Time Series Econometrics - Volume 1: Unit Roots and Trend Breaks, 

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
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Цена: 78150.00 T
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Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation.

Название: Time Series Econometrics - Volume 2: Structural Change
ISBN: 9813237899 ISBN-13(EAN): 9789813237896
Издательство: World Scientific Publishing
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Цена: 184800.00 T
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Описание: Volume 1 covers statistical methods related to unit roots, trend breaks and their interplay. Testing for unit roots has been a topic of wide interest and the author was at the forefront of this research. The book covers important topics such as the Phillips-Perron unit root test and theoretical analyses about their properties, how this and other tests could be improved, and ingredients needed to achieve betters tests and the proposal of a new class of tests. Also included are theoretical studies related to time series models with unit roots and the effect of span versus sampling interval on the power of the tests. Moreover, this book deals with the issue of trend breaks and their effect on unit root tests. This research agenda fostered by the author showed that trend breaks and unit roots can easily be confused. Hence, the need for new testing procedures, which are covered.Volume 2 is about statistical methods related to structural change in time series models. The approach adopted is off-line whereby one wants to test for structural change using a historical dataset and perform hypothesis testing. A distinctive feature is the allowance for multiple structural changes. The methods discussed have, and continue to be, applied in a variety of fields including economics, finance, life science, physics and climate change. The articles included address issues of estimation, testing and/or inference in a variety of models: short-memory regressors and errors, trends with integrated and/or stationary errors, autoregressions, cointegrated models, multivariate systems of equations, endogenous regressors, long-memory series, among others. Other issues covered include the problems of non-monotonic power and the pitfalls of adopting a local asymptotic framework. Empirical analyses are provided for the US real interest rate, the US GDP, the volatility of asset returns and climate change.

Автор: Klaus Neusser
Название: Time Series Econometrics
ISBN: 3319813870 ISBN-13(EAN): 9783319813875
Издательство: Springer
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Цена: 83850.00 T
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Описание: The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics.

Автор: Franses
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521817706 ISBN-13(EAN): 9780521817707
Издательство: Cambridge Academ
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Цена: 99270.00 T
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Описание: With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Автор: M. Hatanaka; H. Yamada
Название: Co-trending: A Statistical System Analysis of Economic Trends
ISBN: 4431659145 ISBN-13(EAN): 9784431659143
Издательство: Springer
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Цена: 74530.00 T
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Описание: In macro-econometrics more attention needs to be paid to the relationships among deterministic trends of different variables, or co-trending, especially when economic growth is of concern.

Автор: Hallin M., Lippi M., Barigozzi M., Forni M., Zaffaroni P.
Название: Time Series in High Dimensions: The General Dynamic Factor Model
ISBN: 9813278005 ISBN-13(EAN): 9789813278004
Издательство: World Scientific Publishing
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Цена: 221760.00 T
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Описание: Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides an extensive account of the so-called General Dynamic Factor Model methods. The topics covered include: asymptotic representation problems, estimation, forecasting, identification of the number of factors, identification of structural shocks, volatility analysis, and applications to macroeconomic and financial data.

Автор: Bee Dagum, Estela Bianconcini, Silvia
Название: Seasonal adjustment methods and real time trend-cycle estimation
ISBN: 3319811274 ISBN-13(EAN): 9783319811277
Издательство: Springer
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Цена: 149060.00 T
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Описание: This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation.

Автор: Bee Dagum
Название: Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
ISBN: 3319318209 ISBN-13(EAN): 9783319318202
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book explores widely used seasonaladjustment methods and recent developments in real time trend-cycle estimation.It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATSand STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate eachmethod and real data examples can be followed throughout the text. Thetrend-cycle estimation is presented using nonparametric techniques based onmoving averages, linear filters and reproducing kernel Hilbert spaces, takingrecent advances into account. The book provides a systematical treatment ofresults that to date have been scattered throughout the literature.Seasonal adjustment and real timetrend-cycle prediction play an essential part at all levels of activity inmodern economies. They are used by governments to counteract cyclicalrecessions, by central banks to control inflation, by decision makers forbetter modeling and planning and by hospitals, manufacturers, builders,transportation, and consumers in general to decide on appropriate action.This book appeals to practitioners ingovernment institutions, finance and business, macroeconomists, and other professionalswho use economic data as well as academic researchers in time series analysis,seasonal adjustment methods, filtering and signal extraction. It is also usefulfor graduate and final-year undergraduate courses in econometrics and timeseries with a good understanding of linear regression and matrix algebra, aswell as ARIMA modelling.

Автор: Mills Terence C.
Название: Modelling Trends and Cycles in Economic Time Series
ISBN: 3030763587 ISBN-13(EAN): 9783030763589
Издательство: Springer
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Цена: 102480.00 T
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Описание: Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s.

Автор: Mills
Название: Modelling Trends and Cycles in Economic Time Series
ISBN: 1403902097 ISBN-13(EAN): 9781403902092
Издательство: Springer
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Цена: 65210.00 T
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Описание: Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s.

Автор: Franses, Philip Hans
Название: Periodicity and Stochastic Trends in Economic Time Series
ISBN: 0198774540 ISBN-13(EAN): 9780198774549
Издательство: Oxford Academ
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Цена: 54910.00 T
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Описание: This is an advanced graduate textbook in econometrics. A large proportion of the data studied by econometricians are series of observations of the same variables made over time (time series). This book provides a comprehensive account of how to allow for seasonal fluctuations in these data by using periodic models.