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Incorporation Of Nonnumeric Information Into The Estimation Of Economic Models: A New Approach For Dealing With Multicollinearity

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  • Parandvash, G. Hossein

Abstract

Results from Monte Carlo experiments indicate reduced squared error loss under most circumstances by a new nonnumeric information mixed estimator (NIME) compared to OLS and three leading ridge estimators in the presence of multicollinearity. There may also be some philosophical advantages of the NIME approach over ridge regression.

Suggested Citation

  • Parandvash, G. Hossein, 1988. "Incorporation Of Nonnumeric Information Into The Estimation Of Economic Models: A New Approach For Dealing With Multicollinearity," 1988 Annual Meeting, August 1-3, Knoxville, Tennessee 270201, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea88:270201
    DOI: 10.22004/ag.econ.270201
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    References listed on IDEAS

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    1. Ron C. Mittelhammer & Douglas L. Young & Damrongsak Tasanasanta & John T. Donnelly, 1980. "Mitigating the Effects of Multicollinearity Using Exact and Stochastic Restrictions: The Case of an Aggregate Agricultural Production Function in Thailand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(2), pages 199-210.
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