James D. Hamilton | University of California, San Diego (original) (raw)

James D. Hamilton

James Hamilton received his Ph.D. in Economics from the University of California at Berkeley in 1983. He has been a professor at the University of California, San Diego since 1992 and served as Chair of the Economics Department from 1999 to 2002. He is the author of Time Series Analysis, the leading text on forecasting and statistical analysis of dynamic economic relationships. He has done extensive research on business cycles, monetary policy, and oil shocks, and has frequently been a research adviser and visiting scholar with the Board of Governors of the Federal Reserve as well as individual Federal Reserve banks.

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Papers by James D. Hamilton

Finance and economics discussion series, Jul 1, 2018

Nber Reporter Online, Jun 22, 2011

Journal of Political Economy, Oct 1, 2002

A consensus has recently emerged that variables beyond the level, slope, and curvature of the yie... more A consensus has recently emerged that variables beyond the level, slope, and curvature of the yield curve can help predict bond returns. This paper shows that the statistical tests underlying this evidence are subject to serious small-sample distortions. We propose more robust tests, including a novel bootstrap procedure specifically designed to test the "spanning hypothesis." We revisit the evidence in five published studies, find most rejections of the spanning hypothesis to be spurious, and conclude that the current consensus is wrong. Only the level and the slope of the yield curve are robust predictors of bond returns.

We revisit the analysis by Drehmann and Yetman (2018) and conclude that measuring the credit gap ... more We revisit the analysis by Drehmann and Yetman (2018) and conclude that measuring the credit gap based on the 5-year growth rate of the credit-to-GDP ratio produces a more reliable and robust predictor of financial crises than does the Hodrick-Prescott filtered series. We also conclude that estimating the credit gap based on the forecast error of a 5-year-ahead regression can be even more useful, provided a sufficiently long sample is available to estimate coefficients of the regression.

Finance and Economics Discussion Series, 2019

The underlying data from which the U.S. unemployment rate, labor-force participation rate, and du... more The underlying data from which the U.S. unemployment rate, labor-force participation rate, and duration of unemployment are calculated contain numerous internal contradictions. This paper catalogs these inconsistencies and proposes a reconciliation. We find that the usual statistics understate the unemployment rate and the labor-force participation rate by about two percentage points on average and that the bias in the latter has increased since the Great Recession. The BLS estimate of the average duration of unemployment overstates by 50% the true duration of uninterrupted spells of unemployment and misrepresents what happened to average durations during the Great Recession and its recovery.

The New Palgrave Dictionary of Economics

Journal of Econometrics, 2012

Journal of Econometrics, 2014

NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate d... more NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to International Finance Discussion Papers (other than an acknowledgement that the writer has had access to unpublished material) should be cleared with the author or authors. Recent IFDPs are available on the Web at www.federalreserve.gov/pubs/ifdp /. This paper can be downloaded without charge from Social

SSRN Electronic Journal, 2021