We study noisy aggregation of dispersed information in financial markets without imposing parametric restrictions on preferences, information, and return distributions. We provide a general characterization of asset returns by means of a risk-neutral probability measure that features excess weight on tail risks. Moreover, we link excess weight on tail risks to observable moments such as forecast dispersion and accuracy, and argue that it provides a unified explanation for several prominent cross-sectional return anomalies. Simple calibrations suggest the model can account for a significant fraction of empirical returns to skewness, returns to disagreement, and interaction effects between the two.
The European Union Emission Trading System is a prominent market-based mechanism to reduce emissions. While the theory is well-understood, we are the first to study the whole cap-and-trade mechanism as a financial market. Analyzing the universe of transactions in 2005-2020 (more than one million records of granular transaction data), we show that this market features significant inefficiencies undermining its goals. First, about 40% of firms never trade in a given year. Second, many firms only trade during surrendering months, when compliance is immediate and prices are predictably high. Third, a number of operators engage in speculative trading, exploiting private information.
Analyzing the universe of federal environmental regulations in the U.S., we construct a measure of regulations—direct taxes on pollution. Analyzing the universe of firms’ investor disclosures, we construct a measure of material environmental concerns—indirect taxes on pollution. These two empirical measures are new to the environmental regulations literature. Thirdly, we document an important new fact that the cross-sectional distribution of pollution changes is lumpy. We build a dynamic heterogeneous firm model with non-convex adjustment costs that fits the cross-sectional pollution evidence. The model explains half of the pollution decline in U.S. manufacturing over the last two decades due to direct and indirect taxes. We show that the dynamics of direct taxes (environmental regulations) and indirect taxes (environmental concerns), non-convex adjustment costs, and idiosyncratic productivity shocks are key determinants of pollution dynamics in U.S. manufacturing.
We empirically and quantitatively study the impact of supply chain disruptions on U.S. businesses. Leveraging granular shipment-level data on the universe of U.S. seaborne imports with nearly 200 million observations, we construct a measure of disruptions at the individual firm level for the time period 2013-2023. We document a significant heterogeneity in disruption rates among U.S. public firms, with a notable increase observed in recent years. We introduce a notion of supplier capital and investigate the effect of supply disruptions on firms’ investment decisions. In the data, firms tend to increase investment in supplier capital following the shock, however, financially distressed firms exhibit a much weaker response. We develop a general equilibrium model with heterogeneous firms and with investment in supplier capital. We show that firms’ ability to accumulate supplier capital by making costly investment is an important margin of adjustment in the aftermath of such crises. Financial constraints help account for the heterogeneous treatment effect observed in the data. Two supply chain initiatives proposed by the U.S. government to mitigate disruptions are evaluated. Finally, we document a significant rise in supply disruptions in sectors critical to the U.S. economy and build an index of critical supply disruptions. We show quantitatively that firms relying heavily on imports of critical products experience a much larger decline in output following a disruption shock relative to firms which are not engaged in critical supply chains.
We develop an economic theory of mental health. The theory is grounded in classic and modern psychiatric literature, is disciplined with micro data, and is formalized in a life-cycle heterogeneous agent framework. In our model, individuals experiencing mental illness have pessimistic expectations and lose time due to rumination. As a result, they work less, consume less, invest less in risky assets, and forego treatment which in turn reinforces mental illness. We quantify the societal burden of mental illness and evaluate the efficacy of prominent policy proposals. We show that expanding the availability of treatment services and improving treatment of mental illness in late adolescence substantially improve mental health and welfare.
We propose a new non-linear single-factor asset pricing model 𝑟𝑖𝑡 = ℎ( 𝑓𝑡 𝜆𝑖) + 𝜖𝑖𝑡 . Despite its parsimony, this model represents exactly any non-linear model with an arbitrary number of factors and loadings – a consequence of the Kolmogorov-Arnold representation theorem. It features only one pricing component ℎ( 𝑓𝑡 𝜆𝑖), comprising a nonparametric link function of the time-dependent factor and factor loading that we jointly estimate with sieve-based estimators. Using 171 assets across major classes, our model delivers superior cross-sectional performance with a low-dimensional approximation of the link function. Most known finance and macro factors become insignificant controlling for our single-factor.
We quantify the effects of the political development cycle – the fluctuations between the left (Maoist) and the right (pragmatist) development policies – on growth and structural transformation of China in 1953-1978. The left policies prioritized structural transformation towards non-agricultural production and consumption at the cost of agricultural development. The right policies prioritized agricultural consumption through slower structural transformation. The imperfect implementation of these policies led to large welfare costs of the political development cycle in a distorted economy undergoing a structural change.
Economic disruptions generally create winners and losers. The compensation problem consists of designing a reform of the existing income tax system that offsets the welfare losses of the latter by redistributing the gains of the former. We derive a formula for the compensating tax reform and its impact on the government budget when only distortionary tax instruments are available and wages are determined endogenously in general equilibrium. We apply this result to the compensation of robotization in the United States.
We analyze the consequences of noisy information aggregation for investment. Market imperfections create endogenous rents that cause overinvestment in upside risks and underinvestment in downside risks. In partial equilibrium, these inefficiencies are particularly severe if upside risks are coupled with easy scalability of investment. In general equilibrium, the shareholders' collective attempts to boost value of individual firms leads to a novel externality operating through price that amplifies investment distortions with downside risks but offsets distortions with upside risks.
We propose a new sorting framework: composite sorting. Composite sorting comprises of (1) distinct worker types assigned to the same occupation, and (2) a given worker type simultaneously being part of both positive and negative sorting. Composite sorting arises when fixed investments mitigate variable costs of mismatch. We completely characterize optimal sorting and additionally show it is more positive when mismatch costs are less concave. We then characterize equilibrium wages. Wages have a regional hierarchical structure − relative wages depend solely on sorting within skill groups. Quantitatively, composite sorting can generate a sizable portion of within-occupations wage dispersion in the US.
This paper studies stochastic hysteresis − general dependence on the path of past decisions and shocks. We develop a new methodology for deriving the explicit dynamics of optimal policy with path-dependence and show that stochastic hysteresis changes optimal policy both qualitatively and quantitatively. We showcase our methodology by deriving new results for optimal policy with stochastic habits, tipping points, robustness concerns, limited commitment, and dynamic private information.
This paper studies stochastic hysteresis − general dependence on the path of past decisions and shocks. We develop a new methodology for deriving the explicit dynamics of optimal policy with path-dependence and show that stochastic hysteresis changes optimal policy both qualitatively and quantitatively. We showcase our methodology by deriving new results for optimal policy with stochastic habits, tipping points, robustness concerns, limited commitment, and dynamic private information.
We develop a dynamic model of input-output networks that incorporates adjustment costs of changing inputs. Our closed-form solution for the dynamics of the economy shows that temporary shocks to upstream sectors, whose output travels through long supply chains, have disproportionately significant welfare impact compared to affected sectors’ Domar weights. We conduct a spectral analysis of the U.S. production network and reveal that the welfare impact of temporary sectoral shocks can be represented by a low-dimensional, 4-factor structure.
We argue that noisy aggregation of dispersed information provides a unified explanation for several prominent cross-sectional return anomalies such as returns to skewness, returns to disagreement and corporate credit spreads. We characterize asset returns with noisy information aggregation by means of a risk-neutral probability measure that features excess weight on tail risks, and link the latter to observable moments of earnings forecasts, in particular forecast dispersion and accuracy. We calibrate our model to match these moments and show that it accounts for a large fraction of the empirical return premia. We further develop asset pricing tools for noisy information aggregation models that do not impose strong parametric restrictions on economic primitives such as preferences, information, or return distributions.
We analyze the consequences of noisy information aggregation for investment. Market imperfections create endogenous rents that cause overinvestment in upside risks and underinvestment in downside risks. In partial equilibrium, these inefficiencies are particularly severe if upside risks are coupled with easy scalability of investment. In general equilibrium, the shareholders' collective attempts to boost value of individual rms leads to a novel externality operating through price that amplifies investment distortions with downside risks but o sets distortions with upside risks.