This volume investigates the accuracy and dynamic performance of a high-frequency forecast model for the Japanese and United States economies based on the Current Quarter Model (CQM) or High Frequency Model (HFM) developed by the late Professor Emeritus Lawrence R. Klein. It also presents a survey of recent developments in high-frequency forecasts and gives an example application of the CQM model in forecasting Gross Regional Products (GRPs).
Описание: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Автор: Evans Название: Macroeconomic Forecasting ISBN: 1138866253 ISBN-13(EAN): 9781138866256 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on interviews with the UK government`s Panel of Independent Forecasters, the author shows how economic models, forecasts and policy analysis depend crucially upon the judgements of economists.
Introduces the latest developments in forecasting in advanced quantitative data analysis
This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable.
Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers.
Presents models that are all classroom tested
Contains real-life data samples
Contains over 350 equation specifications of various time series models
Contains over 200 illustrative examples with special notes and comments
Applicable for time series data of all quantitative studies
Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.
Описание: Introduction (Gilles Dufrйnot and Takashi Matsuki, eds) Part I. Macroeconometrics and international financeChapter 1. Quantile and copula spectrum: a new approach to investigate cyclical dependence in economic time seriesGilles Dufrйnot, Takashi Matsuki and Kimiko Sugimoto1.-Introduction: why using quantile spectrum?2.- Quantile spectrum: non-parametric and parametric Methods2.1.- Non-parametric approach2.2.- Parametric approach: quantile spectrum and quantile regression models3.- Copula spectral density and rank-based Laplace periodogram4. Estimating quantile spectrum using software4.1.-Estimation of non-parametric quantile spectrum using RATS estima4.2.- Using R package to estimate quantile spectrum and cross spectrumReferencesChapter 2. On the seemingly incompleteness of the exchange rate pass-trough to import pricesAntonia Lopez-Villavicencio and Valйrie Mignon1.-Introduction2.- Methodology3.-data3.1.-Time sample3.2- Variables3.3- Indicators of globalization3.4.- Descriptive statistics4.- Results4.1.- Accounting for globalization4.2.- Using disaggregated data accounting for the good level4.3.- Accounting for globalization at the good level5. ConclusionReferencesChapter 3. A state-space model to estimate potential growth in the industrialized countriesThomas Brand, Gilles Dufrйnot, Antoine Mayerowitz1.- Introduction2.- is potential growth led by financial variables: a simple Bayesian estimation3.- A State-space model with theoretical relationships3.1.- The general model3.2.-Sub-models and comparison with other models used in the literature3.3.-Estimation methods3.4.- Data and methods3.5.- ConclusionReferences Chapter 4.- A top-down method for rational bubbles: application of the threshold bounds testing approach to the Japanese, UK and US Financial marketsJun Nagayasu1.-Introduction2.-The threshold autoregressive distributed lag model (T-ADRL)3.-Application: testing bubbles4.- ConclusionReferencesChapter 5.- An analysis of the time-varying behavior of the equilibrium velocity of money in the euro areaMariam Camarero, Juan Sapena and Cecilio Tamarit1.- Introduction: the shockingly low money velocity in the Euro Area (EA) and its consequences2.- Money demand and velocity: income and transactions3.- A short review of the literature4.- Methodology and estimation.4.1.-A time-varying parameters State-Space framework for panel data.4.2.- An application to the money velocity in the EA.5.- ConclusionsReferencesChapter 6.- Revisiting wealth effects in France: a double-nonlinearity approachOlivier Damette and Fredj Jawadi1.- Introduction2.- Econometric methodology2.1. Linear cointegration specification for wealth effects2.2. Threshold ECM effects for wealth effects2.3. Time varying VECM specification for wealth effects3. Data and empirical analysis3.1. Data and preliminary analysis 3.2. The linear cointegration analysis3.3. Nonlinear cointegration with asymmetric adjustment3.4. NECMs with nonlinearity in the long-run5.- ConclusionsReferencesPart II. Financial econometricsChapter 7.- Econometrics of commoditiesJean-Franзois Carpantier1.-Introduction2.- Tests of the Prebisch-Singer hypothesis3.- Tests of the commodity currenc
Автор: Clements M. P. Название: Macroeconomic Survey Expectations ISBN: 3319972227 ISBN-13(EAN): 9783319972220 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Why should we be interested in macroeconomic survey expectations? Clements presents the nature of survey data, addresses some of the difficulties posed by the way in which survey expectations are elicited and considers the evaluation of point predictions and probability distributions.
Автор: Yoshino Andrew Название: Macroeconomic Shocks and Unconventional Monetary Policy ISBN: 0198838107 ISBN-13(EAN): 9780198838104 Издательство: Oxford Academ Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how macroeconomic shocks stemming from the global financial crisis and recent unconventional monetary policies in developed economies have affected financial stability in emerging Asia.
Описание: This book is a further development of the theory of parametric control. It includes: numerical methods of testing (verification) of software implementation of mathematical models by assessing the stability of mappings defined by the model; sufficient conditions for the existence of the solutions of some types of problems of dynamic optimization; the existence of continuous dependence of optimal values of criteria on exogenous functions and parameters; and the existence of points of bifurcation of extremals of such problems. It demonstrates that this theory offers a constructive methodology for middle-term forecasting, macroeconomic analysis and estimation of optimal values of economic characteristics on the basis of advanced global mathematical models, namely Computable General Equilibrium (CGE) Model, Dynamic Stochastic General Equilibrium (DSGE) Model, and Hybrid Econometric model.
In addition, it includes conditions for the applicability of the computational experiments' results, into practice.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107069394 ISBN-13(EAN): 9781107069398 Издательство: Cambridge Academ Рейтинг: Цена: 19325.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107663911 ISBN-13(EAN): 9781107663916 Издательство: Cambridge Academ Рейтинг: Цена: 7445.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Abdol S. Soofi; Liangyue Cao Название: Modelling and Forecasting Financial Data ISBN: 1461353106 ISBN-13(EAN): 9781461353102 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic.
Автор: Clarke, Bertrand S. (university Of Nebraska, Lincoln) Clarke, Jennifer L. (university Of Nebraska, Lincoln) Название: Predictive statistics ISBN: 1107028280 ISBN-13(EAN): 9781107028289 Издательство: Cambridge Academ Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and `black box` settings, with computed examples.
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