Tom Stark

A real-time data set for macroeconomists

This paper presents the concept and uses of a real-time data set that can be used by economists for testing the robustness of published econometric results, for analyzing policy, and for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper illustrates why such data may matter, explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, examines key empirical papers in macroeconomics and investigates their robustness to different vintages, looks at how policy analysis may be affected by data revisions, and shows how forecasts can be affected by data revisions.

Do Phillips curves conditionally help to forecast inflation

This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. Significantly, we also find conditional inferiority, with some exceptions. When we do find improvement, it is asymmetric - Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. Any improvement we find, however, vanished over the post-1984 period.

Is macroeconomic research robust to alternative data sets

This paper uses a real-time data set to analyze data revisions and to test the robustness of published econometric results. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper illustrates why such data may matter, examines the properties of several of the variables in the data set across vintages, and examines key empirical papers in macroeconomics, investigating their robustness to different vintages.

Does Data Vintage Matter for Forecasting

This paper illustrates the use of a real-time data set for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, and shows how forecasts can be affected by data revisions.

A Real-Time Data Set for Macroeconomists: Does Data Vintage Matter for Forecasting?

This paper describes a real-time data set for macroeconomists that can be used for a variety of purposes, including forecast evaluation. The data set consists of quarterly vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, and provides an example showing how data revisions can affect forecasts.

Evaluating McCallum's rule when monetary policy matters

This paper provides new evidence on the usefulness of McCallums proposed rule for monetary policy. The rule targets nominal GDP using the monetary base as the instrument. We analyze the rule using three very different economic models to see if the rule works well in different environments. Our results suggest that while the rule leads to lower inflation than there has been over the last 30 years, instability problems suggest that the rule should be modified to feed back on the growth rate of nominal GDP rather than the level.

What Happened to Regional Inequality in Britain in the Twentieth Century

New estimates of regional GDP for Great Britain in the twentieth century differ from those of Crafts but confirm his hypothesis of a U‐shaped regional inequality curve between 1911 and 2001. Comparison of these estimates with revised estimates for 1861–1911 suggests that the decline in inequality in the first half of the twentieth century forms part of a trend of declining regional inequality and catch‐up of the poorer regions with the richest (the South East) dating back to the 1860s at least. This convergence trend was interrupted by the First World War and the subsequent difficulties of Outer Britain in the 1920s when the gap between the South East and the rest widened. However, sometime after 1931 it picked up again. Since 1971 inequality has worsened and catch‐up has stopped; indeed, there has been divergence of the South East from the rest. This divergence has been especially marked since 1991. Although growth for all regions was faster during the period of increasing regional inequality that encompasses the second half of the twentieth century, the golden age of economic growth for regions outside the South East occurred during the long boom following the Second World War.

Mismeasured Personal Saving and the Permanent Income Hypothesis

Is it possible to forecast using poorly measured data? According to the permanent income hypothesis, a low personal saving rate should predict rising future income (Campbell, 1987). However, the U.S. personal saving rate is initially poorly measured and has been repeatedly revised upward in benchmark revisions. The authors use both conventional and real-time estimates of the personal saving rate in vector autoregressions to forecast real disposable income; using the level of the personal saving rate in real time would have almost invariably made forecasts worse, but first differences of the personal saving rate are predictive. They also test the lay hypothesis that a low personal saving rate has implications for consumption growth and find no evidence of forecasting ability.

Does Current-Quarter Information Improve Quarterly Forecasts for the U.S. Economy?

This paper presents new evidence on the benefits of conditioning quarterly model forecasts on monthly current-quarter data. On the basis of a quarterly Bayesian vector error corrections model, the findings indicate that such conditioning produces economically relevant and statistically significant improvement. The improvement, which begins as early as the end of the first week of the second month of the quarter, is largest in the current quarter, but in some cases, extends beyond the current quarter. Forecast improvement is particularly large during periods of recessions but generally extends to other periods as well. Overall, the findings suggest that it is rational to update ones quarterly forecast in response to incoming monthly data.

A Real-Time Data Set for Macroeconomics

This paper presents the concept and uses of a real-time data set that can be used by economists for testing the robustness of published econometric results, for analyzing policy, and for forecasting. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper illustrates why such data may matter, explains the construction of the data set, examines the properties of several of the variables in the data set across vintages, examines key empirical papers in macroeconomics and investigates their robustness to different vintages, looks at how policy analysis may be affected by data revisions, and shows how forecasts can be affected by data revisions.