Data Revisions Research Articles

Forecast combination for U.S. recessions with real-time data

This paper proposes the use of forecast combination to improve predictive accuracy in forecasting the U.S. business cycle index, as published by the Business Cycle Dating Committee of the NBER. It focuses on one-step ahead out-of-sample monthly forecast utilising the well-established coincident indicators and yield curve models, allowing for dynamics and real-time data revisions. Forecast combinations use log-score and quadratic-score based weights, which change over time. This paper finds that forecast accuracy improves when combining the probability forecasts of both the coincident indicators model and the yield curve model, compared to each model's own forecasting performance.

Real-time estimation of the equilibrium real interest rate: Evidence from Japan

This study demonstrates quantitatively the degree to which uncertainty originates from the revision of data inherent in the real-time estimation of the Japan's equilibrium real interest rate (ERR). It also presents some attempts to reduce that uncertainty. Results show that markedly high uncertainty results from data revision. A modified model is proposed to estimate a more credible ERR that includes lowered uncertainty with revision-free data. Furthermore, the Bank of Japan, while facing that uncertainty, has made three judgment errors because it did not recognize reliable ERR.

Fiscal Planning and Implementation: Euro Area Analysis Based on Real Time Data

This study explores discretionary fiscal policies in the euro area during the time of monetary union (EMU). Ex ante budget plans and policy changes during budget implementation are investigated using real time data from the OECD Economic Outlook publications. The particular focus of the study is on fiscal adjustment to the recent financial crisis and the subsequent global recession. Estimated fiscal policy reaction functions indicate that in the EMU period ex ante fiscal plans in the euro area have basically been long-term oriented and counter-cyclical. In the course of the budgetary year, policies have typically been adjusted due to data revisions and new business cycle information. The crisis had a clear impact on discretionary policies. The periphery countries clearly adjusted their policies already in the budgetary planning stage, but other countries mainly reacted to the crisis during budget implementation. We provide evidence that short-term counter-cyclical fiscal policies may not have been consistent with sound and sustainable public finances. In order to maintain fiscal discipline and avoid excessive indebtedness, careful monitoring of macroeconomic imbalances and reliable as well as more accurate forecasts are needed. Overall, longer term fiscal policy orientation and continuous monitoring of the budgeting processes are crucial in good fiscal governance.

Fiscal Planning and Implementation: Euro Area Analysis Based on Real Time Data

The aim of this study is to explore discretionary fiscal policies in the euro area during the time of monetary union (EMU). Ex ante budget plans and policy changes during budget implementation are investigated using real time data from the OECD Economic Outlook publications. The particular focus of the study is on fiscal adjustment to the recent financial crisis and the subsequent global recession. Estimated fiscal policy reaction functions indicate that in the EMU period ex ante fiscal plans have basically been long-term oriented and counter-cyclical in the euro area. In the course of the budgetary year, policies have typically been adjusted due to data revisions and new business cycle information. The crisis had a clear impact on discretionary policies. The periphery countries clearly adjusted their policies already in the budgetary planning stage, but other countries mainly reacted to the crisis during budget implementation. We provide evidence that short-term counter-cyclical fiscal policies may not have been consistent with sound and sustainable public finances.

A Real-Time Data Set for Switzerland

Summary Accessibility of real-time data is crucial for applied macroeconomic researchers who aim at evaluating forecasts, policy decisions or the accuracy of initial data estimates. To the extent of our knowledge, no appropriate and comprehensive real-time data set has been published for Switzerland so far. This paper introduces such a data set, which can be downloaded online. The balanced database includes quarterly, seasonally adjusted vintages of the most important economic variables on the national level. A short analysis of data revisions is provided for quarterly GDP. The magnitude of revisions are comparable to other countries such as the Euro Area or the United States. However, revision policy may differ considerably and potentially influence a statistical analysis.

Signs of Improving Labor Market Conditions

Data revisions suggest that job growth has been much stronger than initially reported the past two years.

Modeling Multivariate Data Revisions

Data revisions in macroeconomic time series are typically studied in isolation ignoring the joint behaviour of revisions across different series. This ignores (i) the possibility that early releases of some series may help forecast revisions in other series and (ii) the problems statistical agencies may face in producing estimates consistent with accounting identities. This paper extends the Jacobs and van Norden (2011) modeling framework to multivariate data revisions. We consider systems of variables, where true values and news and noise can be correlated, and which may be linked by one or more identities. We show how to model such systems with standard linear state space models. We motivate and illustrate the multivariate modeling framework with Swiss current account data using Bayesian econometric methods for estimation and inference.

TREND-CYCLE DECOMPOSITION OF OUTPUT AND EURO AREA INFLATION FORECASTS: A REAL-TIME APPROACH BASED ON MODEL COMBINATION

This paper estimates univariate and multivariate trend-cycle decomposition models of GDP and considers the novel possibility of regime switches in the growth of potential output. We compute both ex post and real-time estimates of the output gap to check the stability of our estimates to GDP data revisions. We find some evidence of regime changes in the growth of potential output during the recessions experienced by the euro area. We also run a forecasting experiment to evaluate the predictive power of the output gap for inflation. The benchmark autoregressive model tends to obtain the best forecasts for one-quarter-ahead forecasts, but the output gap measures help to forecast inflation for longer horizons.

From numbers to a biological sense: How the strategy chosen for metabolomics data treatment may affect final results. A practical example based on urine fingerprints obtained by LC‐MS

Application of high-throughput technologies in metabolomics studies increases the quantity of data obtained, which in turn imposes several problems during data analysis. Correctly and clearly addressed biological question and comprehensive knowledge about data structure and properties are definitely necessary to select proper chemometric tools. However, there is a broad range of chemometric tools available for use with metabolomics data, which makes this choice challenging. Precisely performed data treatment enables valuable extraction of information and its proper interpretation. The effect of an error made at an early stage will be enhanced throughout the later stages, which in combination with other errors made at each step can accumulate and significantly affect the data interpretation. Moreover, adequate application of these tools may help not only to detect, but sometimes also to correct, biological, analytical, or methodological errors, which may affect truthfulness of obtained results. This report presents steps and tools used for LC-MS based metabolomics data extraction, reduction, and visualization. Following such steps as data reprocessing, data pretreatment, data treatment, and data revision, authors want to show how to extract valuable information and how to avoid misinterpretation of results obtained. The purpose of this work was to emphasize problematic characteristics of metabolomics data and the necessity for their attentive and precise treatment. The dataset used to illustrate metabolomics data properties and to illustrate major data treatment challenges was obtained utilizing an animal model of control and diabetic rats, both with and without rosemary treatment. Urine samples were fingerprinted employing LC-QTOF-MS.

Fiscal Data Revisions in Europe

Revisions of budget balances in Europe could be particularly worrisome as adherence to multilateral surveillance rules is judged upon initial data releases. We use a pool of real‐time vintages of data for 15 EU countries over the period 1995–2008. Our main findings are: (i) preliminary releases are biased and nonefficient predictors of subsequent releases, (ii) such systematic bias in revisions is a general feature of the sample, (iii) Eurostat's decisions explain a significant share of the bias and provide some evidence of window dressing practices, and (iv) expected real gross domestic product growth, political cycles, and the strength of fiscal rules also contribute to explain revision patterns.

What Does Financial Volatility Tell Us About Macroeconomic Fluctuations?

This paper provides an extensive analysis of the predictive ability of financial volatility measures for economic activity. We construct monthly measures of stock and bond market volatility from daily returns and model volatility as composed of a long-run component that is common across all series, and a set of idiosyncratic short-run components. Based on powerful in-sample predictive ability tests, we find that the stock volatility measures and the common factor significantly improve short-term forecasts of conventional financial indicators. A real-time out of sample assessment yields a similar conclusion under the assumption of noisy revisions in macroeconomic data. In a non-linear extension of the dynamic factor model for volatility series, we identify three regimes that describe the joint volatility dynamics: low, intermediate and high-volatility. We also find that the non-linear model performs remarkably well in tracking the Great Recession of 2007-2009 in real-time.

Company sector

The recent national accounts release contained significant data revisions which suggest that the performance of business investment has been even worse than previously thought. It is now estimated to have fallen by almost 34% since early‐2008 and successive falls around the turn of the year mean that the earlier weak recovery has been revised away…

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.

Green shoots and double dips in the euro area: A real time measure

In order to perform real-time business cycle inferences and forecasts of GDP growth rates in the euro area, we use an extension of the Markov-switching dynamic factor models that accounts for the features of the day-to-day monitoring of economic developments, such as ragged edges, mixed frequencies and data revisions. We provide examples that show the nonlinear nature of the relationships between data revisions, point forecasts and forecast uncertainty. Based on our empirical results, we think that the real-time probabilities of recession inferred from the model are an appropriate statistic for capturing what the press call green shoots, and for monitoring double-dip recessions.

Reviewing the revisions: what are the Australian Bureau of Statistics suicide figures really telling us?

For several years, the Australian Bureau of Statistics (ABS) has cautioned data users of likely underreporting of suicide statistics due to delays in coronial processes and (since 2006) exclusive reliance on the National Coronial Information System, which often contains incomplete information on cause of death. In 2009, the ABS introduced data revision processes that allowed additional information received to be added... Language: en

Data revisions and periodic properties of macroeconomic data

Many macroeconomic time series variables show signs of periodicity, that is, seasonal heteroskedasticity and seasonally varying autocorrelation structures. This paper argues that these periodic properties could in part be due to data revisions in case such revisions follow a particular format. Periodicity is shown to appear when quarterly data are revised by allocating updated annual information across the quarters in previous years. An illustration for four waves of seventeen Dutch macroeconomic data emphasizes this result.

On the Informational Role of Term Structure in the U.S. Monetary Policy Rule

The term spread may play a major role in a monetary policy rule whenever data revisions of output and inflation are not well behaved. In this paper we use a structural approach based on the indirect inference principle to estimate a standard version of the New Keynesian Monetary (NKM) model augmented with term structure using both revised and real-time data. The estimation results show that the term spread becomes a significant determinant of the U.S. estimated monetary policy rule when revised and real - time data of output and inflation are both considered.

Extracting GDP signals from the monthly indicator of economic activity

Real-time data are analysed for information on the Chilean monthly economic activity indicator IMACEC and what it indicates of the final GDP, defined as the growth rate that has been subject to at least two annual revisions. Data are presented and revisions analysed briefly. Mincer-Zarnowitz tests suggest that forecast rationality is rejected with respect to the three-month IMACEC growth rate as a nowcast of the first released quarterly GDP, as well as the first published GDP as a nowcast of the final GDP. An out-of-sample nowcasting analysis was conducted using only data which were available in real-time. The results show that small models nowcast better than less parsimonious ones. The evidence from the empirical study suggests no improvement in the nowcasting performance when historical data are supplemented with the first monthly IMACEC of the quarter. On the other hand, when two monthly observations IMACEC are available, the root mean squared nowcast error (RMSNE) decreases by 24%, and a further decline of 33% is obtained when the third monthly observation of the quarter is published. Both of these advances are statistically significant. No further improvement is obtained with the publication of the first release of the quarterly GDP. JEL classifications: C89, E17 Keywords: Real-time data, data revisions, nowcasting

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.

Forecasting through the Rear-View Mirror: Data Revisions and Bond Return Predictability

Macroeconomic data are typically subject to future revisions and released with delay. Predictive return regressions using such data therefore potentially overstate the information set available to investors in real time. We document that data revisions account for a sizable share of in-sample and out-of-sample predictive power for Treasury returns found in macroeconomic data. This is partly explained by the fact that information contained in revisions to prior months' releases is incorporated into bond prices. Survey forecasts available in real time contain information about future revised data that is orthogonal to the real-time data and also helps to predict bond returns.