiao, Cheng & Kapteyn, Arie & Wansbeek, Tom, 1984. "Latent variable models in econometrics," Handbook of Econometrics, Elsevier, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 23, pages 1321-1393 Elsevier.
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