Output Gap Estimates Research Articles

Output Gap Uncertainty and Real-Time Monetary Policy

Output gap estimates are subject to a wide range of uncertainty owing to data revisions and the difficulty in distinguishing between cycle and trend in real time. This is important given the central role in monetary policy of assessments of economic activity relative to capacity. We show that country desks tend to overestimate economic slack, especially during recessions, and that uncertainty in initial output gap estimates persists several years. Only a small share of output gap revisions is predictable ex ante based on characteristics like output dynamics, data quality, and policy frameworks. We also show that for a group of Latin American inflation targeters the prescriptions from typical monetary policy rules are subject to large changes due to output gap revisions. These revisions explain a sizable proportion of the deviation of inflation from target, suggesting this information is not accounted for in real-time policy decisions.

A comparative study of Turkey’s output gaps in the recessions

An effective set of monetary, fiscal, and income policies can only be formulated on the basis of a correct estimation of the position of an economy in a cycle. Output gap estimation provides an important tool for predicting the position of the economy. In this paper, we measure output gap for the Turkish Economy for the period between 2000Q1 and 2013Q4, using production function approach and quarterly data. We utilize two definitions of recession: According to the first definition, we refer a period as recession if output gap as a percent of potential GDP takes negative values for at least two consecutive quarters, while NBER definition refers to a period as recession if we observe at least two consecutive quarters of negative real GDP growth rates. On the basis of first definition we find that the imported crisis lasts shorter but costs more in terms of output gap; while on the basis of NBER definition, the imported crisis lasts longer and costs more in terms of negative real GDP growth

Structural Balance Targeting and Output Gap Uncertainty

Potential output estimation plays a crucial role in conducting fiscal policy based on structural balances. Difficulties in estimating potential output could lead to an erroneous policy stance with a consequent impact on growth. This paper analyzes historical data on revisions of actual and potential growth in the European Union and the implication of these revisions for the measurement of fiscal effort using the cyclically-adjusted primary balance (CAPB). It finds that revisions in output gap estimates were large, at almost 1½ percent of potential GDP on average. Revisions in potential GDP also contributed significantly to revisions in the estimated CAPB, especially during the crisis years. Given these findings and historical correlations, it proposes an indicative rule of thumb for reducing errors in the measurement of fiscal effort by factoring in that about 30 percent of revisions in actual growth capture changes in potential growth. In other words, the standard advice of “letting automatic stabilizers operate fully” in response to a positive/negative growth shocks likely implies a strengthening/weakening of the structural position.

Estimating the output gap in real time: A factor model approach

By using a dynamic factor model, we can substantially improve the reliability of real-time output gap estimates for the U.S. economy. First, we use a factor model to extract a series for the common component in GDP from a large panel of monthly real-time macroeconomic variables. This series is immune to revisions to the extent that revisions are due to unbiased measurement errors or idiosyncratic news. Second, our model is able to handle the unbalanced arrival of the data. This yields favorable nowcasting properties and thus starting conditions for the filtering of data into a trend and deviations from a trend. Combined with the method of augmenting data with forecasts prior to filtering, this greatly reduces the end-of-sample imprecision in the gap estimate. The increased precision has economic importance for real-time policy decisions and improves real-time inflation forecasts.

Modely nepozorovaných komponent pro odhad produkční mezery české ekonomiky

Output gap belongs between imporant indicator of central banks by their executing monetary policy despite output gap is an unobservable variable. Because of importance of accurate measurement of output gap, there are more methods for estimation. The aim of this paper is to discover if univariate and multivariate unobserved components models contribute to more precise measurement of output gap. For confirmation or refusal of this hypothesis, Clark's model (1989) and Kuttner's model (1994) will be used. All two models will be analysed and their advantages and disadvantages will be shown. Results of estimations will be compared with papers dealing with output gap for czech economy. Then, the ability of output gap to forecast inflation will be analysed. At last, multivariate unobserved componenets model will be labeled after some tests as the most suitable method for estimation of output gap.

Modelling Italian Potential Output and the Output Gap

The aim of the paper is to estimate a reliable quarterly time-series of potential output for the Italian economy,exploiting four alternative approaches: a Bayesian unobserved component method, a univariate time-varying autoregressive model, a production function approach and a structural VAR. Based on a wide range of evaluation criteria, all methods generate output gaps that accurately describe the Italian business cycle over the past three decades. All output gap measures are subject to non-negligible revisions when new data become available. Nonetheless they still prove to be informative about the current cyclical phase and, unlike the evidence reported in most of the literature, helpful at predicting inflation compared with simple benchmarks. We assess also the performance of output gap estimates obtained by combining the four original indicators, using either equal weights or Bayesian averaging, showing that the resulting measures (i) are less sensitive to revisions; (ii) are at least as good as the originals at tracking business cycle fluctuations; (iii) are more accurate as inflation predictors.

The (un)reliability of real-time output gap estimates with revised data

This paper investigates the differences between real-time and ex-post output gap estimates using a newly-constructed international real-time dataset over the period from 1973:Q1 to 2012:Q3. We extend the findings in Orphanides and van Norden (2002) for the United States that the use of ex-post information in calculating potential output, not the data revisions themselves, is the major cause of the difference between real-time and ex-post output gap estimates to nine additional OECD countries. The results are robust to the use of linear, quadratic, Hodrick–Prescott, Baxter–King, and Christiano–Fitzgerald detrending methods. By using quasi real-time methods, reliable real-time output gap estimates can be constructed with revised data.

Modelling Italian Potential Output and the Output Gap

The aim of the paper is to estimate a reliable quarterly time-series of potential output for the Italian economy,exploiting four alternative approaches: a Bayesian unobserved component method, a univariate time-varying autoregressive model, a production function approach and a structural VAR. Based on a wide range of evaluation criteria, all methods generate output gaps that accurately describe the Italian business cycle over the past three decades. All output gap measures are subject to non-negligible revisions when new data become available. Nonetheless they still prove to be informative about the current cyclical phase and, unlike the evidence reported in most of the literature, helpful at predicting inflation compared with simple benchmarks. We assess also the performance of output gap estimates obtained by combining the four original indicators, using either equal weights or Bayesian averaging, showing that the resulting measures (i) are less sensitive to revisions; (ii) are at least as good as the originals at tracking business cycle fluctuations; (iii) are more accurate as inflation predictors.

What Is in Your Output Gap? Unified Framework & Decomposition into Observables

This paper discusses several popular methods to estimate the ‘output gap’. It provides a unified, natural concept for the analysis, and demonstrates how to decompose the output gap into contributions of observed data on output, inflation, unemployment, and other variables. A simple bar-chart of contributing factors, in the case of multi-variable methods, sharpens the intuition behind the estimates and ultimately shows ‘what is in your output gap.’ The paper demonstrates how to interpret effects of data revisions and new data releases for output gap estimates (news effects) and how to obtain more insight into real-time properties of estimators.

The Taylor Principle, Interest Rate Smoothing and Fed Policy in the 1970s and 1980s

Using real time estimates of output gaps or Greenbook forecasts of the unemployment rate, this article estimates Taylor-type policy rules that predict the actual behavior of the funds rate during two sample periods, 1968Q1 to 1979Q2 and 1979Q3 to 1994Q4. The inflation rate response coefficient is close to unity over the first sub-period and well above unity over the second, suggesting Fed policy violated the Taylor principle during the first period. The adjustment of the funds rate in response to fundamentals is not as rapid during the first period as it is during the second. Together these results support the conventional view that the Fed was too timid and too sluggish during the late 1960s and the 1970s. Though the Fed smoothes interest rates, the degree of smoothing exhibited is far less than what was previously estimated. The funds rate response to its fundamentals is complete within one year during the first period and within one quarter during the second.

Improving Real-Time Estimates of Output and Inflation Gaps With Multiple-Vintage Models

Real-time estimates of output gaps and inflation gaps differ from the values that are obtained using data available long after the event. Part of the problem is that the data on which the real-time estimates are based is subsequently revised. We show that vector-autoregressive models of data vintages provide forecasts of post-revision values of future observations and of already-released observations capable of improving estimates of output and inflation gaps in real time. Our findings indicate that annual revisions to output and inflation data are in part predictable based on their past vintages. This article has online supplementary materials.

Japan’s output gap estimation and ℓ 1 trend filtering

This paper estimates Japan’s output gap using the recently developed l1 trend filter, which is an alternative to the popular Hodrick–Prescott (HP) filter. This new filter provides a piecewise linear trend line, which means it possibly provides better output gap estimates than the HP filter does for an economy such as Japan that has experienced some structural breaks.

Estimating potential output and output gap through non-structural approaches: An application to Iran

This paper discusses the different and formal approaches of estimation of potential output and output gap through modern time series filtering. The estimation of potential output and output gap is used in different areas such as non-inflationary steady state growth, and shows that adapting different approaches leads to different results. Estimation also helps economists and economic policymakers to evaluate macroeconomic policies and helps them to decide in what conditions the aggregate demand policies should be contractional or expansionary. Finally, this paper presents the estimation results of different approaches using Iran's seasonal data. Here, we preferably have used three approaches, namely, univariate or multivariate Beveridge-Nelson decomposition and Wavelet method. Key words: Potential output, Beveridge-Nelson decomposition, wavelet filter, Iran.

Output gap in Brazil: a real-time data analysis

Recent literature for developed economies has shown that output gap estimates go through important revisions over time, impairing their reliability in real time. We organize a real-time data set for Brazil’s GDP and assess the revisions of the output gap estimated by four different methods. Similar to the findings of studies for developed economies, the output gap revisions in Brazil are substantial in all methods, with frequent changes in the output gap sign. In general, both the GDP data revision and the effect of adding new observations to the sample are relevant sources of output gap revisions. However, differently from those studies, we cannot assert that the latter source is preponderant.

ESTIMATION AND ANALYSIS OF OUTPUT GAP: AN APPLICATION OF STRUCTURAL VECTOR AUTOREGRESSION AND HODRICK-PRESCOTT-FMETHODS

In this study we examined output gap in the Iranian economy. The main question of the study is that ho w much is seasonal output gap in Iranian Economy and which factor affects gap variation. The other quest ion is that whether using HP-F as a statistical based m ethod for estimating output gap, provide different result than using SVAR as theory based method. Accordingly the aim of study is to estimate potential output a nd thus output gap using two method and analysis of th e result. We used two methods (Hodrick-Prescott Fil ter and SVAR) to estimate quarterly output gap for the period 1988:1-2008:4. The results pointed out that the estimation is not sensitive to the method and there is a close relation between oil revenue and output gap. In the period of 1998:3-1999:3, when oil price reduced to $11.45 per barrel, Iranian economy faced with a recession and it affected on output gap with a lag. Output gap increased from 34818 in 2004:1-76782 million dollars in 2008: 4. The comparison of estim ated output gap and changes of oil price in differe nt periods point out the positive relation. According to the estimations of output gap, output gap in the Iranian Economy has intense fluctuation due to the effects of oil proceeds fluctuations. In some years, actual output is more than potential output, that is, output gap is positive and so this situation can be an importa nt reason for inflation in that period and policy maker must do plans and policies for control of inflation and in some years, actual output is less than potential output and this means output gap was negative. This situat ion is a reason for unemployment in these years and therefor e policy makers must do expansionary policies.

A wavelet filtering based estimation of output gap

Accurate estimation of output gap is an important and challenging problem for any economy. We consider here the problem of estimating the output gap for the Indian economy. The estimation of output gap involves a hypothetical variable, the potential output of the economy. In this paper, we propose a wavelet filtering based technique for estimation of output gap using monthly the Index of Industrial Production (IIP) series. We compare the results obtained using the proposed wavelet based technique with the widely used Hodrick–Prescott filtering and Seasonal ARIMA modeling based techniques. In order to compare the output gap estimated using the proposed technique with the other techniques, we explore the causal relationship between the estimates of output gap and the growth rate of an equity market indicator. It is observed that the wavelet filtering technique gives better results than the more popular econometric and standard time-series modeling techniques.

The reliability of real-time estimates of the euro area output gap

This paper provides evidence on the reliability of euro area real-time output gap estimates. A genuine real-time data set for the euro area is used, including vintages of several sets of euro area output gap estimates available from 1999 to 2010. It turns out that real-time estimates of the output gap tend to be characterised by a high degree of uncertainty, much higher than that resulting from model and estimation uncertainty only. In particular, the evidence indicates that both the magnitude and the sign of the real-time estimates of the euro area output gap are very uncertain. The uncertainty is mostly due to parameter instability and model uncertainty, while data revisions seem to play a minor role. Some euro area real-time measures, based on multivariate components models and capacity utilisation, are relatively less uncertain, but do not appear to be fully reliable along some dimensions. To benchmark our results, we repeat the analysis for the US over the same sample. It turns out that US real-time estimates tend to be revised to a lesser extent than euro area estimates. However, euro area real-time output gap estimates tend to display a higher correlation with the final estimates and the sign of the level of US real-time estimates tends to be revised more often compared to the corresponding euro area estimates. In addition, the data revision component of the revision error is larger for US estimates than for the euro area. Overall, the unreliability in real-time of the US output gap measures detected in earlier studies is confirmed in the more recent period.

Testing EU fiscal surveillance: how sensitive is it to variations in output gap estimates?

Real‐time estimates of potential output are used for the calculation of the cyclically adjusted budget balance, one of the main indicators in the assessment of the fiscal performance of EU member states. The estimation of potential output involves a decomposition of actual output into a cyclical and a structural component based on arbitrary assumptions about the statistical properties of the two unobserved components. With a very high degree of smoothing, variations in GDP are mostly taken to be temporary, as are the ensuing changes in the budget deficit. Conversely, with a low degree of smoothing, variations in GDP are mostly taken to be permanent, leading to different policy conclusions. Our paper examines whether and how different potential output estimates would have supported different decisions in the EU budgetary surveillance in terms of both timing and substance. The results show that only a very high degree of smoothing of potential output would significantly reduce the reliability of the surveillance indicators. We conclude that a higher degree of smoothing compared with current practice would not be harmful for EU fiscal surveillance, while it could contribute to more cautious policies by signalling larger and longer periods of economic ‘good times’.

Trend-Cycle Decomposition of Output and Euro Area Inflation Forecasts: A Real-Time Approach Based on Model Combination

The paper focuses on the estimation of the euro area output gap. We construct model-averaged measures of the output gap in order to cope with both model uncertainty and parameter instability that are inherent to trend-cycle decomposition models of GDP. We first estimate nine models of trend-cycle decomposition of euro area GDP, both univariate and multivariate, some of them allowing for changes in the slope of trend GDP and/or its error variance using Markov-switching specifications, or including a Phillips curve. We then pool the estimates using three weighting schemes. We compute both ex-post and real-time estimates to check the stability of the estimates to GDP revisions. We finally run a forecasting experiment to evaluate the predictive power of the output gap for inflation in the euro area. We find evidence of changes in trend growth around the recessions. We also find support for model averaging techniques in order to improve the reliability of the potential output estimates in real time. Our measures help forecasting inflation over most of our evaluation sample (2001-2010) but fail dramatically over the last recession. JEL Classification: C53, E32, E37

Mongolia: Measuring the Output Gap

This paper compares the output gap estimates for Mongolia based on a number of different methods. Special attention is paid to the substantial role of mining in the Mongolian economy. We find that a Blanchard and Quah-type joint model of output and inflation provides a more robust estimate of the output gap for Mongolia than the traditional statistical decompositions.