Direct Democracy and Local Public Finances under Cooperative Federalism

In this paper, we exploit the introduction of the right of local initiatives in the German state of Bavaria in 1995 in order to study the fiscal effects of direct democracy. Our identification strategy combines difference‐in‐differences and regression discontinuity methods: we compare municipal expenditure and revenue between pre‐ and post‐reform periods at population thresholds where the signatures needed to launch initiatives and minimum quorum requirements decrease discontinuously (difference‐in‐discontinuities design). The results suggest that stronger direct democratic institutions lead to an expansion of local government size.     

On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis

This paper aims at analyzing the degree and structure of interdependencies in terms of volatility (transmission, contagion) between Islamic and conventional stock markets on calm periods and at times of financial fragility and crisis. We focused on the recent financial instability periods and used the Quantile Regression-based GARCH model. Main results lead to very interesting conclusions. First, it has been found that Islamic stock markets are not totally immune to the global financial crisis. Second, a very strong interdependence is sensed from the conventional to the Islamic stock markets, especially, from the conventional developed markets to the Islamic Emerging and Arab markets and to the Islamic developed markets. Finally, it has been proved that the interdependencies from conventional to Islamic markets are propagated between Islamic markets. Our findings suggest that the Islamic finance industry does not seem able to provide cushion against economic and financial shocks that affect conventional markets.     

How should Engel's law be formulated?

Engel's law expresses a “negative stochastic association” of income and the proportion of income that is spent on food. However, there are many quite different notions of “negative stochastic association” and consequently there are different ways of defining Engel's law. We relate these different concepts to Engel's original statistical analysis and show that one must give credit to Engel for the first non-parametric statistical analysis of budget-data.     

Stock Price Index and Exchange Rate Nexus in African Markets

This paper examines the relationship between stock price index and exchange rate in six African markets using monthly data for the period January 2007 to October 2015. A quantile regression approach is used. This methodology is shown to perform better than the ordinary least squares estimators, particularly when the conditional distribution is heterogeneous. Our empirical evidence reveals an interesting pattern in the association of these two financial markets in Africa, which shows that the negative relationship between stock and foreign exchange markets is more apparent when exchange rates are extremely low or high. The negative relationship between the two variables is in line with the portfolio balance effect.     

User Fee Abolition and the Demand for Public Health Care

This research examines the effect of the abolition of user fees in South Africa, a policy implemented in 1994 for uninsured children under the age of six and the elderly uninsured, as well as pregnant and nursing mothers. The analysis focuses on the implementation of the policy and the use of curative public healthcare services by children following strict and fuzzy regression discontinuity designs. The estimates point to statistically insignificant average and local average policy effects, even though the policy appears to have been implemented reasonably effectively, albeit imperfectly. In other words, the policy did not, on average, affect the use of curative public healthcare, at least for those children who should have benefited from the policy.     

Bancarization and violent attacks from guerrilla and other illegal groups in Colombia

Income shocks affect violence through the opportunity cost and rapacity effects. Existing studies focus on the impact of transitory shocks, especially commodity price innovations. This paper builds on this literature and studies the causal effect of permanent income shocks on armed conflict in Colombia. Using a rich dataset reporting all guerrilla and other armed groups' attacks by municipality between 2009 and 2014 and information on the provision of banking services, it shows that increasing bancarization leads to reductions in violence. These results have important implications for public policy in countries with a long history of violence. They suggest that promoting financial inclusion is useful for reducing conflict.     

Geography of Italian student mobility: A network analysis approach

Understanding the phenomenon of intra- and international student mobility has become increasingly relevant to the organization of tertiary education systems. Using microdata information provided by the Italian National Student Archive on the cohorts of students enrolled at university in the academic years 2011–12 and 2014–15, we consider a network analysis approach to investigate the incoming and outgoing student flows between territories and universities. More specifically, the paper aims to shed light on the dynamics of Italian student mobility networks at both the bachelor's and master's degree levels by considering attractiveness indicators combined with network centrality measures, clustering techniques for network data and explanatory models. We analyze the partition of the global network structure by means of blockmodeling analysis and we explain the determinants of the differences among universities in attracting students adopting a quantile regression analysis.     

WHICH FISCAL MULTIPLIERS ARE REGIME‐DEPENDENT? A META‐REGRESSION ANALYSIS

We analyse whether estimated multiplier effects are systematically higher if the economy suffers a downturn. For that purpose, we conduct a meta‐regression analysis on a unique data set of 98 empirical studies with more than 1800 observations on multiplier effects and control for regime‐dependence of the multiplier. We find that spending multipliers are much higher (by about 0.7–0.9 units) during a downturn. Tax multipliers are not sensitive to the economic regime, and generally lower than spending multipliers. Finally, for all spending categories other than government consumption, the multiplier significantly exceeds one during downturns.     

Global value chains,large-scale farming,and poverty: Long-term effects in Senegal

This paper presents panel data evidence on the impact of expansion of global value chains and large-scale export-oriented farms in developing countries over almost a decade. We estimate the income effects of wage employment on large-scale farms in the horticultural export sector in Senegal, using data from two survey rounds covering a seven-years period of rapid expansion of the sector. We estimate average income effects as well as heterogeneous income effects, using fixed effects and quantile fixed effects regressions. We find that poverty and inequality reduced much faster in the research area than elsewhere in Senegal. Employment in the horticultural export sector is associated with higher household income and the income effect is strongest for the poorest households. Expansion of the horticultural export sector in Senegal has been particularly pro-poor through creating employment that is accessible and creates substantial income gains for the poorest half of the rural population. These pro-poor employment effects contrast with insights in the literature on increased inequality from rural wage employment.     

A gradient boosting approach to the Kaggle load forecasting competition

We describe and analyse the approach used by Team TinTin (Souhaib Ben Taieb and Rob J Hyndman) in the Load Forecasting track of the Kaggle Global Energy Forecasting Competition 2012. The competition involved a hierarchical load forecasting problem for a US utility with 20 geographical zones. The data available consisted of the hourly loads for the 20 zones and hourly temperatures from 11 weather stations, for four and a half years. For each zone, the hourly electricity loads for nine different weeks needed to be predicted without having the locations of either the zones or stations. We used separate models for each hourly period, with component-wise gradient boosting for estimating each model using univariate penalised regression splines as base learners. The models allow for the electricity demand changing with the time-of-year, day-of-week, time-of-day, and on public holidays, with the main predictors being current and past temperatures, and past demand. Team TinTin ranked fifth out of 105 participating teams.