Drivers of agricultural capital productivity in selected EU member states. Factor Markets Working Paper No. 30, September 2012

The aim of this Working Paper is to provide an empirical analysis of the marginal return on working capital and fixed capital in agriculture, based on data gathered by the Farm Accountancy Data Network from seven EU member states. Particular emphasis is placed on the detection of credit market imperfections. The key idea is to provide farm group-specific estimates of the shadow price of capital, and to use these to analyse the drivers of on-farm capital use in European agriculture. Based on Cobb Douglas estimates of farm-type specific production functions, we find that working capital is typically used in more than economically optimal quantities and often displays negative marginal returns across countries and farm types. This is less often the case with regard to fixed capital, but it is only in a small set of sectors where access to fixed capital appears severely constrained. These sectors include field crop and mixed farms in Denmark, dairy farms in East Germany, as well as mixed farms in Italy and the UK. The relationship between farm financial indicators and the estimated shadow prices of capital varies considerably across countries and sectors. Among the farms with a high shadow price for fixed capital in Denmark, high debt levels and little owned land tended to induce more intensive capital use, which may reflect the liberal Danish banking system. In East Germany, Italy and the UK, high debt levels made farmers more tightly capital constrained. Hence, in the latter group of countries, more traditional mechanisms of capital allocation based on debt capacity seemed to be at work. As a general conclusion, EU agriculture appears to be characterised by overcapitalisation rather than by credit constraints.

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 and Credit Constraints: Firm-Level Evidence from Propensity Score Matching. Factor Markets Working Paper No. 3, September 2011

Drawing on a unique, farm-level panel dataset with 37,409 observations and employing a matching estimator, this paper analyses how farm access to credit affects farm input allocation and farm efficiency in the Central and Eastern European transition countries. We find that farms are asymmetrically credit constrained with respect to inputs. Farm use of variable inputs and capital investment increases up to 2.3% and 29%, respectively, per €1,000 of additional credit. Our estimates also suggest that farm access to credit increases total factor productivity up to 1.9% per €1,000 of additional credit, indicating that an improvement in access to credit results in an adjustment in the relative input intensities on farms. This finding is further supported by a negative effect of better access to credit on labour, suggesting that these two are substitutes. Interestingly, farms are found not to be credit constrained with respect to land.

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.

Identifying Factor Productivity from Micro-data: The case of EU agriculture. Factor Markets Working Paper No. 34, January 2013

The classical problem of agricultural productivity measurement has regained interest owing to recent price hikes in world food markets. At the same time, there is a new methodological debate on the appropriate identification strategies for addressing endogeneity and collinearity problems in production function estimation. We examine the plausibility of four established and innovative identification strategies for the case of agriculture and test a set of related estimators using farm-level panel datasets from seven EU countries. The newly suggested control function and dynamic panel approaches provide attractive conceptual improvements over the received ‘within’ and duality models. Even so, empirical implementation of the conceptual sophistications built into these estimators does not always live up to expectations. This is particularly true for the dynamic panel estimator, which mostly failed to identify reasonable elasticities for the (quasi-) fixed factors. Less demanding proxy approaches represent an interesting alternative for agricultural applications. In our EU sample, we find very low shadow prices for labour, land and fixed capital across countries. The production elasticity of materials is high, so improving the availability of working capital is the most promising way to increase agricultural productivity.

Will improved access to capital dampen the need for more agricultural land? A CGE analysis of agricultural capital markets and world-wide biofuel policies. Factor Markets Working Paper No. 48, May 2013

This paper analyses the consequences of enhanced biofuel production in regions and countries of the world that have announced plans to implement or expand on biofuel policies. The analysis considers biofuel policies implemented as binding blending targets for transportation fuels. The chosen quantitative modelling approach is two-fold: it combines the analysis of biofuel policies in a multi-sectoral economic model (MAGNET) with systematic variation of the functioning of capital and labour markets. This paper adds to existing research by considering biofuel policies in the EU, the US and various other countries with considerable agricultural production and trade, such as Brazil, India and China. Moreover, the application multi-sectoral modelling system with different assumptions on the mobility of factor markets allows for the observation of changes in economic indicators under different conditions of how factor markets work. Systematic variation of factor mobility indicates that the ‘burden’ of global biofuel policies is not equally distributed across different factors within agricultural production. Agricultural land, as the pre-dominant and sector-specific factor, is, regardless of different degrees of inter-sectoral or intra-sectoral factor mobility, the most important factor limiting the expansion of agricultural production. More capital and higher employment in agriculture will ease the pressure on additional land use – but only partly. To expand agricultural production at global scale requires both land and mobile factors adapted to increase total factor productivity in agriculture in the most efficient way.

Synthesis Report on the Impact of Capital Use. Factor Markets Working Document No. 57, August 2013

This paper examines the drivers of productivity in EU agriculture from a factor markets perspective. Using econometrically estimated production elasticities and shadow prices of factors for a set of eight EU member states, we focus on field crop farms represented in the FADN database for the years 2002-08. As it turned out that output reacts most elastically to materials input, we investigate this factor further and find different rationing regimes represented in different member states. Marginal return on materials is low in Denmark and West Germany, but significantly above typical market interest rates in East Germany, Italy and Spain. In the latter countries and in Denmark it also increased towards the end of the observed period. This finding is consistent with a perception of tightening funding access, possibly induced or reinforced by the unfolding financial crisis. Marginal returns to land, labour and fixed capital are generally low. We conclude that the functioning of factor markets plays a crucial role for productivity growth, but that factor market operations display considerable heterogeneity across EU member states.