Arxiu de la categoria: Document de treball

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 2018-03: 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

XREAP2017-14: Housing booms and busts and local fiscal policy

This paper examines how local governments adjust their spending, savings and taxes in response to a temporary revenue windfall generated by a housing boom and how they cope with the inevitable shortfall that appears during the bust. We focus on Spanish local governments given the intensity of the last housing boom-bust experienced there and the large share of construction-related revenues they obtain. We find, first, that just a small share of the boom windfall was saved, with revenues being used primarily to increase spending (above all, current spending) and (to a lesser extent) cut taxes. Second, we find that the failure to save during the boom is higher in places with less informed voters and more contested elections. Third, we also examine what happens during the bust, and find that these governments had to cut abruptly their spending (above all, capital), raise taxes, and allow deficits to grow. Finally, in places wit less informed voters and more contested elections local governments had more trouble in adjusting during the bust, and they tend to rely more on spending cuts than on tax increases.

Solé-Ollé, A. (IEB, XREAP); Viladecans-Marsal, E. (IEB, XREAP)

XREAP2017-14.pdf

XREAP2017-13: The Effects of Immigration on NHS Waiting Times

This paper analyzes the effects of immigration on waiting times for the National Health Service (NHS) in England. Linking administrative records from Hospital Episode Statistics (2003-2012) with immigration data drawn from the UK Labour Force Survey, we find that immigration reduced waiting times for outpatient referrals and did not have significant effects on waiting times in accident and emergency departments (A&E) and elective care. The reduction in outpatient waiting times can be explained by the fact that immigration increases natives’ internal mobility and that immigrants tend to be healthier than natives who move to different areas. Conversely, we observe higher outpatient waiting times in places to which native internal migrants have moved. Finally, we find evidence that immigration increased waiting times for outpatient referrals in more deprived areas outside of London. The increase in average waiting times in more deprived areas is concentrated in the years immediately following the 2004 EU enlargement and disappears in the medium term (e.g., 3 to 4 years).

Giuntella, O., Nicodemo, C. (GEAP, XREAP), Vargas Silva, C.

XREAP2017-13.pdf

XREAP2017-12: Immigration and the Reallocation of Work Health Risks

This paper studies the effects of immigration on the allocation of occupational physical burden and work injury risks. Using data for England and Wales from the Labour Force Survey (2003-2013), we find that, on average, immigration leads to a reallocation of UK-born workers towards jobs characterized by lower physical burden and injury risk. The results also show important differences across skill groups. Immigration reduces the average physical burden of UK-born workers with medium levels of education, but has no significant effect on those with low levels. These findings, together with the evidence that immigrants report lower injury rates than natives, suggest that the reallocation of tasks could reduce overall health care costs and the human and financial costs typically associated with workplace injuries.

Giuntella, O., Mazzonnay, F., Nicodemo, C. (GEAP, XREAP), Vargas Silva, C.

XREAP2017-11.pdf

XREAP2017-11: Efficiency in the transformation of schooling into competences: A cross-country analysis using PIAAC data

This study (i) compares the competence levels of the adult population in a set of OECD countries; (ii) assesses the comparative efficiency with which the education system in each country transforms schooling into competences, distinguishing by educational level, and (iii) tracks the evolution of this efficiency by birth cohorts. Using PIAAC data, the paper applies standard parametric frontier techniques under two alternative specifications. The results obtained under both specifications are similar and identify Finland, Sweden, Denmark and Japan as being the most efficient and Spain, the United Kingdom, Italy, Ireland and Poland as the least efficient. The evolution of the efficiency levels by age cohorts shows that higher education is more efficient for younger cohorts, while lower and upper secondary education present a stable trend over cohorts.

Huertas, I. P.; Raymond, J. L. (GEAP, XREAP); Calero, J. (IEB, XREAP)

XREAP2017-11.pdf

XREAP2017-10: How Costly Are Labor Gender Gaps? Estimates by Age Group for the Balkans and Turkey

In this paper, survey data are used to document the presence of gender gaps in selfemployment, employership, and labor force participation in seven Balkan countries and Turkey. The paper examines the quantitative effects of the gender gaps on aggregate productivity and income per capita in these countries. In the model used to carry out this calculation, agents choose between being workers, self-employed, or employers, and women face several restrictions in the labor market. The data display very large gaps in labor force participation and in the percentage of employers and self-employed in the labor force. In almost all cases, these gaps reveal a clear underrepresentation of women. The calculations show that, on average, the loss associated with these gaps is about 17 percent of income per capita. One-third of this loss is due to distortions in the choice of occupations between men andwomen. The remaining two-thirds corresponds to the costs associated with gaps in labor force participation. The dimensions of these gender gaps and their associated costs vary considerably across ages groups, with the age bracket 36–50 years being responsible for most of the losses.

Cuberes, D., Teignier, M. (CREB, XREAP)

XREAP2017-10.pdf