Accounting for Heterogeneous Returns in Sequential Schooling Decisions

This paper presents a method for estimating returns to schooling that takes into account that returns may be heterogeneous among agents and that educational decisions are made sequentially.A sequential decision model is interesting because it explicitly considers that the level of education of each individual 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 data is stratified by level of education and so estimators are adapted to take this feature into account.Finally, this methodology is used to analyze possible effects of the 1970 reform of the Spanish education system.schooling;selection models;heterogeneity;sequential decisions;policy evaluation JEL classifications

Non-Cognitive Abilities and Spanish Regional Differences in Student Performance in PISA 2009

The goal of this paper is to analyze the role that non-cognitive skills and, in particular, regional differences in those skills, play on the observed differences in 15-year-old student’s academic performance, across Spanish regions, on PISA 2009. Previous research has shown the relevance of differences in student’s personal, family and school characteristics in accounting for academic differences across Spanish regions but it has also found that a sizeable part of the observed differences remained unexplained. We have found that differences in the distribution of certain non-cognitive skills associated to academic performance like focus, perseverance and resilience play a prominent role in accounting for differences in student performance in PISA 2009. We observe these skills by developing new measures of student effort on standardized tests. In particular, our estimates suggest that a standard deviation reduction in the dispersion of non-cognitive skills across Spanish regions would lead to a 25% reduction in the magnitude of the observed differences in student performance across regions. This is a relevant effect as, for example, a one standard deviation reduction in the regional dispersion of parent’s educational levels or occupational status would only lead to at most a 2% reduction in the magnitude of observed differences in performance on PISA across Spanish regions. Put plainly, a substantial portion of the regional variation in test scores appears attributable to effort on the PISA test, and not necessarily just differences in actual knowledge

Spanish Research Report for 1991

10 páginas, 14 tablasPeer reviewe

Prediksi Kenaikan atau Penurunan Indeks Pasar Keuangan Indonesia dengan Menggunakan Bayesian Network

Investasi saham pada pasar keuangan dilakukan untuk meningkatkan aset pada masa depan. Dalam melakukan investasi harus mempertimbangkan hasil yang akan didapatkan atau biasa disebut return. Setiap investor akan berusaha mendapatkan return semaksimal mungkin dari investasi yang dilakukannya. Oleh karena itu, perlu dilakukan prediksi perubahan kenaikan atau penurunan pada pasar saham. Beberapa metode untuk membuat prediksi adalah Bayesian Network dan Algoritma Naive Bayes. Pada Tugas Akhir ini, dilakukan pemodelan jaringan sektor-sektor pasar keuangan Indonesia dengan menggunakan Bayesian Network, lalu melakukan prediksi berdasarkan kenaikan atau penurunan harga penutupan dari tiap sektor. Metode yang digunakan adalah menggunakan Algoritma Naive Bayes Diskrit dan Kontinu. Setelah itu, menentukan metode yang terbaik untuk perhitungan prediksi dengan melihat tingkat akurasi dari setiap metode dengan confusion matrix. Sektor pasar keuangan yang digunakan yaitu nilai tukar USD/IDR, IHSG, dan Obligasi. Perhitungan dilakukan berdasarkan ketergantungan antara nilai tukar USD/IDR terhadap IHSG, dan nilai tukar USD/IDR terhadap Obligasi. Metode Naive Bayes Diskrit menunjukan hasil yang lebih akurat dengan akurasi sebesar 84% untuk IHSG dan 76% untuk Obligasi. Sedangkan perhitungan dengan metode Naive Bayes Kontinu memiliki akurasi sebesar 52% untuk IHSG dan 48% untuk Obligasi. Sektor nilai tukar USD/IDR lebih mempengaruhi IHSG, karena tingkat akurasi yang diperoleh IHSG lebih tinggi dibandingkan dengan Obligasi

Changes in the Cohort Growth Rate of Flemish Cap Cod

14 páginas, 4 figuras, 3 tablas.-- Scientific Council MeetingThe cohort growth rate of the Flemish Cap cod was studied, using data from Canadian research surveys in the period 1977 - 1985, fishing data from the Spanish commercial catches between 1986 and 1987, and data from a research survey carried out by Spain in 1988. We notice that cod growth is linear during the first years of its life. This period may last from five to eleven years in these cohorts. These growth rates show a positive correlation with water temperature in the upper 50 m. during the year of larvae eclosion, and a negative one with the abundance of the same cohort. The growth rates seem to be affected only by initial conditions in the history of each cohort, as abundance or temperature, and also seem to be independent of later changes such as fishing effort, food availability or abundance of other cohorts. We think that the biological parameter variations displayed by the different cohorts indicate a strategic response to changes in enviromental conditions.These growth differences cause size changes in individuals of the same age but belonging to different cohorts. These different sizes show a gradual change, with the smallest sizes for the 1974 and 1982 cohorts and the largets ones in 1978. The sizes of first maturity of females from 1978 to 1985 vary following the size trends of individuals at the age of four. Thus, we suppose that this must be the minimum age at which ovarian maturation in cod takes place.Peer reviewe

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

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

Accounting for Heterogeneous Returns in Sequential Schooling Decisions

This paper presents a method for estimating returns to schooling that takes into account that returns may be heterogeneous among agents and that educational decisions are made sequentially.A sequential decision model is interesting because it explicitly considers that the level of education of each individual 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 data is stratified by level of education and so estimators are adapted to take this feature into account.Finally, this methodology is used to analyze possible effects of the 1970 reform of the Spanish education system

Spanish Research Report for 1991

10 páginas, 14 tablasPeer reviewe