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.

Compositional effects on productivity, labour cost and export adjustments. Bruegel Policy Contribution 2012/11, June 2012

Sectoral shifts, such as shrinkage of low labour productivity and the low-wage construction sector, can lead to apparent increased aggregate average labour productivity and average wages, especially when capital intensity differs across sectors. For 11 main sectors and 13 manufacturing sub-sectors, we quantify the compositional effects on productivity, wages and unit labour costs (ULCs) based and real effective exchange rates (REER), for 24 EU countries. Compositional effects are greatest in Ireland, where the pharmaceutical sector drives the growth of output and productivity, but other sectors have suffered greatly and have not yet recovered. Our new ULC-REER measurements, which are free from compositional effects, correlate well with export performance. Among the countries facing the most severe external adjustment challenges, Lithuania, Portugal and Ireland have been the most successful based on five indicators, and Latvia, Estonia and Greece the least successful. There is evidence of downward wage flexibility in some countries, but wage cuts have corrected just a small fraction of pre-crisis wage rises and came with massive reductions in employment even in the business sector excluding construction and real estate, highlighting the difficulty of adjusting wages downward.

Productivity, labour cost and export adjustment: Detailed results for 24 EU countries. Bruegel Working Paper 2012/11, 12 July 2012

As a background document for Bruegel Policy Contribution 2012/11 ‘Compositional effects on productivity, labour cost and export adjustment’, this working paper presents detailed results for 24 EU countries on: • The sectoral changes in the economy; • The unit labour costs (ULC) based real effective exchange rate (REER) and its main components; • Export performance. • The ULC-REERs are calculated: • For the total economy, the business sector (excluding agriculture, construction and real estate activities), and some main sectors; • Using both actual aggregates and fixed-weight aggregates, as the latter are free from the impacts of compositional changes; • Against 30 trading partners and against three subsets of trading partners: euro-area, non-euro area EU, non-EU.