Gender and regional inequality in human development: the case of Spain1

In this paper, we present estimates of the Human Development Index and the Gender-Related Development Index in the Autonomous Communities of Spain. Our case study of Spain, a developed country with clear gender and regional differences, demonstrates the importance of adjusting human development indices in accordance with gender discrimination and regional inequalities. We also show the significance of the income component in assessing the development level of women in countries like Spain, where lack of employment or low remuneration are the chief characteristics of women's inequality. Our analysis makes clear that the Gender-Related Human Development Index has limited applicability in developed countries; it also illustrates the need for alternative variables or models to assess inequality in those countries.     

Tuition fees and social segregation: lessons from a natural experiment at the University of Paris 9-Dauphine

Using a natural experiment, a sharp rise in tuition fees in some of the programmes at the University of Paris 9-Dauphine, we study the impact of tuition fees on students’ pathways, and outcomes. We apply an optimal matching method to the national database of students’ registrations (SISE) to define a typology of pathways. We then use a nonordered multinomial logit model to evaluate the impact of the rise in tuition fees on the types of pathways selected by the university. We show that there is a significant impact on these pathways. The increase in tuition fees reduces geographic and social mobility, thereby accentuating the phenomena of social segregation. Furthermore, contrary to what some of the studies assert, the rise does not appear to encourage greater effort: we find no impact on the graduation success rate.     

Optimal taxation and growth with public goods and costly enforcement

This paper studies optimal direct and indirect taxation in an endogenous growth framework with a productive public good and costly tax collection. Optimal (growth-maximizing) tax rules are derived under exogenous collection costs. The optimal direct–indirect tax ratio is shown to be negatively related to the administrative costs of collecting these taxes, as documented in cross-country data. This result also holds under endogenous collection costs (with these costs inversely related to administrative spending on tax enforcement), but for these to generate significant effects on tax collection requires implausibly high degrees of efficiency in spending, or the allocation of a large fraction of resources to tax enforcement. Depending on how it is financed, the latter policy may entail adverse effects on growth. Improving ‘tax culture’ and the sense of civic duty through greater budgetary transparency may be a more effective policy to improve tax collection and promote economic growth.     

Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach

This paper proposes a general formulation of a nonparametric frontier model introducing external environmental factors that might influence the production process but are neither inputs nor outputs under the control of the producer. A representation is proposed in terms of a probabilistic model which defines the data generating process. Our approach extends the basic ideas from Cazals et al. (2002) to the full multivariate case. We introduce the concepts of conditional efficiency measure and of conditional efficiency measure of order-m. Afterwards we suggest a practical way for computing the nonparametric estimators. Finally, a simple methodology to investigate the influence of these external factors on the production process is proposed. Numerical illustrations through some simulated examples and through a real data set on Mutual Funds show the usefulness of the approach.JEL Classification: C13, C14, D20     

Aspects of statistical analysis in DEA-type frontier models

In Grosskopf (1995) and Banker (1995) different approaches and problems of statistical inference in DEA frontier models are presented. This paper focuses on the basic characteristics of DEA models from a statistical point of view. It arose from comments and discussions on both papers above. The framework of DEA models is deterministic (all the observed points lie on the same side of the frontier), nevertheless a stochastic model can be constructed once a data generating process is defined. So statistical analysis may be performed and sampling properties of DEA estimators can be established. However, practical statistical inference (such as test of hypothesis, confidence intervals) still needs artifacts like the bootstrap to be performed. A consistent bootstrap relies also on a clear definition of the data generating proces and on a consistent estimator of it: The approach of Simar and Wilson (1995) is described. Finally, some trails are proposed for introducing stochastic noise in DEA models, in the spirit of the Kneip-Simar (1995) approach.     

Do brain drain and poverty result from coordination failures?

The bidirectional causal links between high-skilled emigration and poverty can give rise to multiple equilibria and coordination failures. Two countries sharing identical characteristics may end up in either a “low poverty-low brain drain” equilibrium or in a “high poverty-high brain drain” equilibrium. In this paper, we build a model which endogenizes high-skilled emigration and economic performances in order to derive the conditions under which multiplicity occurs. After identifying country-specific parameters, we find that in the majority of developing countries, the best equilibrium is selected and that the observed brain drain is inevitable. In 22 small developing countries however, the worse equilibrium prevails, implying that poverty and brain drain are increased by coordination failure. These countries require appropriate development policies, such as a temporary subsidization of the repatriation of their high-skilled expatriates. Our results are robust to the inclusion of a brain gain mechanism.     

Interest rate rules, inflation and the Taylor principle: an analytical exploration

Summary. The purpose of this article is to characterize optimal interest rate rules in the framework of a dynamic stochastic general equilibrium model, and notably to scrutinize the “Taylor principle”, according to which the nominal interest rate should respond more than one for one to inflation. This model yields explicit solutions for the optimal rule. We find that the elasticity of response depends on numerous factors, such as the degree of price rigidity, the autocorrelation of the underlying shocks, or which measure of inflation is used. In general the optimal elasticity of the interest rate with respect to inflation needs not be greater than one.Received: 6 November 2003, Revised: 17 August 2004 JEL Classification Numbers: E5, E52, E58.J.-P. Bénassy: I wish to thank Daniel Laskar and an anonymous referee for their perceptive comments on earlier drafts of this paper. Of course all remaining deficiencies are mine.     

Organizing women for combat: The experience of the FARC in the Colombian war

The FARC, which used to be Colombia's main guerrilla force and is now in the midst of a peace process, was to a great extent a feminized group. This paper discusses why it recruited so many women, and why it recruited them as combatants. We suggest that only when the FARC adopted a highly hierarchical, self‐contained, and militaristic organizational blueprint did it get involved in the massive recruitment of women as combatants. We discuss the way in which organizational mechanisms and ideology interacted to produce such an outcome, and how this interaction marked both the organization and the trajectories of the women who joined it.     

State‐contingent analysis of farmers’ response to weather variability: irrigated dairy farming in the Murray Valley,Australia

The agricultural sector is commonly regarded as one of the most vulnerable to climate change. Current understanding of the impact of climate change on this sector relies on the underlying assumptions about farmers’ possible responses to weather variability, including changes in crop choice, input combinations and land management practices. Many previous analyses rely on the implicit (and restrictive) assumption that farmers operate under a fixed technology set across different states of nature. This assumption, represented through stochastic production or profit functions, is commonly made but seldom tested and may understate farmers’ responses to climate change if state‐contingent production technologies are, in reality, more flexible. The potential for farmers to adapt production technologies in response to unforeseen events is at the core of the state‐contingent approach. Advanced in Chambers and Quiggin (2000), the theory contends that producers can manage uncertainty through the allocation of productive inputs to different states of nature. In this article, we test the assumption that farmers’ observed behaviour is consistent with the state‐contingent production theory using farm‐level data from Australia. More precisely, we estimate the milk production technology for a sample of irrigated dairy farms from the southern Murray–Darling Basin over the period from 2006–2007 to 2009–2010.