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.     

Household Adoption of Water-Efficient Equipment: The Role of Socio-Economic Factors,Environmental Attitudes and Policy

Using survey data of around 10,000 households from 10 OECD countries, we identify the driving factors of household adoption of water-efficient equipment by estimating Probit models of a household’s probability to invest in such equipment. The results indicate that environmental attitudes and ownership status are strong predictors of adoption of water-efficient equipment. In terms of policy, we find that households that were both metered and charged for their water individually had a much higher probability to invest in water-efficient equipment compared to households that paid a flat fee.     

Does foreign aid really raise per capita income? A time series perspective

Abstract. We analyze the relationship between per capita income and foreign aid. We employ annual data and five‐year averages and carefully examine the time‐series properties of the data. Panel estimations with dynamic feasible generalized least‐squares (DFGLS) show that aid generally has an insignificant or minute negative significant impact on per capita income (particularly in highly aid‐dependent countries). This holds true for countries with different levels of human development and income, as well as for different regions. We also find that aid has a small positive impact on investment, but a significant negative impact on domestic savings (crowding out) and the real exchange rate (appreciation). JEL classification: F35, O11, C23, C51     

Estimation of zero-intelligence models by L1 data

A unit volume zero-intelligence (ZI) model is defined and the distribution of its L1 process is recursively described. Further, a generalized ZI model allowing non-unit market orders, shifts of quotes and general in-spread events is proposed and a formula for the conditional distribution of its quotes is given, together with a formula for price impact. For both the models, MLE estimators are formulated and shown to be consistent and asymptotically normal. Consequently, the estimators are applied to data of six US stocks from nine electronic markets. It is found that more complex variants of the models, despite being significant, do not give considerably better predictions than their simple versions with constant intensities.     

Optimal dividend policy and growth option

We analyse the interaction between the dividend policy and the decision on investment in a growth opportunity of a liquidity constrained firm. This leads us to study a mixed singular control/optimal stopping problem for a diffusion that we solve quasi-explicitly by establishing a connection with an optimal stopping problem. We characterize situations where it is optimal to postpone the distribution of dividends in order to invest at a subsequent date in the growth opportunity. We show that uncertainty and liquidity shocks have an ambiguous effect on the investment decision.      

Pseudo empirical likelihood method in the presence of missing data

In this paper, we propose an estimator for the population mean when some observations on the study and auxiliary variables are missing from the sample. The proposed estimator is valid for any unequal probability sampling design, and is based upon the pseudo empirical likelihood method. The proposed estimator is compared with other estimators in a simulation study.     

Adam Smith on lotteries: an interpretation and formal restatement

The paper concerns a neglected aspect of the Wealth of Nations (with the notable exception of D. Levy 1999 Levy, D. M. 1999. “Adam Smith’s Katallactic Model of Gambling: Approbation from the Spectator.” Journal of the History of Economic Thought 21 (1): 81–91. doi:10.1017/S1053837200002868.[Crossref] , [Google Scholar]), dealing directly with decision under risk. In a few pages from book I, chapter 10, Adam Smith explicitly named “lotteries” various objects of choice (possible occupations, or investment opportunities, for instance) and provided an analysis which standard expected utility glasses would hardly fit. Taking this into account allows a better understanding of the part played by typical characters like the “projector” or the “sober man”, in such matters as Smith’s conception of entrepreneurship or of the credit market. The use of some modern concepts in decision analysis (inverse stochastic dominance, rank dependent utility, prudence toward risk), is a means to show the existence, in Smith’s work, of an original theory from decision under risk, where his analysis of lotteries in the Wealth of Nations is consistent with statements from his moral philosophy on asymmetric sensitivity to gains and losses and to the regulating part played by the impartial spectator.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.