Effects of Economic Factors on Adoption of Robotics and Consequences of Automation for Productivity Growth of Dairy Farms. Factor Markets Working Paper No. 32, December 2012

In the long term, productivity and especially productivity growth are necessary conditions for the survival of a farm. This paper focuses on the technology choice of a dairy farm, i.e. the choice between a conventional and an automatic milking system. Its aim is to reveal the extent to which economic rationality explains investing in new technology. The adoption of robotics is further linked to farm productivity to show how capital-intensive technology has affected the overall productivity of milk production. The empirical analysis applies a probit model and an extended Cobb-Douglas-type production function to a Finnish farm-level dataset for the years 2000–10. The results show that very few economic factors on a dairy farm or in its economic environment can be identified to affect the switch to automatic milking. Existing machinery capital and investment allowances are among the significant factors. The results also indicate that the probability of investing in robotics responds elastically to a change in investment aids: an increase of 1% in aid would generate an increase of 2% in the probability of investing. Despite the presence of non-economic incentives, the switch to robotic milking is proven to promote productivity development on dairy farms. No productivity growth is observed on farms that keep conventional milking systems, whereas farms with robotic milking have a growth rate of 8.1% per year. The mean rate for farms that switch to robotic milking is 7.0% per year. The results show great progress in productivity growth, with the average of the sector at around 2% per year during the past two decades. In conclusion, investments in new technology as well as investment aids to boost investments are needed in low-productivity areas where investments in new technology still have great potential to increase productivity, and thus profitability and competitiveness, in the long run.

The Reallocation of Agricultural Labour across Sectors: An Empirical Strategy for Micro Data. Factor Markets Working Document No. 45, May 2013

This paper presents an empirical methodology for studying the reallocation of agricultural labour across sectors from micro data. Whereas different approaches have been employed in the literature to better understand the mobility of labour, looking at the determinants to exit farm employment and enter off-farm activities, the initial decision of individuals to work in agriculture, as opposed to other sectors, has often been neglected. The proposed methodology controls for the selectivity bias, which may arise in the presence of a non-random sample of the population, in this context those in agricultural employment, which would lead to biased and inconsistent estimates. A 3-step multivariate probit with two selection and one outcome equations constitutes the selected empirical approach to explore the determinants of farm labour to exit agriculture and switch occupational sector. The model can be used to take into account the different market and production structures across European member states on the allocation of agricultural labour and its adjustments.

Determinants to Leave Agriculture and Change Occupational Sector: Evidence from an Enlarged EU. Factor Markets Working Document No. 46, May 2013

The objective of this paper is to explore the determinants to leave agriculture and change occupational sector. We adopt a 3-step multivariate probit where we control for selection bias at two stages in the decisions to work and, at a later stage, exit agriculture. The analysis is based on the European Union Labour Force Survey data expanded with additional regional indicators. The main results suggest that younger individuals are more likely to leave farming activities, although the largest outflows of agricultural labour are mainly associated with the retirement of people. Self-employed and family workers are generally less likely to leave agriculture and those with low levels of educations are found to be significantly constrained in entering the non-farm economy. Moreover, labour market conditions at the regional level do matter for switching occupational sector. Differences in the results among the selected new member states and the EU-15 can be explained by the diverse production structures, suggesting different capacities to release and absorb labour.