General: Green, W., Econometric Analysis. Prentice-Hall.

General Time series: Hamilton, J. 1994. Time Series Analysis. Princeton University Press.

Classic on general asymptotics: Billingsley, Convergence of Probability Measures, 1968. Wiley:NY.

Time series, deeper theory: Brockwell, P. and Davis, R. 1998. Time Series: Theory and Methods. Springer.

Time series, classic on frequency domain: Brillinger, David. 2001. Time Series Data Analysis and Theory. Society for Industrial and Applied Math.

Time series, finance: Campbell, J.Y., A.W. Lo and C.McKinlay. 1996. The Econometrics of Financial Markets. Princeton University Press.

Time series, finanace: Cochrane, J. 2005. Asset Pricing. Princeton University Press.

General web texts/notes

There are lots of good (and even more bad) web resources. In general, is might be worth a look. As for econometrics, the following are good:

Jonthan Wright's course and notes.

Dan McFadden: stat. tools and econometrics

Jim Stock and Mark Watson gave a great NBER minicourse in 2008 on `What's new in econometrics--Time Series,' [NBER course]

Bruce Hansen: Econometrics text

Guido Imbens: Prob. and Stats.

History of econometrics

Haavelmo, T. 1944. The Probability Approach in Econometrics, Econometrica. Supplement, July. 12:1.

Heckman, J. 1992. Haavelmo and the birth of modern econometrics. A review of “;The history of econometric ideas”; by Mary Martin. Journal of Economic Literature. [download]

Hendry, D.F., Monetary Economic Myth and Econometric Reality, Oxford Review of Economic Policy, vol. 1 no. 1, Spring 1985, pp. 72--84.

King, Robert, Quantitative Theory and Econometrics, Federal Reserve Bank of Richmond Economic Quaterly, Summer 1995, pp.53--105.

Koopmans, T. 1953. Identification Problems in Economic Model Construction. Studies in Econometric Method, (eds.) W.C. Hood and T.C. Koopmans. New York: Wiley.

Leamer, E. 1983. Let's Take the Con Out of Econometrics American Economic Review, 73:1, March, pp. 31--43

Lucas, R.E. 1979. Econometric Policy Evaluation: A Critique Carnegie-Rochester Conference Series on Public Policy, 1976.

Sims, Christopher, Macroeconomics and Reality Econometrica, vol. 48, iss. 1, 1980, pp.1--48. [download]

Faust, Jon, The new macro models: washing our hands and watching for icebergs, Riksbank Economic Review, 2009:1. [download].

Faust, Jon. DSGE Models: I Smell a Rat (and It Smells Good). International Journal of Central Banking, March 2012. [download].

Comments: I am fond of those last two, but they are certainly not classics. They are my attempt to distill and apply the wisdom of the earlier papers in the context of DSGE modelling. The others are all mandatory reading if you want to understand applied macro. Everyone should read the Haavelmo piece once in their career, but …. If you read one short bit of history, Heckman's review of Mary Morgan's excellent book gives a great summary. King makes the case for quantitative macro instead of macroeconometrics in a thoughtful and constructive way: if you are thinking of dropping the class, this'll give you an excuse. You really must read Lucas (1979) and Sims (1980). My papers listed at the end give my spin on these topics.


There are a few good sets of lecture notes on the web. I recommend the GMM chapter in Hansen's web text as a starting point. As usual, McFadden's notes are clear and thorough. The notes by Guido Imbens at Berkeley are very nice and give a nice starting point in terms of applications.

Bruce Hansen: Econometrics text

Guido Imbens notes

Dan McFadden notes

A classic: Large Sample Properties of Generalized Method of Moments Estimators, Lars Peter Hansen, Econometrica, Vol. 50, No. 4. (Jul., 1982), pp. 1029-1054. [download]

Nice background: Bruce E. Hansen and Kenneth D. West, "Generalized Method of Moments and Macroeconomics" Journal of Business and Economic Statistics, 2002 , [download]

Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators, Peter Hall; Joel L. Horowitz, Econometrica, Vol. 64, No. 4. (Jul., 1996), pp. 891-916. [download]

Relevant sample size issues: JBES Special Section on Small-Sample Properties of Generalized Method of Moments (GMM) [download]

Classic asset pricing application

The application: Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models Lars Peter Hansen; Kenneth J. Singleton Econometrica, Vol. 50, No. 5. (Sep., 1982), pp. 1269-1286. [download]

Cautionary tale: On tests of representative consumer asset pricing models Narayana R. Kocherlakota Journal of Monetary Economics Volume 26, Issue 2 , October 1990, Pages 285-304 [download]

Greater detail: Finite-Sample Properties of Some Alternative GMM Estimators Lars Peter Hansen; John Heaton; Amir Yaron Journal of Business & Economic Statistics, Vol. 14, No. 3. (Jul., 1996), pp. 262-280. [download]

SMM: Simulated Moments Estimation of Markov Models of Asset Prices Darrell Duffie; Kenneth J. Singleton Econometrica, Vol. 61, No. 4. (Jul., 1993), pp. 929-952. [download]

Two nice pedagogical exercises regarding moment and weight matrix selection

GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study Torben G. Andersen; Bent E. Sørensen Journal of Business & Economic Statistics, Vol. 14, No. 3. (Jul., 1996), pp. 328-352. [download]

Efficient Prediction of Excess Returns; Faust, Jon; Jonathan H. Wright; Review of Economics and Statistics, May 2011, 93:2, 647--659. [download]

A macro example about optimal instruments involving the NKPC

Estimating Forward-Looking Euler Equations with GMM and Maximum Likelihood Estimators: An Optimal Instruments Approach, Jeff Fuhrer and Giovanni Olivei, Models and Monetary Policy: Research in the Tradition of Dale Henderson, Richard Porter, and Peter Tinsley; Faust, Orphanides, and Reifschneider, eds. [download]

Karl Whelan's notes on the New Keynesian Phillips Curve give a nice background regarding the issues discussed by Fuhrer and Olivei. [download]

The main paper starting this discussion: Inflation dynamics: a structural econometric analysis, Jordi Gali and Mark Gertler, Journal of Monetary Economics,44, 1999, pp. 195-222. [download]

Model selection

Any good text will provide adequate background. Jonathan's notes and Hansen's web text are nice on this.

Herman Bierens's notes

Good paper on inherent conflicts raised by model selection: Yang, (2005, Biometrika): Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation [get it]

Memorable, especially for the sensible perspective in the conclusion: Amemiya,Selection of Regressors,International Economic Review, Vol. 21, No. 2 (Jun., 1980), pp. 331-354 [get it]

Around the late 1980s, when unit root discussions were beginning to dominate the profession, there was an extended and mostly misguided discussion of whether shocks to growth in GDP tended to be offset as time goes by, and if so, how quickly. In the data at that time, the SAMPLE autocorrelation function of quarterly US GDP growth had a couple of strongly positive autocorrelations at the first few lags and then later came several very small negative autocorrelations. Of course, negative autocorrelation is a symptom of earlier shocks being offset. The debate became one about whether these negative autocorrelations were statistically significant. If one used a criterion that strongly favored parsimony to select the AR model, the estimated model would not show these negative autocorrelations. If one used an ARMA specification and a less parsimonious criterion, these negatvies did come through.

The Campbell and Mankiw paper is written by a couple of the smartest guys around, and has a very clear discussion of model selection and estimation in the ARMA context. A very good read. Indeed, an entire traditional graduate time series course is embedded in their exposition. Read this carefully. Ultimately, they were misguided, in my view. The Gagnon paper does a nice job of explaining why. Two of my early papers were motivated by this debate, which was raging while I was a grad. student. These papers are not important but might hint at a research agenda. These two papers were motivated by asking two simple questions of the work in the literature: What is the worst case scenario for the methods folks are using? (See the confidence level zero paper.) When would the methods folks are using be optimal? (See the variance ratio test paper.) The lesson I took: stick with simple but fundamental questions.

Campbell, J.Y. and N.G. Mankiw (1987): Are Output Fluctuations Transitory?, Quarterly Journal of Economics, 102, pp.857-880. [download]

Gagnon, Joeseph, Short-Run Models and Long-Run Forecasts: A Note on the Permanence of Output Fluctuations The Quarterly Journal of Economics, Vol. 103, No. 2 (May, 1988), pp. 415-424 [download]

When Are Variance Ratio Tests for Serial Dependence Optimal?; Faust, Jon; Econometrica, September 1992, v. 60, iss. 5, pp. 1215-26. [download]

Conventional Confidence Intervals for Points on Spectrum Have Confidence Level Zero; Faust, Jon; Econometrica, May 1999, v. 67, iss. 3, pp. 629-37. &link(,[download])


Hansen's text has a good short introduction.

Horowitz, Chapter 52, Handbook of Econometrics, 2001, vol. 5, pp 3159-3228. Excellent.

Books, general references

Efron, The Jackknife, the Bootstrap, and Other Resampling Plans, is a classic.

Efron and Tibshirani, An introduction to the bootstrap

Peter Hall, The bootstrap and edgeworth expansion.

Time series issues in particular

Berkowitz, J. and Lutz Kilian, Recent Developments in Bootstrapping Time Series Econometric Reviews (January 2000). download from Jeremy

Lutz Kilian, Finite-Sample Properties of Percentile and Percentile-t Bootstrap Confidence Intervals for Impulse Responses, The Review of Economics and Statistics, Vol. 81, No. 4. (Nov., 1999), pp. 652-660.

Lutz Kilian, Small-Sample Confidence Intervals for Impulse Response Functions, The Review of Economics and Statistics, Vol. 80, No. 2. (May, 1998), pp. 218-230.

Chris Sims; Tao Zha, Error Bands for Impulse Responses, Econometrica, 67(5), 1999, pp. 1113-1155. This is not exactly on the bootstrap but sheds a good deal of light on related issues regarding impulse response inference.

Testing for breaks: theory and practice

McConnell and Perez-Quiros did a nice job highlighting for the profession what is now called the great moderation and you should probably read it. Of course, we will be focussing on changing co-movement, as opposed to a fall in variability.

My 2005 paper with Brian Doyle came out recently and provides a decent summary of the issues and earlier work on co-movement. Stock and Watson, as always, do a thorough and interesting job on the issue.

You should read Hansen's paper, which is a nontechnical introduction to testing for breaks. The Andrews, and Andrews and Ploberger, papers provide key technical results in this area, but we won't get far into the technical details.

Donald W. K. Andrews. Tests for Parameter Instability and Structural Change With Unknown Change Point. Econometrica, Vol. 61, No. 4 (Jul., 1993) , pp. 821-856

Donald W. K. Andrews, Werner Ploberger. Optimal Tests when a Nuisance Parameter is Present Only Under the Alternative. Econometrica, Vol. 62, No. 6 (Nov., 1994) , pp. 1383-1414

Doyle, B. and J. Faust. 2002. ``An Investigation of Co-movement Among the Growth Rates of the G-7 Countries,'' Federal Reserve Bulletin, vol. 88, pp. 427-437.

Doyle, B., and Faust J. 2005. Breaks in the variability and co-movement of G-7 economic growth; Doyle, Brian M.; Faust, Jon; Review of Economics and Statistics, 7(4), Nov. 721-740.

Hansen, Bruce. 2001. The New Econometrics of Structural Change: Dating Changes in U.S. Labor Productivity. Journal of Economic Perspectives, 15, 117-128. [download]

International Monetary Fund. 2001. Business Cycle Linkages Among Major Advanced Economies, in World Economic Outlook October, pp. 65-79

McConnell, M.M. and G. Perez-Quiros. 2000. Output Fluctuations in the United States: What Has Changed Since the Early 1980s?, American Economic Review, 90, pp.1464-1476.

Romer, C.D. 1986. Is Stabilization of the Postwar Economy A Figment of the Data? American Economic Review, 76, pp.314-334.

Stock, James and Mark Watson . 2002. ``Has the Business Cycle Changed and Why?'' NBER Macroeconomics Annual 2002. MIT Press.

Stock, James and Mark Watson. 2003. Has the Business Cycle Changed? Evidence and Explanations. Monetary Policy and Uncertainty: Adapting to a Changing Economy. Proceedings of Jackson Hole Symposium. Federal Reserve Bank of Kansas City.