Output Gap Estimates Research Articles

STRUCTURAL ESTIMATION OF THE OUTPUT GAP: A BAYESIAN DSGE APPROACH

We estimate the output gap that is consistent with a standard New Keynesian dynamic stochastic general equilibrium (DSGE) model, where the output gap is defined as a deviation of output from its flexible‐price equilibrium, using Bayesian methods. Our output gap illustrates the U.S. business cycles well, compared with other estimates. We find that the main source of the output gap movements is the demand shocks, but that the productivity shocks contributed to the stable output gap in the late 1990s. The robustness analysis shows that the estimated output gap is sensitive to the specification for monetary policy rules. (JEL E30, E32, C11)

Simulating Inflation Forecasting in Real-Time: How Useful is a Simple Phillips Curve in Germany, the U.K.L4434, and the U.S.?

This paper simulates out-of-sample inflation forecasting for Germany, the UK, and the US. In contrast to other studies, we use output gaps estimated with unrevised real-time GDP data. This exercise assumes an information set similar to that available to a policymaker at a given point in time since GDP data is subject to sometimes substantial revisions. In addition to using real-time datasets for the UK and the US, we employ a dataset for real-time German GDP data not used before. We find that Phillips curves based on ex post output gaps generally improve the accuracy of inflation forecasts compared to an AR(1) forecast but that real-time output gaps often do not help forecasting inflation. This raises the question how operationally useful certain output gap estimates are for forecasting inflation.

Simulating Inflation Forecasting in Real-Time: How Useful is a Simple Phillips Curve in Germany, the UK, and the US?

This paper simulates out-of-sample inflation forecasting for Germany, the UK, and the US. In contrast to other studies, we use output gaps estimated with unrevised real-time GDP data. This exercise assumes an information set similar to that available to a policymaker at a given point in time since GDP data is subject to sometimes substantial revisions. In addition to using real-time datasets for the UK and the US, we employ a dataset for real-time German GDP data not used before. We find that Phillips curves based on ex post output gaps generally improve the accuracy of inflation forecasts compared to an AR(1) forecast but that real-time output gaps often do not help forecasting inflation. This raises the question how operationally useful certain output gap estimates are for forecasting inflation.

DO INTERNATIONAL MONETARY FUND PROGRAMS IMPACT ON THE SACRIFICE RATIO?

From time to time, the International Monetary Fund (IMF) makes resources available to member states for short‐term balance‐of‐payments support under an agreed arrangement know as a program. Most IMF programs include quantitative performance criteria for key macroeconomic variables, which borrowers must meet to obtain Fund resources. Standard open economy models predict that if policymakers are able to credibly commit to reducing inflation, rational economic agents will lower their expectations of inflation and, therefore, the trade‐off between inflation and output will fall. The present study tests whether IMF programs, by lending credibility to a country's adjustment program, influence the inflation–output trade‐off. The results from the study suggest that IMF programs do not significantly influence the inflation–output trade‐off. This finding is robust to changes in the estimation approach, the method used to obtain the output gap estimates and outliers.

Improving Real-Time Estimates of the Output Gap

This paper investigates strategies for real-time estimation of the output gap. First, I examine estimates from univariate models with stochastic cycles. This corresponds to the use of model-based band-pass filters in real-time, and I find that the turning points in real-time and final output gap series match more closely for higher order models and that the revisions properties and real-time accuracy are more favorable. Second, I investigate the use of capacity utilization as an auxiliary indicator to improve on output gap estimates in real-time. I find that this bivariate approach leads to significant gains in the accuracy of real-time estimates and in the quality of revisions.

An Estimation of Output Gap in Romanian Economy Using the DSGE Approach

In this paper I use an open economy DSGE model and estimate it for Romanian economy using Bayesian techniques. Based on estimation I derive a smoothed estimation of the output gap. I compare the results with those from standard procedures to estimate the output gap, the Hodrick Prescott ilter, the production function and an unobserved components model. The results show that the DSGE approach can give a better picture of the output gap and it is more consistent with the dynamics of Romanian economy.

Central bank misperceptions and the role of money in interest-rate rules

Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest-rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.

Central Bank Misperceptions and the Role of Money in Interest Rate Rules

Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.

Structural Time Series Models for Business Cycle Analysis

The chapter deals with parametric models for the measurement of the business cycle in economic time series. It presents univariate methods based on parametric trend - cycle decompositions and multivariate models featuring a Phillips type relationship between the output gap and inflation and the estimation of the gap using mixed frequency data. We finally address the issue of assessing the accuracy of the output gap estimates.

Central Bank Misperceptions and the Role of Money in Interest Rate Rules

Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.

Bayesian Analysis of the Output Gap

Our objective is to build output gap estimates that benefit from information provided by Phillips curve theory and business cycle studies. For this, we develop a Bayesian analysis of the bivariate Phillips curve model proposed by Kuttner for estimating potential output. Given our priors, we obtain samples from parameters and state variables joint posterior distribution following a Gibbs sampling strategy. We sample the state variables given parameters using the Carter–Kohn procedure, and we exploit a likelihood factorization to draw parameters given the state. A Metropolis–Hastings step is used to remove the conditioning on starting values. To accommodate the variance moderation that has been observed on U.S. gross domestic product, Kuttner's model is extended for a change in variance parameters. We apply this methodology to the analysis of the output gap in the United States and in the European Monetary Union. Finally, some important extensions to the original Kuttner model are discussed.

Estimating the Output Gap in a Changing Economy

Univariate filters used in output gap estimation are subject to criticism as being purely statistical and having no economic content. The information content of the output gap measures estimated by standard multivariate filtering techniques, on the other hand, can be distorted because of the possibly unrealistic restriction that system parameters stay constant over time. In this study, we seek to address these shortcomings by proposing an output gap estimation method that takes into account changing economic relations. We employ a nonlinear time series framework along with the extended Kalman filter, in which economic content is used by inflation and output gap dynamics and the parameters are allowed to be time varying. We use the Turkish economy as a laboratory to show that our method provides useful results, both in terms of the properties of output gap estimates and for the assessment of change in macroeconomic dynamics.

Protection, Openness, and Factor Adjustment: Evidence from the Manufacturing Sector in Uruguay

The authors use a panel of manufacturing firms to analyze the adjustment process in capital blue collar and white collar employment in Uruguay during a period of trade liberalization when average tariff protection fell from 43 to 14 percent. They calculate the desired factor levels arising from a counterfactual profit maximization in the absence of adjustment costs, generating a measure of factor shortages or surpluses. The average estimated output gap for 1982-95 is 2 percent. The authors' policy analysis shows that trade openness affected the adjustment functions of all three factors of production. Highly protected sectors adjust less when creating jobs (reducing labor shortages) than sectors with low protection. This may be due to fears of policy reversal in highly protected sectors. Also, highly protected sectors adjust more easily (than low protection sectors) when destroying jobs (reducing labor surpluses), especially in the case of blue collar labor. This suggests that trade protection may in fact destroy rather than create jobs within industries, as firms in highly protected sectors are more reluctant to hire and more ready to fire than firms in sectors with low protection. The results for capital are qualitatively similar but quantitatively smaller, suggesting that trade protection plays less of a role in explaining adjustment costs for capital. Interestingly, export-oriented sectors have lower adjustment costs for blue collar labor but not for white collar employment or capital, suggesting that export-led growth may be particularly successful in reducing blue collar unemployment.

Estimating potential output and the output gap for the euro area: a model-based production function approach

This paper provides an analysis of multivariate unobserved components models for the estimation of potential output and the output gap in the euro area. Bivariate models of output and inflation and multivariate model-based implementations of the production function approach are considered; according to the latter potential output is derived from the permanent components of the factors of production consistent with stable inflation, whereas the output gap results from the combination of the transitory components. This approach allows to measure the contribution of the various factors of production to potential output growth, and to assess the reliability of the output gap estimates. Various alternative statistical specifications for the separation of trend and cycle are considered entertaining different economic hypotheses. The paper also provides an assessment of the reliability of the alternative output gap estimates and analyses their predictive validity by means of a rolling forecast exercise that provides an evaluation of the capability to forecast future inflation.

Output Gap Uncertainty: Does it Matter for the Taylor Rule?

This paper analyses the effect of measurement error in the output gap on efficient monetary policy rules in a simple estimated model of the US economy. While it is a well-known result that such additive uncertainty does not affect the optimal feedback rule in a linear-quadratic framework, it is shown that output gap uncertainty can have a significant effect on the efficient response coefficients in restricted instrument rules such as the popular Taylor rule. Output gap uncertainty reduces the response to the current estimated output gap relative to current inflation and may partly explain why the parameters in estimated Taylor rules are often much lower than suggested by optimal control exercises which assume the state of the economy is known.

Real-time data for Norway: Challenges for monetary policy

Monetary policy conducted in real time has to take into account the preliminary nature of recent national accounts data. Not only recent data, but also numbers dating many years back are potentially subject to revision. This means that there is a danger that an important part of the central bank's information set is flawed for a substantial period of time. In this paper, we present results based on quarterly vintages of real-time data for Norway from 1993Q1 to 2003Q4. In the spirit of Orphanides and van Norden [Orphanides, A., & van Norden, S. (2002). The unreliability of output gap estimates in real-time. Review of Economics and Statistics, 84(4), 569–583], we analyze how data revisions, the accumulation of new observations in real time, and model uncertainty affect the reliability of output gap estimates. We find that total revisions of output gap estimates are heavily influenced by uncertainty about the trend at the end of the sample and that data revisions are of less importance, i.e., they are of smaller magnitude and show less persistence, than other sources of output gap revisions. Finally, we discuss the implications of output gap uncertainty for monetary policy using a small New Keynesian macroeconomic model.

The reliability of Canadian output-gap estimates

Recent work on policy rules under uncertainty has highlighted the impact of output-gap measurement errors on economic outcomes and their importance in the formulation of appropriate policy rules. This paper investigates the reliability of current estimates of the output gap in Canada. We begin by assembling a new database of quarterly real-time output estimates which spans the post-WWII period and contains data vintages dating back to 1972. We use this set with a broad range of univariate and multivariate output-gap models to recreate “contemporary” estimates of the output gap and then study how these estimates are revised over time. The nature and sources of these revisions are used to draw conclusions about the overall measurement errors associated with current estimates of the output gap. Relative to similar recent work with U.S. real-time data, we find that revisions in Canadian output gaps are more important and that the role of data revision is less innocuous than previously thought. We also show that using the change rather than the level of the output gap may only modestly reduce the measurement problem.

Real-time estimation of the output gap in Japan and its usefulness for inflation forecasting and policymaking

This paper examines the methods used by the Bank of Japan (BOJ) for estimation of the output gap. Great emphasis is put on the real-time estimation problems. After reviewing the evolution of output-gap estimation at the Bank, I discuss advantages and disadvantages of the various output-gap measures. First, I examine the usefulness of the output gap for inflation forecasting and show that the real-time output gap sometimes includes too much noise. Second, I investigate the implications of the real-time estimation problems for policy evaluation. Third, I exploit the TANKAN to enhance the usefulness of the real-time output gap.

The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time

A stable predictive relationship between inflation and the output gap, often referred to as a Phillips curve, provides the basis for countercyclical monetary policy in many models. In this paper, we evaluate the usefulness of alternative univariate and multivariate estimates of the output gap for predicting inflation. Many of the ex post output gap measures we examine appear to be quite useful for predicting inflation. However, forecasts using real-time estimates of the same measures do not perform nearly as well. The relative usefulness of real-time output gap estimates diminishes further when compared to simple bivariate forecasting models which use past inflation and output growth. Forecast performance also appears to be unstable over time, with models often performing differently over periods of high and low inflation. These results call into question the practical usefulness of the output gap concept for forecasting inflation.

Real-Time Data and Business Cycle Analysis in Germany

This paper examines the consequences of using so-called data for business cycle analysis in Germany. Based on a novel data set covering quarterly real output data from 1980 to 2002 real-time output gaps using some popular filter methods are calculated. They differ considerably from their counterparts based on the most recent data and are, thus, not very reliable. While real-time output gaps are generally not unbiased forecasts of the final output gap series, they provide at least some information regarding the sign of the final output gap. The information content of output gaps calculated in real-time for future inflation is tested by means of an out-of-sample forecast exercise and found to be very limited. Generally, the results for simple growth rates appear to be more promising that the results for simple filters to estimate the output gap. This points to the possibility that the problematic nature of the real-time output gaps is not due to revisions of the underlying data but due to the end-of-sample problem that occurs in filtering recent data. All in all, the results support previous findings regarding other countries that revisions of data and output gap estimates can seriously distort business cycle analysis and, thus, research and policy decisions.