Giancarlo Spagnolo in “Legalizing Bribes”, with Martin Dufwenberg, contributes to identify a set of concrete measures to propose to policy makers to fight corruption, an endemic problem in the developing world. Starting from Kaushik Basu’s recent proposal to “legalize the act of giving the bribe and double the fine for accepting the bribe”, the paper develops a formal model that allows to draw conclusions regarding which legal rules should work well in what setting. In particular, it is shown that Basu’s proposal gets mixed and highly context-dependent results as regards usefulness with harassment bribes (payments people give in order not to be denied what they are legally entitled to). Moreover the analysis highlights complementarities with other policies: Basu’s proposal tends to work best if coupled with measures that increase the costs to bureaucrats of denying citizens what they deserve or that reduce the costs to citizens of getting justice. To overcome many of the objections to Basu’s proposal, the authors put forward the following modification: “rather that legalize bribe-giving, only bribe givers who report should be awarded legal immunity”.
Giancarlo Spagnolo in “Time Horizon and Cooperation in Continuous Time”, with Maria Bigoni, Marco Casari and Andrzej Skrzypacz, uses laboratory experiments on Prisoner’s Dilemma games played in continuous time to study how cooperation levels and learning patterns change under different time horizons and lengths of interaction. Understanding the determinants of cooperation is crucial for all social sciences. Many economic interactions, from teams working in the same plant to firms pricing in electronic markets, are closer to continuous than to discrete time. The paper finds that cooperation levels tend to be higher when the horizon is deterministic rather than stochastic, the opposite than in the discrete case. The strategies employed and the time pattern of cooperation change with the horizon. For instance, the data show a higher initial cooperation and a strong end-of-period reversal to defection under a deterministic horizon. They also suggest that people do not learn to apply backward induction as in discrete games, but instead postpone defection closer and closer to the end.
Franco Peracchi in “Childhood Circumstances and Adult Outcomes: Evidence from World War II”, with Enkelejda Havari, studies the association between the circumstances in childhood and adult outcomes. He concentrates on the cohorts born between 1930 and 1954 in 13 European countries, and exploits the huge variation in the timing, nature and intensity of events related to World War II and the immediate postwar period. The available historical information are then combined with micro-level data from the third wave of the Survey of Health Ageing and Retirement in Europe (SHARE), which provides detailed retrospective information on life histories from childhood to adulthood for people born before 1955. The results show that those who experienced war-related episodes of financial hardship and hunger in childhood have lower educational attainment and worse health in adulthood (but not lower income), relative to those who never suffered these experiences, and especially relative to those born after 1950.
In “Who Is Hurt by E-commerce? Crowding out and Business Stealing in Online Grocery”, Andrea Pozzi shows that large retail chains can exploit online distribution to increase their pull and leverage their advantage in price and product variety on households living further away from their location. This causes market share losses for competitors, especially small grocers who rely on geographic differentiation to withstand competition from big-box stores. The demise of differentiation in location induced by the diffusion of online shopping is poised to increase concentration of market share in the hands of the big chains at the expenses of mom-and-pop stores.
Franco Peracchi in “Using Panel Data to Partially Identify HIV Prevalence when HIV Status Is Not Missing at Random”, with Bruno Arpino and Elisabetta De Cao, uses the partial identification approach to assess the uncertainty caused by missing HIV status on estimates of HIV prevalence. Their paper shows how to exploit the availability of panel data and the absorbing nature of HIV infection to narrow the worst-case bounds without imposing assumptions on the missing-data mechanism. Applied to panel data from rural Malawi, their approach results in a substantial reduction of the width of the worst-case bounds. They also show how to use plausible instrumental variable and monotone instrumental variable restrictions to further narrow the bounds.
Luigi Guiso in “Detecting Propagation Effects by Observing Aggregate Distributions: The Case of Lumpy Investments”, with Chaoqun Lai and Makoto Nirei shows that in a panel of Italian firms the empirical distribution of the fraction of firms that engage in large investments is not normal, but rather double-exponential. Such a distribution can be generated analytically by a model where investments are lumpy (non-linear) and investment decisions by one firm affect those of another, a complementarity that arises because firms are linked by input-output relations as well as through aggregate demand spillovers. Estimation of the model at the firm level provides an empirical measure of this complementarity.
Franco Peracchi in “A Generalized Missing-Indicator Approach to Regression with Imputed Covariates”, with Valentino Dardanoni, Giuseppe Deluca and Salvatore Modica, addresses the problem arising in the estimation of a linear regression model using data where some covariate values are missing, but imputations are available to fill-in the missing values. The availability of imputations generates a trade-off between bias and precision in the estimators of the regression parameters: the complete cases are often too few, so precision is lost, but filling-in the missing values with imputations may lead to bias. The paper provides a new Stata command which allows handling this trade-off using either model reduction or model averaging techniques. The command is then used in an empirical application which investigates the relationship between an objective health indicator and a set of socio-demographic and economic covariates affected by substantial item nonresponse.
Aleh Tsyvinski in “Dynamic Strategic Information Transmission”, with Mikhail Golosov, Vasiliki Skreta and Andrea Wilson, revisits the classic problem of information transmission between an informed expert and a decision maker with not aligned objectives. In a static setting, the expert hides part of his information. Aleh and his co-authors show that in a dynamic environment this can be avoided, and the expert can be induced to reveal, gradually, all his information. The details are technical, but the practical implications of this result are widespread, as most expert-decision maker interactions are of an ongoing, dynamic nature.
Eleonora Patacchini in “Moving to Segregation: Evidence from 8 Italian Cities”, with Tito Boeri, Marta De Philippis and Michele Pellizzari, analyzes the extent to which the concentration of migrants in specific city-neighborhoods affects the probability of being employed. Using data from a new survey, covering both legal and illegal migrants, this study reveals that a 10 percentage points increase of the share of migrants over total local population, a measure of ‘residential segregation’, reduces the probability of getting a job by 7 percentage points; however, such a negative effect emerges only above a threshold value of 15-20 per cent of this share. These results have relevant implications for the design of policy measures aimed at improving overall employment, hence economic integration of migrants.
Francesco Lippi and Nicholas Trachter in “The Optimum Quantity of Money with Borrowing Constraints” analyze optimal systematic monetary policy in an economy with borrowing constraints and random production opportunities. Because of market incompleteness, money (an intrinsically useless object) may serve a fundamental insurance role and be valued. The paper studies what is the optimal money growth rate at which the government should pump money into the economy. It is shown that a trade-off exists between insuring agents who may be unproductive for a long time and minimizing the distortions of the inflation tax. A main point of the paper is that the government money transfers provide a lower bound to the consumption of “unlucky agents”. A central result is that, in the economy with uninsurable risk and incomplete markets, the optimal anticipated monetary policy is expansionary.
Jeffrey Butler and Luigi Guiso in “The Role of Intuition and Reasoning in Driving Aversion to Risk and Ambiguity”, with Tullio Jappelli, argue that decision style, an individual trait, is intrinsically related to individuals’ attitudes towards risk and ambiguity (a situation where one cannot easily attach a probability to an event). They find that people who rely on intuition are less averse to risk and to ambiguity than deliberative ones. Evidence from a large sample of investors as well as lab experiments confirm that intuitive people perform better in situation involving risk and ambiguity. They also propose a novel explanation of some ‘puzzling’ financial decisions based on their finding that wealthy people are less risk averse but more ambiguity averse.
Marco Lippi in “One-Sided Representations of Generalized Dynamic Factor Models”, with Mario Forni, Marc Hallin and Paolo Zaffaroni, adds to their Generalized Dynamic Factor Model a parametric structure for the common components, which does not imply a static representation of the model. The estimate of the new model on US macroeconomic time series receives stronger empirical support than the estimate of the usual static-representation restriction.
Nicholas Trachter in “On the Distribution of College Dropouts: Wealth and Uninsurable Idiosyncratic Risk”, with Ali K. Ozdagli, aims to explain why the distribution of college dropouts is skewed with respect to family’s wealth. In his model students’ choice to drop out depends on their wealth and their own true ability, initially unknown, but revealed through the exams’ outcomes. Conditioning on measures of innate ability the data show, consistently with the model’s predictions, that poorer students are about 30 per cent more likely to drop and they do so around a year before richer students.
Luigi Paciello in “Exogenous Information, Endogenous Information and Optimal Monetary Policy”, with Mirko Wiederholt, shows that complete stabilization of the price level is an optimal response to a large class of shocks when firms rationally decide how much of their limited capabilities in processing information to allocate to the macroeconomic environment. This result contrasts with that obtained with limited but exogenous information.
Nicholas Trachter in “Option value and transitions in a model of postsecondary education”, interprets academic 2-year colleges (a feature of the US educational system) as a cheap way for students to learn about their unknown ability before deciding whether to drop out and go to work or transfer to a 4-year college. He shows that, even though enrollment rates to 2-year colleges are high, the welfare cost of eliminating these colleges would be small.
In his paper “What drives women out of entrepreneurship? The joint role of testosterone and culture”, Luigi Guiso (EUI and EIEF), with Aldo Rustichini, studies how biological and cultural factors influence women’s decision to be an entrepreneur. He finds evidence that in less emancipated societies women need higher intrinsic ability to become an entrepreneur and thus fewer do. But those who do are as successful as men.
In their paper “What Do CEOs Do?”, Luigi Guiso (EUI and EIEF) with O.Bandiera, A. Prat and R. Sadun, analyze how Italian CEOs allocate their time among different work activities and find that CEOs of firms with poor governance spend more time with outsiders, an activity less beneficial to the firm and more beneficial to the CEO.