Working papers results

We use a new dataset on eight Italian cities and a novel identification strategy to analyze the relationship between the employment status of migrants and the percentage of migrants living nearby. Our data contain information at the very local level (i.e. the residential block) and are representative of the population of both legal and illegal migrants. Identification is based on an instrumental variable strategy that exploits the physical characteristics of the local buildings as a source of exogenous variation in the incidence of migrants in each location. We find evidence that migrants who reside in areas with a high concentration of non-Italians are less likely to be employed compared to similar migrants who reside in more mixed areas. This penalty is higher if the migrants leaving nearby are illegal and it is not mitigated by living close to migrants who are from own's ethnic group nor who are more proficient in the Italian language. The employment prospects of natives do not appear to be affected by the vicinity of migrants.

Recent evidence on electronic limit order markets shows a growing use of undisclosed orders. This paper offers a theory for the optimal submission strategy in a limit order book where traders simultaneously select price, quantity and exposure, and choose among limit, market, reserve (partially undisclosed) and hidden (totally invisible) orders. Our findings show that to compete for the provision of liquidity in shallow markets relatively patient traders use reserve orders, whilst aggressive traders use hidden pegged orders to undercut depth at the top of liquid books. Undisclosed orders are effective defensive strategies against front running by parasitic traders, whereas they protect against picking-off by scalpers only in slow markets where Fill&Kill orders are not used. Finally, our results show that undisclosed orders increase market depth on the top of the book, but widen the inside spread; as a result they can benefit institutional investors but harm retail traders.

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In this paper we relate the very persistent component of interest rates to a specific demographic variable, MYt, the proportion of middle-aged to young population. We first reconsider the results in Fama (2006) to document how MYt captures the long run component identified by Fama in his analysis of the one-year spot rate. Using MYt to model this low frequency component of interest rates is particularly useful for forecasting the term structure as the demographic variable is exogenous and highly predictable, even at very long horizons. We then study the forecasting performance of a no-arbitrage affine term structure model that allows for the presence of a persistent component driven by demographics. This performance is superior to that of a traditional affine term structure model with macroeconomic factors (e.g. Ang, Dong and Piazzesi, 2005).

This paper proposes a test of racial bias in capital sentencing based upon patterns of judicial errors in lower courts. We model the behavior of the trial court as minimizing a weighted sum of the probability of sentencing an innocent and that of letting a guilty defendant free. We define racial bias as a situation where the relative weight on the two types of errors is a function of defendant and/or victim race. The key prediction of the model is that if the court is unbiased, ex post the error rate should be independent of the combination of defendant and victim race. We test this prediction using an original dataset that contains the the race of the defendant and of the victim(s) for all capital appeals that became final between 1973 and 1995. We find robust evidence of bias against minority defendants who killed white victims: in Direct Appeal and Habeas Corpus the probability of error in these cases is 3 and 9 percentage points higher, respectively, than for minority defendants who killed minority victims.

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We introduce and study finitely well-positioned sets, a class of asymptotically "narrow" sets that generalize the well-positioned sets recently investigated by Adly, Ernst and Thera in [1] and [3], as well as the plastering property of Krasnoselskii.

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There is a large literature on social interactions and still little is known about the economic mechanisms leading to the high level of clustering in behavior that is so commonly observed in the data. In this paper we present a model in which agents are allowed to interact according to three distinct mechanisms, and we derive testable implications on the mean and the variance of the outcomes within and across groups. The empirical tests allow us to distinguish which mechanism(s) generates the observed patterns in the data. In our application we study the performance of undergraduate students and we find that social interactions take the form of mutual insurance. Such a result bears crucial policy implications for all those situations in which social interactions are important, from teamwork to class formation in education and co-authorship in academic research.

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, teachers still matter substantially. The average difference in subsequent performance between students who were assigned to the best and worst teachers (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 of professors: 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. 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.

This paper uses a structural, large dimensional factor model to evaluate the role of 'news' shocks (shocks with a delayed effect on productivity) in generating the business cycle. We find that (i) existing small-scale VECM models are affected by 'non-fundamentalness' and therefore fail to recover the correct shock and impulse response functions; (ii) news shocks have a limited role in explaining the business cycle; (iii) their effects are in line with what predicted by standard neoclassical theory; (iv) the bulk of business cycle fluctuations are explained by shocks unrelated to technology.

Starting with the seminal paper of Gilboa and Schmeidler (1989) an analogy between the maxmin approach of Decision Theory under Ambiguity and the minimax approach of Robust Statistics -- e.g. Huber and Strassen (1973) -- has been hinted at. The present paper formally clarifies this relation by showing the conditions under which the two approaches are actually equivalent.

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Many separable dynamic incentive problems have primal recursive formulations in which utility promises serve as state variables. We associate families of dual recursive problems with these by selectively dualizing constraints. We make transparent the connections between recursive primal and dual approaches, relate value iteration under each and give conditions for it to be convergent to the true value function.

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