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Uncertainty about future economic and climate conditions substantially affects the choice of policies for managing interactions between the climate and the economy. We develop a framework of dynamic stochastic integration of climate and economy, and show that the social cost of carbon is substantially affected by both economic and climate risks and is a stochastic process with significant variation. We examine a wide but plausible range of values for critical parameters with robust results and show that large-scale computing makes it possible to analyze policies in models substantially more complex and realistic than usually used in the literature.

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

The social cost of carbon is the expected present value of damages from emitting one ton of carbon today. We use perturbation theory to derive an approximate tractable expression for this cost adjusted for climatic and economic risk. We allow for different aversion to risk and intertemporal fluctuations, skewness and dynamics in the risk distributions of climate sensitivity and the damage ratio, and correlated shocks. We identify prudence, insurance, and exposure effects, reproduce earlier analytical results, and offer analytical insights into numerical results on the effects of economic and damage ratio uncertainty and convex damages on the optimal carbon price.

Banking crises are rare events that break out in the midst of credit-intensive booms and bring about deep and long-lasting recessions. This paper presents a textbook dynamic stochastic general equilibrium model to explain these phenomena. The model features a nontrivial banking sector, where bank heterogeneity gives rise to an interbank market. Moral hazard and asymmetric information in this market may lead to sudden market freezes, banking crises, credit crunches, and severe “financial” recessions. Those recessions follow credit booms and are not necessarily triggered by large exogenous adverse shocks.

This work nests the Agent-Based macroeconomic perspective into the earlier history of macroeconomics. We discuss how the discipline in the 70’s took a perverse path relying on models grounded on fictitious rational representative agent in order to try to pathetically circumvent aggregation and coordination problems. The Great Recession was a natural experiment for macroeconomics, showing the inadequacy of the predominant theoretical framework grounded on DSGE models. After discussing the pathological fallacies of the DSGE-based approach, we claim that macroeconomics should consider the economy as a complex evolving system, i.e. as an ecology populated by heterogenous agents, whose far-from-equilibrium interactions continuously change the structure of the system. This in turn implies that more is different: macroeconomics cannot be shrink to representative-agent micro, but agents’ complex interactions lead to emergence of new phenomena and hierarchical structure at the macro level. This is what is taken into account by agent-based models, which provide a novel way to model complex economies from the bottom-up, with sound empirically-based microfoundations. We present the foundations of Agent-Based macroeconomics and we discuss how the contributions of this special issue push its frontier forward. Finally, we conclude by discussing the ways ahead for the fully acknowledgement of agent-based models as the standard way of theorizing in macroeconomics.

We develop an equivalence between the equilibrium effects of incomplete information and those of two behavioral distortions: myopia, or extra discounting of the future; and anchoring of current behavior to past behavior, as in models with habit persistence or adjustment costs. We show how these distortions depend on higher-order beliefs and GE mechanisms, and how they can be disciplined by evidence on expectations. We finally illustrate the use of our toolbox with a quantitative application in the context of inflation, a bridge to the HANK literature, and an extension to networks.

We examine empirically and theoretically the relation between firms’ risk and distance to consumers in a production network. We document two novel facts: firms farther away from consumers have higher risk premiums and higher exposure to aggregate productivity. We quantitatively explain these findings using a general equilibrium model featuring a multilayer production process. The economic force is “vertical creative destruction,” that is, positive productivity shocks to suppliers devalue customers’ assets-in-place, thereby lowering the cyclicality of downstream firms’ values. We show that vertical creative destruction varies with competition and firm characteristics and generates sizable cross-sectional differences in risk premiums.

This article studies how the monetary policy regime affects the relative importance of nominal exchange rates and inflation rates in shaping the response of real exchange rates to shocks. We document two facts about inflation-targeting countries. First, the current real exchange rate predicts future changes in the nominal exchange rate. Second, the real exchange rate is a poor predictor of future inflation rates. We estimate a medium-size, open-economy DSGE model that accounts quantitatively for these facts as well as other empirical properties of real and nominal exchange rates. The key estimated shocks that drive the dynamics of exchange rates and their covariance with inflation are disturbances to the foreign demand for dollar-denominated bonds.

We compute a sunspot equilibrium in an estimated small-scale New Keynesian model with a zero lower bound (ZLB) constraint on nominal interest rates and a full set of stochastic fundamental shocks. In this equilibrium, a sunspot shock can move the economy from a regime in which inflation is close to the central bank’s target to a regime in which the central bank misses its target, inflation rates are negative, and interest rates are close to zero with high probability. A non-linear filter is used to examine whether the U.S. in the aftermath of the Great Recession and Japan in the late 1990s transitioned to a deflation regime. The results are somewhat sensitive to the model specification, but on balance, the answer is affirmative for Japan and negative for the U.S.

This paper jointly examines the link between competition and expected returns in the time series and in the cross-section. To this end, we build a general equilibrium model where markups vary because of firm entry with oligopolistic competition. When concentration is high, markups are more sensitive to entry risk. We find that higher markups are associated with higher expected returns over time and across industries, in line with the data. The model can also quantitatively account for the persistent rise in aggregate risk premiums and macroeconomic volatility associated with the secular increase trend industry concentration since the mid-1980s.