Archivos de la categoría Documento de trabajo

XREAP2018-09: Relocation of the Rich: Migration in Response to Top Tax Rate Changes from Spanish Reforms

Recent Spanish tax reform granted regions the authority to set income tax rates, resulting in substantial tax differentials. We use individual-level information from Social Security records over a period of one decade. Conditional on moving, taxes have a significant effect on location choice. A one percent increase in the net of tax rate for a region relative to others increases the probability of moving to that region by 1.7 percentage points. Focusing on the stock of top-taxpayers, we estimate an elasticity of the number of top taxpayers with respect to net-of-tax rates of 0.85. Using this elasticity, a theoretical model implies that the mechanical increase in tax revenue due to higher tax rates is larger than the loss in tax revenue from the outflow of migration.

Agrawal,D.R., Foremny, D. (IEB, XREAP)

XREAP2018-09.pdf

 

XREAP2018-08: Long-Lasting Social Capital and its Impact on Economic Development: The Legacy of the Commons

This paper analyzes the historical determinants and long-term persistence of social capital, as well as its effect on economic development, by looking at the legacy of the commons in a Spanish region. In medieval times, common goods were granted to townships and were managed collectively by local citizens. This enabled the establishment of institutions for collective action and self-government. Common goods persisted until the second half of the nineteenth century. We argue that the experience of cooperation among villagers, repeated over the centuries, increased the social capital in each local community. In 1845, a law forced small villages to merge with others, a fact which generated exogenous variation in the number of mergers (i.e., cooperative networks) that each modern municipality was required to have. We exploit this change in an IV and RD setting and find that current municipalities formed by a greater number of old townships have a denser network of associations. We also find that higher social capital is associated with more economic development.

Montolio, D. (IEB, XREAP); Tur-Prats, A.

XREAP2018-08.pdf

 

XREAP2018-07: Economic Crisis and Social Trust: Reviewing the effects of economic hardship on interpersonal and institutional confidence

The economic crisis of 2008 led to a significant erosion of trust in those countries that were hit hardest. However, whether this fall in trust can best be explained by external economic factors or by the lack of response on the part of the institutions to civic needs and demands is unclear. This study seeks to address this question by examining the specific case of Spain. Its aim is to analyse in comparison with other factors, the effect of increasing socioeconomic precariousness upon levels of interpersonal and institutional trust. The study examines the respective impact of these factors upon different social groups according to their degree of exposure to the effects of the crisis. Our results show that the deterioration suffered by household economies has important consequences in terms of interpersonal trust. Those most severely affected by the recession lose a great deal of trust in others. We also find that a deterioration in socioeconomic conditions has different effects in relation to institutional trust. The perception of the overall state of the economy is important for all types of institutional trust. Without calling into question the importance of institutional performance on levels of institutional trust, our research sheds new light on the importance of different economic factors for social cohesion.

Torrente, D.; Caïs, J.; Bolancé, C. (RISKCENTER, XREAP)

XREAP2018-07.pdf

 

XREAP 2018-06: New Imported Inputs, Wages and Worker Mobility

We provide a comprehensive assessment of the effects of new imported inputs on wage dynamics, on the skill-composition of the labor force, on worker mobility, and on the efficiency of matching between firms and workers. We employ matched employer-employee data for Italy, over 1995-2007. We complement these data with information on the arrival of new imported inputs at the industry level. We find new imported inputs to have a positive effect on average wage growth at the firm level. This effect is driven by two factors: (1) an increase in the white-collar/blue-collar ratio; and (2) an increase in the average wage growth of blue-collar workers, while the wage growth of white collars is not significantly affected. The individual-level analysis reveals that the increase in the average wage of blue collars is driven by the displacement of the lowest paid workers, while continuously employed individuals are not affected. We estimate the unobserved skills of workers following Abowd et al. (1999). We find evidence that new imported inputs lead to a positive selection of higher-skilled workers, and to an improvement in positive assortative matching between firms and workers.

Colantone, I.; Matano, A. (AQR-IREA, XREAP); Naticchioni, P.

XREAP2018-06.pdf

XREAP 2018-05: Alternative methods of estimating the longevity risk

The aim of this paper is to estimate the longevity risk and its trend according to the age of the individual. We focus on individuals over 65. We use the value-at-risk to measure the longevity risk. We have proposed the use of an alternative methodology based on the estimation of the truncated cumulative distribution function and the quantiles. We apply a robust estimation method for fitting parametric distributions. Finally, we compare
parametric and nonparametric estimations of longevity risk.

Bolance, C. (RISKCENTER-IREA, XREAP); Guillén, M. (RISKCENTER-IREA, XREAP); Ornelas, A. (RISKCENTER-IREA, XREAP)

XREAP2018-05.pdf

XREAP 2018-04: Tracking economic growth by evolving expectations via genetic programming: A two-step approach

The main objective of this study is to present a two-step approach to generate estimates of economic growth based on agents’ expectations from tendency surveys. First, we design a genetic programming experiment to derive mathematical functional forms that approximate the target variable by combining survey data on expectations about different economic variables. We use evolutionary algorithms to estimate a symbolic regression that links survey-based expectations to a quantitative variable used as a yardstick (economic growth). In a second step, this set of empirically-generated proxies of economic growth are linearly combined to track the evolution of GDP. To evaluate the forecasting performance of the generated estimates of GDP, we use them to assess the impact of the 2008 financial crisis on the accuracy of agents’ expectations about the evolution of the economic activity in 28 countries of the OECD. While in most economies we find an improvement in the capacity of agents’ to anticipate the evolution of GDP after the crisis, predictive accuracy worsens in relation to the period prior to the crisis. The most accurate GDP forecasts are obtained for Sweden, Austria and Finland.

Claveria, O. (AQR-IREA, XREAP); Monte, E.; Torra, S. (RISKCENTER, XREAP)

XREAP2018-04.pdf

XREAP 2018-03: Machine Learning Forecasts of Public Transport Demand: A comparative analysis of supervised algorithms using smart card data

Public transport smart cards are widely used around the world. However, while they provide information about various aspects of passenger behavior, they have not been properly exploited to predict demand. Indeed, traditional methods in economics employ linear unbiased estimators that pay little attention to accuracy, which is the main problem faced by the sector’s regulators. This paper reports the application of various supervised machine learning (SML) techniques to smart card data in order to forecast demand, and it compares these outcomes with traditional linear model estimates. We conclude that the forecasts obtained from these algorithms are much more accurate.

Palacio, S. M. (GiM, XREAP)

XREAP2018-03.pdf

XREAP 2018-02: Detecting Outliers with Semi-Supervised Machine Learning: A Fraud Prediction Application

Abnormal pattern prediction has received a great deal of attention from both academia and industry, with applications that range from fraud, terrorism and intrusion detection to sensor events, medical diagnoses, weather patterns, etc. In practice, most abnormal pattern prediction problems are characterized by the presence of a small number of labeled data and a huge number of unlabeled data. While this points most obviously to the adoption of a semi-supervised approach, most empirical studies have opted for a simplification and treated it as a supervised problem, resulting in a severe bias of false negatives. In this paper, we propose an innovative methodology based on semi-supervised techniques and introduce a new metric the Cluster-Score for abnormal homogeneity measurement. Specifically, the methodology involves transmuting unsupervised models to supervised models using the Cluster-Score metric, which defines the objective boundaries between clusters and evaluates the homogeneity of the abnormalities in the cluster construction. We apply this methodology to a problem of fraud detection among property insurance claims. The objectives are to increase the number of fraudulent claims detected and to reduce the proportion of claims investigated that are, in fact, non-fraudulent. The results from applying our methodology considerably improved these objectives.

Palacio, S. M. (GiM, XREAP)

XREAP2018-02.pdf

XREAP2018-01: GENDER DIVERSITY, R&D TEAMS AND PATENTS: AN APPLICATION TO SPANISH FIRMS

Previous results show that gender diversity increases the probability that firms invest in R&D and engage in innovation. This paper explores the relationship between gender diversity of R&D departments and their capacity to patent. Based on the Spanish Community Innovation Survey between 2004 and 2014, we apply a two-step procedure in order to control for endogeneity. Although gender diversity affects OEPM patents negatively, its impact is non-significant for patents with international coverage (EPO, USPTO, or PCT). A relevant result is the fact that the generation of patents is positively affected by the diversity of categories in the R&D labs. Our results highlight that, gender diversity of R&D teams does not play a relevant impact on the capacity of the firm to register patents. However, the diversity according to the professional role in R&D teams exerts a positive influence. In sum, the key question is not the gender diversity per se but the gender diversity jointly with the professional status.

Teruel, M. (GRIT, XREAP); Segarra-Blasco, A. (GRIT, XREAP)

XREAP2018-01.pdf

XREAP2017-15: Eco-strategies and firm growth in European SMEs

This study investigates the effects of eco-strategies on firm performance in terms of sales growth in an extensive sample of 11,336 small and medium-sized enterprises (SMEs) located in 28 European countries. Our empirical results suggest that not all eco-strategies are positively related to better performance, at least not in the short term. We find that European companies using renewable energies, recycling or designing products that are easier to maintain, repair or reuse perform better. Those that aim to reduce water or energy pollution, however, seem to show a negative correlation to firm growth. Our results, also, indicate that high investment in eco-strategies improves firm growth, particularly in new members that joined the EU from 2004 onwards. Finally, we observe a U-shaped relationship between eco-strategies and firm growth, which indicates that a greater breadth of eco-strategies is associated with better firm performance. However, few European SMEs are able to either invest heavily or undertake multiple eco-strategies, thus leaving room for policy interventions.

Jové-Llopis, E. (GRIT, XREAP); Segarra-Blasco, A. (GRIT, XREAP)

XREAP2017-15.pdf