Factores que inciden en la intención de salida de la actividad lechera en la región pampeana de Argentina

[EN] This article examines the factors which explain exit from dairy farming in the Pampas region of Argentina. A representative sample of dairy farms was used, of which 12 % indicated their intention to exit in the next five years. High technical efficiency and the existence of a successor reduce the likelihood of exit dairy farming; while age of farmer, hired labor, and climate risk exposure are positively associated with exit intentions. The small dairy farms are more prone to exit than large ones, albeit with a smaller marginal effect.[ES] Este artículo examina los factores que explican la salida de la producción lechera en la región pampeana de Argentina. Se utilizó una muestra representativa de unidades productivas, de las cuales el 12 % indicó su intención de salir en los próximos cinco años. La eficiencia técnica y la existencia de un sucesor reducen la probabilidad de salida, mientras que la edad del productor, la mano de obra contratada y la exposición al riesgo climático se asocian positivamente con la intención de salida. Las unidades productivas pequeñas son más propensas a salir que las grandes, aunque con un menor efecto marginal respecto de otras variables.Gastaldi, LB.; Galetto, AJ.; Pace Guerrero, IR. (2023). Factors affecting exit intentions from dairy farming in the Pampas region of Argentina. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 23(2):91-116. https://doi.org/10.7201/earn.2023.02.049111623

A Monte Carlo study of the effect of estimation risk on the optimal solutions of risk programming models

In mathematical risk programming models the decision maker is usually assumed to know the distribution of net returns (when other elements of the planning problem are deterministic). However, this assumption is only justified when the probability distribution of returns represents degrees of belief of the decision maker. When sample data obtained from historical information is used, the existence of estimation error must be recognized. This study at an assesses the importance of estimation error in risk programming through a repeated sampling experiment. Two population distributions were used, a multivariate normal and a combination of independently distributed lognormals. Samples of various sizes (5, 6, 7, 8, 9, 10, 15, 20, 50 and 99 years) were obtained and several risk programming models (QP, MOTAD, Target MOTAD and 5 versions of the Safety-First model) were run 100 times, using the above samples as inputs. The results indicate that the variability of solution vector is very high, particularly at the sample sizes most commonly used in applied work. Although the variance decreases as the sample size gets larger, the solution is still far from convergence, even with 99 years of data. These results hold for normal and non-normal populations as well

Factors affecting exit intentions from dairy farming in the Pampas region of Argentina.

[EN] This article examines the factors which explain exit from dairy farming in the Pampas region of Argentina. A representative sample of dairy farms was used, of which 12 % indicated their intention to exit in the next five years. High technical efficiency and the existence of a successor reduce the likelihood of exit dairy farming; while age of farmer, hired labor, and climate risk exposure are positively associated with exit intentions. The small dairy farms are more prone to exit than large ones, albeit with a smaller marginal effect. [ES] Este artículo examina los factores que explican la salida de la producción lechera en la región pampeana de Argentina. Se utilizó una muestra representativa de unidades productivas, de las cuales el 12 % indicó su intención de salir en los próximos cinco años. La eficiencia técnica y la existencia de un sucesor reducen la probabilidad de salida, mientras que la edad del productor, la mano de obra contratada y la exposición al riesgo climático se asocian positivamente con la intención de salida. Las unidades productivas pequeñas son más propensas a salir que las grandes, aunque con un menor efecto marginal respecto de otras variables