Institutional quality and public spending in Europe: A quantile regression approach

We appraise the effects of institutional quality on public spending for a set of 27 European countries and 18 Euro-area economies over the 1996–2017 period. While institutions play a weak role in affecting spending once the fixed-effects model is employed, the application of the quantile regression indicates that improved institutional quality mitigates public spending, although the effects crucially depend on the distribution of public expenditure and the sample examined. For both the Euro-area sample and the full sample, we show that better quality of institutions reduces public spending, although the effects become less significant the higher the levels of public spending. Further, for the Euro-area sample, institutions appear to have a stronger role in mitigating public spending. Several robustness tests confirm our findings.     

Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models

Many static and dynamic models exist to forecast Value-at-Risk and other quantile-related metrics used in financial risk management. Industry practice favours simpler, static models such as historical simulation or its variants. Most academic research focuses on dynamic models in the GARCH family. While numerous studies examine the accuracy of multivariate models for forecasting risk metrics, there is little research on accurately predicting the entire multivariate distribution. However, this is an essential element of asset pricing or portfolio optimization problems having non-analytic solutions. We approach this highly complex problem using various proper multivariate scoring rules to evaluate forecasts of eight-dimensional multivariate distributions: exchange rates, interest rates and commodity futures. This way, we test the performance of static models, namely, empirical distribution functions and a new factor-quantile model with commonly used dynamic models in the asymmetric multivariate GARCH class.     

The returns to education and wage penalty from overeducation: New evidence from Vietnam

This study intends to estimate the rate of returns to education in Vietnam, the distributive effects of education on wages, and the wage penalty from the incidence of overeducation in the Vietnamese labor market during 2004–2016. This study employs a pseudo-panel approach to address omitted variables bias and the unconditional quantile regression to identify the heterogeneity of returns to education across the income distribution. Our main finding indicates that the estimated rate of returns to education in Vietnam is approximately 6.5%, showing a downward bias from previous estimates. The returns vary across wage distributions, where a lower rate of return is observed in lower quantiles and a higher rate among those individuals at the higher quantiles. The returns to education have declined since 2008, confirming the oversupply of highly educated workers in the Vietnamese labor market with an estimated wage penalty of 17%. Government assistance measures are needed to reduce the overeducation and the wage penalty issues in the Vietnamese labor market.     

Internet use and agricultural productivity in rural Vietnam

The use of the internet is growing rapidly and has become an engine for economic development. However, few studies have examined the impact of internet use on agricultural production, and the results are not yet conclusive. Employing a dataset of more than 2000 observations in rural Vietnam, our study analyses the impact of internet use on agricultural productivity using the heteroscedasticity-based instrument approach suggested by Lewbel, Journal of Business and Economic Statistics, 2012, 30, 67–80 and examines the heterogeneity and distribution of the impact using quantile regressions. Our results show that internet use has significant and positive effects on agricultural productivity. However, these effects are heterogeneous across population groups. The positive effects of internet use are stronger for households with a lower level of education, with a young and female head, and from ethnic minorities. The benefits are also found to be skewed towards the group of farmers at the bottom of the productivity distribution. Therefore, we propose facilitating the diffusion of the internet, since it not only boosts agricultural productivity, but also reduces productivity inequality. In addition, we recommend promoting rural education, supporting local markets, investing more in irrigation systems, and facilitating farm mechanisation as these factors are found to contribute to increasing agricultural productivity.     

Measuring technical efficiency of Spanish pig farming: Quantile stochastic frontier approach

The pig meat production plays a significant role in the Spanish agrofood system. The assessment of the efficiency performance with which farmers are operating is necessary to define adequate policy and management strategies. In this context, this study aimed to determine the technical efficiency (TE) performance of pig farms and to examine the key factors that may affect the production system in Spain. To do so, the analysis relies on the quantile stochastic frontier model using a sample of Spanish pig farms. Results show a significant difference between production frontier parameters across the selected quantiles, which support the relevance of using the quantile regression approach. The optimal quantile for the stochastic frontier indicates an average TE level of 75%. In addition, empirical findings suggest that pig farmers in Spain give more importance to the adoption of high technology to improve their economic and technical performance as well as their competitiveness at the European pig market.