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    Bosio, Erica, Simeon Djankov, Edward L. Glaeser, and Andrei Shleifer. 2022. “Public Procurement in Law and Practice.” American Economic Review 112 (4). Abstract

    We examine a new data set of laws and practices governing public procurement, as well as procurement outcomes, in 187 countries.  We measure regulation as restrictions on discretion of the procuring agents.  We find that laws and practices are highly correlated with each other across countries, better practices are correlated with better outcomes, but laws themselves are not correlated with outcomes.  To shed light on this puzzle, we present a model of procurement in which both regulation and public sector capacity determine the efficiency of procurement. In the model, regulation is effective in countries with low public sector capacity, and detrimental in countries with high public sector capacity because it inhibits the socially optimal exercise of discretion.  We find evidence broadly consistent with this prediction: regulation of procurement improves outcomes, but only in countries with low public sector capacity.

    Gennaioli, Nicola, Rafael LaPorta, Florencio Lopez-de-Silanes, and Andrei Shleifer. 2022. “Trust and Insurance Contracts.” Review of Financial Studies 35 (12): 5287–5333. Abstract

    We assemble and analyze a new data set of homeowner insurance claims from 28 independently operated country subsidiaries of a multinational insurance company. A fundamental feature of the data is that such claims are often disputed, and lead to rejections or lower payments. We propose a new model of insurance, in which consumers can make invalid claims and firms can deny valid claims. In this environment, trust and honesty are critical factors that shape insurance contracts and the payment of claims, especially when the disputed amounts are too small for courts. We characterize equilibrium insurance contracts, and show how they depend on the quality of the legal system and the level of trust. We then investigate the incidence of claims, disputes and rejections of claims, and payment of claims in our data, as well as the cost and pricing of insurance. The evidence is consistent with the centrality of trust for insurance markets, as predicted by the model.

    Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. Working Paper. “Real Credit Cycles”. Abstract
    Recent empirical work has revived the Minsky hypothesis of boom-bust credit cycles driven by uctuations in investor optimism. To quantitatively assess this hypothesis, we incorporate diagnostic expectations into an otherwise standard business cycle model with heterogeneous firms and risky debt. Diagnostic expectations are a psychologically founded, forward-looking model of belief formation that captures over-reaction to news. We calibrate the diagnosticity parameter using microdata on the forecast errors of managers of listed firms in the US. The model generates countercyclical credit spreads and default rates, while the rational expectations version generates the opposite pattern. Diagnostic expectations also offer a good fit of three patterns that have been empirically documented: systematic reversals of credit spreads, systematic reversals of aggregate investment, and predictability of future bond returns. Crucially, diagnostic expectations also generate a strong fragility or sensitivity to small bad news after steady expansions. The rational expectations version of the model can account for the rst pattern but not the others. Diagnostic expectations offer a parsimonious account of major credit cycles facts, underscoring the promise of realistic expectation formation for applied business cycle modeling.
    Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, Frederik Schwerter, and Andrei Shleifer. 2021. “Memory and Representativeness.” Psychological Review. Abstract

    We explore the idea that judgment by representativeness reflects the workings of episodic memory, especially interference. In a new laboratory experiment on cued recall, participants are shown two groups of images with different distributions of colors. We find that i) decreasing the frequency of a given color in one group significantly increases the recalled frequency of that color in the other group, ii) for a fixed set of images, different cues for the same objective distribution entail different interference patterns and different probabilistic assessments. Selective retrieval and interference may offer a foundation for the representativeness heuristic, but more generally for understanding the formation of probability judgments from experienced statistical associations.

    Bordalo, Pedro, Nicola Gennaioli, Spencer Yongwook Kwon, and Andrei Shleifer. 2021. “Diagnostic Bubbles.” Journal of Financial Economics 141 (3). Abstract
    We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with two well-known mechanisms: learning from prices and speculation (buying for resale). With diagnostic (but not with rational) expectations, these mechanisms lead to price paths exhibiting three phases: initial underreaction, followed by overshooting (the bubble), and finally a crash. With learning from prices, the model generates price extrapolation as a byproduct of fast moving beliefs about fundamentals, which lasts only as the bubble builds up. When investors speculate, even mild diagnostic distortions generate substantial bubbles.
    Bordalo, Pedro, Katie Coffman, Nicola Gennaioli, and Andrei Shleifer. 2019. “Beliefs about Gender.” American Economic Review 109 (3): 739-773. Abstract
    We conduct laboratory experiments that explore how gender stereotypes shape beliefs about ability of oneself and others in different categories of knowledge. The data reveal two patterns. First, men’s and women’s beliefs about both oneself and others exceed observed ability on average, particularly in difficult tasks. Second, overestimation of ability by both men and women varies across categories. To understand these patterns, we develop a model that separates gender stereotypes from mis-estimation of ability related to the difficulty of the task. We find that stereotypes contribute to gender gaps in self-confidence, assessments of others, and behavior in a cooperative game.
    Bordalo, Pedro, Nicola Gennaioli, Rafael LaPorta, and Andrei Shleifer. 2019. “Diagnostic Expectations and Stock Returns.” Journal of Finance 74 (6): 2839-2874. Abstract

    We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.

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