Psychological pressure in competitive environments: Evidence from a randomized natural experiment

Much like cognitive abilities, emotional skills can have major effects on performance and economic outcomes. This paper studies the behavior of professionalsubjects involved in a dynamic competition in their own natural environment. Thesetting is a penalty shoot-out in soccer where two teams compete in a tournamentframework taking turns in a sequence of five penalty kicks each. As the kicking order is determined by the random outcome of a coin flip, the treatment and control groups are determined via explicit randomization. Therefore, absent any psychological effects, both teams should have the same probability of winning regardless of the kicking order. Yet, we find a systematic first-kicker advantage. Using data on 2,731 penalty kicks from 262 shoot-outs for a three decade period, we find that teams kicking first win the penalty shoot-out 60.5% of the time. A dynamic panel data analysis shows that the psychological mechanism underlying this result arises from the asymmetry in the partial score. As most kicks are scored, kicking first typically means having the opportunity to lead in the partial score, whereas kicking second typically means lagging in the score and having the opportunity to, at most, get even. Having a worse prospect than the opponent hinders subjects' performance.Further, we also find that professionals are self-aware of their own psychological effects. When a recent change in regulations gives winners of the coin toss the chance to choose the kicking order, they rationally react to it by systematically choosing to kick first. A survey of professional players reveals that when asked to explain why they prefer to kick first, they precisely identify the psychological mechanism for which we find empirical support in the data: they want to lead in the score inorder to put pressure on the opponent.

Economic integration and corruption: The corrupt soul of the European Union

We study the link between corruption and economic integration. We show that if an economic union establishes a common regulation for public procurement, the country more prone to corruption benefits more from integration. However, if the propensities to corruption are too distinct, the less corrupt country will not be willing to join the union. This difference in corruption propensities can be offset by a difference in efficiency. We also show that corruption is lower if integration occurs. A panel data analysis for the European Union confirms that more corrupt countries are more favorable towards integration but less acceptable as potential new members.

Mobility and Housing Satisfaction: An Empirical Analysis for Twelve EU Countries

Using panel data for twelve EU countries, we analyze the relationship between selfreported housing satisfaction and residential mobility. Our results indicate the existence of a positive link between the two variables and that housing satisfaction exerts a mediating effect between residential characteristics and dwellers' mobility propensities. Some interesting cross-country differences regarding the effect of other variables on mobility are also observed. Our results can be used in defining, implementing and evaluating housing and neighbourhood policies. Residential satisfaction is put forward as one of the most appropriate indicators of the success or failure of such policies. Keywords: Housing satisfaction, residential mobility JEL classification: R21, D19

High Growth Firms and Innovation: an empirical analysis for Spanish firms

This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to theirfeeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uenceon essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P,S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greaterwhite-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control(Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can givemisleading results. Therefore, to improve the interpretation of the data obtained, weused statistical techniques for compositional data analysis to define groups of metalsand to evaluate the relationships between them, from an inter-population viewpoint.Hypothesis testing on the adequate balance-coordinates allow us to confirm intuitionbased hypothesis and some previous results. The main statistical goal was to test equalmeans of balance-coordinates for the two defined populations. After checking normality,one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances

Estimating the probability of leaving unemployment using uncompleted spells from repeated cross-section data

We propose a new econometric estimation method for analyzing the probabilityof leaving unemployment using uncompleted spells from repeated cross-sectiondata, which can be especially useful when panel data are not available. Theproposed method-of-moments-based estimator has two important features:(1) it estimates the exit probability at the individual level and(2) it does not rely on the stationarity assumption of the inflowcomposition. We illustrate and gauge the performance of the proposedestimator using the Spanish Labor Force Survey data, and analyze the changesin distribution of unemployment between the 1980s and 1990s during a periodof labor market reform. We find that the relative probability of leavingunemployment of the short-term unemployed versus the long-term unemployedbecomes significantly higher in the 1990s.

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

Testing for hysteresis in unemployment in OECD countries: new evidence using stationarity panel tests with breaks

This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

Testing for hysteresis in unemployment in OECD countries: new evidence using stationarity panel tests with breaks

This paper tests hysteresis effects in unemployment using panel data for 19 OECD countries covering the period 1956-2001. The tests exploit the cross-section variations of the series, and additionally, allow for a diferent number of endogenous breakpoints in the unemployment series. The critical values are simulated based on our specific panel sizes and time periods. The findings stress the importance of accounting for exogenous shocks in the series and give support to the natural-rate hypothesis of unemployment for the majority of the countries analyzed

Impact of Duration of Primary Education on School Enrollment, Graduation and Drop-outs: A Cross- Country Analysis

Using a panel data for non-OECD countries covering the period 1970-2012, this chapter analyzes the impact of the duration of primary education on school enrollment, drop-out and completion rates. The empirical results show that for children in elementary school one ad- ditional grade of primary education have a negative impact on the enrollment rate, while the e ect on drop-outs is positive. Analogously, it is obtained that an additional grade in primary education reduces the enrollment rate in secondary education. These results are in line with the fertility model approach, that is, in developing and underdeveloped countries parents do not have incentive to send children to school given the high perceived economic value of children.

Energy efficiency determinants: An empirical analysis of Spanish innovative firms

This paper examines the extent to which innovative Spanish firms pursue improvements in energy efficiency (EE) as an objective of innovation. The increase in energy consumption and its impact on greenhouse gas emissions justifies the greater attention being paid to energy efficiency and especially to industrial EE. The ability of manufacturing companies to innovate and improve their EE has a substantial influence on attaining objectives regarding climate change mitigation. Despite the effort to design more efficient energy policies, the EE determinants in manufacturing firms have been little studied in the empirical literature. From an exhaustive sample of Spanish manufacturing firms and using a logit model, we examine the energy efficiency determinants for those firms that have innovated. To carry out the econometric analysis, we use panel data from the Community Innovation Survey for the period 2008‐2011. Our empirical results underline the role of size among the characteristics of firms that facilitate energy efficiency innovation. Regarding company behaviour, firms that consider the reduction of environmental impacts to be an important objective of innovation and that have introduced organisational innovations are more likely to innovate with the objective of increasing energy efficiency. Keywords: energy efficiency, corporate targets, innovation, Community Innovation Survey. JEL Classification: Q40, Q55, O31

Looking beneath Dalí's paint: non-destructive canvas analysis

A new analytical method was developed to non-destructively determine pH and degree of polymerisation (DP) of cellulose in fibres in 19th 20th century painting canvases, and to identify the fibre type: cotton, linen, hemp, ramie or jute. The method is based on NIR spectroscopy and multivariate data analysis, while for calibration and validation a reference collection of 199 historical canvas samples was used. The reference collection was analysed destructively using microscopy and chemical analytical methods. Partial least squares regression was used to build quantitative methods to determine pH and DP, and linear discriminant analysis was used to determine the fibre type. To interpret the obtained chemical information, an expert assessment panel developed a categorisation system to discriminate between canvases that may not be fit to withstand excessive mechanical stress, e.g. transportation. The limiting DP for this category was found to be 600. With the new method and categorisation system, canvases of 12 Dalí paintings from the Fundació Gala-Salvador Dalí (Figueres, Spain) were non-destructively analysed for pH, DP and fibre type, and their fitness determined, which informs conservation recommendations. The study demonstrates that collection-wide canvas condition surveys can be performed efficiently and non-destructively, which could significantly improve collection management.

Assessing the structural change of strategic mobility: determinants under hypercompetitive environments

The primary purpose of this exploratory empirical study is to examine the structural stability of a limited number of alternative explanatory factors of strategic change. On the basis of theoretical arguments and prior empirical evidence from two traditional perspectives, we propose an original empirical framework to analyse whether these potential explanatory factors have remained stable over time in a highly turbulent environment. This original question is explored in a particular setting: the population of Spanish private banks. The firms of this industry have experienced a high level of strategic mobility as a consequence of fundamental changes undergone in their environmental conditions over the last two decades (mainly changes related to the new banking and financial regulation process). Our results consistently support that the effect of most explanatory factors of strategic mobility considered did not remain stable over the whole period of analysis. From this point of view, the study sheds new light on major debates and dilemmas in the field of strategy regarding why firms change their competitive patterns over time and, hence, to what extent the "contextdependency" of alternative views of strategic change as their relative validation can vary over time for a given population. Methodologically, this research makes two major contributions to the study of potential determinants of strategic change. First, the definition and measurement of strategic change employing a new grouping method, the Model-based Cluster Method or MCLUST. Second, in order to asses the possible effect of determinants of strategic mobility we have controlled the non-observable heterogeneity using logistic regression models for panel data.

Convergence across countries and regions: theory and empirics

This paper surveys the recent literature on convergence across countries and regions. I discuss the main convergence and divergence mechanisms identified in the literature and develop a simple model that illustrates their implications for income dynamics. I then review the existing empirical evidence and discuss its theoretical implications. Early optimism concerning the ability of a human capital-augmented neoclassical model to explain productivity differences across economies has been questioned on the basis of more recent contributions that make use of panel data techniques and obtain theoretically implausible results. Some recent research in this area tries to reconcile these findings with sensible theoretical models by exploring the role of alternative convergence mechanisms and the possible shortcomings of panel data techniques for convergence analysis.