The Successor effect and the Generational Integration Process: key aspects of the family farm succession
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Abstract
This study examines the successor effect and the Generational Integration Process (GIP) in order to generate relevant information on the way to better understand succession process in agriculture. The study was carried out on horticultural family farms in Zarcero, Costa Rica. 126 interviews were conducted between January and May 2019. In order to quantify the successor effect, three farm profiles were generated according to the probability of succession (low, medium and high). Likewise, it was quantified the behavior of the last five years farm`s production (decreased, equal, increased). Through a chi square test it was determine the linkage of the behavior of the production of the farms with the probability of succession. On the other hand, the GIP was quantified using six key actions which were identified amongst the literature. Two Ordinary Least Squares (OLS) models were conducted in which socioeconomic and psychological variables were taken as independent factors. Regarding the successor effect, it was found that farms that have an identified successor (high succession probability), are more likely to show increases in their production during the last five years. The opposite can be observed in farms where succession status is not yet defined. Regarding the GIP, the gender of the successor and proxy variables of wealth, show the highest coefficients within the socioeconomic variables. The psychological variable “intention” shows the highest correlation with the GIP and is one of the explanatory factor that best fit. Having an identified successor is a key factor to improve productivity, competitiveness and sustainability of family farms, likewise, we showed that the traditionalist approach where GIP and succession are tried to be explained by means of socioeconomic variables, yields low explanatory values (R2: 0, 45). This results leaves room to a new strand of related research, where psychological variables and behavioral economics seem to be novel options and the approaches that best suits the subject.
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