Jonathan J. Adams

This paper characterizes a general class of macroeconomic models with incomplete information, which feature endogenous signal processes. These types of models are not always well-behaved, possibly featuring zero or many equilibria, and solution algorithms may not converge. I introduce an Information Feedback Regularity condition to discipline these models.  If the regularity condition is satisfied, then the model exhibits a number of nice properties, including: a "computable" equilibrium must exist, and if an equilibrium is stable, then it is the globally unique stable equilibrium.  I prove that computable equilibria approximate uncomputable infinite-dimensional stable equilibria arbitrarily well, and that the regularity condition is necessary for any equilibrium to be stable.  Then, I study the regularity condition and equilibrium properties in a number of example applications.  Finally, I introduce an algorithm to solve the general model, and provide resources to compute it. 

The consensus among central bankers is that higher inflation expectations can drive up actual inflation. We assess this by devising a novel method for identifying shocks to inflation expectations, estimating a semi-structural VAR where an expectation shock is identified as that which causes measured forecasts to diverge from the rational expectation.  Using data for the United States, we find that a positive inflation expectation shock is contractionary and deflationary: output, inflation, and interest rates all fall. These results are inconsistent with the standard New Keynesian model, which predicts inflation and interest rate hikes.  We discuss possible resolutions to this puzzle.

How should policymakers respond to mistakes made by agents without rational expectations?  I demonstrate in a general setting that the optimal policy is determined by a sufficient statistic: agents' belief distortions.  This result is both simple and only semi-structural: in order to calculate policy from the belief distortion, the policymaker does not need to know the whole macroeconomic model.  They only need to know how beliefs and policies distort decisions.  Crucially, they do not even need to know how expectations are formed; they only need to measure them. Next, I study several examples.  In a behavioral RBC model, the optimal policy is to tax capital when agents are overly optimistic about future returns.  In a behavioral New Keynesian model, the optimal policy is to raise interest rates when agents misperceive the economy to be running hot.

How do investment frictions and information frictions interact?  We study this question in a continuous time model of heterogeneous firms facing incomplete information and irreversible investment.  We analytically characterize how the information friction distorts firms' decision rules and stationary distribution.  The two frictions interact in rich and substantial ways.  Noisier information shrinks a firm's inaction region, reduces the elasticity of investment to productivity, increases steady-state capital, increases capital misallocation, and makes firms less risky.  Then, we test and confirm these predictions using Japanese administrative data that matches firms' forecasts to their balance sheets, incomes, and expenditures.

We propose a method to identify the anticipated components of macroeconomic shocks in a structural VAR. We include empirical forecasts about each time series in the VAR.  This introduces enough linear restrictions to identify each structural shock and to further decompose each one into "news" and "surprise" shocks.  We estimate a VAR on US time series using forecast data from the SPF, CBO, Federal Reserve, and asset prices.  Unanticipated fiscal stimulus and monetary policy shocks have typical effects that match existing evidence.  In our news-surprise decomposition, we find that news drives around one quarter of US business cycle volatility.  News explains a larger share of the variance due to fiscal shocks than for monetary policy shocks.  Finally, we use the news structure of the shocks to estimate counterfactual policy rules, and compare the ability of fiscal and monetary policy to moderate output and inflation.  We find that coordinated fiscal and monetary policy are substantially more effective than either tool is individually.

Behavioral expectations affect determinacy in macroeconomic models.  Relaxing rational expectations can make models more or less well behaved, depending on the behavioral assumptions.  In some cases, multiplicity is created; in other cases, multiplicity is eliminated.  Is it possible to tell exactly when there are multiple solutions?  Yes: I derive a Behavioral Blanchard-Kahn sufficient condition that ensures a unique equilibrium exists.  If and only if this condition or a Sunspot Admissibility condition hold, then a model's solution must be unique.  These conditions depend on the spectrum of the behavioral expectation operator.  I describe how to check these conditions for an arbitrary behavioral expectation, and illustrate with a large variety of popular types of expectations, heuristics, and information frictions.  As an example, I demonstrate that a large class of behavioral expectations imply a unique solution to the New Keynesian model with an interest rate peg, including all strictly backwards-looking heuristics. Another class of expectations imply that asset prices exhibit non-fundamental volatility in a standard model.

Dynamic stochastic models with full information and rational expectations (FIRE) are not as well determined as is commonly believed.  If the assumption of causality is relaxed so that prices and decisions may anticipate future shocks, then FIRE models generally feature multiple equilibria.  The multiplicity is due to the endogenous feedback from choices to information to choices, which in equilibrium may contain self-fulfilling news about future shocks.  I demonstrate the multiplicity in several examples, including canonical asset pricing and business cycle models.  To motivate relaxing the causality assumption, I also study examples with apparent non-causality, even if the model is fundamentally causal.  Then I examine how the multiplicity arises in a dynamic programming problem with decentralized markets.  Finally, I argue that the business cycle literature must reject FIRE.

How do terms of trade shocks affect open economies? We use a panel of global commodity prices to estimate the dynamic effects of terms of trade shocks on macroeconomic variables for 205 countries. We find that terms of trade shocks resemble wealth shocks: a terms of trade improvement increases consumption and investment by more than output and decreases net exports, contrary to prior evidence and standard theory. To explain this outcome, we also show that terms of trade improvements increase countries' net foreign asset position, due to valuation effects of nominal net assets. To make sense of these results, we augment a standard business cycle model with realistic international portfolio choice. We estimate the model for a large sample of countries, and show that it can replicate our empirical findings: terms of trade improvements look like wealth shocks, and their importance for business cycles is heterogeneous, depending on the country's international portfolio position.

Why is growth slowing? Two facts are documented: 1. Richer countries spend a greater share of their income on research and development, and 2. Countries with high spending on research and development grow slower. These facts are evident in both the US time series and in the cross-section of countries. The paper proposes a model that explains these two facts, driven by declining returns to research and development. As technology advances, it costs a greater share of output to increase at the same rate; innovators compensate by spending more in R&D, but cannot compensate fully. In the long run, the R&D share of output asymptotes to 3.0-3.9%, and the per capita GDP growth rate declines to 1.0-1.5%.