Productivity growth in electric energy retail in Colombia. A bootstrapped malmquist indices approach

This paper offers a productivity growth estimate for electric energy commercialization firms in Colombia, using a non-parametric Malmquist bootstrap methodology. The estimation and methodology serve two main purposes. First, in Colombia Commercialization firms are subject to a price-cap regulation scheme, a non-common arrangement in the international experience for this part of the industry. Therefore the paper’s result suggest an estimate of the productivity factor to be used by the regulator, not only in Colombia but in other countries where commercialization is a growing part of the industry (renewable energy, for instance). Second, because of poor data collection from regulators and firms themselves, regulation based on a single estimation of productivity seems inappropriate and error-prone. The nonparametric Malmquist bootstrap estimation allows an assessment of the result in contrast to a single one estimation. This would open an opportunity for the regulator to adopt a narrower and more accurate productivity estimation or override an implausible result and impose a productivity factor in the price-cap to foster the development of the industry.

Statistical inference for testing Gini coefficients: an application for Colombia

This paper uses Colombian household survey data collected over the period 1984-2005 to estimate Gini coe¢ cients along with their corresponding standard errors. We Önd a statistically signiÖcant increase in wage income inequality following the adoption of the liberalisation measures of the early 1990s, and mixed evidence during the recovery years that followed the economic recession of the late 1990s. We also Önd that in several cases the observed di§erences in the Gini coe¢ cients across cities have not been statistically signiÖcant.

Inequality of opportunity in educational achievement in Latin America: evidence from PISA 2006-2009

We assess inequality of opportunity in educational achievement in six Latin American countries, employing two waves of PISA data (2006 and 2009). By means of a non-parametric approach using a decomposable inequality index, GE(0), we rank countries according to their degree of inequality of opportunity. We work with alternative characterizations of types: school type (public or private), gender, parental education, and combinations of those variables. We calculate incremental contributions of each set of circumstances to inequality. We provide rankings of countries based on unconditional inequalities (using conventional indices) and on conditional inequalities (EOp indices), and the two sets of rankings do not always coincide. Inequality of opportunities range from less than 1% to up to 27%, with substantial heterogeneity according to the year, the country, the subject and the specificication of circumstances. Robustness checks based on bootstrap and the use of an alternative index confirm most of the initial results.

Una nota sobre la elección de ancho de banda cuando la hipótesis nula es semiparamétrica.

Este artículo presenta un contraste de aditividad. El modelo aditivo es usado para modelar estructuras paramétricas y semiparamétricas. La hipótesis de aditividad es interesante porque es fácil de interpretar y produce unas tasas de convergencia razonablemente rápidas de estimadores no paramétricos. Una ventaja adicional de las estructuras aditivas es que permiten atacar directamente el problema de la maldición de la dimensionalidad que surge en estimaciones no paramétricas. El procedimiento que proponemos para el contraste de hipótesis está basado en el conocido proceso de remuestreo (bootstrap) de los residuales del modelo aditivo. En la literatura de evaluación no paramétrica, la idea dominante es que el ancho de banda utilizado para producir la muestra bootstrap debe ser más grande que la banda utilizada para la estimación del modelo bajo hipótesis nula. No obstante, hasta el momento la literatura existente no suministra ayuda alguna que permita elegir dicha banda en la práctica. Discutimos, como un primer paso, un tipo de regla para elegir tal banda en este contexto. Nuestras sugerencias están acompañadas de ejercicios de simulación.  

Climas motivacionales, necesidades, motivaci??n y resultados en Educaci??n F??sica

Resumen tomado de la publicaci??n

Factores asociados a la brecha regional del rendimiento espa??ol en la evaluaci??n PISA

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Irrigation performance and gross water productivity in furrow-irrigated ornamental tree production

In the ornamental plant production region of Girona (Spain), which is one of the largest of its kind in southern Europe, most of the surface is irrigated using wide blocked-end furrows. The objectives of this paper were: (1) to evaluate the irrigation scheduling methods used by ornamental plant producers; (2) to analyse different scenarios in order to assess how they affect irrigation performance; (3) to evaluate the risk of deep percolation; and (4) to calculate gross water productivity. A two-year study in a representative commercial field, planted with Prunus cerasifera ‘Nigra’, was carried out. The irrigation dose applied by the farmers was slightly smaller than the required water dose estimated by the use of two different methods: the first based on soil water content, and the second based on evapotranspiration. Distribution uniformity and application efficiency were high, with mean values above 87%. Soil water content measurements revealed that even at the end of the furrow, where the infiltrated water depth was greatest, more than 90% of the infiltrated water was retained in the shallowest 40 cm of the soil; accordingly, the risk of water loss due to deep percolation was minimal. Gross water productivity for ornamental tree production was € 11.70 m–3, approximately 20 times higher than that obtained with maize in the same region

Conductive elastomeric composites

Conductive elastic materials are formed by distributing conductive particles within an elastic polymer. We consider a novel composite based on dendritic nickel particles that exhibit remarkably strong negative piezoresistivity with an increase in conductivity of up to 10 orders of magnitude with strains of the order of 0.2. A vital factor for the conductivity of conductive elastomers is the concentration of conductive fillers and many aspects can be understood in terms of percolation theory. In this system the concentration of particles within the composite does not change with strain, yet due to the shape of the particles, the concentration of electrical contacts between the particles does change. We have developed a new model based on the concentration of contact sites, rather than particles which enables us to successfully model this remarkable strain-dependence of conductivity.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

The use of bootstrapped Malmquist indices to reassess productivity change findings: an application to a sample of Polish farms

This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

Ranking efficiency units in DEA using bootstrapping an applied analysis for Slovenian farm data

This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).

Productivity change in Polish agriculture: an illustration of a bootstrapping procedure applied to Malmquist indices

This article illustrates the usefulness of applying bootstrap procedures to total factor productivity Malmquist indices, derived with data envelopment analysis (DEA), for a sample of 250 Polish farms during 1996-2000. The confidence intervals constructed as in Simar and Wilson suggest that the common portrayal of productivity decline in Polish agriculture may be misleading. However, a cluster analysis based on bootstrap confidence intervals reveals that important policy conclusions can be drawn regarding productivity enhancement.

Modeling of relationships between weather and Septoria tritici epidemics on winter wheat: A critical approach

Two models for predicting Septoria tritici on winter wheat (cv. Ri-band) were developed using a program based on an iterative search of correlations between disease severity and weather. Data from four consecutive cropping seasons (1993/94 until 1996/97) at nine sites throughout England were used. A qualitative model predicted the presence or absence of Septoria tritici (at a 5% severity threshold within the top three leaf layers) using winter temperature (January/February) and wind speed to about the first node detectable growth stage. For sites above the disease threshold, a quantitative model predicted severity of Septoria tritici using rainfall during stern elongation. A test statistic was derived to test the validity of the iterative search used to obtain both models. This statistic was used in combination with bootstrap analyses in which the search program was rerun using weather data from previous years, therefore uncorrelated with the disease data, to investigate how likely correlations such as the ones found in our models would have been in the absence of genuine relationships.

Is agriculture the engine of growth?

We seek to address formally the question raised by Gardner (2003) in his Elmhirst lecture as to the direction of causality between agricultural value added per worker and Gross Domestic Product (GDP) per capita. Using the Granger causality test in the panel data analyzed by Gardner for 85 countries, we find overwhelming evidence that supports the conclusion that agricultural value added is the causal variable in developing countries, while the direction of causality in developed countries is unclear. We also examine further the use of the Granger causality test in integrated data and provide evidence that the performance of the test can be increased in small samples through the use of the bootstrap.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.