After Estonia restored independence, the number of individual farms increased rapidly during the 1990s. Since 2001, the number of farms has substantially decreased. Therefore, based on the survey data, this paper aims to explore the factors underlying the motivation to exit farming in Estonia. Cluster analysis is used to form relatively homogeneous groups of farms, and to investigate between-group differences in the motivation to exit as well as other farm characteristics. Logistic and ordered logistic regressions are applied to estimate the effects of selected variables on exit probability. The study reveals that the farms that are least likely to exit are large-scale farms and small-scale family farms. In small-scale farms, a reliance on family labour and a diversification of activities reduces the exit probability. The size of agricultural area was found to correlate negatively to exit intentions, while a higher share of rented land increases the exit probability. Also, the health of the farmer and the renting out of land are significant determinants to farm exit.
Abstract:The aim of the study was to analyze the productivity change of Estonian dairy farms before and after the accession to the European Union. The Malmquist productivity index was measured and separated into the technical and efficiency change using the data envelopment analysis for the pre-accession period (years 2001-2003) and the post-accession period (2004)(2005)(2006). Second-stage regression was applied to estimate the possible variables determining the productivity and efficiency change. Productivity growth of Estonian dairy farms was negative for both observed periods; the mean annual growth rate of the Malmquist productivity index was -0.7% in 2001-2003 and -2.6% in 2004-2006. The share of farms with declining productivity increased from 36% to 50% after the accession to the EU and is induced mainly by a significant deterioration in the efficiency change. remarkable changes in the line-up of most efficient dairy farms occurred between 2000 and 2006, producers with greater initial efficiency have experienced significant regress, with efficiency score decreasing from 0.842 in 2000 to 0.608 in 2006 and the new front-runners, forming the efficiency frontier, have emerged. capitalization was positively related with the cumulative technical change. nevertheless, increasing investments and assets have not affected efficiency change and investments have often not been harnessed in the best possible way.
The effects of genetic level and output quality characteristics on technical efficiency (TE) of dairy farms were studied. The average total relative breeding value (RBV) at herd level was considered a parameter of the genetic level and production potential of the main input (dairy cows), while somatic cell count (SCC) and milk composition characterise the quality of the main output (milk) of dairy farms. The analysis was carried out in two stages: data envelopment analysis was used in the first stage and fractional regression model in the second stage, combining the data collected by the Estonian Farm Accountancy Data Network with the data from the Estonian Livestock Performance Recording Ltd. The results showed that the TE of fully efficient dairy farms is positively affected by the total RBV (P < 0.05), number of dairy cows in the herd (P < 0.05), and negatively affected by the SCC (P < 0.001) and costs of purchased feed per kg of produced milk (P < 0.01). Among the inefficient farms, the TE was positively affected by the lifetime daily milk yield (P < 0.05), and average milk fat (P < 0.1) and protein (P < 0.05) contents. The results confirm our hypothesis that the genetic level of dairy herd and milk quality have a positive effect on the TE of dairy farms.
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