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This volume collects seven of Marc Nerlove's previously published,
classic essays on panel data econometrics written over the past
thirty-five years, together with a cogent essay on the history of
the subject, which began with George Biddell Airey's monograph
published in 1861. Since Professor Nerlove's 1966 Econometrica
paper with Pietro Balestra, panel data and methods of econometric
analysis appropriate to such data have become increasingly
important in the discipline. The principal factors in the research
environment affecting the future course of panel data econometrics
are the phenomenal growth in the computational power available to
the individual researcher at his or her desktop and the ready
availability of data sets, both large and small, via the Internet.
The best way to formulate statistical models for inference is
motivated and shaped by substantive problems and understanding of
the processes generating the data at hand to resolve them. The
essays illustrate both the role of the substantive context in
shaping appropriate methods of inference and the increasing
importance of computer-intensive methods.
This book, with an overview introduction by Keneth J. Arrow, is
the first volume of the proceedings of the World Economic Congress
held in Athens, Greece in August/September 1989 under the austpices
of the International Economic Association.
This volume collects seven of Nerlove's previously published essays on panel data econometrics written over the past thirty-five years, with a new essay on the history of the subject, which began with George Biddell Airey's monograph in 1861. Since his 1966 Econometrica paper with Pietro Balestra, panel data and methods of econometric analysis have become important in the discipline. The principal factors in the research environment affecting the future course of panel data econometrics are the growth in the computational power available to the individual researcher at his desktop and the ready availability of data sets via the Internet. The best way to formulate statistical models for inference is motivated and shaped by substantive problems and our understanding of the processes generating the data at hand to resolve them. The essays illustrate the substantive context in shaping appropriate methods of inference and the increasing importance of computer-intensive methods.
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