The purpose of this paper is to examine the role of institutional factors in agricultural structural change in the European Union (EU) using the case study of land…
The purpose of this paper is to examine the role of institutional factors in agricultural structural change in the European Union (EU) using the case study of land mobility in Ireland. A range of agricultural land use options are compared in order to examine the effect of domestic and EU policy instruments on land mobility.
Using socio-economic data from the Teagasc National Farm Survey, three hypothetical farms are created using a microsimulation approach to compare incomes across farm systems and land use options. Tax and subsidy policies are applied to derive returns for the hypothetical farms under a variety of land use scenarios.
The analysis finds that in comparing four hypothetical scenarios, leasing out agricultural land on a long-term basis can prove more profitable for cattle and tillage farmers than farming the land. Only dairy farmers derive consistently higher disposable incomes from farming their land as opposed to leasing it out. Changes in CAP rules can also negatively affect farmers taking advantage of Ireland’s tax-based leasing incentives.
A gap in the literature exists in terms of how institutional factors may act to prevent either land supply or demand channels from functioning properly. This paper addresses that gap, using Ireland as a case study.
The economic reality of the 1990s in Europe forced the labor markets to become more flexible. Using a consistent comparative dataset for 14 countries, the European…
The economic reality of the 1990s in Europe forced the labor markets to become more flexible. Using a consistent comparative dataset for 14 countries, the European Community Household Panel (ECHP), we explore the degree of earnings mobility and inequality across Europe, and the role of labor market institutions in understanding the cross-national differences in earnings mobility. We study the degree of rank mobility and the degree of mobility as equalizer of long-term earnings. The country ranking in long-term earnings inequality is similar with the country ranking in annual inequality, which is a sign of limited long-term equalizing mobility within countries with higher levels of annual inequality. In long-term earnings inequality, Denmark renders the most mobile earnings distribution with the second highest equalizing effect. The only disequalizing mobility in a lifetime perspective is found in Portugal. With respect to the relationship between earnings mobility and earnings inequality, we find a significant negative association both in the short and the long run. Based on the rankings in long-term Fields mobility and long-term inequality, Denmark is expected to have the lowest lifetime earnings inequality in Europe, followed by Finland, Austria, and Belgium. The Mediterranean countries (Spain and Portugal) are expected to have the highest long-term inequality. With respect to the institutional factors that may be related to earnings mobility, we bring evidence that the deregulation in the labor and product markets, the degree of unionization, the degree of corporatism and the spending on ALMPs are positively associated with earnings mobility.
Although they are neighbouring Asian countries with many similarities, India and Indonesia have different levels of household expenditure inequality. During the end of…
Although they are neighbouring Asian countries with many similarities, India and Indonesia have different levels of household expenditure inequality. During the end of 2000s, the Gini coefficient of Indonesia was 9.1 percentage points larger than the Gini coefficient of India. To understand the determinants of this difference, this study decomposes it into the contribution of price effects, demographic effects and labour market structure effects. Differences in expenditure structures (price effects) and demographic characteristics are found to be the greatest contributors to the inequality gap across the two countries. The difference in the education distribution of household heads also has a positive and significant impact on the inequality gap. Differences in the labour market structure, on the other hand, turn out to be less important.