Family Background, Self-Confidence and Economic Outcomes

In this paper we analyze the role played by self-confidence, modeled as beliefs about one's ability, in shaping task choices. We propose a model in which fully rational agents exploit all the available information to update their beliefs using Bayes' rule, eventually learning their true type. We show that when the learning process does not convergence quickly to the true ability level, even small differences in initial confidence can result in diverging patterns of human capital accumulation between otherwise identical individuals. As long as inital differences in the level of self-confidence are correlated with the socioeconomic background (as a large body of empirical evidence suggests), self-confidence turns out to be a channel through which education and earnings inequalities are transmitted across generations. Our theory suggests that cognitive tests should take place as early as possible, in order to avoid that systematic differences in self-confidence among equally talented people lead to the emergence of gaps in the accumulation of human capital.self-confidence, family background

Evaluating students' evaluations of professors

This paper contrasts measures of teacher effectiveness with the students’ evaluations of the same teachers using administrative data from Bocconi University (Italy). The effectiveness measures are estimated by comparing the subsequent performance in follow-on coursework of students who are randomly assigned to teachers in each of their compulsory courses. We find that, even in a setting where the syllabuses are fixed, teachers still matter substantially. Additionally, we find that our measure of teacher effectiveness is negatively correlated with the students’ evaluations of professors: in other words, teachers who are associated with better subsequent performance receive worse evaluations from their students. We rationalize these results with a simple model where teachers can either engage in real teaching or in teaching-to-the-test, the former requiring greater student effort than the latter. Teaching-to-the-test guarantees high grades in the current course but does not improve future outcomes. Hence, if students are short-sighted and give better evaluations to teachers from whom they derive higher utility in a static framework, the model is capable of predicting our empirical finding that good teachers receive bad evaluations.teacher quality, postsecondary education

Evaluating Students' Evaluations of Professors

This paper contrasts measures of teacher effectiveness with the students' evaluations for the same teachers using administrative data from Bocconi University (Italy). The effectiveness measures are estimated by comparing the subsequent performance in follow-on coursework of students who are randomly assigned to teachers in each of their compulsory courses. We find that, even in a setting where the syllabuses are fixed and all teachers in the same course present exactly the same material, teachers still matter substantially. The average difference in subsequent performance between students who were assigned to the best and worst teacher (on the effectiveness scale) is approximately 43% of a standard deviation in the distribution of exam grades, corresponding to about 5.6% of the average grade. Additionally, we find that our measure of teacher effectiveness is negatively correlated with the students' evaluations: in other words, teachers who are associated with better subsequent performance receive worst evaluations from their students. We rationalize these results with a simple model where teachers can either engage in real teaching or in teaching-to-the-test, the former requiring higher students’ effort than the latter. Teaching-to-the-test guarantees high grades in the current course but does not improve future outcomes. Hence, if students are myopic and evaluate better teachers from which they derive higher utility in a static framework, the model is capable of predicting our empirical finding that good teachers receive bad evaluations, especially when teaching-to-the-test is very effective (for example, with multiple choice tests). Consistently with the predictions of the model, we also find that classes in which high skill students are over-represented produce evaluations that are less at odds with estimated teacher effectiveness.teacher quality, postsecondary education

Cherubini (1814) nella storia della prima lessicografia dialettale

L'articolo inquadra la prima edizione del vocabolario milanese di Cherubini (814) nella produzione dei primi vocabolari dialettali, dal veneziano al siciliano

Multiple imputation and selection of ordinal level 2 predictors in multilevel models. An analysis of the relationship between student ratings and teacher beliefs and practices

The paper is motivated by the analysis of the relationship between ratings and teacher practices and beliefs, which are measured via a set of binary and ordinal items collected by a specific survey with nearly half missing respondents. The analysis, which is based on a two-level random effect model, must face two about the items measuring teacher practices and beliefs: (i) these items level 2 predictors severely affected by missingness; (ii) there is redundancy in the number of items and the number of categories of their measurement scale. tackle the first issue by considering a multiple imputation strategy based on information at both level 1 and level 2. For the second issue, we consider regularization techniques for ordinal predictors, also accounting for the multilevel data structure. The proposed solution combines existing methods in an original way to solve specific problem at hand, but it is generally applicable to settings requiring to select predictors affected by missing values. The results obtained with the final model out that some teacher practices and beliefs are significantly related to ratings about teacher ability to motivate students.Comment: Presented at the 12th International Multilevel Conference is held April 9-10, 2019 , Utrech