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Nowadays applied work in business and economics requires a solid
understanding of econometric methods to support decision-making.
Combining a solid exposition of econometric methods with an
application-oriented approach, this rigorous textbook provides
students with a working understanding and hands-on experience of
current econometrics. Taking a 'learning by doing' approach, it
covers basic econometric methods (statistics, simple and multiple
regression, nonlinear regression, maximum likelihood, and
generalized method of moments), and addresses the creative process
of model building with due attention to diagnostic testing and
model improvement. Its last part is devoted to two major
application areas: the econometrics of choice data (logit and
probit, multinomial and ordered choice, truncated and censored
data, and duration data) and the econometrics of time series data
(univariate time series, trends, volatility, vector
autoregressions, and a brief discussion of SUR models, panel data,
and simultaneous equations). * Real-world text examples and
practical exercise questions stimulate active learning and show how
econometrics can solve practical questions in modern business and
economic management. * Focuses on the core of econometrics,
regression, and covers two major advanced topics, choice data with
applications in marketing and micro-economics, and time series data
with applications in finance and macro-economics. *
Learning-support features include concise, manageable sections of
text, frequent cross-references to related and background material,
summaries, computational schemes, keyword lists, suggested further
reading, exercise sets, and online data sets and solutions. *
Derivations and theory exercises are clearly marked for students in
advanced courses. This textbook is perfect for advanced
undergraduate students, new graduate students, and applied
researchers in econometrics, business, and economics, and for
researchers in other fields that draw on modern applied
econometrics.
With a new author team contributing decades of practical
experience, this fully updated and thoroughly classroom-tested
second edition textbook prepares students and practitioners to
create effective forecasting models and master the techniques of
time series analysis. Taking a practical and example-driven
approach, this textbook summarises the most critical decisions,
techniques and steps involved in creating forecasting models for
business and economics. Students are led through the process with
an entirely new set of carefully developed theoretical and
practical exercises. Chapters examine the key features of economic
time series, univariate time series analysis, trends, seasonality,
aberrant observations, conditional heteroskedasticity and ARCH
models, non-linearity and multivariate time series, making this a
complete practical guide. A companion website with downloadable
datasets, exercises and lecture slides rounds out the full learning
package.
Econometrics can at first appear a highly technical subject, but it
can also equip the practitioner with a useful skillset of smart
ways to formulate research questions and collect data. Enjoyable
Econometrics applies econometric methods to a variety of unusual
and engaging research questions, often beyond the realm of
economics, demonstrating the great potential of using such methods
to understand a wide range of phenomena. Unlike the typical
textbook approach, Enjoyable Econometrics follows in the footsteps
of Freakonomics by posing interesting questions first before
introducing the methodology to find the answers. Therefore, rather
than equation-heavy sections based around complex methodologies,
the reader is presented with chapters on 'Money' and 'Fashion, Art
and Music'. Franses writes in a way that will enthuse and motivate
the economics student embarking upon the essential study of
econometrics. Indeed, the book shows that econometric methods can
be applied to almost anything.
Econometrics can at first appear a highly technical subject, but it
can also equip the practitioner with a useful skillset of smart
ways to formulate research questions and collect data. Enjoyable
Econometrics applies econometric methods to a variety of unusual
and engaging research questions, often beyond the realm of
economics, demonstrating the great potential of using such methods
to understand a wide range of phenomena. Unlike the typical
textbook approach, Enjoyable Econometrics follows in the footsteps
of Freakonomics by posing interesting questions first before
introducing the methodology to find the answers. Therefore, rather
than equation-heavy sections based around complex methodologies,
the reader is presented with chapters on 'Money' and 'Fashion, Art
and Music'. Franses writes in a way that will enthuse and motivate
the economics student embarking upon the essential study of
econometrics. Indeed, the book shows that econometric methods can
be applied to almost anything.
With a new author team contributing decades of practical
experience, this fully updated and thoroughly classroom-tested
second edition textbook prepares students and practitioners to
create effective forecasting models and master the techniques of
time series analysis. Taking a practical and example-driven
approach, this textbook summarises the most critical decisions,
techniques and steps involved in creating forecasting models for
business and economics. Students are led through the process with
an entirely new set of carefully developed theoretical and
practical exercises. Chapters examine the key features of economic
time series, univariate time series analysis, trends, seasonality,
aberrant observations, conditional heteroskedasticity and ARCH
models, non-linearity and multivariate time series, making this a
complete practical guide. A companion website with downloadable
datasets, exercises and lecture slides rounds out the full learning
package.
Advances in data collection and data storage techniques have
enabled marketing researchers to study the individual
characteristics of a large range of transactions and purchases, in
particular the effects of household-specific characteristics. This
2001 book presents important and practically relevant quantitative
models for marketing research. Each model is presented in detail
with a self-contained discussion, which includes: a demonstration
of the mechanics of the model, empirical analysis, real world
examples, and interpretation of results and findings. The reader of
the book will learn how to apply the techniques, as well as
understand the methodological developments in the academic
literature. Pathways are offered in the book for students and
practitioners with differing numerical skill levels; a basic
knowledge of elementary numerical techniques is assumed.
An insightful and up-to-date study of the use of periodic models in
the description and forecasting of economic data. Incorporating
recent developments in the field, the authors investigate such
areas as seasonal time series; periodic time series models;
periodic integration; and periodic cointegration. The analysis from
the inclusion of many new empirical examples and results. Advanced
Texts in Econometrics is a distinguished and rapidly expanding
series in which leading econometricians assess recent developments
in such areas as stochastic probability, panel and time series data
analysis, modeling, and cointegration. In both hardback and
affordable paperback, each volume explains the nature and
applicability of a topic in greater depth than possible in
introductory textbooks or single journal articles. Each definitive
work is formatted to be as accessible and convenient for those who
are not familiar with the detailed primary literature.
This book is an ideal introduction for beginning students of econometrics that assumes only basic familiarity with matrix algebra and calculus. It features practical questions which can be answered using econometric methods and models. Focusing on a limited number of the most basic and widely used methods, the book reviews the basics of econometrics before concluding with a number of recent empirical case studies. The volume is an intuitive illustration of what econometricians do when faced with practical questions.
Although many of the models commonly used in empirical finance are
linear, the nature of financial data suggests that non-linear
models are more appropriate for forecasting and accurately
describing returns and volatility. The enormous number of
non-linear time series models appropriate for modeling and
forecasting economic time series models makes choosing the best
model for a particular application daunting. This classroom-tested
advanced undergraduate and graduate textbook, first published in
2000, provides a rigorous treatment of recently developed
non-linear models, including regime-switching and artificial neural
networks. The focus is on the potential applicability for
describing and forecasting financial asset returns and their
associated volatility. The models are analysed in detail and are
not treated as 'black boxes'. Illustrated using a wide range of
financial data, drawn from sources including the financial markets
of Tokyo, London and Frankfurt.
This book provides a self-contained account of periodic models for
seasonally observed economic time series with stochastic trends.
Two key concepts are periodic integration and periodic
cointegration. Periodic integration implies that a seasonally
varying differencing filter is required to remove a stochastic
trend. Periodic cointegration amounts to allowing cointegration
paort-term adjustment parameters to vary with the season. The
emphasis is on useful econrameters and shometric models that
explicitly describe seasonal variation and can reasonably be
interpreted in terms of economic behaviour. The analysis considers
econometric theory, Monte Carlo simulation, and forecasting, and it
is illustrated with numerous empirical time series. A key feature
of the proposed models is that changing seasonal fluctuations
depend on the trend and business cycle fluctuations. In the case of
such dependence, it is shown that seasonal adjustment leads to
inappropriate results.
About the Series
Advanced Texts in Econometrics is a distinguished and rapidly
expanding series in which leading econometricians assess recent
developments in such areas as stochastic probability, panel and
time series data analysis, modeling, and cointegration. In both
hardback and affordable paperback, each volume explains the nature
and applicability of a topic in greater depth than possible in
introductory textbooks or single journal articles. Each definitive
work is formatted to be as accessible and convenient for those who
are not familiar with the detailed primary literature.
To what extent should anybody who has to make model forecasts
generated from detailed data analysis adjust their forecasts based
on their own intuition? In this book, Philip Hans Franses, one of
Europe's leading econometricians, presents the notion that many
publicly available forecasts have experienced an 'expert's touch',
and questions whether this type of intervention is useful and if a
lighter adjustment would be more beneficial. Covering an extensive
research area, this accessible book brings together current
theoretical insights and new empirical results to examine expert
adjustment from an econometric perspective. The author's analysis
is based on a range of real forecasts and the datasets upon which
the forecasters relied. The various motivations behind experts'
modifications are considered, and guidelines for creating more
useful and reliable adjusted forecasts are suggested. This book
will appeal to academics and practitioners with an interest in
forecasting methodology.
An insightful and up-to-date study of the use of periodic models in the description and forecasting of economic data. Incorporating recent developments in the field, the authors investigate such areas as seasonal time series; periodic time series models; periodic integration; and periodic cointegration. The analysis benefits from the inclusion of many new empirical examples and results.
This book is an ideal introduction for beginning students of econometrics that assumes only basic familiarity with matrix algebra and calculus. It features practical questions which can be answered using econometric methods and models. Focusing on a limited number of the most basic and widely used methods, the book reviews the basics of econometrics before concluding with a number of recent empirical case studies. The volume is an intuitive illustration of what econometricians do when faced with practical questions.
This book presents the most important and practically relevant quantitative models for marketing research. Each model includes a demonstration of the mechanics of the model, empirical analysis, real world examples, and an interpretation of results and findings. The reader will learn how to apply the techniques, as well as understand the latest methodological developments in the academic literature. Students and practitioners with differing numerical skills are guided through the book, although a knowledge of elementary numerical techniques is assumed.
This is the most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed nonlinear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. It uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.
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