Cardinality-based equality of opportunities

We study possible rankings of opportunity profiles. An opportunity profile is a list of opportunity sets, one for each agent in the society. We compare profiles on the basis of the notion of “equality of opportunities”. Our main results show the necessary and sufficient conditions for this comparison to be made using exclusively the information provided by two cardinal measures: the number of common alternatives in all sets of a given profile and the difference between the number of alternatives in the individual sets. We also show that, under additional axioms, we can combine these criteria only in a weighted procedure or in some lexicographic refinements of a weighted procedure.      

Employment shifts, economic reform and the changes in public/private sector wages in Mexico: 1987–1997

Over the last decade, the public sector in Mexico experienced substantial fiscal reform, divestiture of public enterprises, and the elimination of many regulations affecting pay and employment. This study analyzes the changes in the public/private sector differences in wages during the 1987–1997 period. The results from analyzing microdata from the Encuesta Nacional de Empleo Urbano show that relative public sector wages increased from 1987 to 1997. Most of the relative wage increase in the public sector can be explained by increases in the price of skills and by changes in sorting across sectors. The results have important public policy implications since they suggest that public sector workers earn more and their wages have grown faster than those of their private sector counterparts. As such, policies contemplating public sector reform should take into account the effect of these measures on the inter-sectoral income distribution and the overall economic growth. First version received: April 2000/Final version received: December 2000     

The Weekend and 'Reverse' Weekend Effects: An Analysis by Month of the Year, Week of the Month, and Industry

In this paper, we examine whether the 'reverse' weekend effect recently documented by Brusa, Liu and Schulman (2000) is concentrated in a few industries or widely spread across all the industries. The findings in this paper indicate that the 'reverse' weekend effect exists not only in broad indices, but also in most industries . The results suggest that the 'reverse' weekend effect may be driven by economic events that affect all industries, rather than industry‐specific factors . Although the patterns of Monday returns are similar between broad indices and industry indices, they are different between the pre ‐ and the post ‐1988 periods. Monday returns tend to be negative in the pre ‐1988 period, but tend to be positive in the post ‐1988 period, for both broad market indices and industry indices. These conclusions are valid even after considering the influence of the month‐of‐the‐year and the week‐of‐the‐month effects.     

Using partial identification methods to estimate the effect of violence against women on their children’s health outcomes

A growing literature in economics seeks to estimate the costs of violence against women by examining, for example, its impact on the health outcomes of their children. However, it is difficult to assign a causal interpretation to these nonexperimental studies due to the presence of unobservable characteristics affecting violence and health outcomes simultaneously. The lack of credible instrumental variables applicable in several countries further limits our knowledge. I address this gap by using new partial identification methods to estimate the relative size of the unobservables needed to eliminate the estimated effects in nonexperimental studies. I also expand the external validity of the analysis by using data from five standardized nationally representative household surveys in Latin America. Consistent with previous studies, cross-sectional estimates show large negative associations between violence against women and an array of child health outcomes. However, when accounting for omitted variable bias, at best, two-thirds of the estimates remain robust and they are concentrated on the outcomes with the largest cross-sectional estimated impacts.     

Perception evaluation kit: a case study with materials and learning styles

International Journal of Technology and Design Education - Materials are elements that configure our built environment and are key components in design and engineering education. This research aims...     

Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

Model for evaluating the environmental sustainability of energy projects

This article focuses on the problem of assessing the environmental sustainability of energy projects. For this purpose an original model, which is based on various indicators that measure the environmental sustainability of energy projects, has been developed. This model, so called index of environmental sustainability of energy projects (IESEP), can be used in scenario comparison, while measuring the effectiveness of the proposed alternatives. Finally, an example of how to use this model is provided by analyzing alternatives to ameliorate the environmental sustainability of a hydroelectric project. In doing so, it is possible to show the usefulness of this model when used as a decision making tool for energy planners.     

Measuring the cost of liquidity in agricultural futures markets: Conventional and Bayesian approaches

Estimating the cost of liquidity in agricultural futures markets is challenging because bid‐ask spreads are usually not observed. Based on an ability to reflect simulated data from Roll's spread model, we assess the effectiveness of conventional and Bayesian bid‐ask spread estimators under different market conditions. Conventional serial covariance and absolute price change spread estimators appear to be biased. Hasbrouck's Bayesian estimator generates small costs of liquidity whose values depend on the correlation and noise in the data. The absolute value Bayesian estimator is precise and works well under conditions of high levels of noise and correlation usually found in agricultural futures markets. Using data from live cattle (LC) and lean hog (LH) contracts, we find similar patterns of performance that produce economically meaningful cost of liquidity differences.