Output Gap Estimates Research Articles

Business cycle synchronization and asymmetry in the European Union

Measuring output gaps and assessing business cycle synchronization across countries can be an important research theme for an economic union. However, different empirical models can lead to very different inference about output gaps. We analyze business cycle movements and synchronization for all European Union members for the period 1975Q1–pre-COVID and 1975Q1–2022Q4. We account for model uncertainty by averaging across a set of output gap models both by using a Phillips Curve motivated weighted average and a simple average. Similarly, we compare several alternative synchronization measures. We find that, in contrast to the previous literature, both the estimated output gap and the level of synchronization depend on the individual empirical measure used. Our averaged gaps match recession dates well and suggest that many of the countries exhibit a high degree of business cycle nonlinearities. Finally, the core Eurozone countries are highly synchronized, but there are differences in synchronization outside the core.

Estimating time-varying potential output and NAIRU using a multivariate filter for Türkiye

This paper extends the multivariate filter approach for estimating potential output and NAIRU developed for Türkiye by integrating the capacity utilization block into the model. The model gives more negative estimates of the output gap and smaller estimates of NAIRU in recession periods compared to estimates without a capacity utilization block. In addition, applying an alternative model including a broader-defined unemployment rate to Turkish data results in significantly less negative output gap and unemployment gap compared to estimates with the original unemployment rate. The idea of traditional unemployment rate measurements may not adequately capture the cycle conditions of labor market is brought up in this extension.

Dynamic hysteresis effects

We study how the output gap affects potential output over time—i.e., the dynamic hysteresis effect. To do so, we introduce novel unobserved components (UC) models that consider hysteresis as a sequence of lagged effects, thus separating the long-run recession-induced adverse effects from other trend-cycle interactions. The proposed models nest several existing UC models in the literature and accommodate two key characteristics of output dynamics: non-neutrality in the long-run and time-to-build effects. Using Bayesian estimation methods, we find robust evidence supporting the presence of hysteresis effects after the 1970s, with the negative long-run effect of the Global Financial Crisis and the COVID-19 recessions robustly identified. Via Bayesian model averaging, we provide precise and intuitive output gap estimates that highlight the relationship between business cycle fluctuations and the decline in economic growth. Our findings indicate that output trend-cycle decompositions that do not consider hysteresis effects can alter stabilization policy trade-offs.

AN EMPIRICAL TAKE ON THE “PLUCKING” MODEL

Traditional estimates of potential output based on the symmetric business cycle (boom–bust) view are prone to large retrospective revisions. The plucking view, which is supported by empirics, offers possible respite. Serious attempts to estimate the output ceiling in the plucking view, analogous to potential output in the traditional view, are scarce. This paper has three parts. The first estimates the output ceiling in a computationally simple approach. The second analyzes the relationship of the resultant output gap with inflation and with the unemployment rate. A comparison is made against output gap estimates based on prevailing methods. The third uses a vector autoregression (VAR) to analyze responses to supply and demand shocks. The paper finds that the plucking model offers three points of improvement over prevailing methods based on the boom–bust view. First, boom–bust estimates are prone to large retrospective revisions when two-sided filters are used, while the plucking estimates are not. Second, output gap estimates from both views do not correlate well with core inflation. This absence of evidence for a Phillips curve is problematic for the boom–bust view. The plucking estimates correlated well with the unemployment rate but the boom–bust estimates did not. Third, the output ceiling from the plucking model responded only to supply (oil price) shocks and not demand (interest rate) shocks, hence fits the description of a supply measure. This paper provides a template to estimate the output ceiling of the plucking model in other countries using publicly available macroeconomic data.

Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate

AbstractA factor stochastic volatility model estimates the common component to output gap estimates produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The output gap estimates are uncertain even well after the fact. Nevertheless, the common component is clearly procyclical, and positive innovations to the common component produce movements in macroeconomic variables consistent with an increase in aggregate demand. Heightened macroeconomic uncertainty, as measured by the common component's volatility, leads to persistently negative economic responses.

Potenciální produkt a mezera výstupu v období ekonomických krizí

The article investigates potential output and output gap modelling and estimation in the Czech Republic in the period 1996-2021, including the global recession from 2008 and the recent crisis caused by government measures against the COVID-19 pandemic. The unobserved components (UC) methodology is applied, coefficients are estimated by the maximum likelihood method, unobserved variables are estimated using the Kalman filter. The standard UC model is modified in an original way to nonlinearly describe the hysteresis effect by allowing the output gap to have an asymmetrical influence on potential output. The econometric model verification proved significance of the hysteresis effect and showed a substantial inertia of negative consequences of both crises. Predictions of an impact of the War in Ukraine on the gap were also calculated and the uncertainty associated with these predictions was quantified.

Global and local components of output gaps

This paper proposes a multi-level dynamic factor model to identify common components in output gap estimates. We pool multiple estimates for 157 countries and decompose them into one global, eight regional, and 157 country-specific cycles. Our approach easily deals with mixed frequencies, ragged edges, and discontinuities in the underlying output gap estimates. To restrict the parameter space in the Bayesian state space model, we apply a stochastic search variable selection approach and base the prior inclusion probabilities on spatial information. Our results suggest that the global and the regional cycles explain a substantial proportion of the output gaps. On average, 18% of a country’s output gap is attributable to the global cycle, 24% to the regional cycle, and 58% to the local cycle.

Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic

We estimate the euro area output gap by applying the Beveridge–Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis and addresses data issues associated with the COVID-19 pandemic. The estimated output gap lines up well with the CEPR chronology of the business cycle for the euro area and we find that hours worked, more than the unemployment rate, provides the key source of information about labor utilization in the economy, especially in pinning down the depth of the output gap during the COVID-19 recession when the unemployment rate rose only moderately. Our findings confirm that labor market adjustments to the business cycle in the euro area occur more through the intensive, rather than extensive, margin.

The Unreliability of Output-Gap Estimates in Real Time

Most research on monetary policy assumes availability of information regarding the current state of economy, at the time of the policy decision. A key challenge for policy-makers is to find indicators that give a clear and precise signal of the state of the economy in real time—that is, when policy decisions are actually taken. One of the indicators used to asses the economic condition is the output gap; and the estimates of output gap from real time data misrepresents the true state of economy. So the policy decisions taken on the basis of real time noisy data are proved wrong when true data become available. Within this context we find evidence of wrong estimates of output gap in real time data. This is done by comparing estimates of output gap based on real time data with that in the revised data. The quasi real time data are also constructed such that the difference between estimates of output gap from real time data and that from quasi real time data reflects data revision and the difference between estimates of output gap from final data and that from quasi real time data portray other revisions including end sample bias. Moreover, output gap is estimated with the help of five methods namely the linear trend method, quadratic trend method, Hordrick-Prescott (HP) filter, production function method, and structural vector autoregressive method. Results indicate that the estimates of output gap in real time data are different from what have been found in final data but other revisions, compared to data revisions, are found more significant. Moreover, the output gap measured using all the methods, except the linear trend method, appropriately portray the state of economy in the historical context. It is also found that recessions can be better predicted by real time data instead of revised data, and final data show more intensity of recession compared with what has been shown in real time data. JEL Classification: E320 Keywords: Data Uncertainty, Measurement Uncertainty, Output Gap, Business Cycle, Economic Activity

Improved output gap estimates and forecasts using a local linear regression

The output gap, the difference between potential and actual output, has a direct impact on policy decisions, e.g., monetary policy. Estimating this gap and its further analysis remains subject of many debates due to methodological problems. We propose a local polynomial regression and its forecasting extension for a systematic output gap estimation. Further, the local polynomial regression is proposed for the (multivariate) OECD production function approach and its reliability is demonstrated in forecasting output growth. A comparison of the proposed gap to the Hodrick-Prescott filter as well as to estimations by experts from the FED and OECD shows a higher correlation of our output gap with those from economic institutions. Furthermore, it sometimes happens that gaps with different magnitude and different positions above or below the trend are observed between different methods. This may cause competing policy implications which can be improved with our results.

Norges Bank Output Gap Estimates: Forecasting Properties, Reliability, Cyclical Sensitivity and Hysteresis

AbstractThis paper documents the suite of models (SoMs) used by Norges Bank to estimate the output gap. The models are estimated using data on GDP, unemployment, inflation, wages, investment, house prices and credit. We evaluate the estimated output gap series in terms of its forecasting properties, its reliability and its cyclical sensitivity to various measures of demand and supply shocks. A simple equally weighted average of estimates from different models features a better forecasting performance than each individual model. In addition, it helps predicting inflation in pseudo real time and exhibits limited variations when new data become available. The summary measure of potential output responds strongly and rapidly to permanent shocks and to narrative measures of technology shocks but, although to a more limited extent, also to demand shocks, thus partly capturing hysteresis effects.

Assessing uncertainty of output gap estimates: Evidence from Visegrad countries

The reliability of output gap estimates is a crucial factor for the successful implementation of economic policy. We evaluate the robustness and stability of output gap estimates while comparing structural and non-structural techniques, using recursive estimates and alternative stability indicators. Our results provide evidence that some structural approaches outperform other available methods. Structural approaches exhibit a higher order of stability. Especially the methods based on the Beveridge–Nelson decomposition outperform the other structural and non-structural methods. The stability of structural approaches increases as new data becomes available. Moreover, output gap uncertainty diminishes during the positive business cycle phases, and structural approaches offer better overall stability performance and exhibit more stable concordance of these estimates. Our results are robust to alternative prior density settings and reveal similar output gap uncertainty patterns for the Visegrad countries, the euro area, and the United States.

A new measure of the output gap, inflation dynamics, and the New Keynesian Phillips Curve

Literature suggests that measures of slack such as unemployment, output, labour share, and inflation have been separated in recent years, particularly after the global crisis. Some claimed that the Phillips curve had vanished. Because of the unobservable nature of the natural rates, estimation of the output and unemployment gaps might not offer precise outcomes. The inflation model permits a fraction of firms that use a backwards-looking rule to set prices, as Gali and Gertler (2000) did. The essential contrast between their paper and mine is that they utilized marginal cost estimates as the applicable determinant of inflation, and I utilized the estimated output gap. Gali and Gertler supposed real marginal costs are a significant determinant of inflation. They also believed the output gap was negative and inconsequential. I have indicated that a precise output gap estimate is significant and positive. CBO output gap is also used to inspect for robustness. However, it was also insignificant, as the literature suggests. Therefore, the model used the estimated output gap instead of marginal cost. I calculated the output gap with a new methodology and could replicate their results with the new measure. I extended their study to 2019Q4; It is showed that their measure for inflation slack which was marginal cost becomes insignificant; however, my measure of the output gap is still significant. Therefore, it was inferred that the New Keynesian Phillips curve reasonably still explains inflation dynamics. I also concluded that the hybrid new Keynesian Phillips curve might explain the inflation dynamics.

A dissection of Indian growth using a DSGE filter

In order to build a strong and sustainable recovery post the COVID-19 pandemic, we need to draw important observations from the growth experience of the past. In this context, this paper uses a dynamic stochastic general equilibrium (DSGE) model that takes into account persistent growth rate shocks to decompose the Indian GDP into potential output and output gap. Apart from analysing the trajectory of potential output-output gap, it also examines their underlying drivers. The results suggest that a combined deceleration in neutral and investment-specific technology growth post 2016, brought down the potential growth to around 6 per cent in 2020Q1. The output gap also witnessed a persistent decline since 2018Q1, primarily due to weak demand and a rise in investment adjustment costs reflecting heightened stress in the investment and financial sectors. A forecasting exercise is also undertaken which shows that the estimates of output gap from the model possess competing inflation forecasting ability compared to HP filtered output gap.

The updated Okun method for estimation of potential output with alternative measures of labor underutilization

This paper extends the Updated Okun Method (UOM) for estimation of potential output proposed in Fontanari et al. (2020), which, from a demand-led growth perspective, regards potential output as an empirical approximation to full-employment output, as in A.M. Okun's (1962) original method. Based on the apparent incapability of the official rate of unemployment to fully account for labor underutilization, we offer estimates of Okun's law both with alternative unemployment indicators and with an indicator of ‘standardized hours worked’ which we propose as a novel measure of the labor input. The paper reflects on the possible different empirical measures of full employment. The different estimates of potential output that we obtain show greater output gaps than those produced by standard methods, thus highlighting a systematic tendency of the latter to underestimate potential output. We define a ‘corridor’ of output gap estimates and propose a two-step procedure to identify the most relevant gap for policy purposes. JEL Codes: E60; E24; O40; E12; C30

An Evaluation of World Economic Outlook Growth Forecasts, 2004–17

This paper examines the performance of World Economic Outlook (WEO) growth forecasts for 2004-17. Short-term real GDP growth forecasts over that period exhibit little bias, and their accuracy is broadly similar to those of Consensus Economics forecasts. By contrast, two- to five-year ahead WEO growth forecasts in 2004-17 tend to be upward biased, and in up to half of countries less accurate than a naive forecast given by the average growth rate in the recent past. The analysis suggests that a more efficient use of available information on internal and external factors—such as the estimated output gap, projected terms of trade, and the growth forecasts of major trading partners—can improve the accuracy of some economies’ growth forecasts.

Potential GDP Modeling and Output Gap Estimation as a Basis for Countercyclical Fiscal Policy in Kazakhstan.

This paper identifies key risks of the public sector in Kazakhstan. Methods for modeling potential output and output gap in international research practice and their application in countercyclical fiscal policy are considered. The potential output of Kazakhstan is retrospectively analyzed using the Hodrick–Prescott (HP) filter. Periods of the procyclical budgetary policy are identified. It is proposed to introduce a fiscal model of the structural budget balance, to target a zero output gap in the short term, and to increase the potential output through structural reforms.

Time-varying Uncertainty of the Federal Reserve's Output Gap Estimate

<ns3:p>A factor stochastic volatility model estimates the common component to estimates of the output gap produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. Output gap estimates are very uncertain, even well after the fact, especially at business cycle turning points. However, the common component of the output gap estimates is clearly procyclical, and innovations to the common factor produce persistent positive effects on economic activity. Output gaps estimated by the Congressional Budget Office have very similar properties. Increased macroeconomic uncertainty, as measured by the common factor's volatility, leads to persistent negative responses in economic variables.</ns3:p>

Semi-Structural VAR and Unobserved Components Models to Estimate Finance-Neutral Output Gap

The paper assesses the impact of adding information on financial cycles on the output gap estimates for eight advanced economies using two unobserved components models: a reduced form extended Hodrick-Prescott filter, and a standard semi-structural unobserved components model. To complement these models, a semi-structural vector autoregression model is proposed in which only supply shocks are identified. The accuracy of the output gap estimates is assessed based on their performance in predicting recessions. The models with financial variables generally produce more accurate output gap estimates at the expense of increased real-time volatility. While the extended Hodrick-Prescott filter is particularly appealing for its real-time stability, it lags behind the two semi-structural models in terms of forecasting performance. The vector autoregression model augmented with financial variables features the best in-sample forecasting performance, and it has similar real-time prediction capabilities to the semi-structural unobserved components model. Overall, financial cycles appear to be relevant in Japan, Spain, the UK, and – to a lesser extent – in the US and in France, while they are relatively muted in Canada, Germany, and Italy.

A Multivariate Unobserved Components Model to Estimate Potential Output in the Euro Area: A Production Function Based Approach

This paper builds an unobserved components model that combines a multivariate filter approach with a Cobb-Douglas production function. This combination allows potential output estimates to incorporate more economic structure than the traditional production function approach, while retaining the ability to conduct growth accounting exercises. The model is a backward-looking state space model estimated with Bayesian methods employing the Kalman filter to jointly decompose six key observable variables (real GDP, unemployment rate, labour force participation rate, hours worked per person, a measure of core inflation and wage inflation) into trend and cyclical components. To do so, it relies on several reduced form relationships across the cyclical components, such as a wage and a price Phillips curve and an Okun's law type relationship, while it also assumes common trends for a few variables and allows for hysteresis effects. The model is estimated on aggregate euro area data with Bayesian methods. The paper finds that the resulting output gap estimates have good revision properties and reasonable forecasting performance in particular in terms of GDP and core inflation vis-a-vis a set of benchmarks.