Table Of ContentModern Econometric Analysis
Surveys on Recent Developments
Olaf Hiibler • Joachim Frohn
(Editors)
Modern
Econometric Analysis
Surveys on Recent Developments
With 8 Figures and 11 Tables
Springer
Professor Dr. Olaf Hiibler
University of Hannover
Empirical Economic Research
and Econometrics
Konigsworther Platz 1
30167 Hannover
Germany
[email protected]
Professor Dr. Joachim Frohn
University of Bielefeld
Universitatsstrafie 25
33615 Bielefeld
Germany
[email protected]
First published in
Allgemeines Statistisches ArchiVy Vol 90, Issue 1, 2006
ISBN-10 3-540-32692-8 Springer Berlin Heidelberg New York
ISBN-13 978-3-540-32692-2 Springer Berlin Heidelberg New York
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Preface
The importance of empirical economics and econometric methods has greatly in
creased during the last 20 years due to the availability of better data and the
improved performance of computers. In an information-driven society such as ours
we need quickly to obtain complete and convincing statistical results. This is only
possible if the appropriate econometric methods are applied.
Traditional econometric analysis concentrates on classical methods which are far
from suitable for handling actual economic problems. They can only be used as a
starting point for students to learn basic econometrics and as a reference point for
more advanced methods. Modern Econometrics tries to develop new approaches
from an economic perspective. A consequence is that we have less of a unified
econometric theory than in former times. Specific branches which require specific
methods have been established. Nowadays, nobody has complete knowledge of every
area of econometrics. If someone is interested to learn more about a field, relatively
unknown to them, they will require support.
This volume is intended to be both an introduction to new econometric methods
and a reference for professional econometricians and graduate students. The book
provides concise surveys have been carefully selected of many relevant new develop
ments in econometrics. Nevertheless, the contributions are selective. We have asked
leading German econometricians to write papers about their specific research fields
with emphasis on their own area of interest. Nearly all of them have responded with
enthusiasm and we are very pleased with the outcome. Hopefully, the reader will
share this positive impression. The papers cover the methods used in simultaneous
equation models over modern time series, the use of duration and panel data analy
sis, microeconometrics, and specific data problems. The reader will find discussion
of the benefits and pitfalls as well as the statistical properties of the methods pre
sented. The authors emphasize the advantages and disadvantages. They outline
the progress which has been made is made in the last few years and the problems
which remain unsolved. It is not our intention to demonstrate the workability of
the methods by specific applications. For this purpose the reader should consult
other publications. Nevertheless, in some chapters advices can be found. All of the
contributions in this book are also published in the Journal of the German Statis
tical Society (Allgemeines Statistisches Archiv), Volume 90 (2006), Issue 1.
We would Hke to thank all the authors who have produced a superb series of papers
and the referees who have contributed to a lot of improvements. The support of
the German Statistical Society, particularly of Karl Mosler, the president of the
society, is gratefully acknowledged. Last but not least we thank the Springer Pub-
VI Preface
lishers and especially Werner A. Miiller for their cooperation, and their prompt and
professional editorial assistance.
Olaf Hiibler, Hannover
Joachim Prohn, Bielefeld March 2006
Contents
1 Developments and New Dimensions in Econometrics 1
Olaf Hiibler, Joachim Prohn
2 Large Scale Simultaneous Structural Models 7
Pu Chen, Joachim Prohn
3 Dynamic Factor Models 25
Jorg Breitung, Sandra Eickmeier
4 Unit Root Testing 41
Jiirgen Welters, Uwe Hassler
5 Autoregressive Distributed Lag Models and Cointegration 57
Uwe Hassler, Jiirgen Welters
6 Cointegrated Structural VAR Analysis 73
Helmut Liitkepehl
7 Econometric Analysis of High Frequency Data 87
Helmut Herwartz
8 Using Quantile Regression for Duration Analysis 103
Bernd Fitzenberger, Ralf A. Wilke
9 Multilevel and Nonlinear Panel Data Models 119
Olaf Hiibler
10 Nonparametric Models and Their Estimation 137
Goran Kauermann
11 Microeconometric Models and Anonymized Micro Data 153
Gerd Ronning
12 Ordered Response Models 167
Stefan Bees, Rainer Winkelmann
13 Measurement Error Models and Methods 183
Hans Schneewei£, Thomas August in
VIII Contents
14 Microeconoraetric Estimation of Treatment Effects 199
Marco Caliendo, Reinhard Hujer
15 Survey Item Nonresponse and its Treatment 215
Susanne Rassler, Regina T. Riphahn
1 Developments and New
Dimensions in Econometrics
Olaf Hiibler"^ and Joachim Prohn^
^ Institute of Empirical Economic Research, University of Hannover
[email protected]
^ Faculty of Economics, University of Bielefeld
[email protected]
Summary. This book presents 14 papers with surveys on the development and
new topics in econometrics. The articles aim to demonstrate how German econo-
metricians see the discipline from their specific view. They briefly describe the main
strands and emphasize some recent methods.
1.1 Introduction
75 years ago on the 30th of December in 1930 the Econometric Society was founded
and two years later the Society has decided to establish its own journal 'Economet-
rica'. This was the birth of econometrics, but the roots lie in the mathematical and
statistical economics of the nineteenth century. The 1930s were determined by the
enthusiasm of an international group of young people. National style and theoreti
cal allegiance seemed to matter less than their common methodological programme.
Ragnar Frisch (1970, p. 152), the first editor of Econometrica, describes this feeling
when he talks about the First European Meeting of the Econometric Society in
1931 in Lausanne: 'We, the Lausanne people, were indeed so enthusiastic all of us
about the new venture, and so eager to give and take, that we had hardly time to eat
when we sat together at lunch or at dinner with all our notes floating around on the
table to the despair of the waiters'. The first years can definitely be characterized
by mathematical models and methods to describe macroeconomic problems and a
lack of suitable data sets. Since this time we have observed a rapid and sustainable
development. Was it a success story or a chain of frustrations? Both is true.
On the one hand the enthusiasm has vanished, the belief that large econometric
models can completely explain the economic development has given way to a more
skeptical view. The strategy of the Cowles Commission was criticized and alterna-
1 Developments and New Dimensions in Econometrics
tive approaches were presented as 'general to specific modelling' by Hendry (1980),
'sensitivity analysis' by Learner (1985) or 'reduced form vector antoregressive mod
els' by Sims (1980). Forecasts are not always satisfactory. Many researchers believe
that it is not really possible to estimate structural models. Summers (1991), for
example, is convinced that applied econometrics is ineffective, not more than ex
plorative data analysis can be done by econometrics. Nevertheless, many econome-
tricians still have the objective to estimate structural models. Some of the following
contributions demonstrate the progress in this field, especially the first and the fifth
paper.
On the other hand the data situation has significantly improved. Not only are
aggregated yearly time series available, but quarterly, monthly, weekly and even
daily or tick-by-tick data can be used. Furthermore, large cross-sectional, panel,
duration and multilevel data are the basis of many applied econometric studies.
Computers give us the chance to process such large information. This was and is
a good motivation to develop estimation methods and testing procedures for these
specific data constellations.
In particular progress in time series analysis has been made, since this field is
considered in the perspective of econometric regression models. Nowadays, unit
roots and co-integration investigations are standard in single equations models and
vector antoregressive models. This means non-stationary in contrast to traditional
time series are feasible; the bridge is made between economic theory of equilibria and
the econometricians, whose models concentrated on the short-run dynamics, and
poor performance of simultaneous macroeconometric models has improved. Recent
developments tackle the problem for structural multivariate models, but seasonal
models are also considered and structural shifts are in discussion. Econometricians
also try to benefit from traditional multivariate statistical methods, like factor
analysis and combine these with modern time series methods.
While in the 1930's and over a period of 40 years macroeconometric models with
many equations have dominated our discipline, in the 1970's the situation changed.
The beginning of this new phase is characterized by the new interest in microe-
conomic questions and the availability of large cross-sectional data sets, but in
applied econometrics the old methods were still used. A little later a revolution of
new approaches started in many fields and is still continuing. First, the range of
estimation methods extends enormously. Besides the traditional least squares, max
imum likelihood methods and methods of moments we find several further methods
in the literature: instrumental variable methods, generalized methods of moments,
quasi maximum likelihood, quantile estimators, extremum estimator, generalized
estimating equations, simulation based estimators. Non- and semi-parametric pro
cedures are developed. Second, researchers pay more attention to testing. Especially
the spectrum of specifications tests is extended. Incorrect omission of regressors,
inclusion- of other variables that are proxies for the omitted variables and a false
functional form of the econometric relationship are leading sources of biased estima
tions. Third, nonlinear approaches become more relevant. Specific microeconomic
data lead to binary, multinomial and ordered probit or logit, count data, duration
and tobit models. All of them have a specific nonlinear character and the problem of
unobserved heterogeneity has to be solved. Fourth, econometricians analyze specific
data problems in more detail. These include measurement errors, anonymization of
1.2 Contributions
data and missing values. Fifth, evaluation methods of poUcy intervention and the
measurement of treatment effects are more important in economically difficult pe
riods. In Germany, this phase started some years after the German reunification.
The main problem is to compare two situations where only one is observable.
1.2 Contributions
This book contains 14 contributions. Most of the new developments are more or
less intensively reviewed.
The first paper, presented by Pu Chen and Joachim Prohn, is in some sense a reha
bilitation of large scale structural macro econometric models. The authors emphasize
the relevance for empirical economics. Apart from traditional aspects like identifica
tion and estimation of simultaneous approaches the paper integrates non-stationary
variables and co-integration. In detail, statistical inference in large systems is dis
cussed. The paper argues that until now the modern statistical inference is not fully
integrated into the simultaneous structural approach. Chen and Prohn describe the
state of the art of large scale simultaneous econometric models, identify the major
unsolved problems and suggest a combined data-theory strategy to look for the
specification of the models.
The second paper also focusses on empirical macroeconomic models. Jorg Breitung
and Sandra Eickmeier discuss large dimensional dynamic factor models which have
recently become popular in this field, especially in macroeconomic policy analy
sis. The basic idea is to reduce the dimensionality. The large number of available
macroeconomic variables is combined with factors that should be interpret able. The
paper gives a short survey on factor models and considers different procedures for
determining the number of factors. The main new aspect is the introduction of dy
namic factor models and procedures to estimate the innovations (error terms) of the
factors where VAR models are used. Furthermore, the authors present an overview
of economic applications and add their own empirical contribution to co-movements
in Europe.
Jiirgen Wolters and Uwe Hassler address problems of unit root testing, which nowa
days is the starting point of most empirical studies of time series. First, the most
popular approach, the Dickey-Fuller and the augmented Dickey-Fuller test includ
ing the distribution of the test statistics is presented. Additionally, the authors
describe the selection of the lag length, the treatment of the deterministic part in
the augmented Dickey-Fuller regression and problems with the variation of time
span and frequency of observations. Most important is the overview to unit root
testing under structural shifts. Consequences of ignoring breaks, suggestions of cor
rections under situations with breaks, smooth and multiple breaks are the content
of this section.
Co-integration in single equation models within an autoregressive distributed lag
framework is the topic of the next contribution. Uwe Hassler and Jiirgen Wolters
start their paper with different representations of autoregressive distributed lag
model including the error correction model. Inference to a co-integration vector and
CO-integration testing follows using error correction models. Several approaches and
