Knowledge that Transforms

Abstract It is well-known that individual beliefs cannot be identified using traditional choice data, unless we exogenously assume state-independent utilities. In this paper, I propose a novel methodology that solves this long-standing identification problem in a simple way. This method relies on extending the state space by introducing a proxy, for which the agent has no stakes conditional on the original state space. The latter allows us to identify the agent’s conditional beliefs about the proxy given each state realization, which in turn suffices for indirectly identifying her beliefs about the original state space. This approach is analogous to the one of instrumental variables in econometrics. Similarly to instrumental variables, the appeal of this method comes from the flexibility in selecting a proxy.

Abstract We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behaviour and establish conditions under which all parts of the model can be recovered from a sequence of choices. We allow peers to affect preferences, consideration, or both. We show that these peer-effect mechanisms have different behavioural implications in the data. This allows us to recover the set and the type of connections between the agents in the network. We then use this information to recover each agent’s preferences and consideration mechanisms. These nonparametric identification results allow for general forms of heterogeneity across agents and do not rely on the variation of either exogenous covariates or the set of available options (menus). We apply our results to model expansion decisions by tea chains and find evidence of limited consideration. We simulate counterfactual predictions and show how limited consideration slows market penetration and competition.

Abstract This paper develops a new framework for understanding when and how migrants shape culture, applying it to the Confederate diaspora—a small migrant group that left a large cultural imprint. Southern Whites that migrated after the Civil War played a pivotal role in spreading Confederate symbols and racial norms across the U.S. by the early 20th century. Their far-reaching influence stemmed from two key conditions: (i) an ideological intensity rooted in their experiences of slavery, secession, and military defeat and (ii) access to malleable power structures during westward expansion and post-war reconciliation. These conditions enabled them to transmit Confederate culture to both kin and non-Southern neighbours and to expand their reach by mobilising civil society organisation and leveraging positions of authority. They shaped policies and institutions that helped entrench racial norms and inequalities in labour markets, housing, and the criminal justice system. Our findings provide empirical foundations for understanding how migrants can transform local culture, rather than merely assimilate.

Abstract We introduce a survey instrument to measure earnings risk allowing for the possibility of quitting or being fired from the current job. We find these transitions to be the key drivers of subjective risk. A link with administrative data provides multiple credibility checks and reveals that subjective earnings risk varies systematically across the population. It is also many times smaller than traditional estimates even when conditioning richly on demographics and job history. We show that subjective earnings risk can help explain why many hold limited liquid assets.

Abstract What are the channels through which monetary policy affects financial stability? Can (and should) central banks prevent financial crises by deviating from price stability? To what extent may monetary policy itself unintentionally breed financial vulnerabilities? We answer these questions using a New Keynesian model with capital accumulation and endogenous financial crises due to adverse selection and moral hazard in credit markets. Our findings are threefold. First, monetary policy affects the probability of a crisis both in the short run (via aggregate demand) and in the medium run (via capital accumulation). Second, the central bank can reduce the incidence of crises in the medium run by tolerating higher inflation volatility in the short run. Third, prolonged periods of loose monetary policy followed by a sharp tightening can lead to financial crises.

Abstract We develop new robust discrete choice tools to learn about the average willingness to pay for a price subsidy and its effects on demand given exogenous, discrete variation in prices. Our starting point is a non-parametric, non-separable model of choice. We exploit the insight that our welfare parameters in this model can be expressed as functions of demand for the different alternatives. However, while the variation in the data reveals the value of demand at the observed prices, the parameters generally depend on its values beyond these prices. We show how to sharply characterize what we can learn when demand is specified to be entirely non-parametric or to be parametrized in a flexible manner, both of which imply that the parameters are not necessarily point identified. We use our tools to analyse the welfare effects of price subsidies provided by school vouchers in the DC Opportunity Scholarship Program. We find that the provision of the status quo voucher and a wide range of counterfactual vouchers of different amounts can have positive and potentially large benefits net of costs. The positive effect can be explained by the popularity of low-tuition schools in the programme; removing them from the programme can result in a negative net benefit. We also find that various standard logit specifications, in comparison, limit attention to demand functions with low demand for the voucher, which do not capture the large magnitudes of benefits credibly consistent with the data.

Abstract Bank capital requirements are based on book values, which are slow to reflect losses. In this article, we develop a dynamic model of banks to study the interaction of regulation and delayed accounting. Our model explains four stylized facts: book and market values diverge during crises, the market-to-book ratio predicts future profitability, book leverage constraints rarely bind strictly even as market leverage fans out during crises, and banks delever gradually after net-worth shocks. We show how delayed accounting can allow the regulator to achieve better outcomes than immediate (mark-to-market) accounting. In an estimated version of the model, the optimal regulation couples faster loan-loss recognition with a modest relaxation of the book leverage constraint.

Abstract We study repurchase options (repo contracts) in a competitive asset market with adverse selection. Gains from trade emerge from a liquidity need, but private information about asset quality prevents the full realization of trades. In equilibrium, a single repo contract pools all assets. The embedded repurchase option mitigates adverse selection by improving the volume of trades relative to outright sales. However, liquidity provision can be inefficiently low as lenders compete to attract high-quality assets via high haircuts and low rates. The equilibrium has a closed form and aligns well with empirical patterns across Mortgage-Backed Securities repos.

Abstract We study the use of Temporal-Difference learning for estimating the structural parameters in dynamic discrete choice models. Our algorithms are based on the conditional choice probability approach but use functional approximations to estimate various terms in the pseudo-log-likelihood function. We suggest two approaches: The first—linear semi-gradient—provides approximations to the recursive terms using basis functions. The second—Approximate Value Iteration—builds a sequence of approximations to the recursive terms by solving non-parametric estimation problems. Our approaches are fast and naturally allow for continuous and/or high-dimensional state spaces. Furthermore, they do not require specification of transition densities. In dynamic games, they avoid integrating over other players’ actions, further heightening the computational advantage. Our proposals can be paired with popular existing methods such as pseudo-maximum-likelihood, and we propose locally robust corrections for the latter to achieve parametric rates of convergence. Monte Carlo simulations confirm the properties of our algorithms in practice.

Abstract We show that the formalization of representativeness (Kahneman and Tversky (1972)) developed by Gennaioli and Shleifer (2010) features an intrinsic connection between uncertainty and overreaction. In the time series domain, we develop this connection in a smooth version of Diagnostic Expectations (DE), where overreaction varies smoothly with uncertainty. Intuitively, under smoothness, lower uncertainty leaves less room for representativeness to distort beliefs. Smooth DE provides a joint, parsimonious micro-foundation for key features of survey data: overreaction to news, stronger overreaction at longer horizons, overconfidence in subjective uncertainty, and a new stylized fact documented here—overreaction intensifies with higher uncertainty. An analytical Real Business Cycle model with Smooth DE accounts for survey overreaction and overconfidence, as well as three salient business cycle properties: asymmetry, countercyclical macro volatility, and countercyclical micro volatility.