Unit roots, cointegration and structural change:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge Univ. Press
2007
|
| Ausgabe: | transf. to digital print. |
| Schriftenreihe: | Themes in modern econometrics
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020845915&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020845915&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVIII, 505 S. |
| ISBN: | 0521587824 0521582571 |
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Datensatz im Suchindex
| _version_ | 1819365046323511296 |
|---|---|
| adam_text | Contents
Figures
page xü
Tables
xiii
Preface
xvii
Part I Introduction and basic concepts
1
1
Introduction
3
References
6
2
Basic concepts
8
2.1
Stochastic processes
8
2.2
Some commonly used stationary models
11
2.3
Box-Jenkins methods IV
2.4
Integrated variables and
cointegration
20
2.5
Spurious regression
28
2.6
Deterministic trend and stochastic trend
29
2.7
Detrending methods
32
2.8
VAR,
ECM, and ADL
34
2.9
Unit root tests
37
2.10
Cointegration
tests and ECM
39
2.11
Summary
41
References
42
Part II Unit roots and
cointegration
45
3
Unit roots
47
3.1
Introduction
47
3.2
Unit roots and Wiener processes
49
3.3
Unit root tests without a deterministic trend
60
3.4
DF test with a linear deterministic trend
65
3.5
Specification of deterministic trends
72
3.6
Unit root tests for a wide class of errors
74
3.7
Sargan-Bhargava and Bhargava tests
82
3.8
Variance ratio tests
86
3.9
Tests for TSP versus DSP
87
3.10
Forecasting from TS versus DS models
89
3.11
Summary and conclusions
92
References
92
4
Issues in unit root testing
98
4.1
Introduction
98
4.2
Size distortion and low power of unit root tests
100
4.3
Solutions to the problems of size and power
103
4.4
Problem of overdifferencing: MA roots
116
4.5
Tests with stationarity as null
120
4.6
Confirmatory analysis
126
4.7
Frequency of observations and power of unit root tests
129
4.8
Other types of nonstationarity
131
4.9
Panel data unit root tests
133
4.10
Uncertain unit roots and the
pre-
testing problem
139
4.11
Other unit root tests
140
4.12
Median-unbiased estimation
141
4.13
Summary and conclusions
145
References
146
5
Estimation of cointegrated systems
155
5.1
Introduction
155
5.2
A general
CI
system
155
5.3
A two-variable model: Engle-Granger methods
156
5.4
A triangular system
160
5.5
System estimation methods
165
5.6
The identification problem
173
5.7
Finite sample evidence
175
5.8
Forecasting in cointegrated systems
184
5.9
Miscellaneous other problems
187
5.10
Summary and conclusions
191
References
191
6
Tests for
cointegration
198
6.1
Introduction
198
6.2
Single equation methods: residual-based tests
198
6.3
Single
equation methods: ECM tests
203
6.4
Tests with
cointegration
as null
205
6.5
Multiple equation methods
211
6.6
Cointegration
tests based on LCCA
222
6.7
Other tests for
cointegration
226
6.8
Miscellaneous other problems
228
6.9
Of what use are
cointegration
tests?
233
6.10
Conclusions
241
References
242
7
Econometric modeling with integrated regressors
249
7.1 1(1)
regressors not cointegrated
249
7.2 1(1)
regressors cointegrated
250
7.3
Unbalanced equations
251
7.4
Lagged dependent variables: the ARDL model
252
7.5
Uncertain unit roots
254
7.6
Uncertain unit roots and
cointegration
256
7.7
Summary and conclusions
258
References
258
Part III Extensions of the basic model
261
8
The Bayesian analysis of stochastic trends
263
8.1
Introduction to Bayesian inference
264
8.2
The posterior distribution of an
autoregressive
parameter
266
8.3
Bayesian inference on the Nelson-Plosser data
268
8.4
The debate on the appropriate prior
271
8.5
Classical tests versus Bayesian tests
277
8.6
Priors and time units of measurement
277
8.7
On testing point null hypotheses
278
8.8
Further comments on prior distributions
284
8.9
Bayesian inference on cointegrated systems
287
8.10
Bayesian long-run prediction
290
8.11
Conclusion
291
References
292
9
Fractional unit roots and fractional
cointegration
296
9.1
Some definitions
296
9.2
Unit root tests against fractional alternatives
298
9.3
Estimation of ARFIMA models
300
9.4
Estimation of fractionally cointegrated models
302
9.5
Empirical relevance of fractional unit roots
303
9.6
Summary and conclusions
305
References
306
10
Small sample inference: bootstrap methods
309
10.1
Introduction
309
10.2
A review of the bootstrap approach
309
10.3
The AR(1) model
322
10.4
Bootstrapping unit root tests
325
10.5
The moving block bootstrap and extensions
328
10.6
Issues in bootstrapping cointegrating regressions
332
10.7
Miscellaneous other applications
335
10.8
Conclusions
336
References
336
11
Cointegrated systems with
1(2)
variables
342
11.1
Determination of the order of differencing
342
11.2
Cointegration
analysis with
1(2)
and
1(1)
variables
348
11.3
Empirical applications
355
11.4
Summary and conclusions
358
References
359
12
Seasonal unit roots and seasonal
cointegration
362
12.1
Effect of seasonal adjustment
364
12.2
Seasonal integration
365
12.3
Tests for seasonal unit roots
366
12.4
The unobserved component model
371
12.5
Seasonal
cointegration
375
12.6
Estimation of seasonally cointegrated systems
376
12.7
Empirical evidence
378
12.8
Periodic autoregression and periodic integration
379
12.9
Periodic
cointegration
and seasonal
cointegration
381
12.10
Time aggregation and systematic sampling
381
12.11
Conclusion
382
References
383
Part
IV Structural change
387
13
Structural change, unit roots, and
cointegration
389
13.1
Tests for structural change
390
13.2
Tests with known break points
390
13.3
Tests with unknown break points
391
13.4
A summary assessment
398
13.5
Tests for unit roots under structural change
399
13.6
The Bayesian approach
402
13.7
A summary assessment of the empirical work
407
13.8
Effect of structural change on
cointegration
tests
410
13.9
Tests for structural change in cointegrated relationships
411
13.10
Miscellaneous other issues
414
13.11
Practical conclusions
416
References
418
14
Outliers and unit roots
425
14.1
Introduction
425
14.2
Different types of outliers in time series models
425
14.3
Effects of outliers on unit root tests
428
14.4
Outlier detection
437
14.5
Robust unit root tests
440
14.6
Robust estimation of cointegrating regressions
445
14.7
Outliers and seasonal unit roots
448
14.8
Conclusions
448
References
449
15
Regime switching models and structural time series models
454
15.1
The switching regression model
454
15.2
The Markov switching regression model
455
15.3
The Hamilton model
457
15.4
On the usefulness of the MSR model
460
15.5
Extensions of the MSR model
463
15.6
Gradual regime switching models
466
15.7
A model with parameters following a random, walk
469
15.8
A general state-space model
470
15.9
Derivation of the
Kalman
filter
472
15.10
Harvey s structural time series model
(1989) 475
15.11
Further comments on structural time series models
477
15.12
Summary and conclusions
479
References
479
16
Future directions
486
References
488
Appendix
1
A brief guide to asymptotic theory
490
Author index
492
Subject index
500
Time series analysis has undergone many changes in recent years with the advent
of unit roots and
cointegration. Maddala
and Kim present a comprehensive
review of these important developments and examine structural change. The
volume provides an analysis of unit root tests, problems with unit root testing,
estimation of
cointegration
systems,
cointegration
tests, and econometric
estimation with integrated regressors. The authors also present the Bayesian
approach to these problems and bootstrap methods for small-sample inference.
Unit Roots,
Cointegration,
and Structural Change is a major contribution to
Themes in Modern Econometrics, of interest both to specialists and graduate
and upper-graduate students.
|
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| discipline | Mathematik Wirtschaftswissenschaften |
| edition | transf. to digital print. |
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| id | DE-604.BV036930860 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T14:44:52Z |
| institution | BVB |
| isbn | 0521587824 0521582571 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020845915 |
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| physical | XVIII, 505 S. |
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| series2 | Themes in modern econometrics |
| spellingShingle | Maddala, Gangadharrao S. 1933- Kim, In-Moo 1958- Unit roots, cointegration and structural change Zeitreihenanalyse (DE-588)4067486-1 gnd Ökonometrie (DE-588)4132280-0 gnd |
| subject_GND | (DE-588)4067486-1 (DE-588)4132280-0 |
| title | Unit roots, cointegration and structural change |
| title_auth | Unit roots, cointegration and structural change |
| title_exact_search | Unit roots, cointegration and structural change |
| title_full | Unit roots, cointegration and structural change G. S. Maddala ; In-Moo Kim |
| title_fullStr | Unit roots, cointegration and structural change G. S. Maddala ; In-Moo Kim |
| title_full_unstemmed | Unit roots, cointegration and structural change G. S. Maddala ; In-Moo Kim |
| title_short | Unit roots, cointegration and structural change |
| title_sort | unit roots cointegration and structural change |
| topic | Zeitreihenanalyse (DE-588)4067486-1 gnd Ökonometrie (DE-588)4132280-0 gnd |
| topic_facet | Zeitreihenanalyse Ökonometrie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020845915&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020845915&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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