Monetary Policy Estimation in Real Time: Forward‐Looking Taylor Rules without Forward‐Looking Data

I propose a methodology for estimating forward‐looking Taylor rules in real time when forward‐looking real‐time central bank data are unavailable. The methodology consists of choosing appropriate models to closely replicate U.S. Greenbook forecasts and then applying these models to Canada, Germany, and the U.K. The results show that German and U.S. Taylor rules are characterized by inflation coefficients increasing with the forecast horizon and a positive output gap response. The U.K. and Canada interest rate reaction functions achieve maximum inflation response at middle‐term horizons of about 1/2 years and the output gap coefficient is insignificant.     

Putting the New Keynesian DSGE Model to the Real‐Time Forecasting Test

The paper compares the quality of real‐time forecasts from a standard medium‐scale New Keynesian dynamic stochastic general equilibrium (DSGE) model to those from the Survey of Professional Forecasters (SPF) and DSGE‐VARs. It is shown that the DSGE model is relatively successful in forecasting the U.S. economy. This is especially true for forecasts conditional on SPF nowcasts, in which case the forecasting power of the DSGE turns out to be similar or better than that of the SPF for all the variables and horizons. An important weakness of the benchmark DSGE model is the poor absolute performance of its point forecasts and rather badly calibrated forecast densities.     

Credit Indicators as Predictors of Economic Activity: A Real‐Time VAR Analysis

Using readily available indicators of the profitability, price, and availability of credit—the term spread, junk‐bond spread, and banks’ “willingness to lend” as reported by the Federal Reserve—we show that it is possible to significantly improve on the real‐time output and employment predictions of forecasting professionals at the medium‐run horizons that are most relevant to policymakers and private decision makers. Key to this improvement is a flexible state–space model of data revisions. The willingness‐to‐lend variable is the best real‐time predictor of GDP growth. For forecasting job growth, all three credit indicators prove helpful.     

Identifying Discretionary Fiscal Policy Reactions with Real‐Time Data

We propose a method of identifying discretionary fiscal policy reactions using real‐time data. Automatic stabilizers should depend on true GDP, while discretionary fiscal policy is contingent on the information that policy makers have in real time. We can compute a real‐time measurement error by comparing the first release of GDP data with later revisions. Discretionary fiscal policy is influenced by this measurement error, whereas automatic fiscal policy is not. We use this identification approach to test the central identifying assumption of Blanchard and Perotti’s (2002) seminal structural vector autoregression (VAR). According to this assumption, fiscal policy makers do not react to GDP developments contemporaneously in a discretionary fashion. We find that government expenditure is adjusted upward if GDP growth in real time is lower than true GDP. This suggests that fiscal policy makers use short‐term funds to buy goods and services in response to their perception of GDP dynamics.     

Do Data Revisions Matter for DSGE Estimation?

This paper checks whether the coefficient estimates of a famous dynamic stochastic general equilibrium (DSGE) model are robust to macroeconomic data revisions. The effects of revisions are captured by rerunning the estimation on a real‐time data set compiled using the latest time series available each quarter from 1997 through 2015. Results show that estimates of the structural parameters are generally robust to changes in the data that have occurred over the past 20 years. By comparison, standard error estimates are more sensitive to revisions. The latter implies that judgments about the statistical significance of certain parameters depend on which data vintage is used for estimation.     

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.     

Estimating Probabilities of Recession in Real Time Using GDP and GDI

This work estimates Markov switching models on real‐time data and shows that the growth rate of gross domestic income (GDI), deflated by the gross domestic product (GDP) deflator, has done a better job recognizing the start of recessions than has the growth rate of real GDP. This result suggests that placing an increased focus on GDI may be useful in assessing the current state of the economy. In addition, the paper shows that the definition of a low‐growth phase in the Markov switching models changed considerably from 1978 to 2005. The models increasingly came to define this phase as an extended period of around zero rather than negative growth, diverging somewhat from the traditional definition of a recession.     

An Empirical Investigation of the Effects of Rounding on the SPF Probabilities of Decline and Output Growth Histograms

I consider the possibility that respondents to the Survey of Professional Forecasters round their probability forecasts of the event that real output will decline in the future, as well as their reported output growth probability distributions. I make various plausible assumptions about respondents’ rounding practices, and show how these impinge upon the apparent mismatch between probability forecasts of a decline in output and the probabilities of this event implied by the annual output growth histograms. I find that rounding accounts for about a quarter of the inconsistent pairs of forecasts.     

Time Aggregation and the Relationship between Inflation and Money Growth

Using panel data for 99 countries, we confirm that the measured elasticity of prices with respect to money is higher, and closer to unity, the higher is money growth and the longer the time horizon over which the data are averaged. We propose two explanations. In one, the true model of inflation involves a lagged response to money growth. In the other, there is negative correlation between shocks to inflation and money growth. Our empirical results can be explained if high–money‐growth countries have (i) shorter lags or (ii) less negative correlation, when compared to countries with low money growth.     

What Makes the Output–Inflation Trade‐Off Change? The Absence of Accelerating Deflation in Japan

It is standard to model the output–inflation trade-off as a linear relationship with a time-invariant slope. We assess empirical evidence for two sets of theories that allow for endogenous variation in the slope of the short-run Phillips curve. At an empirical level, we examine why large negative output gaps in Japan in the late 1990s did not lead to accelerating deflation but instead coincided with stable, albeit moderately negative inflation. Our results suggest that this episode is most convincingly interpreted as reflecting a gradual flattening of the Phillips curve. We find that this flattening is best explained by models with endogenous price durations. These models imply that in any economy where trend inflation is substantially lower (or substantially higher) today than in past decades, time variation in the slope of the Phillips curve has become too important to ignore.     

The Output Effect of a Transition to Price Stability When Velocity Is Time Varying

This paper explores the effect of time‐varying velocity on output responses to policies for reducing/stopping inflation. We study a dynamic general equilibrium model with sticky prices in which we introduce time‐varying velocity. Specifically, we endogenize time‐varying velocity into the model developed by Ireland (1997) for analyzing optimal disinflation. The nonlinear solution method reveals that, depending on velocity, the “disinflationary boom” found by Ball (1994) may disappear even under perfect credibility and that early output losses may be much larger than previously thought. Indeed, we find that a gradual disinflation from a low inflation may even be undesirable.     

Time Variation in the Inflation Passthrough of Energy Prices

From Bayesian estimates of a vector autoregression that allows for both coefficient drift and stochastic volatility, we obtain the following three results. First, beginning in approximately 1975, the responsiveness of core inflation to changes in energy prices in the United States fell rapidly and remains muted. Second, this decline in the passthrough of energy inflation to core prices has been sustained through a recent period of markedly higher volatility of shocks to energy inflation. Finally, reduced energy inflation passthrough has persisted in the face of monetary policy that became less responsive to energy inflation starting around 1985.     

Real‐Time Forecasting and Political Stock Market Anomalies: Evidence for the United States

Using monthly data from 1953 to 2003, we apply a real‐time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns in real‐time. Our empirical findings show that political variables, chosen on the basis of widely used model‐selection criteria, are often included in real‐time forecasting models. However, political variables do not contribute systematically to improving the performance of simple trading rules. For this reason, political stock market anomalies are not necessarily an indication of market inefficiency.     

A New Model of Inflation,Trend Inflation,and Long‐Run Inflation Expectations

This paper develops a bivariate model of inflation and a survey‐based long‐run forecast of inflation that allows for the estimation of the link between trend inflation and the long‐run forecast. Thus, our model allows for the possibilities that long‐run forecasts taken from surveys can be equated with trend inflation, that the two are completely unrelated, or anything in between. Using a variety of inflation measures and survey‐based forecasts for several countries, we find that long‐run forecasts can provide substantial help in refining estimates and fitting and forecasting inflation. It is less helpful to simply equate trend inflation with the long‐run forecasts.     

A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output

We compare a number of widely used trend‐cycle decompositions of output in a formal Bayesian model comparison exercise. This is motivated by the often markedly different results from these decompositions—different decompositions have broad implications for the relative importance of real versus nominal shocks in explaining variations in output. Using U.S. quarterly real GDP, we find that the overall best model is an unobserved components model with two features: (i) a nonzero correlation between trend and cycle innovations and (ii) a break in trend output growth in 2007. The annualized trend output growth decreases from about 3.4% to 1.2%–1.5% after the break. The results also indicate that real shocks are more important than nominal shocks. The slowdown in trend output growth is robust when we expand the set of models to include bivariate unobserved components models.     

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.     

Trend Inflation and the Nature of Structural Breaks in the New Keynesian Phillips Curve

We show that with a unit root in inflation, the new Keynesian Phillips curve (NKPC) implies an unobserved components model with a stochastic trend component and an inflation gap. Our empirical results suggest that with an increase in trend inflation during the Great Inflation, the response of inflation to real economic activity decreases and the persistence of the inflation gap increases due to an increase in the persistence of the unobserved stationary component. These results are in line with the predictions of Cogley and Sbordone ( 2008 ), who show that the coefficients of the NKPC are functions of time‐varying trend inflation.     

Estimates of the macroeconomic costs of cyber‐attacks

This paper estimates the macroeconomic losses related to the cyber‐attacks originating from the information and communications technology (ICT) and the financial sectors. The study accounts for the interdependency of various economic sectors and looks to the cascading effect of cyber‐attacks on production network in the United States and leading Organisation for Economic Co‐operation and Development countries with the help of the input–output methodology and the World Input–Output Database. Our results suggest that cyber‐attacks that affect the ICT and finance sectors result in losses which also impact different economic sectors, due to cascading effects.     

Long‐Run Inflation and the Distorting Effects of Sticky Wages and Technical Change

We show that the Calvo price‐setting model is not necessarily inconsistent with evidence of a weak relation between positive trend inflation and price dispersion. We identify the interaction between sticky wages and technical change as factors disrupting the allocative role of the wage system under positive trend inflation. In turn, this interaction generates inefficient wage dispersion, as opposed to price dispersion, which fuels inflation costs. We conclude that it is too early to dismiss the New Keynesian model as a useful vehicle to assess the costs of inflation.     

The Meta Taylor Rule

We characterize U.S. monetary policy within a generalized Taylor rule framework that accommodates uncertainties about the duration of policy regimes and the specification of the rule, in addition to the standard parameter and stochastic uncertainties inherent in traditional Taylor rule analysis. Our approach involves estimation and inference based on Taylor rules obtained through standard linear regression methods, but combined using Bayesian model averaging techniques. Employing data that were available in real time, the estimated version of the “meta” Taylor rule provides a flexible but compelling characterization of monetary policy in the United States over the last 40 years.