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.     

An Unobserved Components Model that Yields Business and Medium‐Run Cycles

We generalize the unobserved components (UC) model to allow the permanent component to have different dynamics than the transitory components when decomposing U.S. economic activity using a multivariate UC model of (log) output, consumption, and investment. We find that these proposed dynamics in the permanent component are statistically significant and distinct from those of the transitory components. Our approach provides an alternative explanation for the growth cycles identified by Comin and Gertler ( 2006 ) that is related to the cyclical movements in technology, in a framework consistent with the Beveridge and Nelson ( 1981 ) decomposition.     

Forecasting National Recessions Using State‐Level Data

We investigate whether there is information useful for identifying U.S. business cycle phases contained in subnational measures of economic activity. Using a probit model to forecast the National Bureau of Economic Research expansion and recession classification, we assess the incremental information content of state‐level employment growth over a commonly used set of national‐level predictors. As state‐level data adds a large number of predictors to the model, we employ a Bayesian model averaging procedure to construct forecasts. Based on a variety of forecast evaluation metrics, we find that including state‐level employment growth substantially improves nowcasts and very short‐horizon forecasts of the business cycle phase. The gains in forecast accuracy are concentrated during months of national 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.     

Analyzing U.S. Output and the Great Moderation by Simultaneous Unobserved Components

This paper seeks to determine the causal interaction between structural trend and cycle innovations in an unobserved components framework of aggregate output. For the purpose of identification, I propose allowing for shifts in volatility. This strategy provides good estimation precision when applied to U.S. industrial production. In the early 1980s, predominance of cycle shocks gives way to strong negative spillovers of trend impulses, consistent with real business cycle theories. The coincident reduction of macroeconomic volatility was mainly caused by pronounced dampening of transitory disturbances. This is in accordance with an important role of macroeconomic policy in explaining the Great Moderation.     

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 Cost Channel Reconsidered: A Comment Using an Identification‐Robust Approach

We reexamine the empirical relevance of the cost channel of monetary policy (e.g., Ravenna and Walsh 2006 ), employing recently developed moment‐conditions inference methods, including identification‐robust procedures. Using U.S. data, our results suggest that the cost channel effect is poorly identified and we are thus unable to corroborate the previous results in the literature.     

State‐Dependent Transmission of Monetary Policy in the Euro Area

We estimate a logit mixture vector autoregressive model describing monetary policy transmission in the euro area over the period 1999–2015. In contrast to other classes of nonlinear vector autoregressive models, regime affiliation is neither strictly binary, nor binary with a transition period, and based on multiple variables. We show that monetary policy transmission in the euro area can be described as a mixture of two states. In both states, output and prices are found to decrease after contractionary monetary policy shocks. However, the effects of monetary policy are less enduring in the “crisis state.”     

Intrinsic Persistence of Wage Inflation in New Keynesian Models of the Business Cycles

We derive and estimate a New Keynesian wage Phillips curve that accounts for intrinsic inertia. In line with microevidence on wage setting, we consider a wage‐setting model featuring an upward‐sloping hazard function, based on the notion that the probability of resetting a wage depends on the time elapsed since the last reset. Our wage Phillips curve embeds also backward terms. We test the hazard function slope using generalized method of moment estimation. Then, placing our equation in a small‐scale New Keynesian model, we investigate its dynamic properties using Bayesian estimation. Model comparison shows that our model outperforms commonly used alternative methods to introduce persistence.     

The Real‐Time Properties of the Bank of Canada's Staff Output Gap Estimates

We study the revision properties of the Bank of Canada's staff output gap estimates since the mid‐1980s and show that the average revision has been significantly smaller since the early 2000s. Alternatively, revisions from econometric output gap estimates have not experienced a similar improvement. We show that the overestimation of potential output in real time following the 1991–92 recession explains the large revisions in the first half of the sample. Although Phillips‐curve inflation forecasts slightly worsen when conditioned on real time instead of final gaps, their relative poor performance reflects the general lack of inflation predictability rather than real‐time gap measurement issues.     

Inventory Shocks and the Great Moderation

Why did the volatility of U.S. real GDP decline by more than the volatility of final sales with the Great Moderation in the mid‐1980s? One explanation is that firms shifted their inventory behavior toward a greater emphasis on production smoothing. We investigate the role of inventories in the Great Moderation by estimating an unobserved components model that identifies inventory and sales shocks and their propagation in the aggregate data. Our estimates provide no support for increased production smoothing. Instead, smaller transitory inventory shocks are responsible for the excess volatility reduction in output compared to sales. These shocks behave like informational errors related to production that must be set in advance and their reduction also helps explain the changed forecasting role of inventories since the mid‐1980s. Our findings provide an optimistic prognosis for a continuation of the Great Moderation, despite the dramatic movements in output during the recent economic crisis.     

A Historical Analysis of the Taylor Curve

Taylor (1979) shows that there is a permanent trade‐off between the volatilities of the output gap and inflation. Although a number of papers argue that the so‐called Taylor curve is a policy menu, we use it as an efficiency locus to gauge the appropriateness of monetary policy. We examine the efficiency of U.S. monetary policy from 1875 onward by measuring the orthogonal distance between the observed volatilities of the output gap and inflation from the Taylor curve. We also identify time periods in which the variability of the U.S. economy changed by observing shifts in this efficiency frontier.     

Deep Habits in the New Keynesian Phillips Curve

We derive and estimate a New Keynesian Phillips Curve (NKPC) in a model with deep habits. Habits are deep in that they apply to individual consumption goods instead of aggregate consumption. This alters the NKPC in a fundamental manner since it introduces consumption growth and future demand terms into the NKPC equation. We construct the driving process in the deep habits NKPC by using the model's optimality conditions to impute time series for unobservable variables. The resulting series is considerably more volatile than unit labor cost. Generalized methods of moments estimation shows an improved fit and a much lower degree of indexation compared to the standard NKPC.     

Aggregate Implications of Heterogeneous Households in a Sticky‐Price Model

This paper analyzes the role of heterogeneous households in propagating shocks over the business cycle by generalizing a basic sticky‐price model to allow for imperfect risk sharing between households that differ in labor incomes. I show that imperfectly insured household consumption distorts household incentive to supply labor hours through an idiosyncratic income effect, which in turn generates strategic complementarities in price setting and thus amplifies business cycle fluctuations. This mechanism diminishes the role of nominal rigidities and makes sticky‐price models more consistent with microeconomic evidence on the frequency of price changes.     

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.     

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.     

Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison

We use several U.S. and euro‐area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time‐varying uncertainty. We obtain survey‐consistent distributions of future inflation at any horizon, both in the U.S. and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the United States, while mild de‐anchoring occurred in the euro area. As of our sample end, both areas appear to be almost equally anchored.     

Making Weak Instrument Sets Stronger: Factor‐Based Estimation of Inflation Dynamics and a Monetary Policy Rule

The problem of weak identification has recently attracted attention in the analysis of structural macroeconomic models. Using robust methods can result in large confidence sets making precise inference difficult. We overcome this problem in the analysis of the hybrid New Keynesian Phillips Curve and a forward‐looking Taylor rule by employing stronger instruments. We suggest exploiting information from a large macroeconomic data set by generating factors and using them as additional instruments. This approach results in stronger instrument sets and hence smaller weak‐identification robust confidence sets. It allows us to conclude that there has been a shift toward more active monetary policy from the pre‐Volcker regime to the Volcker–Greenspan tenure.     

Price Setting in the Euro Area: Some Stylized Facts from Individual Producer Price Data

This paper summarizes the microevidence on the setting of producer prices in the euro area. The main findings are: (i) 21% of producer prices are adjusted each month, (ii) producer prices are changed more frequently and by smaller amounts than consumer prices (even after controlling for product characteristics), (iii) price decreases are relatively frequent, (iv) inflation correlates positively with the difference between the frequency of price increases and decreases, and (v) there is substantial variation in price flexibility across sectors, which can be explained in part by differences in the cost structure, the degree of competition, and the level of sectoral inflation.     

Effective Use of Survey Information in Estimating the Evolution of Expected Inflation

The evolution of the term structure of expected U.S. inflation is modeled using survey data to provide timely information on structural change not contained in lagged inflation data. To capture shifts in subjective perceptions, the model is adaptive to long‐horizon survey expectations. However, even short‐horizon survey expectations inform shifting‐endpoint estimates that capture the lag between inflation and the perceived inflation target, which anchors inflation expectations. Results show movements of the perceived target are an important source of inflation persistence and suggest historical U.S. monetary policy was not fully credible for much of the postwar sample.