Optimal sticky prices under rational inattention

This paper presents a model in which price setting firms decide what to pay attention to, subject to a constraint on information flow. When idiosyncratic conditions are more variable or more important than aggregate conditions, firms pay more attention to idiosyncratic conditions than to aggregate conditions. When we calibrate the model to match the large average absolute size of price changes observed in micro data, prices react fast and by large amounts to idiosyncratic shocks, but prices react only slowly and by small amounts to nominal shocks. Nominal shocks have strong and persistent real effects. We use the model to investigate how the optimal allocation of attention and the dynamics of prices depend on the firms’ environment. JEL Classification: E3, E5, D8rational inattention, real effects of nominal shocks, sticky prices

Business cycle dynamics under rational inattention

We develop a dynamic stochastic general equilibrium model with rational inattention by households and firms. Consumption responds slowly to interest rate changes because households decide to pay little attention to the real interest rate. Prices respond quickly to some shocks and slowly to other shocks. The mix of fast and slow responses of prices to shocks matches the pattern found in the empirical literature. Changes in the conduct of monetary policy yield very different outcomes than in models currently used at central banks because systematic changes in policy cause reallocation of attention by decision-makers in households and firms. JEL Classification: D83, E31, E32, E52business cycles, information choice, monetary policy, rational inattention

What does the Bank of Japan do to East Asia?

In recent policy debates some have argued that expansionary monetary policy in Japan can increase real output in Japan and in Japan´s neighbors, while others have warned that it is a beggar-thy-neighbor policy. In this paper we estimate structural vector autoregressions to assess the effects of Japanese monetary policy shocks. We find that the effects of Japanese monetary policy shocks on macroeconomic variation in East Asia have been modest and difficult to reconcile with the beggar-thy-neighbor view. We estimate that the Asian crisis was preceded by expansionary monetary policy shocks in Japan, but we fail to find support for the view that these shocks contributed to the crisis

External Shocks, U.S. Monetary Policy and Macroeconomic Fluctuations in Emerging Markets

Using structural VARs, I find that external shocks are an important source of macroeconomic fluctuations in emerging markets. Furthermore, U.S. monetary policy shocks affect quickly and strongly interest rates and the exchange rate in a typical emerging market. The price level and real output in a typical emerging market respond to U.S. monetary policy shocks by more than the price level and real output in the U.S. itself. These findings are consistent with the idea that “when the U.S. sneezes, emerging markets catch a cold.” At the same time, U.S. monetary policy shocks are not important for emerging markets relative to other kinds of external shocks

On implications of micro price data for macro models

We review the recent literature that studies new, detailed micro data on prices. We discuss implications of the new micro data for macro models. We argue that the new micro data are helpful for macro models, but not decisive. There is no simple mapping from the frequency of price changes in micro data to impulse responses of prices and quantities to shocks. We discuss ideas that promise to deliver macro models matching the impulse responses seen in macro data while being broadly in line with micro data

Granger-causal-priority and choice of variables in vector autoregressions

A researcher is interested in a set of variables that he wants to model with a vector auto-regression and he has a dataset with more variables. Which variables from the dataset to include in the VAR, in addition to the variables of interest? This question arises in many applications of VARs, in prediction and impulse response analysis. We develop a Bayesian methodology to answer this question. We rely on the idea of Granger-causal-priority, related to the well-known concept of Granger-non-causality. The methodology is simple to use, because we provide closed-form expressions for the relevant posterior probabilities. Applying the methodology to the case when the variables of interest are output, the price level, and the short-term interest rate, we find remarkably similar results for the United States and the euro area

Inattention to rare events

The world recently experienced several rare events with disastrous consequences: the global financial crisis, the European sovereign debt crisis, and the Fukushima nuclear accident. These events have in common that key decision-makers were unprepared for them, which aggravated these events. We develop a model in which agents make state-contingent plans — prepare to act in different contingencies — subject to the constraint that agents can process only a finite amount of information. We identify the forces that make agents prepare little for some contingencies. We study whether a social planner would want agents to prepare more for rare events

The rational inattention filter

Dynamic rational inattention problems used to be difficult to solve. This paper provides simple, analytical results for dynamic rational inattention problems. We start from the benchmark rational inattention problem. An agent tracks a variable of interest that follows a Gaussian process. The agent chooses how to pay attention to this variable. The agent aims to minimize, say, the mean squared error subject to a constraint on information flow, as in Sims (2003). We prove that if the variable of interest follows an ARMA(p,q) process, the optimal signal is about a linear combination of {Xt,…,Xt-p+1} and {εt,…, εt-q+1}, where Xt denotes the variable of interest and εt denotes its period t innovation. The optimal signal weights can be computed from a simple extension of the Kalman filter: the usual Kalman filter equations in combination with first-order conditions for the optimal signal weights. We provide several analytical results regarding those signal weights. We also prove the equivalence of several different formulations of the information flow constraint. We conclude with general equilibrium applications from Macroeconomics

Gambling to preserve price (and fiscal) stability

We study a model in which policy aims at aggregate price stability. A fiscal imbalance materializes that, if uncorrected, must cause inflation, but the imbalance may get corrected in the future with some probability. By maintaining price stability in the near term, monetary policy can buy time for a correction to take place. The policy gamble may succeed, with price stability preserved indefinitely, or fail, leading to a delayed, possibly large jump in the price level. The resulting dynamics resemble the models of a currency crisis following Krugman (1979) and Obstfeld (1986). Like in Obstfeld’s work, multiple equilibria arise naturally: whether or not price stability is preserved may depend on private agents’ expectations. The model can be reinterpreted as a model of partial default on public debt, in which case it is reminiscent of Calvo (1988)

Priors about Observables in Vector Autoregressions *

Abstract We formulate a prior about observables in a vector autoregression (VAR) and then solve the deconvolution problem for the implied prior about VAR parameters. Formulating a prior about observables is more intuitive than formulating a prior about VAR parameters directly, because VAR parameters are hard to interpret. Our numerical algorithm for approximating the implied prior about parameters works well even in high-dimensional problems and can be applied also for models other than VARs. In the empirical application we formulate a prior about growth rates of the observables in a VAR model of the United States economy. We find that this prior makes a big difference for the estimated persistence of output responses to monetary policy shocks, compared with the results of standard priors for VARs