We investigate the impact of sustainable investing—the investing practice that accounts for environmental/societal/governance factors—in a macroeconomic model with dynamic general equilibrium forces. Preference-driven sustainable investing impacts firms’ cost of capital and investors’ saving incentives, resulting in a dynamic feedback loop between productive capital reallocation and investor wealth ownership. We investigate the magnitude and timing of the impact in a calibrated quantitative model where sustainable preferences are disciplined by estimated portfolio return differentials. We finally present a policy implementation exercise that highlights the potential and the limits of sustainable investing as a market-driven mechanism to deliver policy-relevant macroeconomic impact.

In this paper, we study the economics of satellite launches to understand the impact of the collision risk externality on the dynamics of orbit use. We show that autocatalytic debris growth may render Earth’s orbit unusable, an outcome known as Kessler Syndrome. In our benchmark calibration, Kessler Syndrome can emerge anytime between the year 2040 and the year 2184,

In this paper, using firm-level data from CRSP, we document empirically that stock prices can simultaneously display “microefficiency” and “macroinefficiency;” an idea accredited to Paul Samuelson. To investigate the source of our empirical findings, we propose a theory of aggregation bias based on incomplete information and segmented markets.

In this paper, we show that dynamic models with dispersed information can be equivalently represented as models with hierarchical information. The result is useful because models with hierarchical information are easier to solve analytically.

In this paper, we establish and characterize a novel propagation mechanism under rational expectations, which we term confounding dynamics, that is responsible for the persistence of imperfect information across economic agents over time on relevant economic variables even when equilibrium variables are observed.

Small changes in agents’ information can produce very different rational expectations equilibria. We show that equilibria preserving incomplete information are informationally stable and learnable, while those fully revealing the underlying shocks are not.

In a large Cournot market, firms’ output decisions are strategic substitutes but their information acquisition can be complementary. The reversal arises because better-informed firms make the financial asset price less informative.

Stabilization policies can reduce volatility at some frequencies while increasing it at others. We characterize these design limits in systems with rational expectations and apply the results to monetary policy rules.

We resolve Futia’s apparent non-existence of rational expectations equilibria with endogenous signal extraction. Accounting for agents’ knowledge of the model reveals an equilibrium identical to the Full Communication equilibrium.

We examine how evidence of nonlinear growth can inform policy and develop methods for evaluating alternative policies. Applied to foreign aid, the results reject the recommendation to allocate more aid to countries with higher policy quality.

Stabilization policies face tradeoffs across frequencies: reducing volatility at one horizon can increase it at another. We show how these design limits depend on forward-looking behavior and affect the evaluation of policy rules.

We compare simple feedback rules with model-specific optimal rules under uncertainty about the economy and policymakers’ objectives. Examining outcomes at different frequencies shows why the case for optimal rules can break down.