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.

CAP Subsidies and the Productivity of EU Farms. Factor Markets Working Paper No. 37, March 2013

This paper investigates the impact of subsidies from the common agricultural policy on the total factor productivity of farms in the EU. We employ a structural, semi-parametric estimation algorithm, directly incorporating the effect of subsidies into a model of unobserved productivity. We empirically study the effects using samples from the Farm Accountancy Data Network for EU-15 countries. Our main findings are clear: subsidies had a negative impact on farm productivity in the period before the decoupling reform was implemented; after decoupling the effect of subsidies on productivity was more nuanced, as in several countries it turned positive.

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.

Exports and Firm Productivity: The effect of US steel safeguards. Bruges European Economic Research (BEER) Papers 19/January 2011

This paper investigates possible negative effects of the 2002 US steel safeguards on productivity of Eurozone steel companies. The analysis is based on an extensive literature which predicts that exporting firms not only are bigger and more productive, but also that exporting itself has positive effects, improving efficiency and leading to better utilization of firm resources. The paper investigates a large sample of EU-13 steel producing firms, in the 1998 - 2005 period. Using three methods of Total Factor Productivity (TFP) estimation among which the Olley-Pakes semiparametric estimator, we first calculate the productivity levels of companies, and then check for any unusual fluctuation in this performance variable. We find that in 2002 there has been a significant drop in TFP. The paper is an invitation for further research in this field, given the possible important effects of safeguard measures on exporters.

How did Targeted Government Trade Policies Impact the Productivity of Manufacturing Firms in Eastern Europe and Central Asia between 1995 and 2009? ACES Working Papers, 28 August 2012

This study investigates whether trade-related, targeted, government policies had an impact on the total factor productivity (TFP) of manufacturing firms in Eastern Europe and Central Asia (ECA region) between 1995 and 2009. It does so by looking at how different types of primarily industry-specific trade policies (or their combinations) impacted firm productivity. The dependent variable is firm total factor productivity (TFP), calculated using the Levinsohn-Petrin approach. As an alternative measure of firm productivity, this study uses labor productivity. This study finds that, in most instances (10 out of 14 times), targeted policies do not show a significant impact on manufacturing firms’ TFP. Based on the analysis of 588 manufacturing firms in the ECA region, this study finds that, contrary to proponents of targeted policies, targeted trade-related government policies have a limited impact on the total factor productivity (TFP) in developing countries.

The triggers of competitiveness: the EFIGE cross-country report. Bruegel Blueprint 17, 17 July 2012

There is a pressing need for Europe to grow out of the crisis, meaning that Europe needs to become more competitive, enabling it to capture growth currently taking place mainly in emerging markets. But what are the triggers of competitiveness? The EFIGE project, led by Bruegel, takes a fresh look by inquiring into the determinants of firm-level international performance – focusing on external competitiveness. In the competitiveness debate, it is crucial to understand not only the macroeconomic challenge, but also to find the right micro-level triggers that will generate growth and exports. The authors identify firm-level total factor productivity as a major determinant of growth and exports. Human capital, research, equity finance and performance based incentives for employees also play their parts. Moreover, size matters and large firms typically are much better exporters than their smaller counterparts. This report builds on previous EFIGE research and studies in depth firm performance in seven countries (Austria, France, Germany, Hungary, Italy, Spain, United Kingdom) to identify the triggers of competitiveness.

Investment as the key to recovery in the euro area? CEPS Policy Brief No. 326, 18 November 2014

Investment has declined in the euro area since the start of the economic and financial crisis, but this does not mean that there is necessarily an ‘investment gap’, explains Daniel Gros in this CEPS Policy Brief. Investment was probably above a sustainable level due to the credit boom before 2007. Moreover, the fall in the euro area’s potential growth − due to a combination of a sharp demographic slowdown and lower total factor productivity (TFP) growth − should also lead to a permanently lower investment rate. Increasing the investment rate might thus be the wrong target for economic policy. The author advises that the aim of economic policy should be to increase consumption, rather than investment overall. Increasing infrastructure investment might be justified in some member countries, but it is not a ‘free lunch’ when efficiency levels are low, which seems to be the case in some of the financially stressed euro area countries.

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.

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.

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.