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We apply a range of models to the U.K. data to obtain estimates of the output gap. A structural VAR with an appropriate identification strategy provides improved estimates of output gap with better real time properties and lower sensitivity to temporary shocks than the usual filtering techniques. It also produces smaller out-of-sample forecast errors for inflation. At the same time, however, our results suggest caution in basing policy decisions on output gap estimates.
Estimates of output gaps continue to play a key role in assessments of the stance of business cycles. This paper uses three approaches to examine the historical record of output gap measurements and their use in surveillance within the IMF. Firstly, the historical record of global output gap estimates shows a firm negative skew, in line with previous regional studies, as well as frequent historical revisions to output gap estimates. Secondly, when looking at the co-movement of output gap estimates and realized measures of slack, a positive, but limited, association is found between the two. Thirdly, text analysis techniques are deployed to assess how estimates of output gaps are used in Fund surveillance. The results reveal no strong bearing of output gap estimates on the coverage of the concept or direction of policy advice. The results suggest the need for continued caution in relying on output gaps for real-time policymaking and policy assessment.
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.
We suggest a new approach for analyzing the role of financial variables and shocks in computing the output gap. We estimate a two-region DSGE model for the euro area, with financial frictions at the household level, between 2000-2013. After joining the monetary union, a decline in some countries’ borrowing costs contributed to a credit, housing and real boom and bust cycle. We show that financial frictions amplified economic fluctuations and the measure of the output gap in those countries. On the contrary, in countries such as France and Germany, financial frictions played a minor role in output gap measures. We also present evidence of the trade-offs faced by the European Central Bank when trying to stabilize two regions in a currency union with unsynchronized economic cycles.
We study the properties of the IMF-WEO estimates of real-time output gaps for countries in the euro area as well as the determinants of their revisions over 1994-2017. The analysis shows that staff typically saw economies as operating below their potential. In real time, output gaps tend to have large and negative averages that are largely revised away in later vintages. Most of the mis-measurement in real time can be explained by the difficulty in predicting recessions and by overestimation of the economy’s potential capacity. We also find, in line with earlier literature, that real-time output gaps are not useful for predicting inflation. In addition, countries where slack (and potential growth) is overestimated to a larger extent primary fiscal balances tend to be lower and public debt ratios are higher and increase faster than projected. Previous research suggests that national authorities’ real-time output gaps suffer from a similar bias. To the extent these estimates play a role in calibrating fiscal policy, over-optimism about long-term growth could contribute to excessive deficits and debt buildup.
The gap between potential and actual output—the output gap—is a key variable for policymaking. This paper adapts the methodology developed in Blagrave and others (2015) to estimate the path of output gap in the U.S. economy. The results show that the output gap has considerably shrunk since the Great Recession, but still remains negative. While the results are more robust than other existing methodologies, there is still significant uncertainty surrounding the estimates.
The output gap - the difference between actual and potential output - is widely regarded as a useful guide to future inflationary pressures, as well as an important indicator of the state of the economy in its own right. Since the output gap is unobservable, however, its estimation is prone to error, particularly in real time. Errors result both from revisions to the underlying data, as well as from end-point problems that are endemic to econometric procedures used to estimate output gaps. These problems reduce the reliability of output gaps estimated in real time, and lead to questions about their usefulness. We examine 121 vintages of Australian GDP data to assess the seriousness of these problems. Our study, which is the first to address these issues using Australian data, is of interest for the method we use to obtain real-time output-gap estimates. Over the past 28 years, our real-time output-gap estimates show no apparent bias, when compared with final output-gap estimates derived with the benefit of hindsight using the latest available data. Furthermore, the root-mean-square difference between the real-time and final output-gap series is less than 2 percentage points, and the correlation between them is over 0.8. Our general conclusion is that quite good estimates of the output gap can be generated in real time, provided a sufficiently flexible and robust approach is used to obtain them.0D0A.
We argue that in an economy with downward nominal wage rigidity, the output gap is negative on average. Because it is more difficult to cut wages than to increase them, firms reduce employment more during downturns than they increase employment during expansions. This is demonstrated in a simple New Keynesian model with asymmetric wage adjustment costs. Using the model's output gap as a benchmark, we further show that common output gap estimation methods exhibit a systematic bias because they assume a zero mean. The bias is especially large in deep recessions when potential output tends to be most severely underestimated.
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.
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.