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This paper illustrates how outliers can affect both the estimation and testing of leverage effect by focusing on the TGARCH model. Three estimation methods are compared through Monte Carlo experiments: Gaussian Quasi-Maximum Likelihood, Quasi-Maximum Likelihood based on the Student-t likelihood and Least Absolute Deviation method. The empirical behavior of the t-ratio and the Likelihood Ratio tests for the significance of the leverage parameter is also analyzed. Our results put forward the unreliability of Gaussian Quasi-Maximum Likelihood methods in the presence of outliers. In particular, we show that one isolated outlier could hide true leverage effect whereas two consecutive outliers bias the estimated leverage coefficient in a direction that crucially depends on the sign of the first outlier and could lead to wrongly reject the null of no leverage effect or to estimate asymmetries of the wrong sign. By contrast, we highlight the good performance of the robust estimators in the presence of one isolated outlier. However, when there are patches of outliers, our findings suggest that the sizes and powers of the tests as well as the estimated parameters based on robust methods may still be distorted in some cases. We illustrate these results with two series of daily returns. ; Generalitat Valenciana, Funder Id: http://dx.doi.org/10.13039/501100003359, Grant Number: AICO/2019/295. Consejería de Educación, Junta de Castilla y León, Funder Id: http://dx.doi.org/10.13039/501100008431, Grant Number: VA148G18. Spanish Government, Grant Number: ECO2017-87069-P and ECO2016-77900-P.

The objective of this paper is to replicate the results in Kristoufek (2014) on the leverage effect in energy futures and to analyze its robustness to both the methodology and the type of returns used. We first apply correlation-based tools for detecting both conditional heteroscedasticity and leverage effect. Then, we estimate asymmetric and long memory GARCH-type models using the data provided by Kristoufek (2014) by considering different software and the possibility that innovations follow a non-Gaussian distribution. Our findings confirm most of the results in the replicated paper. In particular, we can strongly confirm there is a significant leverage effect in the return series of WTI (West Texas Intermediate) and Brent crude oils. For the heating oil and the natural gas series, the statistical significance of the leverage effect depends on both the methodology and the type of returns used. ; Financial support from the Spanish Government under projects ECO2017-87069-P and ECO2016-77900-P is gratefully acknowledged by the first and second authors, respectively.

This paper analyzes the performance of multiple steps estimators of vector autoregressive multivariate conditional correlation GARCH models by means of Monte Carlo experiments. We show that if innovations are Gaussian, estimating the parameters in multiple steps is a reasonable alternative to the maximization of the full likelihood function. Our results also suggest that for the sample sizes usually encountered in financial econometrics, the differences between the volatility and correlation estimates obtained with the more efficient estimator and the multiple steps estimators are negligible. However, when innovations are distributed as a Student-t, using multiple steps estimators might not be a good idea. ; Financial support from IVIE (Instituto Valenciano de Investigaciones Económicas) to the project "Estimating Multivariate GARCH Models in Multiple Steps with an Application to Stock Markets" is gratefully acknowledged. We also acknowledge the Spanish Government for grant ECO2011-29751.

This article studies the relationship between the prices of fuel and EU Allowances (EUA) for carbon emissions during Phase 3 of the European Union Emissions Trading System. We find that the forward prices of EUA, coal, gas and Brent oil are jointly determined in equilibrium. The existence of such a long-run relationship entails a permanent-transitory decomposition for the series of EUA and fuel prices that reveals the short- and long-term causal influence of the EUA market in shaping the joint dynamics of fuel prices. This result complements the literature that suggests that EUA prices are driven by the dynamics of fuel prices. Interestingly, we do not find an equilibrium relationship in the spot market. EUA and fuel spot prices are driven by independent unit root processes. The differences between spot and forward markets are attributed to the tradability of forward prices that are used for speculation and hedging in financial markets. In contrast, spot prices are mainly driven by supply and demand in energy markets.

This article studies the relationship between the prices of fuel and EU Allowances (EUA) for carbon emissions during Phase 3 of the European Union Emissions Trading System. We find that the forward prices of EUA, coal, gas and Brent oil are jointly determined in equilibrium. The existence of such a long-run relationship entails a permanent-transitory decomposition for the series of EUA and fuel prices that reveals the short- and long-term causal influence of the EUA market in shaping the joint dynamics of fuel prices. This result complements the literature that suggests that EUA prices are driven by the dynamics of fuel prices. Interestingly, we do not find an equilibrium relationship in the spot market. EUA and fuel spot prices are driven by independent unit root processes. The differences between spot and forward markets are attributed to the tradability of forward prices that are used for speculation and hedging in financial markets. In contrast, spot prices are mainly driven by supply and demand in energy markets. ; This research was funded by Spanish Government under Grant Number ECO2017-87069-P, and the APC was funded by Newbers Energy Analytics.

This article studies the services exchanged in a particular Spanish time bank. Using data from users and transactions, we analyse the users' profile as well as the determinants of providing and receiving different services. Our results show that the representative user is a Spanish female, not married, middle aged, highly educated and unemployed. We also find differences in the personal characteristics driving the supply and demand of services. ; Financial support from the Spanish Government under project ECO2011-29751 by the first author, under project ECO2010-17943 by the second author and under project ECO2012-32854 by the third author is gratefully acknowledged. The first author also acknowledges financial support from Generalitat Valenciana under project PROMETEO/2013/037.

The objective of this paper is to analyze empirically the problem of mobbing in Spain. Based on the fifth Spanish survey on working conditions, we find that during 2003, around 5% of workers declared being mobbed at their workplace. Some personal, job characteristics and working conditions are found to be significant at explaining the probability of being a mobbing victim. Finally, we find differences in the variables affecting such probability depending on the victim's gender