Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal

This comment corrects the errors in the estimation process that appear in Martins (2001). The first error is in the parametric probit estimation, as the previously presented results do not maximize the log-likelihood function. In the global maximum more variables become significant. As for the semiparametric estimation method, the kernel function used in Martins (2001) can take on both positive and negative values, which implies that the participation probability estimates may be outside the interval [0,1]. We have solved the problem by applying local smoothing in the kernel estimation, as suggested by Klein and Spady (1993).

Knowledge of Catalan, public/private sector choice and earnings: Evidence from a double sample selection model

This paper explores the earnings return to Catalan knowledge for public and private workers in Catalonia. In doing so, we allow for a double simultaneous selection process. We consider, on the one hand, the non-random allocation of workers into one sector or another, and on the other, the potential self-selection into Catalan proficiency. In addition, when correcting the earnings equations, we take into account the correlation between the two selectivity rules. Our findings suggest that the apparent higher language return for public sector workers is entirely accounted for by selection effects, whereas knowledge of Catalan has a significant positive return in the private sector, which is somewhat higher when the selection processes are taken into account.

Selection bias and unobservable heterogeneity applied at the wage equation of European married women

This paper utilizes a panel data sample selection model to correct the selection in the analysis of longitudinal labor market data for married women in European countries. We estimate the female wage equation in a framework of unbalanced panel data models with sample selection. The wage equations of females have several potential sources of.

Innovation and firm growth: Does firm age play a role?

This paper explores the relationship between firm growth, innovation and firm age. We hypothesize that young firms undertake riskier innovation activities and are more oriented towards employment growth than towards harvesting returns in the form of sales growth. Using an extensive sample of Community Innovation Survey for the period 2004-2010, we apply quantile regressions and a Heckman sample selection technique to study the impact of R&D activities on firm growth according to firm age. Our results show that R&D intensity is positively associated with firm growth. However, for young firms R&D shows an increasing influence across the quantiles, while for old firms R&D shows a stable or perhaps decreasing effect over the quantiles. Firm age shows a significant negative impact among young firms, while for the sample of old firms the impact of firm age becomes non-significant. Our Heckman estimations show the evolution of the impact of the R&D on firm growth confirming a significant impact on sales and productivity growth, while the impact is negligible for employment growth. Keywords: firm age, firm growth, innovation, quantile regression. JEL CODES: L25, L20

Do Spanish informal caregivers come to the rescue of dependent people with formal care unmet needs?

This paper analyses the effect of unmet formal care needs on informal caregiving hours in Spain using the two wavesof the Informal Support Survey (1994, 2004). Testing for double sample selection from formal care receipt and theemergence of unmet needs provides evidence that the omission of either variable would causes underestimation of thenumber of informal caregiving hours. After controlling for these two factors the number of hours of care increaseswith both the degree of dependency and unmet needs. More importantly, in the presence of unmet needs, the numberof informal caregiving hours increases when some formal care is received. This result refutes the substitution modeland supports complementarity or task specificity between both types of care. For a given combination of formal careand unmet needs, informal caregiving hours increased between 1994 and 2004. Finally, in the model for 2004, theselection term associated with the unmet needs equation is larger than that of the formal care equation, suggestingthat using the number of formal care recipients as a quality indicator may be confounding, if we do not complete thisinformation with other quality indicators.

Trade-off between formal and informal care in Spain

The remarkable growth of older population has moved long term care to the front ranks of the social policy agenda. Understanding the factors that determine the type and amount of formal care is important for predicting use in the future and developing long-term policy. In this context we jointly analyze the choice of care (formal, informal, both together or none) as well as the number of hours of care received. Given that the number of hours of care is not independent of the type of care received, we estimate, for the first time in this area of research, a sample selection model with the particularity that the first step is a multinomial logit model. With regard to the debate about complementarity or substitutability between formal and informal care, our results indicate that formal care acts as a reinforcement of the family care in certain cases: for very old care receivers, in those cases in which the individual has multiple disabilities, when many care hours are provided, and in case of mental illness and/or dementia. There exist substantial differences in long term care addressed to younger and older dependent people and dependent women are in risk of becoming more vulnerable to the shortage of informal caregivers in the future. Finally, we have documented that there are great disparities in the availability of public social care across regions.

How well do individuals predict the selling prices of their homes?

Self-reported home values are widely used as a measure of housing wealth by researchers employing a variety of data sets and studying a number of different individual and household level decisions. The accuracy of this measure is an open empirical question, and requires some type of market assessment of the values reported. In this research, we study the predictive power of self-reported housing wealth when estimating sales prices utilizing the Health and Retirement Study. We find that homeowners, on average, overestimate the value of their properties by between 5% and 10%. More importantly, we are the first to document a strong correlation between accuracy and the economic conditions at the time of the purchase of the property (measured by the prevalent interest rate, the growth of household income, and the growth of median housing prices). While most individuals overestimate the value of their properties, those who bought during more difficult economic times tend to be more accurate, and in some cases even underestimate the value of their house. These results establish a surprisingly strong, likely permanent, and in many cases long-lived, effect of the initial conditions surrounding the purchases of properties, on how individuals value them. This cyclicality of the overestimation of house prices can provide some explanations for the difficulties currently faced by many homeowners, who were expecting large appreciations in home value to rescue them in case of increases in interest rates which could jeopardize their ability to live up to their financial commitments.

High-growth firms and innovation: an empirical analysis for Spanish firms

This paper analyses the effect of R&D investment on firm growth. We use an extensive sample of Spanish manufacturing and service firms. The database comprises diverse waves of Spanish Community Innovation Survey and covers the period 2004–2008. First, a probit model corrected for sample selection analyses the role of innovation on the probability of being a high-growth firm (HGF). Second, a quantile regression technique is applied to explore the determinants of firm growth. Our database shows that a small number of firms experience fast growth rates in terms of sales or employees. Our results reveal that R&D investments positively affect the probability of becoming a HGF. However, differences appear between manufacturing and service firms. Finally, when we study the impact of R&D investment on firm growth, quantile estimations show that internal R&D presents a significant positive impact for the upper quantiles, while external R&D shows a significant positive impact up to the median. Keywords : High-growth firms, Firm growth, Innovation activity. JEL Classifications : L11, L25, L26, O30

Measuring intergenerational earnings mobility in Spain: a selection-bias-free approach

This paper analyses intergenerational earnings mobility in Spain correcting for different selection biases. We address the co-residence selection problem by combining information from two samples and using the two-sample two-stage least square estimator. We find a small decrease in elasticity when we move to younger cohorts. Furthermore, we find a higher correlation in the case of daughters than in the case of sons; however, when we consider the employment selection in the case of daughters, by adopting a Heckman-type correction method, the diference between sons and daughters disappears. By decomposing the sources of earnings elasticity across generations, we find that the correlation between child's and father's occupation is the most important component. Finally, quantile regressions estimates show that the influence of the father's earnings is greater when we move to the lower tail of the offspring's earnings distribution, especially in the case of daughters' earnings.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Adaptive model selection using empirical complexities

Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

Citation auctions as a method to improve selection of scientific papers

This paper describes the basis of citation auctions as a new approach to selecting scientific papers for publication. Our main idea is to use an auction for selecting papers for publication through - differently from the state of the art - bids that consist of the number of citations that a scientist expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper's content to judge the quality of its contribution. Additionally, the method will not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives. Sample analyses of the number of citations collected in papers published in years 1999-2004 for one journal, and in years 2003-2005 for a series of conferences (in a totally different discipline), via Google scholar, are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach

Single period Markowitz portfolio selection, performance gauging and duality: a variation on Luenberger's shortage function

Markowitz portfolio theory (1952) has induced research into the efficiency of portfolio management. This paper studies existing nonparametric efficiency measurement approaches for single period portfolio selection from a theoretical perspective and generalises currently used efficiency measures into the full mean-variance space. Therefore, we introduce the efficiency improvement possibility function (a variation on the shortage function), study its axiomatic properties in the context of Markowitz efficient frontier, and establish a link to the indirect mean-variance utility function. This framework allows distinguishing between portfolio efficiency and allocative efficiency. Furthermore, it permits retrieving information about the revealed risk aversion of investors. The efficiency improvement possibility function thus provides a more general framework for gauging the efficiency of portfolio management using nonparametric frontier envelopment methods based on quadratic optimisation.

The Cost of ownership in the governance of interfirm collaborations

This paper investigates the selection of governance forms in interfirm collaborations taking into account the predictions from transaction costs and property rights theories. Transaction costs arguments are often used to justify the introduction of hierarchical controls in collaborations, but the ownership dimension of going from “contracts” to “hierarchies” has been ignored in the past and with it the so called “costs of ownership”. The theoretical results, tested with a sample of collaborations in which participate Spanish firms, indicate that the cost of ownership may offset the benefits of hierarchical controls and therefore limit their diffusion. Evidence is also reported of possible complementarities between reputation effects and forms of ownership that go together with hierarchical controls (i.e. joint ventures), in contrast with the generally assumed substitutability between the two.