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Objective: The article evaluates the 2007 introduction of nontransferable and fully paid paternity leave in Spain. Background: Previous research has focused on paternity leave reforms, especially in the Nordic and continental countries. This article studies characteristics of the parental leave system design, including transferability, payment, and purpose of different types of leave for mothers and fathers in a Mediterranean country. Method: We use a quasi‐experimental approach based on a sample of heterosexual dual‐earner couples with children born before and after the paternity leave introduction. We estimate differences in differences regression models. Results: The 2007 reform caused a significant increase in fathers' number of days of parental leave. Most fathers used the whole nontransferable and fully paid paternity leave, but they hardly used transferable or unpaid leave. Mothers used all of these, especially paid leave. Conclusion: The number of nontransferable fully paid days of parental leave provided by law approximates the actual number of days most fathers used. Implications: The policy design matters. A design of equal, nontransferable, and fully paid leave for each parent is necessary for equal use by fathers and mothers—and thus for gender equality in families and work. [ABSTRACT FROM AUTHOR]

Structural change tests aim to identify evidence of a structural break or change in the underlying generating process of a time series. The BDS test has its origins in chaos theory and seeks to test, using the correlation integral, the hypothesis that a time series is generated by an identically and independently distributed (IID) stochastic process over time. The BDS test is already widely used as a powerful tool for testing the hypothesis of white noise in the residuals of time series models. In this paper, we illustrate how the BDS test can be implemented also in a recursive manner to evaluate the hypothesis of structural change in a time series, taking advantage of its ability to test the IID hypothesis. We apply the BDS test repeatedly, starting with a sub-sample of the original time series and incrementally increasing the number of observations until it is applied to the full sample time series. A structural change in the unknown underlying generator model is detected when a change in the trend shown by this recursively computed BDS statistic is detected. The strength of this recursive BDS test lies in the fact that it does not require making any assumptions about the underlying time series generator model. We ilustrate the power and potential of this recursive BDS test through an application to real economic data. In this sense, we apply the test to assess the structural changes caused by the COVID-19 pandemic in international financial markets. Using daily data from the world's top stock indices, we have detected strong and statistically significant evidence of two major structural changes during the period from June 2018 to June 2022. The first occurred in March 2020, coinciding with the onset of economic restrictions in the main Western countries as a result of the pandemic. The second occurred towards the end of August 2020, with the end of the main economic restrictions and the beginning of a new post-pandemic economic scenario. This methodology to test for structural changes in a time series is easy to implement and can detect changes in any system or process behind the time series even when this generating system is not known, and without the need to specify or estimate any a priori generating model. In this sense, the recursive BDS test could be incorporated as an initial preliminary step to any exercise of time series modeling. If a structural change is detected in a time series, rather than estimating a single predictive model for the full-sample time series, efforts should be made to estimate different predictive models, one for the time before and one for the time after the detected structural change. [ABSTRACT FROM AUTHOR]

Chaos theory has been hailed as a revolution of thoughts and attracting ever-increasing attention of many scientists from diverse disciplines. Chaotic systems are non-linear deterministic dynamic systems which can behave like an erratic and apparently random motion. A relevant field inside chaos theory is the detection of chaotic behavior from empirical time-series data. One of the main features of chaos is the well-known initial-value sensitivity property. Methods and techniques related to testing the hypothesis of chaos try to quantify the initial-value sensitive property estimating the so-called Lyapunov exponents. This paper describes the main estimation methods of the Lyapunov exponent from time series data. At the same time, we present the DChaos library. R users may compute the delayed-coordinate embedding vector from time series data, estimates the best-fitted neural net model from the delayed-coordinate embedding vectors, calculates analytically the partial derivatives from the chosen neural nets model. They can also obtain the neural net estimator of the Lyapunov exponent from the partial derivatives computed previously by two different procedures and four ways of subsampling by blocks. To sum up, the DChaos package allows the R users to test robustly the hypothesis of chaos in order to know if the data-generating process behind time series behaves chaotically or not. The package's functionality is illustrated by examples. [ABSTRACT FROM AUTHOR]

• Two new computational algorithms are proposed for estimating the Lyapunov exponents from time series data in order to test the null hypothesis of a chaotic behavior. • The results obtained provide robust evidence that the Jacobian indirect methods provide better estimates than traditional direct methods in all the experiments we have conducted. • We have shown empirically that the algorithms proposed are robust to the presence of (small) measurement errors because the results obtained are comparable to those which are noise free. • The empirical size of the algorithms proposed decreased and the empirical power increased as the sample size increased which means that our hypothesis tests are consistent and reliable. • This paper opens a new research line where new contributions may appear considering new machine learning methods and deep learning algorithms for estimating the Lyapunov exponents from time series data. Most of the existing methods and techniques for the detection of chaotic behaviour from empirical time series try to quantify the well-known sensitivity to initial conditions through the estimation of the so-called Lyapunov exponents corresponding to the data generating system, even if this system is unknown. Some of these methods are designed to operate in noise-free environments, such as those methods that directly quantify the separation rate of two initially close trajectories. As an alternative, this paper provides two nonlinear indirect regression methods for estimating the Lyapunov exponents on a noisy environment. We extend the global Jacobian method, by using local polynomial kernel regressions and local neural net kernel models. We apply such methods to several noise-contaminated time series coming from different data generating processes. The results show that in general, the Jacobian indirect methods provide better results than the traditional direct methods for both clean and noisy time series. Moreover, the local Jacobian indirect methods provide more robust and accurate fit than the global ones, with the methods using local networks obtaining more accurate results than those using local polynomials. [ABSTRACT FROM AUTHOR]

While football is a billionaire spectacle, the figure of the referee mainly presents an amateur career and a notorious diversity among the different national and regional federations. In this article, we analyse which variables determine the lifespan of the referee's career in Madrid. We apply survival analysis toa dataset of 2,978 registered referees provided by the Real Federation de Fútbol de Madrid (RFFM). The results show relevant conclusions like the different career paths of men and women, the incidence of belonging to each of the three branch offices, the effect of being a 'talent', which are the category levels where men and women mainly drop, the relevance of starting on an earlier age and the positive effect of having been born in Madrid for men. They all constitute remarkable insights to be considered when establishing recruitment policies, training and development and support for young and active referees. [ABSTRACT FROM AUTHOR]

This article addresses the question of to what extent young people show an inclination to accept some sacrifice in their career progression in the future in order to reach a better work–family balance. Data come from a survey conducted among a sample of 2383 university students who attended three universities: University of Nairobi, University of Iceland, and Complutense University of Madrid. After building a set of indicators about career and family involvement aspirations of respondents, and after conducting a statistical and regression analysis, this research shows that young women (on average) still have a greater predisposition than young men to make sacrifices in the future in their working careers in order to achieve a better work–family balance. Moreover, having a high degree of leadership aspirations and belonging to an egalitarian household tend to reduce the inclination to sacrifice career opportunities, whereas having a high inclination to be involved in childcare in the future and having the perception of a future work–family conflict tend to increase it. Gender attitudes have a differential effect on female and male students: having traditional gender attitudes tends to increase the inclination to sacrifice career opportunities in the case of female students and reduce it in the case of male students. [ABSTRACT FROM AUTHOR]

This article is based on a survey that we conducted among 1,130 couples with children 38 years old, in Madrid and its metropolitan area. This allowed us, in the first place to obtain an estimation of the take-up rate and duration of the different kinds of childbirth leaves that Spanish workers use when they have or adopt a child. In the second place, the participation of the father has been analyzed in comparison to the mother's in 18 specific childcare activities. A measure for father involvement in childcare (relative to the mother) that included 14 non-playful activities of childcare was built from there. Then, from a quantitative analysis with path analysis modelling with Amos program, we have obtained evidence that fathers who took more time off later tended to be more involved in the most routine childcare activities. Moreover, when considering other determinants of father's involvement in childcare, we can highlight the importance of having egalitarian gender attitudes, working in a family-friendly company, the net earnings, and the mother's working week. Most of these variables affect father's involvement in childcare directly and indirectly, through their effects on the duration of childbirth leave (which serves as a mediating variable). Finally, a specific determinant of the duration of childcare leave was the introduction of a 13-day paternity leave in Spain, in March 2007. [ABSTRACT FROM AUTHOR]

The main idea proposed in this article is that organizations which provide facilities for reconciling working and family life among their employees-family-friendly companies-not only make it easier for mothers to combine work and family, but also, for fathers. Consequently, working in this type of environment may stimulate the father's involvement in childcare. For the case of Spain, based on the sample of 3,094 males originating in the macro Survey of Quality of Life in the Workplace of 2007, an indicator of a family-friendly company was constructed. From this indicator, as well as other socio-labor variables that appear in the survey, a descriptive statistical analysis and a multivariate logistic regression analysis was carried in order to know, first, if working in this type of workplace exerts a positive effect on male workers' willingness to take maternity leave (in the event of having a child); and, second, what is the effect on this willingness of some other relevant socio-labor variables (age, university studies, non-working partner, working in public administration and high net monthly earnings). Findings indicated that age, having a non-working partner and being high income men are factors reducing male workers' inclination to ask for leave. And, conversely, working in family-friendly companies makes it more likely that males will take leave. [ABSTRACT FROM AUTHOR]

In this paper we applied the dynamic system theory to the measurement of the stability of the European process of convergence. In particular, Lyapunov's exponents are used to verify the influence of political and economic decisions made during the creation of the European Union on the stability (or instability) of exchange rate fluctuation in different European countries. We find evidence of such relationship. [ABSTRACT FROM AUTHOR]

A controlled experiment was conducted to detect gender biases that participants, acting as advisers, may have when providing guidance to teenagers on their career choice. We presented a fictional profile to the study participants – university students from Spain – of a 15-year-old person, called Manuel or María, with two possible levels of academic record. The participants were asked to evaluate the student's mathematical ability and provide guidance regarding whether or not he or she should study engineering in the future. We assumed that the effect of being a male target on the recommendation to study engineering is partially mediated by the fact that the participants attribute a greater mathematical ability to males. Our results suggest that a significant degree of gender bias in favour of males persists in the recommendation to study engineering. We propose some practical implications for advisers and for equality policies. [ABSTRACT FROM AUTHOR]