An introduction to applied econometrics: a time series approach
This new book is designed for second and final year economics undergraduates taking an introductory or applied course in econometrics. Covering the essential elements of the subject, the author also introduces and explains techniques that are now widely used in applied work.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Basingstoke u.a.
Macmillan
2000
|
| Ausgabe: | 1. publ. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | This new book is designed for second and final year economics undergraduates taking an introductory or applied course in econometrics. Covering the essential elements of the subject, the author also introduces and explains techniques that are now widely used in applied work. |
| Beschreibung: | XXVII, 795 S. graph. Darst. |
| ISBN: | 0333802454 0333802462 |
Internformat
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| 100 | 1 | |a Patterson, Kerry D. |e Verfasser |0 (DE-588)131958070 |4 aut | |
| 245 | 1 | 0 | |a An introduction to applied econometrics |b a time series approach |c Kerry Patterson |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Basingstoke u.a. |b Macmillan |c 2000 | |
| 300 | |a XXVII, 795 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 520 | 3 | |a This new book is designed for second and final year economics undergraduates taking an introductory or applied course in econometrics. Covering the essential elements of the subject, the author also introduces and explains techniques that are now widely used in applied work. | |
| 650 | 7 | |a Econometria |2 larpcal | |
| 650 | 4 | |a Econometrics | |
| 650 | 0 | 7 | |a Ökonometrie |0 (DE-588)4132280-0 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
| _version_ | 1804128029414260736 |
|---|---|
| adam_text | Contents
List of Figures
Preface
Acknowledgements
PART I Foundations
Chapter
quantitative economics
1.1
1.2
1.3
models in economics
1.4
quantitative economics
1.4.1
1.4.2
1.4.3
1.5
1.5.1
1.5.2
1.5.3
structure of this book
1.5.4
1.6
Review
Review questions
Chapter
2.1
2.2
the data
2.2.1
2.2.2
2.2.3
2.2.4
2.2.5
series data
xviii
2.2.6
Nonexperimental data
30
xxiii
2.2.7
Experimental data
31
xxvii
2.3
Lagging and leading time series data
32
2.3.1
Lagging time series data
32
1
2.3.2
Leading time series data
33
2.4
The lag operator
34
2.4.1
Definition of the lag operator
34
3
2.4.2
The lag polynomial
34
3
2.4.3
Obtaining the sum of the lag
3
coefficients
34
2.4.4
A univariate dynamic model
35
4
2.5
Bivariate relationships
36
2.5.1
A deterministic bivariate
5
model
36
5
2.5.2
A stochastic bivariate model
36
8
2.5.3
Visual representation of
10
two variables
37
14
2.5.4
Dynamic bivariate models
38
14
2.5.5
Autoregressive
17
lag (ADL) models
39
2.5.6
The distributed lag function
40
19
2.5.7
More than one conditioning
20
variable
41
21
2.5.8
Notation in more complex
21
models
42
23
2.6
Several equations together
42
2.7
Concluding remarks
45
24
Review
46
24
Review aue
stions
49
24
24
25
26
26 3.1
3.2
27 3.2.1
3.3
Random variables
3.3.1
3.4
variable
3.3.2
variable
3.3.3
Joint events, covariance,
autocovariance and autocorrelation
3.4.1
3.4.2
autocovariance
3.4.3
3.4.4
order stationarity
3.4.5
random variables
3.4.6
3.4.7
nonstationary time series
Correlation and the<
56
59
61
62
62
64
66
67
68
69
autocorrelation function
70
3.4.8
72
3.4.9
73
3.5
74
3.5.1
74
3.6
76
3.6.1
76
3.6.2
77
3.6.3
79
3.7
79
4.6
Review
80
4.7
Review questions
82
PART II Estimation and simulation
Chapter
testing in simple
regression models
4.1
4.2
4.2.1
density
4.2.2
function, CEF, as the regression
function
4.2.3
4.3
estimates
4.3.1
4.3.2
estimation
4.4
4.4.1
4.4.2
4.4.2a Examples
4.4.2b Speed of
convergence
4.4.3
4.4.4
4.4.5
4.5
ßi
4.5.1
unconditionally unbiased
4.5.2
class of linear unbiased
estimators
4.5.2a The variance of
4.5.2b The variance of /?i
4.5.2c The unconditional
variances of
ßi
4.5.2d The Gauss-Markov
theorem
A nonlinear CEF
Goodness of fit
4.7.1
population, rf
4.7.2
sample, Rz 111
4.7.3 %
goodness of fit
4.8
4.9
4.9.1
parameters of interest
4.9.2
estimation
4.10
4.10.1
4.10.2
4.10.3
4.11
empirical example
4.11.1
4.11.2
4.12
Review
Review questions
Appendices
A4.1 Maximum likelihood estimation
A4.1.1 The likelihood function
A4.1.2 The binomial distribution
of probabilities
A4.1.3
estimation: the regression
model
A4.1.4
models
A4.1.5 Hypothesis testing
A4.2 Computer output
A4.2.1
A4.2.2 TSP
A4.2.3 RATS
A4.2.4 PCGIVE
Chapter
model building to several
regressors
5.1
5.2
more than two regressors
5.2.1
set-up
5.2.2
5.2.3
matrix of
5.3
5.3.1
5.3.2
matrix of the GLS estimator,
Var(/3°)
5.3.3
5.4
5.4.1
Multiplier,
ratio
5.4.2
hypotheses
5.5
for OLS estimation and tests
5.5.1
heteroscedastidty
5.5.2
5.5.2a White s
5.5.2b The
test
5.5.2c The Breusch-Pagan/
Godfrey test
5.5.3
test statistics for
heteroscedasticity
5.6
effects
5.6.1
5.6.1a The Durbin-Watson,
DW, statistic
5.6.1b The Lagrange-
Multiplier (LM) test
for serial correlation
5.6.1c The Box-Pearce
and Ljung-Box
tests
5.6.2
LM tests
5.6.3
test statistics for serial
correlation
5.6.4
of the variance(-covariance)
matrix of
5.7
Bera test
5.7.1
5.7.2
5.8
RESET test
5.8.1
nonlinearity
5.8.2
5.9
coeffidents
5.9.1
5.9.2
tests
5.9.2a Chow s (second) test:
a test for predictive
failure
5.9.2b A forecast
(deterioration) test
5.9.3
5.10
5.11
5.11.1
5.11.2
model
5.11.3
misspecification tests
5.11.3a Serial correlation
5.11.3b Heteroscedastidty
5.11.4
5.11.5
the RESET test
5.11.6
5.11.6a Chow s first test
5.11.6b Chow s second
test: predictive
failure
5.11.7
5.12
Review
Review questions
Chapter
nonstationary univariate
time series models
6.1
6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5
drift
6.2.6
6.2.7
autocorrelations of an AR(1)
process
6.2.8
trend stationary series
6.3
6.3.1
6.3.2
6.3.3 $3
6.3.4
Dickey-Fuller test statistics
6.3.5
statistics on the intercept
and trend
6.3.6
ADF, test
6.4
6.4.1
6.4.2
trended and the mean under
the alternative is nonzero
6.4.3
trended and the mean under
the alternative is zero
6.4.4
6.5
Review
Review questions
Chapter
nonstationary univariate
time series models
7.1
7.2
7.3
selection strategies using ADF test
statistics
7.4
7.4.1
and
7.4.2
(WS)
(1994) 262
7.4.3
of the DF tests
7.5
univariate time series models
7.5.1
series models
7.5.2
hypothesis
7.6
7.7
7.7.1
processes
7.7.2
seasonal process
7.8
7.8.1
to a single structural break
7.8.2
Haldrup
7.8.3
7.9
time series
7.9.1
on nondurables
7.9.2
7.9.3
7.9.4
nonstationarity:
UK employees
7.10
stationary time series
7.11
Review
Review questions
Appendix
Chapter
nonstationarity in
single-equation
regression analysis
8.1
8.2
estimators by simulation
8.2.1
8.2.2
variable
8.2.2a Xt stationary:
white noise
8.2.2b Xt stationary:
an AR(1) process
8.2.3
stochastic varible
8.2.4
8.2.5
8.3
8.3.1
8.3.2
regressions
8.4
the Engle-Granger
8.4.1
approach (the bivariate case)
8.4.2
statistic f~: simulation
332
8.4.3
for critical values
8.4.4
8.4.5
procedure
8.4.6
regression
8.5
error correction models
8.5.1
stage estimation method
8.5.2
correction: an alternative test
statistic for cointegration
8.5.2a Known cointegration
coefficients
8.5.2b Unknown
cointegration
coefficients
8.6
long-run relationship
8.6.1
ECM (the two variable case)
8.6.2
8.6.3
8.6.4
model: alternative
representations
8.7
simulation
8.7.1
ways of estimating the
cointegrating coefficients
8.7.1a Simulation set-up
8.7.2 Simulation
358
8.7.2a
coefficients
359
8.7.2b Distribution of the
t statistics
364
8.8
366
Review
368
Review questions
369
Appendix
372
Chapter
modified OLS estimator
9.1
9.2
9.2.1
and long-run variance
matrices
9.2.1a
processes
9.2.1b First order moving
average process
9.2.1c Decomposition of
the long-run variance
matrix
9.2.2
9.2.2a MA(1) example
9.2.2b AR(1) example
9.3
9.3.1
9.3.1a Contemporaneity
9.3.1b Weak exogeneity
9.3.2
expectation) function and
weak exogeneity
9.4
OLS estimator
9.4.1
endogeneity
9.4.1a A bias correction
9.4.1b An endogeneity
correction
9.4.1c A semi-parametric
approach to
estimating the
corrections
9.4.2
when OLS on the ADL model
is optimal
9.4.3
estimation
9.4.3a The consumption-
income example
9.4.3b Long and short
interest rates
9.4.4
9.4.4a Simulation results:
Phillips and
Hansen (1990) 394
9.4.4b Simulation results:
Hansen
(1990) 395
9.4.4c Simulation results:
Inder (1993) 396
9.5
processes and endogeneity
9.5.1
integrated, no endogeneity
9.5.2
integrated and endogenous
9.5.2a Contemporaneity
9.5.2b Failure of weak
exogeneity
9.5.2c Summary
9.5.3
design parameters: slow
adjustment
9.6
Review
Review questions
PART HI Applications
413
Chapter
10.1
10.2
10.2.1
10.2.2
10.2.3
10.2.4
10.2.5
together
10.2.6
theme: the velocity of
circulation
10.3
German hyperinflation
10.3.1
10.3.2
demand for money
function: background
10.3.3
function: basic
specification
10.3.4
the data
10.3.5
10.3.6
10.3.7
10.4
recent US data
10.4.1
10.4.2
10.4.3
data
10.4.4
10.4.5
10.4.6
10.4.7
performance
10.4.8
Hoffman and
(1991)
and Starr
10.5
Review
Review questions
Chapter
Interest rates
11.1
11.2
11.2.1
11.2.2
interest rate and
continuous compounding
11.2.3
11.3
term structure
11.3.1
the forward rate
11.3.2
11.3.3
policy
11.4
11.4.1
expectations model
11.4.2
11.4.3
data: yields
11.4.4
yields
11.4.5
data: spreads
11.4.6
spreads
11.4.7
equations
11.4.8
perfect foresight spread
11.5
testing the expectations model
11.5.1
11.5.2
tend to indicate rejection?
11.6
Review
Review questions
Chapter
12.1
12.2
12.2.1
12.2.2
and interpretation
12.2.3
of choice?
12.2.4
United States: an early view
12.2.5
Phillips data for
1861-1913 513
12.2.6
12.2.7
Phillips curve,
12.3
12.3.1
(1958)
12.3.2
12.3.3
12.3.4
Friedman curves
12.3.5
reformulation of the
Phillips curve
12.3.6
interpretation
of the importance of
inflation expectations
12.4
augmented Phillips curve (EAPC)
12.4.1
12.4.2
hypothesis: formulation
12.4.3
12.4.4
of the identifying
assumption
12.4.5
adaptive expectations
augmented Phillips
curve
12.4.6
general principles
12.4.7
expectations
12.4.8
(weakly) rational
expectations
12.5
12.5.1
12.5.2
tests
12.5.3
12.5.4
wage/price inflation and
unemployment, United
Kingdom
514
517
518
519
520
522
12.5.5
wage/price inflation and
unemployment, United
States
12.6
Review
Review questions
523
and purchasing
power parity
523 13.1
13.2
13.2.1
13.2.2
525
13.2.3
525
525
13.2.4
526 13.3
527 13.3.1
13.3.2
exchange rate
529 13.3.3
data
13.3.4
root tests
531 13.4
considerations and tests
533 13.4.1
persistence of shocks
533 13.4.2
a panel unit root test
13.4.3
535
536
537 13.5
13.5.1
539 cointegraüng
540 13.5.2
cointegrating regressions
13.5.3
modified ADF test statistic
541 13.5.4
543
545
548
551
553
553
554
555
556
557
558
559
559
560
561
566
572
573
573
576
579
579
580
582
582
13.6
13.6.1
model
13.6.2
with US
13.7
Review
Review questions
PART IV Extensions
597
Chapter
and
14.1
14.2
14.2.1
14.2.2
in the VAR
14.2.3
univariate model
14.2.4
the multivariate model
14.2.5
unit root
14.3
correction models
14.3.1
14.3.2
the existence of
cointegrating vectors
14.3.3
cointegrating vector
14.3.4
14.3.5
the existence of a unit root
and reduced rank of n
14.4
14.4.1
for inference on the
cointegrating rank
14.4.2
and test statistics for testing
the cointegrating rank
(optional)
14.4.3
cointegrating rank
14.4.4
selecting the cointegrating
rank
14.4.5
the VAR for the trace and
Amax statistics
14.4.6
variables
14.5
14.5.1
form error correction
models
14.5.2
cointegrating vectors
14.5.3
restrictions on the
cointegrating vectors
14.5.4
short-run structure
14.6
Review
Review questions
Chapter
multivariate models
involving
15.1
15.2
uncovered interest parity, Johansen
and Juselius
15.2.1
15.2.2
the cointegrating
relationships
15.2.3
cointegrating rank
15.2.4
cointegrating vectors
15.3
States, Dickey and Rossana
15.3.1
cointegrating rank
15.3.2
15.3.3
cointegrating vectors
15.4
Juselius
15.4.1
structure
15.4.2
structure
15.5
United Kingdom, Hendry and
Mizon
15.5.1
cointegrating rank
15.5.2
the cointegrating vectors
and adjustment
coefficients
15.5.3
cointegrating vectors
15.5.4
15.5.5
short-run structure
15.6
valid to model the partial
system?
15.6.1
variables in the VAR
15.6.2
15.6.3
marginal models
15.6.4
weak exogeneity
15.6.5
weak exogeneity
15.7
(1995)
imports in Belgium
15.7.1
cointegrating rank
15.7.2
cointegrating vectors
15.7.3
15.7.4
PVAR, and SECM
15.8
in the United States
15.8.1
choosing the lag length
15.8.2
estimating the cointegrating
rank by the Johansen
method
15.8.3
estimating the cointegrating
rank by the
Information Criterion (SIC)
15.8.4
15.8.5
OLS results
15.8.6
model and parsimonious
encompassing
15.8.7
money, income and the
interest rate
15.9
Review
Review questions
Chapter
hetcroscedasticity:
modelling volatility
16.1
16.2
16.2.1
unconditional variances:
a crucial distinction
16.2.2
16.2.3
16.2.4
ARCH effect look like?
16.3
standard models
16.3.1
16.3.2
16.3.3
16.3.4
in GARCH models
16.4
16.4.1
16.4.2
beats the linear OLS
estimator
16.5
16.5.1
effects
16.5.2
16.6
theme
16.6.1
16.6.1a ABSGARCH
16.6.1b EGARCH
16.6.2
ABSGARCH-M,
EGARCH-M
16.7
ARCH models
16.7.1
16.7.2
impact curve
16.7.3
16.7.3a TheAGARCHand
GJR asymmetric
models
16.7.4
16.8
16.8.1
16.8.2
16.8.3
returns
16.8.4
the returns for Standard
and Poor s
the United States
16.9
Review
Review questions
Appendix
Al
ARCH model
A16.2 Nonnormality
A16.3 Properties of the maximum
likelihood estimators in GARCH
models
A16.4 Practical ARCH/GARCH
Appendix
Al
A2 The f
A3
A4
A5 Critical values of the Durbin-
Watson test
References
Index
|
| any_adam_object | 1 |
| author | Patterson, Kerry D. |
| author_GND | (DE-588)131958070 |
| author_facet | Patterson, Kerry D. |
| author_role | aut |
| author_sort | Patterson, Kerry D. |
| author_variant | k d p kd kdp |
| building | Verbundindex |
| bvnumber | BV013264267 |
| callnumber-first | H - Social Science |
| callnumber-label | HB139 |
| callnumber-raw | HB139 |
| callnumber-search | HB139 |
| callnumber-sort | HB 3139 |
| callnumber-subject | HB - Economic Theory and Demography |
| classification_rvk | QH 237 QH 300 |
| classification_tum | WIR 017f MAT 634f |
| ctrlnum | (OCoLC)44784768 (DE-599)BVBBV013264267 |
| dewey-full | 330.015195 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 330 - Economics |
| dewey-raw | 330.015195 |
| dewey-search | 330.015195 |
| dewey-sort | 3330.015195 |
| dewey-tens | 330 - Economics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV013264267 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T18:42:45Z |
| institution | BVB |
| isbn | 0333802454 0333802462 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009042326 |
| oclc_num | 44784768 |
| open_access_boolean | |
| owner | DE-573 DE-384 DE-19 DE-BY-UBM DE-M49 DE-BY-TUM DE-20 DE-739 DE-521 DE-522 DE-11 DE-188 |
| owner_facet | DE-573 DE-384 DE-19 DE-BY-UBM DE-M49 DE-BY-TUM DE-20 DE-739 DE-521 DE-522 DE-11 DE-188 |
| physical | XXVII, 795 S. graph. Darst. |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Macmillan |
| record_format | marc |
| spelling | Patterson, Kerry D. Verfasser (DE-588)131958070 aut An introduction to applied econometrics a time series approach Kerry Patterson 1. publ. Basingstoke u.a. Macmillan 2000 XXVII, 795 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier This new book is designed for second and final year economics undergraduates taking an introductory or applied course in econometrics. Covering the essential elements of the subject, the author also introduces and explains techniques that are now widely used in applied work. Econometria larpcal Econometrics Ökonometrie (DE-588)4132280-0 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 s Ökonometrie (DE-588)4132280-0 s DE-604 Digitalisierung UBPassau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009042326&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Patterson, Kerry D. An introduction to applied econometrics a time series approach Econometria larpcal Econometrics Ökonometrie (DE-588)4132280-0 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4132280-0 (DE-588)4067486-1 |
| title | An introduction to applied econometrics a time series approach |
| title_auth | An introduction to applied econometrics a time series approach |
| title_exact_search | An introduction to applied econometrics a time series approach |
| title_full | An introduction to applied econometrics a time series approach Kerry Patterson |
| title_fullStr | An introduction to applied econometrics a time series approach Kerry Patterson |
| title_full_unstemmed | An introduction to applied econometrics a time series approach Kerry Patterson |
| title_short | An introduction to applied econometrics |
| title_sort | an introduction to applied econometrics a time series approach |
| title_sub | a time series approach |
| topic | Econometria larpcal Econometrics Ökonometrie (DE-588)4132280-0 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Econometria Econometrics Ökonometrie Zeitreihenanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009042326&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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