José Manuel Cordero

Alternative approaches to include exogenous variables in DEA measures: A comparison using Monte Carlo

The theory for measuring efficiency of producers has developed alternative approaches to correct for the effect of non-discretionary variables in the analysis. A review of different options in the specific literature of Data envelopment analysis (DEA) allows us to identify three main approaches: one-stage, two-stage and multi-stage models. Recently, some of these models have been improved through the development of bootstrap methods making it possible to make inference and to avoid bias in the estimation of efficiency scores. The aim of this paper is to test the performance of these recent models and to compare among them using simulated data from a Monte Carlo experimental design.

Efficiency assessment of primary care providers: A conditional nonparametric approach

This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) regarding the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric approach to deal with the presence of undesirable outputs in data, represented by the number of readmissions and hospitalization rates of ambulatory care sensitive condition (ASCS). The empirical results of our application show that all the exogenous variables considered have a significant and negative effect on efficiency estimates.

Testing the accuracy of DEA estimates under endogeneity through a Monte Carlo simulation

Endogeneity, and the distortions on the estimation of economic models that it causes, is a usual problem in the econometrics literature. Although non-parametric methods like Data Envelopment Analysis (DEA) are among the most used techniques for measuring technical efficiency, the effects of such problem on efficiency estimates have received little attention. The aim of this paper is to alert DEA practitioners about the accuracy of their estimates under the presence of endogeneity. For this, first we illustrate the endogeneity problem and its causes in production processes and its implications for the efficiency measurement from a conceptual perspective. Second, using synthetic data generated in a Monte Carlo experiment we evaluate how different levels of positive and negative endogeneity can impair DEA estimations. We conclude that, although DEA is robust to negative endogeneity, a high positive endogeneity level, i.e., the existence of a high positive correlation between one input and the true efficiency level, might bias severely DEA estimates.

Assessing European primary school performance through a conditional nonparametric model

This paper uses a fully nonparametric framework to assess the efficiency of primary schools using data about schools in 16 European countries participating in PIRLS 2011. This study represents an original enterprise since most of the empirical research in the field is restricted to evaluations at regional or national level and focused on secondary education. For our purpose, we adapt the metafrontier framework to compare and decompose the technical efficiency of primary schools operating in heterogeneous contexts, which in our case is represented by different educational systems or countries. Similarly, we use an extension of the conditional nonparametric robust approach to test the potential influence of a mixed set of environmental school factors and variables representing cultural values of each country. Our results indicate that the intergenerational transmission of non-cognitive skills such as responsibility or perseverance are significantly related to school efficiency, whereas most school factors do not seem to have a significant influence on school performance.

CAUSAL INFERENCE ON EDUCATION POLICIES: A SURVEY OF EMPIRICAL STUDIES USING PISA, TIMSS AND PIRLS

The identification of the causal effects of educational policies is the top priority in recent education economics literature. As a result, a shift can be observed in the strategies of empirical studies. They have moved from the use of standard multivariate statistical methods, which identify correlations or associations between variables only, to more complex econometric strategies, which can help to identify causal relationships. However, exogenous variations in databases have to be identified in order to apply causal inference techniques. This is a far from straightforward task. For this reason, this paper provides an extensive and comprehensive overview of the literature using quasi-experimental techniques applied to three well-known international large-scale comparative assessments, such as PISA, PIRLS or TIMSS, over the period 2004-2016. In particular, we review empirical studies employing instrumental variables, regression discontinuity designs, difference in differences and propensity score matching to the above databases. Additionally, we provide a detailed summary of estimation strategies, issues treated and profitability in terms of the quality of publications to encourage further potential evaluations. The paper concludes with some operational recommendations for prospective researchers in the field.

Exploring factors affecting the level of happiness across countries: A conditional robust nonparametric frontier analysis

In this paper we propose an innovative approach based on life satisfaction to estimate efficiency measures for individuals considering how they convert their resources into higher levels of happiness. We use an extension of the conditional nonparametric robust approach which allows us to consider a mixed set of contextual variables that can affect the levels of life satisfaction. Our empirical analysis includes data about 31,854 individuals from 26 OECD countries participating in the last wave of the World Values Survey. Results obtained indicate that the most efficient individuals in achieving happiness tend to live in northern and central European countries whereas the less efficient individuals are found, in average, in Asian transitional economies. In addition, it is also found that most of the traditional determinants of wellbeing (e.g. age, marital status, religion or unemployment) also have a significant impact on efficiency measures.

A comparison of public and private schools in Spain using robust nonparametric frontier methods

This paper uses an innovative approach to evaluate educational performance of Spanish students in PISA 2009. Our purpose is to decompose their overall inefficiency between different components with a special focus on studying the differences between public and state subsidized private schools. We use a technique inspired by the non-parametric free disposal hull and the application of robust order-

European Regional Efficiency and Geographical Externalities: A Spatial Nonparametric Frontier Analysis

m