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.
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.
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.
We model the world economy as one system of endogenous input-output relationships subject to frictions and study how the world's input-output structure and world's GDP change due to changes in frictions. We derive a sufficient statistic to identify frictions from the observed world input-output matrix, which we fully match for the year 2011. We show how changes in internal frictions impact the whole structure of the world's economy and that they have a much larger effect on world's GDP than external frictions. We also use our approach to study the role of internal frictions during the Great Recession of 2007–2009.
We build a general equilibrium production-based asset pricing model with heterogeneous rms that jointly accounts for rm-level and aggregate facts emphasized by the recent macroeconomic literature, and for important asset pricing moments. Using administrative rm-level data, we establish empirical properties of large negative idiosyncratic shocks and their evolution. We then demonstrate that these shocks play an important role for delivering both macroeconomic and asset pricing predictions. Finally, we combine our model with data on the universe of U.S. seaborne import since 2007, and establish the importance of supply chain disasters for the cross-section of asset prices.
We build a general equilibrium production-based asset pricing model with heterogeneous firms that jointly accounts for firm-level and aggregate facts emphasized by the recent macroeconomic literature, and for important asset pricing moments. Using administrative firm-level data, we establish empirical properties of large negative idiosyncratic shocks and their evolution. We then demonstrate that these shocks play an important role for delivering both macroeconomic and asset pricing predictions. Finally, we combine our model with data on the universe of U.S. seaborne import since 2007, and establish the importance of supply chain disasters for the cross-section of asset prices.
We characterize optimal policies in a multidimensional nonlinear taxation model with bunching. We develop an empirically relevant model with cognitive and manual skills, firm heterogeneity, and labor market sorting. The analysis of optimal policy is based on two main results. We first derive an optimality condition − a general ABC formula − that states that the entire schedule of benefits of taxes second order stochastically dominates the entire schedule of tax distortions. Second, we use Legendre transforms to represent our problem as a linear program. This linearization allows us to solve the model quantitatively and to precisely characterize the regions and patterns of bunching. At an optimum, 9.8 percent of workers is bunched both locally and nonlocally. We introduce two notions of bunching – blunt bunching and targeted bunching. Blunt bunching constitutes 30 percent of all bunching, occurs at the lowest regions of cognitive and manual skills, and lumps the allocations of these workers resulting in a significant distortion. Targeted bunching constitutes 70 percent of all bunching and recognizes the workers’ comparative advantage. The planner separates workers on their dominant skill and bunches them on their weaker skill, thus mitigating distortions along the dominant skill dimension. Tax wedges are particularly high for low skilled workers who are bluntly bunched and are also high along the dimension of comparative disadvantage for somewhat more skilled workers who are targetedly bunched.
In this paper, we introduce the weighted-average quantile regression framework, R 1 0 qY |X(u)ψ(u)du = X0β, where Y is a dependent variable, X is a vector of covariates, qY |X is the quantile function of the conditional distribution of Y given X, ψ is a weighting function, and β is a vector of parameters. We argue that this framework is of interest in many applied settings and develop an estimator of the vector of parameters β. We show that our estimator is √ T-consistent and asymptotically normal with mean zero and easily estimable covariance matrix, where T is the size of available sample. We demonstrate the usefulness of our estimator by applying it in two empirical settings. In the first setting, we focus on financial data and study the factor structures of the expected shortfalls of the industry portfolios. In the second setting, we focus on wage data and study inequality and social welfare dependence on commonly used individual characteristics.
We consider the problem of revenue-maximizing Bayesian auction design with several i.i.d. bidders and several items. We show that the auctiondesign problem can be reduced to the problem of continuous optimal transportation introduced by Beckmann (1952). We establish the strong duality between the two problems and demonstrate the existence of solutions. We then develop a new numerical approximation scheme that combines multi-tosingle-agent reduction and the majorization theory insights to characterize the solution.