Does it matter how much land your neighbour owns? The functioning of land markets in Poland from a social comparison perspective. Factor Markets Working Document No. 59, August 2013

While many factors have been studied in relation to the functioning of land markets, the role of land distribution has received relatively little attention. In this paper, we ask to what extent farmers’ propensity to buy land is related to the difference between them and their neighbours in terms of land ownership. To this end, we employ the concept of relative deprivation. Drawing on micro-level data from the transition period in Poland and using both OLS and instrumental variables strategy, we find that interpersonal comparisons with others in one’s reference group may have motivated a farmer’s behaviour in the land market. In particular, the propensity to purchase land is positively associated with experiencing higher relative deprivation. In addition, this relationship waned over time in a predictable manner: late in the transition period it was weaker than at the beginning of the period.

Off-farm Labour Decision of Italian Farm Operators. Factor Markets Working Document No. 61, August 2013

This paper analyses the factors affecting off-farm labour decisions of Italian farm operators. Using micro-level data from the Farm Business Survey (REA) over the pre- and post-2003 CAP reform periods, we investigated the impact that operator, family, farm and market characteristics exert on these choices. Among other things, the paper focuses also on the differential impact of those variables for operators of smaller and larger holdings. The main results suggest that operator and family characteristics have a significant impact on the decision to participate in off-farm work more for smaller than for bigger farms. By contrast, farm characteristics are more relevant variables for bigger farms. In particular, decoupled farm payments, by increasing the marginal productivity of farm labour, lower the probability of working off the farm only in bigger farms, while coupled subsidies in pre-reform years do not have a significant impact on labour decisions. Finally, we show that, after accounting for the standard covariates, local and territorial labour market characteristics generally have a low effect on off-farm work operators’ choices.

Practical Modified Gini Index. ACES Working Papers, 2012

The Gini index is the most common method for estimating the level of income inequality in countries. In this paper we suggest a simple modification that takes into account the moderating effect of in-kind government benefits. Unlike other studies that use micro level data that is rarely available for many countries or over a period of time, the proposed modified Gini index could be calculated using just the regularly available data for each country. Such data includes the original Gini coefficient, government consumption expenditures, GDP and total tax revenue as a percentage of GDP. This modified version of the Gini index allows us to calculate the level of inequality more precisely, and make better comparisons between countries and over time.

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.

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.

Life Is Getting Worse in ESS Data: Is This Due to Micro or Macro Factors? Bruges European Economic Research (BEER) Papers 28/November 2013

In order to evaluate the success of a society, measuring well-being might be a fruitful avenue. For a long time, governments have trusted economic measures, Gross Domestic Product (GDP) in particular, to assess their success. However GDP is only a limited measure of economic success, which is not enough to show whether policies implemented by governments have a positive perceived impact on the people they represent. This paper belongs to the studies of the relationship between measures of well-being and economic factors. More precisely, it tries to evaluate the decrease in happiness and life satisfaction that can be observed in European countries in the 2000-2010 decade. It asks whether this deterioration is mainly due to microeconomic factors, such as income and individual characteristics, or rather to environmental (macroeconomics) factors such as unemployment, inflation or income inequality. Such aggregate factors could impact individual happiness per se because they are related to the perception of an aggregate risk of unemployment or income fall. In order to strengthen this interpretation, this paper checks whether the type of social protection regime existing in different countries mediates the impact of macroeconomic volatility on individual well-being. To go further, adopting the classification of welfare regimes proposed by Esping-Andersen (1990), it verifies whether the decreasing pattern of subjective well-being varies across these regimes. This is partly due to the aggregate social protection expenditure. Hence, this paper brings some additional evidence to the idea that macroeconomic uncertainty has a cost in terms of well-being. More protective social regimes are able to reduce this cost. It also proposes an evaluation of the welfare cost of unemployment and inflation (in terms of happiness and life satisfaction), in each of the different social protection regimes. Finally different measures of well-being, i.e. cognitive, hedonic and eudaimonic, are used to confirm the above mentioned result.

Mapping competitiveness with European data. Bruegel Blueprint 23, 6 March 2015

Europe needs improved competitiveness to escape the current economic malaise, so it might seem surprising that there is no common European definition of competitiveness, and no consensus on how to consistently measure it. To help address this situation, this Blueprint provides an inventory and an assessment of the data related to the measurement of competitiveness in Europe. It is intended as a handbook for researchers interested in measuring competiveness, and for policymakers interested in new and better measures of competitiveness. MAPCOMPETE has been designed to provide an assessment of data opportunities and requirements for the comparative analysis of competitiveness in European countries at the macro and the micro level.