Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation -intramural and external R&D- on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140. Keywords: Innovation sources, R&D, Productivity, Quantile regression

Innovation sources and productivity: a quantile regression analysis

This paper explores the effects of two main sources of innovation —intramural and external R&D— on the productivity level in a sample of 3,267 Catalan firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and services industries.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

How wide is the gap? An investigation of gender wage differences using quantile regression

In this paper we examine the determinants of wages and decompose theobserved differences across genders into the "explained by differentcharacteristics" and "explained by different returns components"using a sample of Spanish workers. Apart from the conditionalexpectation of wages, we estimate the conditional quantile functionsfor men and women and find that both the absolute wage gap and thepart attributed to different returns at each of the quantiles, farfrom being well represented by their counterparts at the mean, aregreater as we move up in the wage range.

The importance of individual heterogeneity in the decomposition of measures of socioeconomic inequality in health: An approach based on quantile regression

This paper shows how recently developed regression-based methods for thedecomposition of health inequality can be extended to incorporateindividual heterogeneity in the responses of health to the explanatoryvariables. We illustrate our method with an application to the CanadianNPHS of 1994. Our strategy for the estimation of heterogeneous responsesis based on the quantile regression model. The results suggest that thereis an important degree of heterogeneity in the association of health toexplanatory variables which, in turn, accounts for a substantial percentageof inequality in observed health. A particularly interesting finding isthat the marginal response of health to income is zero for healthyindividuals but positive and significant for unhealthy individuals. Theheterogeneity in the income response reduces both overall health inequalityand income related health inequality.

Eyes wide shut - unusual two stage repair of pectus excavatum and annuloaortic ectasia in a 37 year old marfan patient: Case report

We report about a 37 year old male patient with a pectus excavatum. The patient was in NYHA functional class III. After performed computed tomography the symptoms were thought to be related to the severity of chest deformation. A Ravitch-procedure had been accomplished in a district hospital in 2009. The crack of a metal bar led to a reevaluation 2010, in which surprisingly the presence of an annuloaortic ectasia (root 73 × 74 mm) in direct neighborhood of the formerly implanted metal-bars was diagnosed. Echocardiography revealed a severe aortic valve regurgitation, the left ventricle was massively dilated presenting a reduced ejection fraction of 45%. A marfan syndrome was suspected and the patient underwent a valve sparing aortic root replacement (David procedure) in our institution with an uneventful postoperative course. A review of the literature in combination with discussion of our case suggests the application of stronger recommendations towards preoperative cardiovascular assessment in patients with pectus excavatum.

Innovation and absorptive capacity: What is the role of technological frontier?

This paper explores how absorptive capacity affects the innovative performance and productivity dynamics of Spanish firms. A firm’s efficiency levels are measured using two variables: the labour productivity and the Total Factor Productivity (TFP). The theoretical framework is based on the seminal contributions of Cohen and Levinthal (1989, 1990) regarding absorptive capacity; and the applied framework is based on the four-stage structural model proposed by Crépon, Duguet and Mairesse (1998) for setting the determinants of R&D, the effects of R&D activities on innovation outputs, and the impacts of innovation on firm productivity. The present study uses a twostage structural model. In the first stage, a probit estimation is used to investigate how the sources of R&D, the absorptive capacity and a vector of the firm’s individual features influence the firm’s likelihood of developing innovations in products or processes. In the second phase, a quantile regression is used to analyze the effect of R&D sources, absorptive capacity and firm characteristics on productivity. This method shows the elasticity of each exogenous variable on productivity according to the firms’ levels of efficiency, and thus allows us to distinguish between firms that are close to the technological frontier and those that are further away from it. We used extensive firm-level panel data from 5,575 firms for the 2004-2009 period. The results show that the internal absorptive capacity has a strong impact on the productivity of firms, whereas the role of external absorptive capacity differs according to nature of the each industry and according the distance of firms from the technological frontier. Key words: R&D sources, innovation strategies, absorptive capacity, technological distance, quantile regression.

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.

Changes in wage structure in Mexico going beyond the mean: An analysis of differences in distribution, 1987-2008

This paper conducts an empirical analysis of the relationship between wage inequality, employment structure, and returns to education in urban areas of Mexico during the past two decades (1987-2008). Applying Melly’s (2005) quantile regression based decomposition, we find that changes in wage inequality have been driven mainly by variations in educational wage premia. Additionally, we find that changes in employment structure, including occupation and firm size, have played a vital role. This evidence seems to suggest that the changes in wage inequality in urban Mexico cannot be interpreted in terms of a skill-biased change, but rather they are the result of an increasing demand for skills during that period.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Capital humano local y productividad en las provincias españolas

En la última década, distintos estudios han intentado contrastar empíricamente la existencia de una relación entre el stock de capital humanolocal y la productividad del territorio, así como la posible presencia de economías externas asociadas a aquél. El resultado común de dichos estudios ha consistido en encontrar una correlación positiva entre ambas variables Losdiversos autores no coinciden, en cambio, a la hora de explicar dicho resultado: un primer grupo de autores argumenta la presencia de economíasexternas vinculadas al capital humano mientras que un segundo grupo plantea la existencia de relaciones de complementariedad entre los diversos factores productivos y, más en concreto, entre el capital humano y el capital físico.El objetivo de este trabajo es analizar la existencia de una posible relación positiva entre el nivel de capital humano de las provincias españolas y su productividad de éstas y, a continuación, averiguar si el canal a través delcual se produce el efecto son las economías externas. Para ello, se aplica unametodología que consta de dos etapas. En la primera, se estima una ecuación de Mincer utilizando información de la Encuesta de Presupuestos Familiares a fin de obtener una estimación de la productividad media de cada una de las provincias españolas una vez controlado el efecto del capital humano de los individuos sobre su propia productividad. En una segunda etapa, la estimación de la productividad provincial media estimada se introduce como variable endógena en una nueva ecuación cuyas variables explicativas intentan aproximar el nivel de capital humano de cada una de las provincias. A partir de esta segunda regresión se detecta una relación positiva entre la productividad media estimada del territorio y el nivel educativo medio delmismo. Sin embargo, la principal conclusión del análisis realizado es que dicha relación no puede explicarse por el impacto de las economías externas generadas exógenamente por el capital humano, sino que debe atribuirse a otros efectos que, actuando también por lado de la demanda, impulsen al alza la productividad.

Capital humano local y productividad en las provincias españolas

En la última década, distintos estudios han intentado contrastar empíricamente la existencia de una relación entre el stock de capital humanolocal y la productividad del territorio, así como la posible presencia de economías externas asociadas a aquél. El resultado común de dichos estudios ha consistido en encontrar una correlación positiva entre ambas variables Losdiversos autores no coinciden, en cambio, a la hora de explicar dicho resultado: un primer grupo de autores argumenta la presencia de economíasexternas vinculadas al capital humano mientras que un segundo grupo plantea la existencia de relaciones de complementariedad entre los diversos factores productivos y, más en concreto, entre el capital humano y el capital físico.El objetivo de este trabajo es analizar la existencia de una posible relación positiva entre el nivel de capital humano de las provincias españolas y su productividad de éstas y, a continuación, averiguar si el canal a través delcual se produce el efecto son las economías externas. Para ello, se aplica unametodología que consta de dos etapas. En la primera, se estima una ecuación de Mincer utilizando información de la Encuesta de Presupuestos Familiares a fin de obtener una estimación de la productividad media de cada una de las provincias españolas una vez controlado el efecto del capital humano de los individuos sobre su propia productividad. En una segunda etapa, la estimación de la productividad provincial media estimada se introduce como variable endógena en una nueva ecuación cuyas variables explicativas intentan aproximar el nivel de capital humano de cada una de las provincias. A partir de esta segunda regresión se detecta una relación positiva entre la productividad media estimada del territorio y el nivel educativo medio delmismo. Sin embargo, la principal conclusión del análisis realizado es que dicha relación no puede explicarse por el impacto de las economías externas generadas exógenamente por el capital humano, sino que debe atribuirse a otros efectos que, actuando también por lado de la demanda, impulsen al alza la productividad.