Individual and place-based drivers of self-employment in Chile

This paper analyzes the importance of individual and place characteristics on the selection into self-employment in Chile. Following a structural and multilevel empirical approach, we test whether both sets of variables explain the variation of individual wages, self-employed earnings, and the propensity of being in independent work. The results indicate that while most of the variation in these three outcomes is explained by individuals’ traits, place-related variables account for a non-negligible share of spatial variation. Second, as suggested by occupational choice theories, the propensity of being in self-employment positively correlates with larger expected earning differentials, but only in the case of employers. This, along with other results, suggests that while employers seem to choose their occupational status, own accounts in Chile seem to respond to factors pushing them into self-employment.     

Economic impact of cruise activity: the case of Barcelona

ABSTRACT

This article shows the methodology and the main figures of the local and regional economic impact generated by cruise activity. This article is pioneering in combining different issues: estimating the impact of the cruise port activity, presenting these impacts disaggregated at a sectoral level, using a rigorous methodology and carrying out extensive fieldwork. It is demonstrated that all sectors, not just traditional tourism-related sectors, benefit from cruise tourism. In order to test and apply our methodology we focus the analysis on the Port of Barcelona, which has become the leading cruise port in the Mediterranean area.     

Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries

This paper considers the application of copula models to study the shifts in extremal economic dependence of the Eastern European countries, i.e., Ukraine and its neighbouring countries, from 1969 to 2014. Extremal economic dependence is analysed in terms of poverty and affluence and with regard to growth rate. This paper contributes to the previous literature by applying the copula approaches to derive the measurements of the economic interdependence in terms of poverty and affluence. The received results depict the pattern of the (inter)dependence and its evolution across the analysed countries. Dependence on other countries in the extreme values can potentially be useful in adjustments of the economic policy of a country to minimize poverty and prevent high inequality.

     

The impact of taxes and wasteful government spending on giving

We examine how taxes impact charitable giving and how this relationship is affected by the degree of wasteful government spending. In our model, individuals make donations to charities knowing that the government collects a flat-rate tax on income (net of charitable donations) and redistributes part of the tax revenue. The rest of the tax revenue is wasted. The model predicts that a higher tax rate increases charitable donations. Surprisingly, the model shows that a higher degree of waste decreases donations (when the elasticity of marginal utility with respect to consumption is high enough). We test the model’s predictions using a laboratory experiment with actual donations to charities and find that the tax rate has an insignificant effect on giving. The degree of waste, however, has a large, negative and highly significant effect on giving.

     

Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model

The aim of this paper is to extend the index of financial safety (IFS) approach with improving its predictive performance and to show the applicability of artificial neural networks to economic and financial short time series. To this end, prediction is performed by means of the nonlinear autoregressive with exogenous inputs (NARX) model that represents the neural networks and can emulate any nonlinear dynamic state space model. Thus, a NARX model, trained by means of Levenberg–Marquardt algorithm, was chosen since it gave the best performance. Results reveal that the NARX models are suitable for performing short time series composite indexes prediction.

     

Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance

We examine whether there is contagion from the US stock market to six Central and Eastern European stock markets. We use a novel measure of contagion that examines whether volatility shocks in the US stock market coupled with negative returns are followed by higher co-exceedance between US and emerging stock markets. Using our approach and controlling for a set of market-related variables, we show that during the period from 1998 to 2014, financial contagion occurred, that is, unexpected negative events in the US market are followed by higher co-exceedance between US and Central and Eastern European stock markets. Even though contagion is stronger during the financial crisis, it also occurs in tranquil times.     

What is the impact of problem loans on Japanese bank productivity growth?

This paper examines for the first time the impact of problem loans on Japanese productivity growth. We exploit a new data set of Japanese problem loans classified into two categories: bankrupt and restructured loans. We opt for a novel and flexible productivity growth decomposition that allows to measure the direct impact of these problem loans on productivity growth. The results reveal that Japanese bank productivity growth was severely constrained by bankrupt and restructured loans early in 2000s, whilst some persistence of the negative impact of problem loans on productivity growth is observed in the late 2000s. Thereafter, there is only some partial recovery in the productivity growth from 2012 to 2015. Further, we also perform cluster analysis to examine convergence or divergence across regions and over time. We observe limited convergence, though Regional Banks seem to form clusters in some regions.     

Transparency and trust: the case of the European Central Bank

We examine how the transparency of the European Central Bank’s monetary policy affects the amount of trust that the citizens of the European Union have in this institution. We use nearly half a million individual responses from the European Commission’s Eurobarometer survey from 2000 to 2011 and estimate probit regressions with sample selection. We find that transparency exerts a non-linear effect on trust. Transparency increases trust, but only up to a certain point; too much transparency harms trust. This result is robust to controlling for a number of macroeconomic conditions, financial stability transparency measures, and economic and socio-demographic characteristics of respondents, including examining respondents in European Union countries that do not use the euro and addressing clustering issues.