Handbook of computational econometrics:
"Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software,...
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Chichester
Wiley
2009
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Klappentext Inhaltsverzeichnis |
| Zusammenfassung: | "Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher "This project's main focus is to provide a handbook on all areas of computing that have a major impact, either directly or indirectly, on econometric techniques and modelling. The book sets out to introduce each topic along with a more in-depth look at methodologies used in computational econometrics, to include use of econometric software and evaluation, bootstrap testing, algorithms for control and optimization and looks at recent computational advances"--Provided by publisher |
| Beschreibung: | XVIII, 496 S. graph. Darst. |
| ISBN: | 0470743859 9780470743850 |
Internformat
MARC
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| 245 | 1 | 0 | |a Handbook of computational econometrics |c ed. by David A. Belsley ... |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Chichester |b Wiley |c 2009 | |
| 300 | |a XVIII, 496 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 520 | 3 | |a "Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher | |
| 520 | 3 | |a "This project's main focus is to provide a handbook on all areas of computing that have a major impact, either directly or indirectly, on econometric techniques and modelling. The book sets out to introduce each topic along with a more in-depth look at methodologies used in computational econometrics, to include use of econometric software and evaluation, bootstrap testing, algorithms for control and optimization and looks at recent computational advances"--Provided by publisher | |
| 650 | 0 | |a Econometrics / Computer programs | |
| 650 | 0 | |a Economics / Statistical methods | |
| 650 | 0 | |a Econometrics / Data processing | |
| 650 | 7 | |a Computergestütztes Verfahren |2 stw | |
| 650 | 7 | |a Datenverarbeitung |2 stw | |
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| 650 | 7 | |a Statistische Methode |2 stw | |
| 650 | 7 | |a Wirtschaftswissenschaft |2 stw | |
| 650 | 7 | |a Wissenschaftliche Methode |2 stw | |
| 650 | 7 | |a Ökonometrie |2 stw | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Wirtschaft | |
| 650 | 4 | |a Econometrics |x Computer programs | |
| 650 | 4 | |a Econometrics |x Data processing | |
| 650 | 4 | |a Economics |x Statistical methods | |
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Datensatz im Suchindex
| _version_ | 1804139431246954496 |
|---|---|
| adam_text | Contents
List of Contributors
xv
Preface
xvii
1
Econometric software
1
Charles G. Renfro
1.1
Introduction
1
1.2
The nature of econometric software
5
1.2.1
The characteristics of early econometric software
9
1.2.2
The expansive development of econometric software
11
1.2.3
Econometric computing and the microcomputer
17
1.3
The existing characteristics of econometric software
19
1.3.1
Software characteristics: broadening and deepening
21
1.3.2
Software characteristics: interface development
25
1.3.3
Directives versus constructive commands
29
1.3.4
Econometric software design implications
35
1.4
Conclusion
39
Acknowledgments
41
References
41
2
The accuracy of econometric software
55
B. D. McCullough
2.1
Introduction
55
2.2
Inaccurate econometric results
56
2.2.1
Inaccurate simulation results
57
2.2.2
Inaccurate GARCH results
58
2.2.3
Inaccurate
VAR
results
62
2.3
Entry-level tests
65
2.4
Intermediate-level tests
66
2.4.1
NIST Statistical Reference
Datasets
67
viii CONTENTS
2.4.2
Statistical distributions
71
2.4.3
Random numbers
72
2.5
Conclusions
75
Acknowledgments
76
References
76
3
Heuristic optimization methods in econometrics
81
Manfred Gilli and Peter Winker
3.1
Traditional numerical versus heuristic optimization methods
81
3.1.1
Optimization in econometrics
81
3.1.2
Optimization heuristics
83
3.1.3
An incomplete collection of applications of optimization
heuristics in econometrics
85
3.1.4
Structure and instructions for use of the chapter
86
3.2
Heuristic optimization
87
3.2.1
Basic concepts
87
3.2.2
Trajectory methods
88
3.2.3
Population-based methods
90
3.2.4
Hybrid metaheuristics
93
3.3
Stochastics of the solution
97
3.3.1
Optimization as stochastic mapping
97
3.3.2
Convergence of heuristics
99
3.3.3
Convergence of optimization-based estimators
101
3.4
General guidelines for the use of optimization heuristics
102
3.4.1
Implementation
103
3.4.2
Presentation of results
108
3.5
Selected applications
109
3.5.1
Model selection in
VAR
models
109
3.5.2
High breakdown point estimation
111
3.6
Conclusions
114
Acknowledgments
115
References
115
4
Algorithms for minimax and expected value optimization
121
Panos Parpas
and
Berç
Růstem
4.1
Introduction
121
4.2
An interior point algorithm
122
4.2.1
Subgradient
of
Ф(х)
and basic iteration
125
4.2.2
Primal-dual step size selection
130
4.2.3
Choice of
с
and
μ
131
4.3
Global optimization of polynomial minimax problems
137
4.3.1
The algorithm
138
4.4
Expected value optimization
143
4.4.1
An algorithm for expected value optimization
145
CONTENTS ix
4.5 Evaluation
framework for minimax
robust
policies and expected
value optimization
147
Acknowledgments
148
References
148
5
Nonparametric estimation
153
RandR. Wilcox
153
155
156
158
160
164
166
169
169
170
171
171
172
173
174
175
177
Bootstrap hypothesis testing
183
James G. MacKinnon
6.1
Introduction
183
6.2
Bootstrap and Monte Carlo tests
184
6.3
Finite-sample properties of bootstrap tests
187
6.4
Double bootstrap and fast double bootstrap tests
189
6.5
Bootstrap data generating processes
193
6.5.1
Resampling and the pairs bootstrap
193
6.5.2
The residual bootstrap
195
6.5.3
The wild bootstrap
196
6.5.4
Bootstrap DGPs for multivariate regression models
197
6.5.5
Bootstrap DGPs for dependent data
198
6.6
Multiple test statistics
200
6.6.1
Tests for structural change
201
6.6.2
Point-optimal tests
202
6.6.3
Non-nested hypothesis tests
203
6.7
Finite-sample properties of bootstrap supF tests
204
6.8
Conclusion
210
Acknowledgments
210
References
210
5.1
Introduction
5.1.1
Comments on software
5.2
Density estimation
5.2.1
Some illustrations
5.3
Nonparametric regression
5.3.1
An illustration
5.3.2
Multiple predictors
5.3.3
Some illustrations
5.3.4
Estimating conditional associations
5.3.5
An illustration
5.4
Nonparametric inferential techniques
5.4.1
Some motivating examples
5.4.2
A bootstrap-/ method
5.4.3
The percentile bootstrap method
5.4.4
Simple ordinary least squares regression
5.4.5
Regression with multiple predictors
References
к
CONTENTS
7
Simulation-based Bayesian econometric inference: principles
and some recent computational advances
215
Lennart
F.
Hoogerheide, Herman K. van
Dijk
and
Rutger
D.
van Oest
7.1
Introduction
215
7.2
A primer on Bayesian inference
217
7.2.1
Motivation for Bayesian inference
217
7.2.2
Bayes
theorem as a learning device
218
7.2.3
Model evaluation and model selection
225
7.2.4
Comparison of Bayesian inference and frequentist approach
232
7.3
A primer on simulation methods
233
7.3.1
Motivation for using simulation techniques
233
7.3.2
Direct sampling methods
234
7.3.3
Indirect sampling methods yielding independent draws
236
7.3.4
Markov chain Monte Carlo: indirect sampling methods
yielding dependent draws
249
7.4
Some recently developed simulation methods
261
7.4.1
Adaptive radial-based direction sampling
262
7.4.2
Adaptive mixtures of
t
distributions
272
7.5
Concluding remarks
276
Acknowledgments
277
References
277
8
Econometric analysis with vector
autoregressive
models
281
Helmut Liitkepohl
8.1
Introduction
281
8.1.1
Integrated variables
282
8.1.2
Structure of the chapter
283
8.1.3
Terminology and notation
284
8.2
VAR
processes
285
8.2.1
The levels
VAR
representation
285
8.2.2
The VECM representation
286
8.2.3
Structural forms
288
8.3
Estimation of
VAR
models
289
8.3.1
Estimation of unrestricted VARs
289
8.3.2
Estimation of VECMs
291
8.3.3
Estimation with linear restrictions
293
8.3.4
Bayesian estimation of VARs
294
8.4
Model specification
295
8.4.1
Choosing the lag order
295
8.4.2
Choosing the cointegrating rank of a VECM
297
8.5
Model checking
298
8.5.1
Tests for residual autocorrelation
298
8.5.2
Tests for non-normality
300
8.5.3
ARCH tests
301
8.5.4
Stability analysis
301
8.6
Forecasting
303
CONTENTS xi
8.6.1
Known
processes
303
8.6.2
Estimated
processes
304
8.7
Causality analysis
305
8.7.1
Intuition and theory
305
8.7.2
Testing for Granger-causality
306
8.8
Structural VARs and impulse response analysis
306
8.8.1
Levels VARs
306
8.8.2
Structural VECMs
308
8.8.3
Estimating impulse responses
309
8.8.4
Forecast error variance decompositions
310
8.9
Conclusions and extensions
311
Acknowledgments
311
References
312
9
Statistical signal extraction and filtering: a partial survey
321
D. Stephen G. Pollock
9.1
Introduction: the semantics of filtering
321
9.2
Linear and circular convolutions
322
9.2.1
Kernel smoothing
324
9.3
Local polynomial regression
326
9.4
The concepts of the frequency domain
332
9.4.1
The
periodogram
334
9.4.2
Filtering and the frequency domain
335
9.4.3
Aliasing and the Shannon-Nyquist sampling theorem
337
9.4.4
The processes underlying the data
339
9.5
The classical Wiener-Kolmogorov theory
341
9.6
Matrix formulations
345
9.6.1
Toeplitz matrices
346
9.6.2
Circulant
matrices
348
9.7
Wiener-Kolmogorov filtering of short stationary sequences
350
9.8
Filtering nonstationary sequences
354
9.9
Filtering in the frequency domain
359
9.10
Structural time-series models
360
9.11
The
Kalman
filter and the smoothing algorithm
368
9.11.1
The smoothing algorithms
371
9.11.2
Equivalent and alternative procedures
372
References
373
10
Concepts of and tools for nonlinear time-series modelling
377
Alessandra Amendola
and Christian
Franca
10.1
Introduction
377
10.2
Nonlinear data generating processes and linear models
382
10.2.1
Linear and nonlinear processes
382
10.2.2
Linear representation of nonlinear processes
384
10.3
Testing linearity
385
xii CONTENTS
10.3.1
Weak white noise and strong white noise
testing
386
10.3.2
Testing linearity against a specific nonlinear model
389
10.3.3
Testing linearity when the model is not identified under the null
392
10.4
Probabilistic tools
395
10.4.1
A strict stationarity condition
395
10.4.2
Second-order stationarity and existence of moments
397
10.4.3
Mixing coefficients
398
10.4.4
Geometric ergodicity and mixing properties
399
10.5
Identification, estimation and model adequacy checking
401
10.5.1
Consistency of the QMLE
402
10.5.2
Asymptotic distribution of the QMLE
404
10.5.3
Identification and model adequacy
406
10.6
Forecasting with nonlinear models
409
10.6.1
Forecast generation
409
10.6.2
Interval and density forecasts
412
10.6.3
Volatility forecasting
414
10.6.4
Forecast combination
415
10.7
Algorithmic aspects
416
10.7.1
MCMC methods
416
10.7.2
Optimization algorithms for models with several latent
processes
418
10.8
Conclusion
422
Acknowledgments
422
References
422
11
Network economics
429
Anna Nagurney
11.1
Introduction
429
11.2
Variational inequalities
432
11.2.1
Systems of equations
433
11.2.2
Optimization problems
434
11.2.3
Complementarity problems
436
11.2.4
Fixed point problems
438
11.3
Transportation networks: user optimization versus system optimization
443
11.3.1
Transportation network equilibrium with travel disutility
functions
444
11.3.2
Elastic demand transportation network problems with known
travel demand functions
447
11.3.3
Fixed demand transportation network problems
449
11.3.4
The system-optimized problem
450
11.4
Spatial price equilibria
454
11.4.1
The quantity model
455
11.4.2
The price model
457
11.5
General economic equilibrium
458
11.6
Oligopolistic market equilibria
459
CONTENTS xiii
11.6.1
The classical oligopoly
problem
460
11.6.2
A spatial oligopoly model
461
11.7
Variational inequalities and projected dynamical systems
463
11.7.1
Background
463
11.7.2
The projected dynamical system
465
11.8
Dynamic transportation networks
470
11.8.1
The path choice adjustment process
470
11.8.2
Stability analysis
472
11.8.3
Discrete-time algorithms
473
11.8.4
A dynamic spatial price model
475
11.9
Supernetworks:
applications to telecommuting decision making
and
teleshopping
decision making
476
11.10
Supply chain networks and other applications
478
Acknowledgments
480
References
480
Index
487
Handbook of
Computational
Econometrics
Editors
David A. Belsley
Boston College, USA.
Erricos John Kontoghiorghes
University of Cyprus and Queen Mary, University of London, UK.
Handbook of Computational Econometrics examines the state of the art of
computational econometrics and provides exemplary studies dealing with
computational issues arising from a wide spectrum of econometric fields including
such topics as bootstrapping, the evaluation of econometric software, and
algorithms for control, optimization, and estimation. Each topic is fully introduced
before proceeding to a more in-depth examination of the relevant methodologies
and valuable illustrations.
This book:
S
Provides self-contained treatments of issues in computational
econometrics with illustrations and invaluable bibliographies.
■
Brings together contributions from leading researchers.
■
Develops the techniques needed to carry out computational econometrics.
■
Features network studies, non-parametric estimation, optimization
techniques, Bayesian estimation and inference, testing methods, time-series
analysis, linear and nonlinear methods,
VAR
analysis, bootstrapping
developments, signal extraction, software history and evaluation.
This book will appeal to econometricians, financial statisticians, econometric
researchers, and students of econometrics at both graduate and advanced
undergraduate levels.
|
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| callnumber-subject | HB - Economic Theory and Demography |
| classification_rvk | QH 300 SK 850 |
| ctrlnum | (OCoLC)319499406 (DE-599)GBV599321954 |
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| dewey-ones | 330 - Economics |
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| dewey-search | 330.0285/555 |
| dewey-sort | 3330.0285 3555 |
| dewey-tens | 330 - Economics |
| discipline | Mathematik Wirtschaftswissenschaften |
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This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">"This project's main focus is to provide a handbook on all areas of computing that have a major impact, either directly or indirectly, on econometric techniques and modelling. 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| id | DE-604.BV035710655 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:43:58Z |
| institution | BVB |
| isbn | 0470743859 9780470743850 |
| language | English |
| lccn | 2009025907 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017764405 |
| oclc_num | 319499406 |
| open_access_boolean | |
| owner | DE-945 DE-703 DE-384 DE-M382 DE-521 DE-11 DE-188 |
| owner_facet | DE-945 DE-703 DE-384 DE-M382 DE-521 DE-11 DE-188 |
| physical | XVIII, 496 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Wiley |
| record_format | marc |
| spelling | Handbook of computational econometrics ed. by David A. Belsley ... 1. publ. Chichester Wiley 2009 XVIII, 496 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier "Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels"--Provided by publisher "This project's main focus is to provide a handbook on all areas of computing that have a major impact, either directly or indirectly, on econometric techniques and modelling. The book sets out to introduce each topic along with a more in-depth look at methodologies used in computational econometrics, to include use of econometric software and evaluation, bootstrap testing, algorithms for control and optimization and looks at recent computational advances"--Provided by publisher Econometrics / Computer programs Economics / Statistical methods Econometrics / Data processing Computergestütztes Verfahren stw Datenverarbeitung stw Mathematik stw Statistische Methode stw Wirtschaftswissenschaft stw Wissenschaftliche Methode stw Ökonometrie stw Datenverarbeitung Wirtschaft Econometrics Computer programs Econometrics Data processing Economics Statistical methods Wirtschaftswissenschaften (DE-588)4066528-8 gnd rswk-swf Ökonometrie (DE-588)4132280-0 gnd rswk-swf Computerunterstütztes Verfahren (DE-588)4139030-1 gnd rswk-swf Ökonometrie (DE-588)4132280-0 s Computerunterstütztes Verfahren (DE-588)4139030-1 s DE-604 Wirtschaftswissenschaften (DE-588)4066528-8 s Belsley, David A. Sonstige oth Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017764405&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017764405&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Handbook of computational econometrics Econometrics / Computer programs Economics / Statistical methods Econometrics / Data processing Computergestütztes Verfahren stw Datenverarbeitung stw Mathematik stw Statistische Methode stw Wirtschaftswissenschaft stw Wissenschaftliche Methode stw Ökonometrie stw Datenverarbeitung Wirtschaft Econometrics Computer programs Econometrics Data processing Economics Statistical methods Wirtschaftswissenschaften (DE-588)4066528-8 gnd Ökonometrie (DE-588)4132280-0 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd |
| subject_GND | (DE-588)4066528-8 (DE-588)4132280-0 (DE-588)4139030-1 |
| title | Handbook of computational econometrics |
| title_auth | Handbook of computational econometrics |
| title_exact_search | Handbook of computational econometrics |
| title_full | Handbook of computational econometrics ed. by David A. Belsley ... |
| title_fullStr | Handbook of computational econometrics ed. by David A. Belsley ... |
| title_full_unstemmed | Handbook of computational econometrics ed. by David A. Belsley ... |
| title_short | Handbook of computational econometrics |
| title_sort | handbook of computational econometrics |
| topic | Econometrics / Computer programs Economics / Statistical methods Econometrics / Data processing Computergestütztes Verfahren stw Datenverarbeitung stw Mathematik stw Statistische Methode stw Wirtschaftswissenschaft stw Wissenschaftliche Methode stw Ökonometrie stw Datenverarbeitung Wirtschaft Econometrics Computer programs Econometrics Data processing Economics Statistical methods Wirtschaftswissenschaften (DE-588)4066528-8 gnd Ökonometrie (DE-588)4132280-0 gnd Computerunterstütztes Verfahren (DE-588)4139030-1 gnd |
| topic_facet | Econometrics / Computer programs Economics / Statistical methods Econometrics / Data processing Computergestütztes Verfahren Datenverarbeitung Mathematik Statistische Methode Wirtschaftswissenschaft Wissenschaftliche Methode Ökonometrie Wirtschaft Econometrics Computer programs Econometrics Data processing Economics Statistical methods Wirtschaftswissenschaften Computerunterstütztes Verfahren |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017764405&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=017764405&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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