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.     

A mixed-mode sensitive research on cannabis use and sexual addiction: improving self-reporting by means of indirect questioning techniques

In this article, we describe the methods employed and the results obtained from a mixed-mode “sensitive research” conducted in Spain to estimate certain aspects concerning patterns of cannabis consumption and sexual addiction among university students. Three different data-collection methods are considered and compared: direct questioning, randomized response technique and item sum technique. It is shown that posing direct questions to obtain sensitive data produces significantly lower estimates of the surveyed characteristics than do indirect questioning methods. From the analysis, it emerges that male students seem to be more affected by sex addiction than female students while for cannabis consumption there is no evidence of a predominant gender effect.     

Editors’ note

Portuguese Economic Journal -     

Computing DSGE models with recursive preferences and stochastic volatility

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as those in Epstein and Zin, 1989, Epstein and Zin, 1991 and stochastic volatility. Models with these two features have recently become popular, but we know little about the best ways to implement them numerically. To fill this gap, we solve the stochastic neoclassical growth model with recursive preferences and stochastic volatility using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main finding is that perturbations are competitive in terms of accuracy with Chebyshev polynomials and value function iteration while being several orders of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.     

Environmental Product Differentiation and Environmental Awareness

In this paper, we have considered a duopolistic model of environmental product differentiation with two types of consumers (green and brown) to analyze how environmental awareness affects the environment. “Green” consumers value the physical and environmental attributes of the good they purchase while “brown” consumers only value the physical attributes. We find that more environmental awareness may not be good news for the environment as the firm that produces the good without environmental attributes may increase its sales. The result depends on the degree of product differentiation and the cost to achieve it. Social welfare can also be inversely related to environmental awareness if the negative environmental effect dominates the positive market effect.      

Regional and Sector-specific Determinants of Industry Dynamics and the Displacement–replacement Effects

In this paper, we empirically assess the importance of regional and sector-specific determinants of industry dynamics. To this aim we test three hypotheses (originally proposed by Shapiro and Khemani (1987, Int J Indust Organ 5:15–26)) for the relationship between the entry and exit of firms: independence, symmetry and simultaneity. Estimates from a panel data system of equations seem to confirm the simultaneity hypothesis for Spain, i.e. we find evidence of a displacement (replacement) effect between the gross rate of entry (exit) and the gross rate of exit (entry). Also, our results show that, irrespective of the hypothesis we use, both sectorial and regional variables affect entry and exit.

Value at Risk and Economic Growth

The improvement of data statistics as well as the econometrician methods have facilitated the introduction the new variables and factors I the economic growth analysis. In this sense, real variables have mainly been considered in the economic growth studies, but not financial or risk management aspects. In this sense, it is interesting to analyze the relationship between economic growth and value at risk and the feed-back process. The goal of the paper is to analyze the relationship between economic growth and risk management and the feed-back process. We will consider economic variables, including economic growth, rule of law, human capital, fiscal policy and monetary policy, among others, in our analysis. We will analyze the theoretical relationships between these variables and risk and the effects of risk on economic growth. We will also develop an empirical analysis considering the case of 15 European Union countries.

On the performance of the Chow-Lin procedure for quarterly interpolation of annual data: Some Monte-Carlo analysis

Most of the countries of the OECD offer quarterly estimates of their national growth or of their Gross National Product. Official Statistical Agencies in western countries have to deal with the problem of estimating Quarterly National Accounts series congruently with Annual National Accounts. In Spain, the Instituto Nacional de Estadística uses the Chow-Lin disaggregation method, which is based on information provided by a group of high-frequency related variables, to estimate the quarterly components of National Accounts from annual components. In this paper, we analyse the relative quality of the estimates obtained through the Chow-Lin procedure, under different sets of hypotheses.JEL Classification: C15, C43, M40We are grateful to Maria Amparo Ripoll for her assistance. The authors also wish to thank three anonymous referees and an editor for their constructive suggestions and comments. This research was partially made during the stay of the first author at the Universidad Carlos III de Madrid. It has been partially supported by the research project DGCYT PB98-1460.