Heterogeneous Inflation Expectations and Learning

Using the panel component of the Michigan Survey of Consumers, we estimate a learning model of inflation expectations, allowing for heterogeneous use of private information and lifetime inflation experience. Life experience inflation has a significant impact on individual expectations, but only for 1‐year‐ahead inflation. Public information is substantially more relevant for longer horizon expectations. Even controlling for life experience inflation and public information, idiosyncratic information explains a nontrivial proportion of the inflation forecasts of agents. Women, ethnic minorities, and less educated agents have a higher degree of heterogeneity in their idiosyncratic information, and give less importance to recent movements in inflation.     

News on Inflation and the Epidemiology of Inflation Expectations

This paper examines the nexus between news coverage on inflation and households’ inflation expectations. In doing so, we test the epidemiological foundations of the sticky information model (Carroll 2003, 2006 ). We use both aggregate and household‐level data from the Survey Research Center at the University of Michigan. We highlight a fundamental disconnection among news on inflation, consumers’ frequency of expectation updating, and the accuracy of their expectations. Our evidence provides at best weak support to the epidemiological framework, as most of the consumers who update their expectations do not revise them toward professional forecasters’ mean forecast.     

Why Has U.S. Inflation Become Harder to Forecast?

We examine whether the U.S. rate of price inflation has become harder to forecast and, to the extent that it has, what changes in the inflation process have made it so. The main finding is that the univariate inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an integrated moving average process with time-varying parameters. This model explains a variety of recent univariate inflation forecasting puzzles and begins to explain some multivariate inflation forecasting puzzles as well.     

Survey Measures of Expected Inflation and the Inflation Process

The accuracy of inflation forecasts obtained from household and professional surveys has deteriorated noticeably of late, to the extent that a simple autoregressive specification outperforms survey forecasts. The decline in (absolute and relative) accuracy has taken place at about the same time as an apparent change in the inflation process. Projections of household forecasts on realized inflation suggests that households have not recognized this change. For the professionals, projections of expected inflation on headline inflation have changed, but on core inflation have not. By contrast, projections of realized headline inflation on core have changed sharply.     

Measuring Inflation Expectations Uncertainty Using High‐Frequency Data

Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.     

A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations

We study the evolution of U.S. inflation by means of a new noncausal autoregressive model with time‐varying parameters that outperforms the corresponding causal and constant‐parameter noncausal models in terms of fit and forecast accuracy. Our model also beats the unobserved component stochastic volatility (UCSV) model, one of the best‐performing univariate inflation forecasting models, in terms of both point and density forecasts. We also show how the new Keynesian Phillips curve can be estimated based on our noncausal model. Both expected and lagged inflation turn out important, but the former dominates in determining the current inflation.     

Economic Literacy and Inflation Expectations: Evidence from a Laboratory Experiment

We present experimental evidence of a link between economic literacy and inflation forecast accuracy. The experiment investigates two channels through which economic literacy may enable better forecasts: (i) choice of information and (ii) use of information. More literate subjects choose more relevant information and use the given information more effectively. Starting from a 10th percentile score, the boost in literacy from taking an economics course predicts a 0.64 standard deviation decline in mean absolute forecasting error. Our findings suggest that a significant portion of demographic heterogeneity in inflation expectations—observed in survey data—may be driven by heterogeneity in economic literacy.     

Inflation Announcements and Social Dynamics

We propose a new framework for understanding the effectiveness of central bank announcements when firms have heterogeneous inflation expectations. Expectations are updated through social dynamics and, with heterogeneity, not all firms choose to operate, putting downward pressure on realized inflation. Our model rationalizes why countries stuck at the zero lower bound have had a hard time increasing inflation without being aggressive. The same model also predicts that announcing an abrupt target to disinflate will cause inflation to undershoot the target, whereas announcing gradual targets will not. We present new empirical evidence that corroborates this prediction.     

Inflation targeting: An indirect approach to assess the direct impact

It is quite difficult to assess the benefits of inflation targeting (IT) since its immediate effect will be on inflation expectations, an unobserved variable. Due to lack of comprehensive data on inflation expectations, most studies so far concentrated on the impact of IT either on observable variables like output, unemployment, and inflation or compared post-IT surveys of IT countries with non-IT countries. In our study, we focus on a yet unanswered question, i.e., how the expectations change with the adoption of IT. We suggest that heterogeneous inflation expectations lead to long memory in actual inflation, and IT, if successful, should decrease this persistence by concentrating the public’s expectations toward the announced target. Empirical results confirm our hypothesis with a reduction in inflation memory after the adoption of IT in almost all eight developed countries in our sample.     

Nowcasting U.S. Headline and Core Inflation

Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. consumer price index and price index for personal consumption expenditures that relies on relatively few variables. The model's nowcasting accuracy improves as information accumulates over a month or quarter, outperforming statistical benchmarks. In real‐time comparisons, the model's headline inflation nowcasts substantially outperform those from the Blue Chip consensus and the Survey of Professional Forecasters. Across all four inflation measures, the model's nowcasting accuracy is comparable to that of the Federal Reserve Board's Greenbook.     

Does Global Liquidity Help to Forecast U.S. Inflation?

We construct a measure of global liquidity using the growth rates of broad money for the G7 economies. Global liquidity produces forecasts of U.S. inflation that are significantly more accurate than the forecasts based on U.S. money growth, Phillips curve, and autoregressive and moving average models. The marginal predictive power of global liquidity is strong at 3-year horizons. Results are robust to alternative measures of inflation.     

Fiscal Adjustment and Inflation Targeting in Less Developed Countries

Inflation targeting may not be viable in less developed countries (LDCs) where policymakers rely too heavily on cuts in infrastructure investment to balance the budget. Using a mix of analytical and numerical methods, we demonstrate that the equilibrium ceases to be saddle point stable under active policy when infrastructure cuts account for 30–70% of fiscal adjustment and the return on infrastructure exceeds a comparatively low threshold value. The result is robust to the form of the Taylor rule, the degree of real wage flexibility, the initial level of debt, the choice of a balanced‐budget or debt‐targeting rule, and the q‐elasticity of private investment spending.     

Expectations of future income and real exchange rate movements

We show that changes in expectations of future income driven by exogenous factors (such as the discovery of oil and an increase in global demand for natural resources) can cause movements in the real exchange rate (RER) in excess of, and sometimes even in the opposite direction to, what one would expect given the changes in current income. We provide both a theoretical model and empirical evidence of this. In particular, we show that the signing of numerous production sharing agreements (PSAs) between the government of Azerbaijan and foreign oil companies in 1994–1998 fueled expectations of higher future incomes, resulting in a considerable appreciation of the RER. Some of these PSAs subsequently failed or ran into difficulties, which led to a downward revision of expected future income and a depreciation of the RER in 1999–2003, even though the current income started to rise, due to an increase in the current oil revenue.     

Quantifying the Risk of Deflation

We propose formal and quantitative measures of the risk that future inflation will be excessively high or low relative to the range preferred by a private sector agent. Unlike alternative measures of risk, our measures are designed to make explicit the dependence of risk measures on the private sector agent's preferences with respect to inflation. We illustrate our methodology by estimating the risks of deflation for the United States, Germany, and Japan for horizons of up to 2 years. The question of how large these risks are has been subject to considerable public debate. We find that, as of September 2002 when this question first arose, there was no evidence of substantial deflation risks for the United States and for Germany, contrary to some conjectures at the time. In contrast, there was evidence of substantial deflation risks in Japan.     

Inflation dynamics: A cross-country investigation

We document that “persistent and lagged” inflation (with respect to output) is a world-wide phenomenon in that these short-run inflation dynamics are highly synchronized across countries. In particular, the average cross-country correlation of inflation is significantly and systematically stronger than that of output, while the cross-country correlation of money growth is essentially zero. We investigate whether standard monetary models driven by monetary shocks are consistent with the empirical facts. We find that neither the new Keynesian sticky-price model nor the sticky-information model can fully explain the data. An independent contribution of the paper is to provide a simple solution technique for solving general equilibrium models with sticky information.     

An Inflation‐Predicting Measure of the Output Gap in the Euro Area

Using a small Bayesian dynamic factor model of the euro area, we estimate the deviations of output from its trend that are consistent with the behavior of inflation. We label these deviations the output gap. In order to pin down the features of the model, we evaluate the accuracy of real‐time inflation forecasts from different model specifications. The version that forecasts inflation best implies that after the 2011 sovereign debt crisis, the output gap in the euro area has been much larger than the official estimates. Versions featuring a secular stagnation‐like slowdown in trend growth, and hence a small output gap after 2011, do not adequately capture the inflation developments.     

Inflation and productive activity in a multiple-matching model of money

This paper investigates the relationship between money growth, inflation, and productive activity in a dynamic general-equilibrium, multiple-matching framework where trade frictions are manifested by limited consumption variety. Productive activity and matching in the goods market are endogenized by a time allocation decision of work and search effort. We find that a high degree of complementarity between participation in the labor and goods markets creates a channel by which inflation can positively influence production and output. This feature arises when household preferences for consumption variety is sufficiently large and it can also lead to the multiplicity of monetary equilibria.     

Relative Prices as Aggregate Supply Shocks with Trend Inflation

Ball and Mankiw (1995) use a static menu-cost model to explain the historical behavior of the first and higher moments of commodity price changes in U.S. producer prices. We show that when appropriately modified for a world of positive trend inflation and forward-looking behavior by firms, the menu-cost model predicts a much weaker (possibly zero) correlation between the mean and the skewness of price changes than that found in the data.     

Are Some Forecasters Really Better Than Others?

In any data set with individual forecasts of economic variables, some forecasters will perform better than others. However, it is possible that these ex post differences reflect sampling variation and thus overstate the ex ante differences between forecasters. In this paper, we present a simple test of the null hypothesis that all forecasters in the U.S. Survey of Professional Forecasters have equal ability. We construct a test statistic that reflects both the relative and absolute performance of the forecaster and use bootstrap techniques to compare the empirical results with the equivalents obtained under the null hypothesis of equal forecaster ability. Results suggest little support for the idea that the best forecasters are actually innately better than others, though there is evidence that a relatively small group of forecasters perform very poorly.