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Farmers' Exit Decisions and Early Retirement Programs in Finland

  • Pietola, Kyosti
  • Vare, Minna
  • Oude Lansink, Alfons G.J.M.

This paper estimates farmer decisions between three discrete occupational choices: exit and close down the farming operation (1), exit and transfer the farm to a new entrant (2), or continue farming and retain the option to exit later on (3). The farmer optimisation problem is formulated as a recursive optimal stopping problem. The unknown parameters are first estimated by a switching-type, reduced form Probit models and, then by the Simulated maximum likelihood (SML) method, controlling for serial correlation in the errors. Serial correlation in the errors is controlled for by the Geweke-Hajivassiliou-Keane (GHK) simulation technique. The results suggest that the timing and the type of farmer exit decisions respond elastically to farmer characteristics, farm characteristics, and economic environment. Early retirement programs and the level of farmer retirement benefits are predicted to play a key role in steering structural development and enhancing family farms in the Nordic agricultural sectors.

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File URL: http://purl.umn.edu/24825
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Paper provided by European Association of Agricultural Economists in its series 2002 International Congress, August 28-31, 2002, Zaragoza, Spain with number 24825.

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Date of creation: 2002
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Handle: RePEc:ags:eaae02:24825
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  1. Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
  2. Bill Provencher, 1997. "Structural Versus Reduced-Form Estimation of Optimal Stopping Problems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 357-368.
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  6. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-72, November.
  7. Robin L. Lumsdaine & James H. Stock & David A. Wise, 1990. "Three Models of Retirement: Computational Complexity Versus Predictive Validity," NBER Working Papers 3558, National Bureau of Economic Research, Inc.
  8. Ariel Pakes, 1984. "Patents as Options: Some Estimates of the Value of Holding European Patent Stocks," NBER Working Papers 1340, National Bureau of Economic Research, Inc.
  9. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
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  11. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
  12. David Zilberman & Doug Parker, 1996. "Explaining Irrigation Technology Choices: A Microparameter Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(4), pages 1064-1072.
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