Modelling trends and cycles in economic time series:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Palgrave Macmillan
[2021]
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| Ausgabe: | Second edition |
| Schriftenreihe: | Palgrave Texts in Econometrics
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xi, 214 Seiten |
| ISBN: | 9783030763589 |
| ISSN: | 2662-6594 |
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Datensatz im Suchindex
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| adam_text | Contents 1 Introduction 1.1 Historical Perspective 1.2 Overview of the Book References 2 ‘Classical’Techniques of Modelling Trends and Cycles 2.1 2.2 The Classical Trend-Cycle Decomposition Deterministic Trend Models 2.2.1 Linear Trends 2.2.2 Nonlinear Trends 2.2.3 Breaking and Segmented Trends 2.2.4 Smooth Transitions and Fourier Series Approximations 2.3 Estimating Trends Using Moving Averages 2.3.1 Simple Moving Averages 2.3.2 Weighted Moving Averages 2.4 The Cyclical Component 2.4.1 Autoregressive Processes for the Cyclical Component 2.4.2 Estimating the Cyclical Component 2.5 Some Problems Associated with the Classical Approach to Detrending 2.5.1 Eurther Reading and Background Material References 1 1 10 11 17 17 18 18 19 20 21 27 27 29 30 30 34 37 39 41 v
vi CONTENTS 3 Stochastic Trends andCycles 3.1 An Introduction to Stochastic Trends 3.2 Determining the Order of Integration of a TimeSeries 3.3 Some Examples of AKİMA Modelling ЗА Trend Stationarity Versus Difference Stationarity 3.4.1 Distinguishing Between Trend and Difference Stationarity ., 3.4.2 Estimating Trends Robustly 3.4.3 Breaking Trends and Unit Root Tests 3.5 Unobserved Component Models and Signal Extraction 3.5.1 Unobserved Component Models 3.5.2 The Beveridge-Nelson Decomposition 3.5.3 Signal Extraction 3.5.4 Basic Structural Models 3.6 Further Reading and Background Material References 4 Filtering Economic TimeSeries 4.1 Detrending Using Linear Filters 4.1.1 Symmetric Linear Filters 4.1.2 Frequency-Domain Properties of Linear Filters 4.1.3 Designing a Low-Pass Filter 4.1.4 High-Pass and Band-Pass Filters 4.2 The Hodrick-Prescott Filter 4.2.1 The Hodrick-Prescott Filter in Infinite Samples 4.2.2 The Finite Sample H-P Filter 4.2.3 Optimising the Smoothing Parameter and Critiques of H-P Filtering 4.3 Filters and Structural Models 4.3.1 A Structural Model for the H-P Filter 4.3.2 More General Structural Models and Their Filters 4.3.3 Model-Based Filters 4.3.4 Structural Trends and Cycles 4.4 Further Reading and Background Material References 43 43 52 53 58 58 63 65 72 72 74 79 81 87 88 91 91 91 93 102 104 109 109 111 112 117 117 118 119 120 122 123
CONTENTS 5 Nonlinear and Nonparametric Trend and Cycle Modelling 5.1 Regime Shift Models cS.1.1 Markov Models 5.1.2 STAR Models 5.2 Nonparametric Trends 5.2.1 Smoothing Estimators 5.2.2 Kernel Regression 5.2.3 Local Polynomial Regression 5.3 Nonlinear Stochastic Trends 5.4 Further Reading and Background Material References 6 Multivariate Modelling of Trendsand Cycles 6.1 Common Features in Time Series 6.1.1 Specification and Testing of Common Features 6.1.2 Common Cycles and Codependence 6.1.3 Common Deterministic Trends 6.2 Stochastic common trends 6.2.1 Cointegration 6.2.2 Vector Autoregressions with Cointegrated Variables: The VECM 6.2.3 Estimation of VECMs and Tests of Cointegrating Rank 6.2.4 Common Cycles in a VECM 6.3 Multivariate Filtering 6.4 Co-Breaking 6.5 Further Reading and Background Material References 7 Conclusions References vii 125 125 125 130 137 137 140 141 143 144 144 147 147 147 151 152 153 153 158 162 167 171 176 179 180 183 184 Computed Examples 187 Author Index 203 Subject Index 207
|
| adam_txt |
Contents 1 Introduction 1.1 Historical Perspective 1.2 Overview of the Book References 2 ‘Classical’Techniques of Modelling Trends and Cycles 2.1 2.2 The Classical Trend-Cycle Decomposition Deterministic Trend Models 2.2.1 Linear Trends 2.2.2 Nonlinear Trends 2.2.3 Breaking and Segmented Trends 2.2.4 Smooth Transitions and Fourier Series Approximations 2.3 Estimating Trends Using Moving Averages 2.3.1 Simple Moving Averages 2.3.2 Weighted Moving Averages 2.4 The Cyclical Component 2.4.1 Autoregressive Processes for the Cyclical Component 2.4.2 Estimating the Cyclical Component 2.5 Some Problems Associated with the Classical Approach to Detrending 2.5.1 Eurther Reading and Background Material References 1 1 10 11 17 17 18 18 19 20 21 27 27 29 30 30 34 37 39 41 v
vi CONTENTS 3 Stochastic Trends andCycles 3.1 An Introduction to Stochastic Trends 3.2 Determining the Order of Integration of a TimeSeries 3.3 Some Examples of AKİMA Modelling ЗА Trend Stationarity Versus Difference Stationarity 3.4.1 Distinguishing Between Trend and Difference Stationarity ., 3.4.2 Estimating Trends Robustly 3.4.3 Breaking Trends and Unit Root Tests 3.5 Unobserved Component Models and Signal Extraction 3.5.1 Unobserved Component Models 3.5.2 The Beveridge-Nelson Decomposition 3.5.3 Signal Extraction 3.5.4 Basic Structural Models 3.6 Further Reading and Background Material References 4 Filtering Economic TimeSeries 4.1 Detrending Using Linear Filters 4.1.1 Symmetric Linear Filters 4.1.2 Frequency-Domain Properties of Linear Filters 4.1.3 Designing a Low-Pass Filter 4.1.4 High-Pass and Band-Pass Filters 4.2 The Hodrick-Prescott Filter 4.2.1 The Hodrick-Prescott Filter in Infinite Samples 4.2.2 The Finite Sample H-P Filter 4.2.3 Optimising the Smoothing Parameter and Critiques of H-P Filtering 4.3 Filters and Structural Models 4.3.1 A Structural Model for the H-P Filter 4.3.2 More General Structural Models and Their Filters 4.3.3 Model-Based Filters 4.3.4 Structural Trends and Cycles 4.4 Further Reading and Background Material References 43 43 52 53 58 58 63 65 72 72 74 79 81 87 88 91 91 91 93 102 104 109 109 111 112 117 117 118 119 120 122 123
CONTENTS 5 Nonlinear and Nonparametric Trend and Cycle Modelling 5.1 Regime Shift Models cS.1.1 Markov Models 5.1.2 STAR Models 5.2 Nonparametric Trends 5.2.1 Smoothing Estimators 5.2.2 Kernel Regression 5.2.3 Local Polynomial Regression 5.3 Nonlinear Stochastic Trends 5.4 Further Reading and Background Material References 6 Multivariate Modelling of Trendsand Cycles 6.1 Common Features in Time Series 6.1.1 Specification and Testing of Common Features 6.1.2 Common Cycles and Codependence 6.1.3 Common Deterministic Trends 6.2 Stochastic common trends 6.2.1 Cointegration 6.2.2 Vector Autoregressions with Cointegrated Variables: The VECM 6.2.3 Estimation of VECMs and Tests of Cointegrating Rank 6.2.4 Common Cycles in a VECM 6.3 Multivariate Filtering 6.4 Co-Breaking 6.5 Further Reading and Background Material References 7 Conclusions References vii 125 125 125 130 137 137 140 141 143 144 144 147 147 147 151 152 153 153 158 162 167 171 176 179 180 183 184 Computed Examples 187 Author Index 203 Subject Index 207 |
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| spelling | Mills, Terence C. 1952- Verfasser (DE-588)129450790 aut Modelling trends and cycles in economic time series Terence C. Mills Second edition Cham Palgrave Macmillan [2021] xi, 214 Seiten txt rdacontent n rdamedia nc rdacarrier Palgrave Texts in Econometrics 2662-6594 Economic Theory/Quantitative Economics/Mathematical Methods Econometrics Statistics for Business, Management, Economics, Finance, Insurance Macroeconomics/Monetary Economics//Financial Economics Economic theory Statistics Macroeconomics Zeitreihe (DE-588)4127298-5 gnd rswk-swf Ökonometrisches Modell (DE-588)4043212-9 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Konjunkturzyklus (DE-588)4032134-4 gnd rswk-swf Konjunkturzyklus (DE-588)4032134-4 s Zeitreihe (DE-588)4127298-5 s Ökonometrisches Modell (DE-588)4043212-9 s DE-604 Zeitreihenanalyse (DE-588)4067486-1 s Erscheint auch als Online-Ausgabe 978-3-030-76359-6 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032901350&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mills, Terence C. 1952- Modelling trends and cycles in economic time series Economic Theory/Quantitative Economics/Mathematical Methods Econometrics Statistics for Business, Management, Economics, Finance, Insurance Macroeconomics/Monetary Economics//Financial Economics Economic theory Statistics Macroeconomics Zeitreihe (DE-588)4127298-5 gnd Ökonometrisches Modell (DE-588)4043212-9 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd Konjunkturzyklus (DE-588)4032134-4 gnd |
| subject_GND | (DE-588)4127298-5 (DE-588)4043212-9 (DE-588)4067486-1 (DE-588)4032134-4 |
| title | Modelling trends and cycles in economic time series |
| title_auth | Modelling trends and cycles in economic time series |
| title_exact_search | Modelling trends and cycles in economic time series |
| title_exact_search_txtP | Modelling trends and cycles in economic time series |
| title_full | Modelling trends and cycles in economic time series Terence C. Mills |
| title_fullStr | Modelling trends and cycles in economic time series Terence C. Mills |
| title_full_unstemmed | Modelling trends and cycles in economic time series Terence C. Mills |
| title_short | Modelling trends and cycles in economic time series |
| title_sort | modelling trends and cycles in economic time series |
| topic | Economic Theory/Quantitative Economics/Mathematical Methods Econometrics Statistics for Business, Management, Economics, Finance, Insurance Macroeconomics/Monetary Economics//Financial Economics Economic theory Statistics Macroeconomics Zeitreihe (DE-588)4127298-5 gnd Ökonometrisches Modell (DE-588)4043212-9 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd Konjunkturzyklus (DE-588)4032134-4 gnd |
| topic_facet | Economic Theory/Quantitative Economics/Mathematical Methods Econometrics Statistics for Business, Management, Economics, Finance, Insurance Macroeconomics/Monetary Economics//Financial Economics Economic theory Statistics Macroeconomics Zeitreihe Ökonometrisches Modell Zeitreihenanalyse Konjunkturzyklus |
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