Publishing performance in economics: Spanish rankings (1990–1999)

Abstract. This paper contributes to the growing literature that analyses the Spanish publishing performance in Economics throughout the 1990s. Several bibliometric indicators are used in order to provide Spanish rankings (of both institutions and individual authors) based on Econlit journals. Further, lists of the ten most influential authors and articles over that period, in terms of citations, are reported. We are grateful to many colleagues who made very useful remarks to preliminary versions of this paper, as well as to two anonymous referees. We are particularly indebted to Xavier Sala-i-Martín, without whose invaluable help this work would not have been possible. All errors or omissions are of our exclusive responsibility.     

Teacher qualifications and student achievement in urban elementary schools

Teacher quality is a key element of student academic success, but few specific teacher characteristics influence classroom outcomes. This research examines whether teacher licensure test scores and other teacher attributes affect elementary student achievement. The results are based on longitudinal student-level data from Los Angeles. California requires three types of teacher licensure tests as part of the teacher certification process; a general knowledge test, a subject area test (single subject for secondary teachers and multiple subject for elementary teachers), and a reading pedagogy test for elementary school teachers. The student achievement analysis uses a value-added approach that adjusts for both student and teacher fixed effects. The results show large differences in teacher quality across the school district, but measured teacher characteristics explain little of the difference. Teacher licensure test scores are unrelated to teacher success in the classroom. Similarly, student achievement is unaffected by whether classroom teachers have advanced degrees. Student achievement increases with teacher experience, but the linkage is weak and largely reflects poor outcomes for teachers during their first year or two in the classroom.     

Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products

Energy supply and demand, and as a consequence energy prices, are likely to represent one of the biggest challenges of the 21st century. Commodity markets exhibit increased volatility when there is little or no underutilized supply capability to meet natural fluctuations in demand. In the case of energy markets, the large capital requirements and significant lead times associated with energy production and delivery make them more susceptible to the imbalances in supply capability and demand. Energy price volatility has destructive impact on market agents, and this impact is intensified when the prices exhibit asymmetric volatility. This article pursues two aspects of the issue. First we consider general aspects, especially the asymmetric pattern of volatility of daily returns of different types of energy products. Then, we analyze the behaviour of daily returns by using traditional models of volatility that include AGARCH, TGARCH, EGARCH, and ARSV strategies, as well as a threshold asymmetric autoregressive stochastic volatility (TA-ARSV) model that we propose. The energy products considered in this analysis are probably the most relevant energy products for the economic activity of the nations and the economic relations between countries: Crude Oil (OPEC reference basket and London Brent index), Gasoline, Natural Gas, Butane, and Propane. We use spot prices and the time reference ranges from 1986–1993 to 2009 depending on the product.     

A MODEL OF GROWTH AUGMENTED WITH INSTITUTIONS

This paper shows that the inclusion of institutional indicators in a traditional model of growth substantially improves its explanatory capacity. The results have implications for economic policy, because not all the dimensions of institutional quality influence growth to the same extent. A large sample of 165 countries and estimation methods with instrumental variables are used to solve endogeneity problems.     

Rate of Return Regulation: The Case of Spanish Ports

An original model is put forward in this article to explain and consider the behavior of some of the most important public services in Spain. The cost function approach and the input distance function approach are used to estimate the existence of overcapitalization as a result of rate of return regulation. The results show that overcapitalization generated by this regulation is too significant not to be taken into account.     

A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy

This paper focuses on a new strand of research that uses stochastic approach for making spatial price comparisons. We propose a novel method to account for the presence of spatial dependencies in consumer prices and consequently in price indexes by imposing penalization conditions on the estimation of traditional CPD models leading to the spatially-penalized country-product-dummy (SP-CPD) model. The paper proposes an appropriate estimation strategy, which enables us to simultaneously estimate all the parameters in the model, including the smoothing parameter of the penalization term instead of determining it externally. In order to estimate spatial price indexes for areas lacking in price data, we suggest applying the kriging methodology to the price indexes obtained from the SP-CPD model. This new approach is applied to official Italian CPI data for constructing regional spatial price indexes for 2014. The results show that price levels are higher in the Northern-Central regions than in the South.     

Accounting for heterogeneous returns in sequential schooling decisions

This paper presents a method for estimating returns to multiple schooling levels taking into account that returns may be heterogeneous among agents and that educational decisions are made sequentially. A sequential decision model explicitly considers that the level of education is the result of previous schooling choices and so, the variation of supply-side instruments over time will emerge as a source of identification of the desired parameters. A test for heterogeneity in returns from sequential schooling decisions is developed and expressions for Marginal Treatment Effects are obtained in this context. Returns are estimated and tested from cross-sectional data from a Spanish household survey that contains rich family background information and useful instruments. This methodology is used to analyze possible effects of the 1970 reform of the Spanish education system.     

Spatial Regression Analysis vs. Kriging Methods for Spatial Estimation

Due to the rapid development of Geographic Information Systems (GIS) in recent years, spatial data analysis has received considerable attention and played an important role in social science. Although many standard statistical techniques are attractive in traditional data analysis, they cannot be implemented uncritically for spatial data. Generally, most of the studies in spatial data analysis can be divided into two branches: the model-driven approach and the data-driven approach. The main aim of this paper is the comparison of both approaches. To carry out such a task, crime rate data in Columbus (Ohio), coming from a well-known database, have been used. The main aim of this paper is to illustrate how spatial effects can be viewed as spatial econometric models, which assess the limitations of standard techniques in a spatial context, suggesting alternative methods to deal with this problem. An application to the crime rate in Columbus (Ohio) has been carried out.

Spatial modeling of stock market comovements

We model the complex global dependencies in international financial markets using spatial techniques. Our methodology allows us to go beyond conventional correlation analyses and volatility-spillover models confined to studying pairwise relationships, and improves the accuracy of return predictions. We find that stock market comovements are unrelated to geographical proximity, and that financial linkages, as measured by foreign direct investment (FDI) ties, are important in accounting for markets comovements. Our results suggest that the proposed measure of financial distance, coupled with spatial methodology, captures fairly accurately the dependencies in the world financial markets, providing important implications for policymaking and portfolio management.