Tables 8, 9, 10, and 11 in Baltagi's “Worldwide Institutional and Individual Rankings in Econometrics over the Period 1989–1999: An Update” (2003, Econometric Theory 19, 165–224) were based on impact factor conversions multiplied by the actual pages in each journal. These should have been multiplied by the standardized pages, with Econometrica having a standardized page of one. The impact factors were additionally divided by 2.072 to make the impact factor for Econometrica equal to one. The corrected tables are given here.

I am grateful to Professor Neuberg for taking the time to study my book Causality and for summarizing its main ideas in a language familiar to readers of Econometric Theory. I will comment on several issues that I believe warrant further discussion. First, I will summarize in my own style what economists can learn from Causality, and, second, I will correct several inaccuracies in the summary of Professor Neuberg.

Normal's deconvolution and the independence of sample mean and variance.

Durbin–Watson statistic and random individual Effects.

In the past thirty-five years, time-series econometrics developed from infancy to relative maturity. A large part of that development is due to Robert F. Engle, whose work is distinguished by exceptional creativity in the empirical modeling of dynamic economic and financial phenomena. Engle's footsteps range widely, from early work on band-spectral regression, testing, and exogeneity through more recent work on cointegration, autoregressive conditional heteroskedasticity (ARCH) models, and ultra-high-frequency financial asset return dynamics. The booming field of financial econometrics, which did not exist twenty-five years ago, is built in large part on the volatility models pioneered by Engle, and their many variations and extensions, which have found widespread application in financial risk management, asset pricing, and asset allocation.

We began the interview in fall 1998 at Spruce in Chicago, the night before the annual NBER/NSF Time Series Seminar; continued in fall 2000 at Tabla in New York; continued again in summer 2001 at the Conference on Market Microstructure and High-Frequency Data in Finance, Sandbjerg Estate, Denmark; and wrapped up by telephone in January 2003.For their cheerful and effective assistance in transcribing this interview, I thank (without implicating) Sean Campbell, Michele Souli, and Clara Vega.

Unbiasedness of the OLS estimator with random regressors.

The asymptotic distribution of the Dickey–Fuller statistic under nonnegativity constraint.

Regression with an evaporating logarithmic trend—solution.

The central limit theorem for student's distribution.

02.6.1. Oblique projectorsTwo solutions are published, proposed independently by Götz Trinkler (the poser of the problem) and by Hans Joachim Werner. Excellent solutions have been independently proposed by G. Dhaene, L. Lauwers, S. Lawford, and H. Neudecker.—solution.

Badly weighted least squares—solution.An excellent solution was independently proposed by Geert Dhaene. A proof for the case p = 1 based on the convexity of Laplace transforms was also provided by Koenker and Portnoy, the posers of the problem.

02.6.1. Oblique projectors—solution.

On Hadamard product of square roots of correlation matrices—solution.

Autoregression and redundant instruments—solution.

On the rank of a matrix useful in goodness-of-fit testing of structural equation models—solution.An excellent solution was independently proposed by A. Satorra and H. Neudecker, the posers of the problem.

We are pleased to announce award of the A.R. Bergstrom Prize in Econometrics for 2003. The award is to Dr. Chirok Han, School of Economics and Finance, Victoria University of Wellington, for his paper, “The Bias of Fixed Effects Estimators for Panel Binary Choice Models.”