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Structural Vector Autoregressive Analysis.pdf
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Structural Vector Autoregressive Analysis Lutz Kilian & Helmut L¨utkepohl 高清英文版 非扫描
Objectives of the Book
Since the seminal work of Sims (1980a), structural vector autoregressions have
evolved into one of the most widely used models in empirical research using time
series data. They are used in macroeconomics and in empirical finance, but also
in many other fields including agricultural economics and energy economics.
The evolution of the structural vector autoregressive (VAR) methodology since
1980 has not always been smooth. Over time many new ideas have been explored,
sometimes uncritically applied or misunderstood by practitioners, then
questioned, and later refined or replaced by alternative methods. The development
of new methods of identification, estimation, and inference for structural
VAR models continues at a rapid pace even today. One of the objectives of this
book is to summarize these new developments and to put them in perspective.
The other is to take stock of what we have learned about more traditional structural
VAR models and to interpret these models from today’s perspective. The
profession’s understanding of these models has evolved substantially, becoming
more nuanced in recent years and allowing us to understand better some of the
methodological debates of the past.
In this book, we not only review the ever-increasing range of structural VAR
tools and methods discussed in the literature, but we also highlight their pros
and cons in practice and provide guidance to empirical researchers as to the
most appropriate modeling choices. In addition, we trace the evolution of the
structural VAR methodolgy and contrast it with other common methodologies
including the narrative approach to identification and the use of calibrated or
estimated dynamic stochastic general equilibrium (DSGE) models. We stress
that structural VAR models should be viewed as one of several econometric tools
used in empirical work, each of which has its own strengths and weaknesses.
The book is intended as a bridge between the often quite technical econometric
literature on structural VAR modeling and the needs of empirical researchers.
The focus of the book is not on providing the most rigorous theoretical arguments,
but on enhancing the reader’s understanding of the methods in question
and their assumptions, allowing him or her to decide on the most suitable
methods for applied work. In many cases, empirical examples are provided for
illustration. References to articles in academic journals are provided for readers
with an interest in the more technical aspects of the discussion.
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