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Functional Form Model Specification: An Application to Hedonic Pricing

Published online by Cambridge University Press:  15 September 2016

Jeff E. Brown  and
Don E. Ethridge
Jeff E. Brown
Affiliation:
Department of Agricultural Economics, Texas Tech University
Don E. Ethridge
Affiliation:
Department of Agricultural Economics, Texas Tech University
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Abstract

A combination of conceptual analysis and empirical analysis—partial regression and residuals analysis—was used to derive an appropriate functional form hedonic price model. These procedures are illustrated in the derivation of a functional form hedonic model for an automated, econometric daily cotton price reporting system for the Texas-Oklahoma cotton market. Following conceptualization to deduce the general shapes of relationships, the appropriate specific functional form was found by testing particular attribute transformations identified from partial regression analysis. Minimizing structural errors across attribute levels and estimation accuracy were used in determining when an appropriate functional form for both implicit and explicit prices was found.

Type
Articles
Information
Agricultural and Resource Economics Review , Volume 24 , Issue 2 , October 1995 , pp. 166 - 173
Copyright
Copyright © 1995 Northeastern Agricultural and Resource Economics Association 

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References

Belsley, D.A., Kuh, E., and Welsch, R.E. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity New York: John Wiley and Sons, Inc, 1980.CrossRefGoogle Scholar
Bowman, K.R. “A Multi-Stage Hedonic Market Model of Cotton Characteristics With Separable Supply and Demand.” Unpublished Ph.D. Dissertation, Texas Tech University, 1989.Google Scholar
Bowman, K.R., and Ethridge, D.E. “Characteristic Supplies and Demands in a Hedonic Framework: U.S. Market for Cotton Fiber Attributes.” American Journal of Agricultural Economics 74 (1992): 991–1002.Google Scholar
Brown, J.E. “The Optimal Hedonic Model Structure for Daily Cotton Market Price Reporting.” M.S. thesis, Texas Tech University, 1993.Google Scholar
Burgess, J.F. Jr., and Harmon, O.R. “Specification Tests in Hedonic Models.” Journal of Real Estate Finance and Economics 4(Dec. 1991): 375.CrossRefGoogle Scholar
Can, A. “Specification and Estimation of Hedonic Housing Price Models.” Regional Science and Urban Economics 22(Sept. 1992): 453.Google Scholar
Carrasco-Tauber, C., and Moffitt, L.J. “Damage Control Econometrics: Functional Specification and Pesticide Productivity.” American Journal of Agricultural Economics 74(Feb. 1992): 158–62.Google Scholar
Davidson, R., and MacKinnon, J.G. “Convenient Specification Tests for Logit and Probit Models.” Journal of Economics 25(July 1984): 241–62.Google Scholar
Ethridge, D.E. and Davis, B. “Hedonic Price Estimation for Commodities: An Application to Cotton.” Western Journal of Agricultural Economics 7 (1982): 156–63.Google Scholar
Ethridge, D.E., Engels, C., and Brown, J.E. “An Econometric Approach for Estimating Daily Market Prices.” 1992 Belt-wide Cotton Conference Proceedings, Cotton Economics and Marketing Conference, National Cotton Council: 190–4.Google Scholar
Ethridge, D.E. and Mathews, K.H. “Reliability of Spot Cotton Quotations for Price Discovery in the West Texas Cotton Market.” Agricultural Economics Dept., Texas Tech University College of Agr. Sciences Pub No. T-1-212. Aug. 1983.Google Scholar
Ethridge, D.E. and Neeper, J.T. “Producer Returns From Cotton Strength and Uniformity: An Hedonic Price Approach.” Southern Journal of Agricultural Economics 19 (1987): 91–7.Google Scholar
Ethridge, D.E., Shaw, D.L., and Ross, J.E. “An Evaluation of the Impact of Instrument Test Line Values on Cotton Marketing and Use: Progress Report.” CED Working Paper, Economic Research Service, USDA, Aug. 1977.Google Scholar
Godfrey, L.G. Misspecification Tests in Econometics: The Lagrange Multiplier Principle and Other Approaches. Cambridge: Cambridge University Press, 1988.Google Scholar
Hembree, J.F., Ethridge, D.E., and Neeper, J.T. “Market Values of Fiber Properties in Southeastern Textile Mills.” Textile Research Journal 56(Feb. 1986): 140–41.Google Scholar
Hudson, D., Ethridge, D., and Brown, J. “Producer Prices in Cotton Markets: Evaluation of Reported Price Information Accuracy.” Agribusiness: An International Journal (in press).Google Scholar
Kang, H.B., and Reichert, A.K. “An Evaluation of Alternative Estimation Techniques and Functional Forms in Developing Statistical Appraisal Models.” Journal of Real Estate Resources 87(Fall 1987): 1.Google Scholar
Lichtenberg, E. and Zilberman, D. “The Econometrics of Damage Control: Why Specification Matters.” American Journal of Agricultural Economics 68 (1986): 261–73.Google Scholar
Mosteller, F. and Tukey, J.W. Data Analysis and Regression Reading, Mass: Addison-Wesley, 1977.Google Scholar
Neter, J.A., Wasserman, W., and Kutner, M.H. Applied Linear Regression Models. 2nd ed. Homewood, IL.: Richard D. Irwin, Inc., 1989.Google Scholar
Ozuna, T. Jr., Jang, K.Y., and Stoll, J.R. “Testing for Misspecification in the Referendum Contingent Valuation Approach.” American Journal of Agricultural Economics 75(May 1993): 332–8.Google Scholar
Pace, R.K., and Gilley, O.W. “Estimation Employing A Priori Information Within Mass Appraisal and Hedonic Pricing Models.” Journal of Real Estate Finance and Economics 3(Mar. 1990): 55.CrossRefGoogle Scholar
U.S. Department of Agriculture, “Daily Spot Cotton Quotations.” Market News Branch, Cotton Division, Agricultural Marketing Service, Memphis, TN. Daily issues.Google Scholar
Yatchew, A. and Griliches, Z. “Specification Errors in Probit Models.” Review of Economics and Statistics 67(Feb. 1985): 134–9.Google Scholar