Introduction to econometrics:
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Andover
Cengage Learning
2014
|
| Edition: | Europe, Middle East and Africa ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVIII, 603 S. graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 9781408093757 |
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| 020 | |a 9781408093757 |c pbk. |9 978-1-4080-9375-7 | ||
| 035 | |a (OCoLC)873442081 | ||
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| 100 | 1 | |a Wooldridge, Jeffrey M. |d 1960- |e Verfasser |0 (DE-588)131680463 |4 aut | |
| 245 | 1 | 0 | |a Introduction to econometrics |c Jeffrey M. Wooldridge |
| 250 | |a Europe, Middle East and Africa ed. | ||
| 264 | 1 | |a Andover |b Cengage Learning |c 2014 | |
| 300 | |a XVIII, 603 S. |b graph. Darst. |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-027068790 | |
Record in the Search Index
| DE-BY-862_location | 2000 |
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| DE-BY-FWS_katkey | 507379 |
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| adam_text |
BRIEF
CONTENTS
IMISMM
MM
I**I
CHAPTER
1
THE
NATURE
OF
ECONOMETRICS
AND
ECONOMIC
DATA
1
PART
1:
REGRESSION
ANALYSIS
WITH
CROSS-SECTIONAL
DATA
17
CHAPTER
2
THE
SIMPLE
REGRESSION
MODEL
18
CHAPTER
3
MULTIPLE
REGRESSION
ANALYSIS:
ESTIMATION
56
CHAPTER
4
MULTIPLE
REGRESSION
ANALYSIS:
INFERENCE
94
CHAPTER
5
MULTIPLE
REGRESSION
ANALYSIS:
OLS
ASYMPTOTICS
135
CHAPTER
6
MULTIPLE
REGRESSION
ANALYSIS:
FURTHER
ISSUES
150
CHAPTER
7
MULTIPLE
REGRESSION
ANALYSIS
WITH
QUALITATIVE
INFORMATION:
BINARY
(OR
DUMMY)
VARIABLES
182
CHAPTER
8
HETEROSKEDASTICITY
212
CHAPTER
9
MORE
ON
SPECIFICATION
AND
DATA
ISSUES
241
PART
2:
REGRESSION
ANALYSIS
WITH
TIME
SERIES
DATA
273
CHAPTER
10
BASIC
REGRESSION
ANALYSIS
WITH
TIME
SERIES
DATA
274
CHAPTER
11
FURTHER
ISSUES
IN
USING
OLS
WITH
TIME
SERIES
DATA
305
CHAPTER
12
SERIAL
CORRELATION
AND
HETEROSKEDASTICITY
IN
TIME
SERIES
REGRESSIONS
330
PART
3:
ADVANCED
TOPICS
359
CHAPTER
13
POOLING
CROSS
SECTIONS
ACROSS
TIME:
SIMPLE
PANEL
DATA
METHODS
360
CHAPTER
14
ADVANCED
PANEL
DATA
METHODS
387
CHAPTER
15
INSTRUMENTAL
VARIABLES
ESTIMATION
AND
TWO
STAGE
LEAST
SQUARES
405
CHAPTER
16
SIMULTANEOUS
EQUATIONS
MODELS
437
CHAPTER
17
LIMITED
DEPENDENT
VARIABLE
MODELS
AND
SAMPLE
SELECTION
CORRECTIONS
459
CHAPTER
18
ADVANCED
TIME
SERIES
TOPICS
498
CHAPTER
19
CARRYING
OUT
AN
EMPIRICAL
PROJECT
535
REFERENCES
561
GLOSSARY
567
INDEX
585
R-
1
1
*J
TJ
PREFACE
XI
ABOUT
THE
AUTHOR
XVIII
CHAPTER
1
THE
NATURE
OF
ECONOMETRICS
AND
ECONOMIC
DATA
1
1.1
WHAT
IS
ECONOMETRICS?
1
1.2
STEPS
IN
EMPIRICAL
ECONOMIC
ANALYSIS
2
1.3
THE
STRUCTURE
OF
ECONOMIC
DATA
5
CROSS-SECTIONAL
DATA
5
TIME
SERIES
DATA
8
POOLED
CROSS
SECTIONS
9
PANEL
OR
LONGITUDINAL
DATA
10
A
COMMENT
ON
DATA
STRUCTURES
11
1.4
CAUSALITY
AND
THE
NOTION
OF
CETERIS
PARIBUS
IN
ECONOMETRIC
ANALYSIS
12
SUMMARY
16
PART
1
REGRESSION
ANALYSIS
WITH
CROSS-SECTIONAL
DATA
17
CHAPTER
2
THE
SIMPLE
REGRESSION
MODEL
18
2.1
DEFINITION
OF
THE
SIMPLE
REGRESSION
MODEL
18
2.2
DERIVING
THE
ORDINARY
LEAST
SQUARES
ESTIMATES
23
A
NOTE
ON
TERMINOLOGY
30
2.3
PROPERTIES
OF
OLS
ON
ANY
SAMPLE
OF
DATA
31
FITTED
VALUES
AND
RESIDUALS
31
ALGEBRAIC
PROPERTIES
OF
OLS
STATISTICS
32
GOODNESS-OF-FIT
34
2.4
UNITS
OF
MEASUREMENT
AND
FUNCTIONAL
FORM
35
THE
EFFECTS
OF
CHANGING
UNITS
OF
MEASUREMENT
ON
OLS
STATISTICS
36
INCORPORATING
NONLINEARITIES
IN
SIMPLE
REGRESSION
37
THE
MEANING
OF
*LINEAR*
REGRESSION
40
2.5
EXPECTED
VALUES
AND
VARIANCES
OF
THE
OLS
ESTIMATORS
41
UNBIASEDNESS
OF
OLS
41
VARIANCES
OF
THE
OLS
ESTIMATORS
46
ESTIMATING
THE
ERROR
VARIANCE
50
2.6
REGRESSION
THROUGH
THE
ORIGIN
AND
REGRESSION
ON
A
CONSTANT
53
SUMMARY
54
CHAPTER
3
MULTIPLE
REGRESSION
ANALYSIS:
ESTIMATION
56
3.1
MOTIVATION
FOR
MULTIPLE
REGRESSION
57
THE
MODEL
WITH
TWO
INDEPENDENT
VARIABLES
57
THE
MODEL
WITH
K
INDEPENDENT
VARIABLES
59
3.2
MECHANICS
AND
INTERPRETATION
OF
ORDINARY
LEAST
SQUARES
60
OBTAINING
THE
OLS
ESTIMATES
60
INTERPRETING
THE
OLS
REGRESSION
EQUATION
62
ON
THE
MEANING
OF
*HOLDING
OTHER
FACTORS
FIXED"
IN
MULTIPLE
REGRESSION
64
CHANGING
MORE
THAN
ONE
INDEPENDENT
VARIABLE
SIMULTANEOUSLY
65
OLS
FITTED
VALUES
AND
RESIDUALS
65
A
*
PARTIALLING
OUT*
INTERPRETATION
OF
MULTIPLE
REGRESSION
66
COMPARISON
OF
SIMPLE
AND
MULTIPLE
REGRESSION
ESTIMATES
66
GOODNESS-OF-FIT
68
REGRESSION
THROUGH
THE
ORIGIN
69
VI
CONTENTS
3.3
THE
EXPECTED
VALUE
OF
THE
OLS
ESTIMATORS
71
INCLUDING
IRRELEVANT
VARIABLES
IN
A
REGRESSION
MODEL
76
OMITTED
VARIABLE
BIAS:
THE
SIMPLE
CASE
76
OMITTED
VARIABLE
BIAS:
MORE
GENERAL
CASES
19
3.4
THE
VARIANCE
OF
THE
OLS
ESTIMATORS
81
THE
COMPONENTS
OF
THE
OLS
VARIANCES:
MULTICOLLINEARITY
82
VARIANCES
IN
MISSPECIFIED
MODELS
86
ESTIMATING
A
2
:
STANDARD
ERRORS
OF
THE
OLS
ESTIMATORS
87
3.5
EFFICIENCY
OF
OLS:
THE
GAUSS-MARKOV
THEOREM
89
3.6
SOME
COMMENTS
ON
THE
LANGUAGE
OF
MULTIPLE
REGRESSION
ANALYSIS
91
SUMMARY
92
CHAPTER
4
MULTIPLE
REGRESSION
ANALYSIS:
INFERENCE
94
4.1
SAMPLING
DISTRIBUTIONS
OF
THE
OLS
ESTIMATORS
94
4.2
TESTING
HYPOTHESES
ABOUT
A
SINGLE
POPULATION
PARAMETER:
THE
T
TEST
97
TESTING
AGAINST
ONE-SIDED
ALTERNATIVES
99
TWO-SIDED
ALTERNATIVES
104
TESTING
OTHER
HYPOTHESES
ABOUT
(3J
106
COMPUTING
P-VALUESFORT
TESTS
109
A
REMINDER
ON
THE
LANGUAGE
OF
CLASSICAL
HYPOTHESIS
TESTING
III
ECONOMIC,
OR
PRACTICAL,
VERSUS
STATISTICAL
SIGNIFICANCE
III
4.3
CONFIDENCE
INTERVALS
114
4.4
TESTING
HYPOTHESES
ABOUT
A
SINGLE
LINEAR
COMBINATION
OF
THE
PARAMETERS
11
6
4.5
TESTING
MULTIPLE
LINEAR
RESTRICTIONS:
THE
F
TEST
119
TESTING
EXCLUSION
RESTRICTIONS
119
RELATIONSHIP
BETWEEN
F
AND
T
STATISTICS
25
THE
R
-SQUARED
FORM
OF
THE
F
STATISTIC
126
COMPUTING
P-VALUES
FOR
F
TESTS
127
THE
F
STATISTIC
FOR
OVERALL
SIGNIFICANCE
OF
A
REGRESSION
/
28
TESTING
GENERAL
LINEAR
RESTRICTIONS
129
4.6
REPORTING
REGRESSION
RESULTS
130
SUMMARY
133
CHAPTER
5
MULTIPLE
REGRESSION
ANALYSIS:
OLS
ASYMPTOTICS
135
5.1
CONSISTENCY
136
DERIVING
THE
INCONSISTENCY
IN
OLS
39
5.2
ASYMPTOTIC
NORMALITY
AND
LARGE
SAMPLE
INFERENCE
140
OTHER
LARGE
SAMPLE
TESTS:
THE
LAGRANGE
MULTIPLIER
STATISTIC
145
5.3
ASYMPTOTIC
EFFICIENCY
OF
OLS
148
SUMMARY
149
CHAPTER
6
MULTIPLE
REGRESSION
ANALYSIS:
FURTHER
ISSUES
150
6.1
EFFECTS
OF
DATA
SCALING
ON
OLS
STATISTICS
150
BETA
COEFFICIENTS
153
6.2
MORE
ON
FUNCTIONAL
FORM
155
MORE
ON
USING
LOGARITHMIC
FUNCTIONAL
FORMS
155
MODELS
WITH
QUADRATICS
158
MODELS
WITH
INTERACTION
TERMS
162
6.3
MORE
ON
GOODNESS-OF-FIT
AND
SELECTION
OF
REGRESSORS
164
ADJUSTED
R-SQUARED
166
USING
ADJUSTED
R
-SQUARED
TO
CHOOSE
BETWEEN
NONNESTED
MODELS
167
CONTROLLING
FOR
TOO
MANY
FACTORS
IN
REGRESSION
ANALYSIS
169
ADDING
REGRESSORS
TO
REDUCE
THE
ERROR
VARIANCE
170
6.4
PREDICTION
AND
RESIDUAL
ANALYSIS
171
CONFIDENCE
INTERVALS
FOR
PREDICTIONS
171
RESIDUAL
ANALYSIS
175
PREDICTING
Y
WHEN
LOGIY)
IS
THE
DEPENDENT
VARIABLE
176
SUMMARY
180
CHAPTER
7
MULTIPLE
REGRESSION
ANALYSIS
WITH
QUALITATIVE
INFORMATION:
BINARY
(OR
DUMMY)
VARIABLES
182
7.1
DESCRIBING
QUALITATIVE
INFORMATION
182
7.2
A
SINGLE
DUMMY
INDEPENDENT
VARIABLE
183
INTERPRETING
COEFFICIENTS
ON
DUMMY
EXPLANATORY
VARIABLES
WHEN
THE
DEPENDENT
VARIABLE
IS
LOG(Y)
188
CONTENTS
VII
7.3
USING
DUMMY
VARIABLES
FOR
MULTIPLE
CATEGORIES
190
INCORPORATING
ORDINAL
INFORMATION
BY
USING
DUMMY
VARIABLES
192
7A
INTERACTIONS
INVOLVING
DUMMY
VARIABLES
195
INTERACTIONS
AMONG
DUMMY
VARIABLES
195
ALLOWING
FOR
DIFFERENT
SLOPES
196
TESTING
FOR
DIFFERENCES
IN
REGRESSION
FUNCTIONS
ACROSS
GROUPS
199
7.5
A
BINARY
DEPENDENT
VARIABLE:
THE
LINEAR
PROBABILITY
MODEL
202
7.6
MORE
ON
POLICY
ANALYSIS
AND
PROGRAMME
EVALUATION
207
7.7
INTERPRETING
REGRESSION
RESULTS
WITH
DISCRETE
DEPENDENT
VARIABLES
209
SUMMARY
211
CHAPTER
8
HETEROSKEDASTICITY
212
8.1
CONSEQUENCES
OF
HETEROSKEDASTICITY
FOROLS
212
8.2
HETEROSKEDASTICITY-ROBUST
INFERENCE
AFTER
OLS
ESTIMATION
213
COMPUTING
HETEROSKEDASTICITY-ROBUST
LM
TESTS
218
8.3
TESTING
FOR
HETEROSKEDASTICITY
219
THE
WHITE
TEST
FOR
HETEROSKEDASTICITY
223
8.4
WEIGHTED
LEAST
SQUARES
ESTIMATION
224
THE
HETEROSKEDASTICITY
IS
KNOWN
UP
TO
A
MULTIPLICATIVE
CONSTANT
225
THE
HETEROSKEDASTICITY
FUNCTION
MUST
BE
ESTIMATED:
FEASIBLE
GLS
230
WHAT
IF
THE
ASSUMED
HETEROSKEDASTICITY
FUNCTION
IS
WRONG?
234
PREDICTION
AND
PREDICTION
INTERVALS
WITH
HETEROSKEDASTICITY
236
8.5
THE
LINEAR
PROBABILITY
MODEL
REVISITED
238
SUMMARY
240
CHAPTER
9
MORE
ON
SPECIFICATION
AND
DATA
ISSUES
241
9.1
FUNCTIONAL
FORM
MISSPECIFICATION
242
RESET
AS
A
GENERAL
TEST
FOR
FUNCTIONAL
FORM
MISSPECIFICATION
244
TESTS
AGAINST
NONNESTED
ALTERNATIVES
245
9.2
USING
PROXY
VARIABLES
FOR
UNOBSERVED
EXPLANATORY
VARIABLES
246
USING
LAGGED
DEPENDENT
VARIABLES
AS
PROXY
VARIABLES
251
A
DIFFERENT
SLANT
ON
MULTIPLE
REGRESSION
252
9.3
MODELS
WITH
RANDOM
SLOPES
253
9.4
PROPERTIES
OF
OLS
UNDER
MEASUREMENT
ERROR
255
MEASUREMENT
ERROR
IN
THE
DEPENDENT
VARIABLE
256
MEASUREMENT
ERROR
IN
AN
EXPLANATORY
VARIABLE
258
9.5
MISSING
DATA,
NONRANDOM
SAMPLES,
AND
OUTLYING
OBSERVATIONS
262
MISSING
DATA
262
NONRANDOM
SAMPLES
262
OUTLIERS
AND
INFLUENTIAL
OBSERVATIONS
264
9.6
LEAST
ABSOLUTE
DEVIATIONS
ESTIMATION
269
SUMMARY
272
PART
2
REGRESSION
ANALYSIS
WITH
TIME
SERIES
DATA
273
CHAPTER
10
BASIC
REGRESSION
ANALYSIS
WITH
TIME
SERIES
DATA
274
10.1
THE
NATURE
OF
TIME
SERIES
DATA
274
10.2
EXAMPLES
OF
TIME
SERIES
REGRESSION
MODELS
275
STATIC
MODELS
276
FINITE
DISTRIBUTED
LAG
MODELS
276
A
CONVENTION
ABOUT
THE
TIME
INDEX
279
10.3
FINITE
SAMPLE
PROPERTIES
OF
OLS
UNDER
CLASSICAL
ASSUMPTIONS
279
UNBIASEDNESS
OF
OLS
279
THE
VARIANCES
OF
THE
OLS
ESTIMATORS
AND
THE
GAUSS-MARKOV
THEOREM
282
INFERENCE
UNDER
THE
CLASSICAL
LINEAR
MODEL
ASSUMPTIONS
285
10.4
FUNCTIONAL
FORM,
DUMMY
VARIABLES,
AND
INDEX
NUMBERS
286
10.5
TRENDS
AND
SEASONALITY
293
CHARACTERISING
TRENDING
TIME
SERIES
293
USING
TRENDING
VARIABLES
IN
REGRESSION
ANALYSIS
296
VLIL
CONTENTS
A
DETRENDING
INTERPRETATION
OF
REGRESSIONS
WITH
A
TIME
TREND
298
COMPUTING
R-SQUARED
WHEN
THE
DEPENDENT
VARIABLE
IS
TRENDING
300
SEASONALITY
301
SUMMARY
303
CHAPTER
11
FURTHER
ISSUES
IN
USING
OLS
WITH
TIME
SERIES
DATA
305
11.1
STATIONARY
AND
WEAKLY
DEPENDENT
TIME
SERIES
306
STATIONARY
AND
NONSTATIONARY
TIME
SERIES
306
WEAKLY
DEPENDENT
TIME
SERIES
307
11.2
ASYMPTOTIC
PROPERTIES
OF
OLS
309
11.3
USING
HIGHLY
PERSISTENT
TIME
SERIES
IN
REGRESSION
ANALYSIS
316
HIGHLY
PERSISTENT
TIME
SERIES
316
TRANSFORMATIONS
ON
HIGHLY
PERSISTENT
TIME
SERIES
320
DECIDING
WHETHER
A
TIME
SERIES
IS
1(1)
321
11.4
DYNAMICALLY
COMPLETE
MODELS
AND
THE
ABSENCE
OF
SERIAL
CORRELATION
324
11.5
THE
HOMOSKEDASTICITY
ASSUMPTION
FOR
TIME
SERIES
MODELS
327
SUMMARY
327
CHAPTER
12
SERIAL
CORRELATION
AND
HETEROSKEDASTICITY
IN
TIME
SERIES
REGRESSIONS
330
12.1
PROPERTIES
OF
OLS
WITH
SERIALLY
CORRELATED
ERRORS
330
UNBIASEDNESS
AND
CONSISTENCY
330
EFFICIENCY
AND
INFERENCE
331
GOODNESS-OF-FIT
332
SERIAL
CORRELATION
IN
THE
PRESENCE
OF
LAGGED
DEPENDENT
VARIABLES
333
12.2
TESTING
FOR
SERIAL
CORRELATION
334
A
T
TEST
FOR
AR(
I)
SERIAL
CORRELATION
WITH
STRICTLY
EXOGENOUS
REGRESSORS
334
THE
DURBIN-WATSON
TEST
UNDER
CLASSICAL
ASSUMPTIONS
336
TESTING
FOR
AR(
1)
SERIAL
CORRELATION
WITHOUT
STRICTLY
EXOGENOUS
REGRESSORS
338
TESTING
FOR
HIGHER
ORDER
SERIAL
CORRELATION
339
12.3
CORRECTING
FOR
SERIAL
CORRELATION
WITH
STRICTLY
EXOGENOUS
REGRESSORS
341
OBTAINING
THE
BEST
LINEAR
UNBIASED
ESTIMATOR
IN
THE
AR(1)
MODEL
341
FEASIBLE
GLS
ESTIMATION
WITH
AR(L)
ERRORS
343
COMPARING
OLS
AND
FGLS
345
CORRECTING
FOR
HIGHER
ORDER
SERIAL
CORRELATION
346
12.4
DIFFERENCING
AND
SERIAL
CORRELATION
347
12.5
SERIAL
CORRELATION-ROBUST
INFERENCE
AFTER
OLS
349
12.6
HETEROSKEDASTICITY
IN
TIME
SERIES
REGRESSIONS
352
HETEROSKEDASTICITY-ROBUST
STATISTICS
353
TESTING
FOR
HETEROSKEDASTICITY
353
AUTOREGRESSIVE
CONDITIONAL
HETEROSKEDASTICITY
354
HETEROSKEDASTICITY
AND
SERIAL
CORRELATION
IN
REGRESSION
MODELS
356
SUMMARY
357
PART
3
ADVANCED
TOPICS
359
CHAPTER
13
POOLING
CROSS
SECTIONS
ACROSS
TIME:
SIMPLE
PANEL
DATA
METHODS
360
13.1
POOLING
INDEPENDENT
CROSS
SECTIONS
ACROSS
TIME
361
THE
CHOW
TEST
FOR
STRUCTURAL
CHANGE
ACROSS
TIME
365
13.2
POLICY
ANALYSIS
WITH
POOLED
CROSS
SECTIONS
366
13.3
TWO-PERIOD
PANEL
DATA
ANALYSIS
371
ORGANISING
PANEL
DATA
377
13.4
POLICY
ANALYSIS
WITH
TWO-PERIOD
PANEL
DATA
377
13.5
DIFFERENCING
WITH
MORE
THAN
TWO
TIME
PERIODS
380
POTENTIAL
PITFALLS
IN
FIRST
DIFFERENCING
PANEL
DATA
385
SUMMARY
386
CONTENTS
IX
CHAPTER
14
ADVANCED
PANEL
DATA
METHODS
387
14.1
FIXED
EFFECTS
ESTIMATION
387
THE
DUMMY
VARIABLE
REGRESSION
391
FIXED
EFFECTS
OR
FIRST
DIFFERENCING
?
392
FIXED
EFFECTS
WITH
UNBALANCED
PANELS
394
14.2
RANDOM
EFFECTS
MODELS
395
RANDOM
EFFECTS
OR
FIXED
EFFECTS?
398
14.3
THE
CORRELATED
RANDOM
EFFECTS
APPROACH
400
14.4
APPLYING
PANEL
DATA
METHODS
TO
OTHER
DATA
STRUCTURES
402
SUMMARY
404
CHAPTER
15
INSTRUMENTAL
VARIABLES
ESTIMATION
AND
TWO
STAGE
LEAST
SQUARES
405
15.1
MOTIVATION:
OMITTED
VARIABLES
IN
A
SIMPLE
REGRESSION
MODEL
406
STATISTICAL
INFERENCE
WITH
THE
IV
ESTIMATOR
410
PROPERTIES
OF
IV
WITH
A
POOR
INSTRUMENTAL
VARIABLE
414
COMPUTING
R-SQUARED
AFTER
IV
ESTIMATION
416
15.2
IV
ESTIMATION
OF
THE
MULTIPLE
REGRESSION
MODEL
417
15.3
TWO
STAGE
LEAST
SQUARES
421
A
SINGLE
ENDOGENOUS
EXPLANATORY
VARIABLE
421
MUITICOLLINEARITY
AND
2SLS
423
MULTIPLE
ENDOGENOUS
EXPLANATORY
VARIABLES
424
TESTING
MULTIPLE
HYPOTHESES
AFTER
2SLS
ESTIMATION
424
15.4
IV
SOLUTIONS
TO
ERRORS-IN-VARIABLES
PROBLEMS
425
15.5
TESTING
FOR
ENDOGENEITY
AND
TESTING
OVERIDENTIFYING
RESTRICTIONS
427
TESTING
FOR
ENDOGENEITY
427
TESTING
OVERIDENTIFICATION
RESTRICTIONS
428
15.6
2SLS
WITH
HETEROSKEDASTICITY
431
15.7
APPLYING
2SLS
TO
TIME
SERIES
EQUATIONS
431
15.8
APPLYING
2SLS
TO
POOLED
CROSS
SECTIONS
AND
PANEL
DATA
433
SUMMARY
435
CHAPTER
16
SIMULTANEOUS
EQUATIONS
MODELS
437
16.1
THE
NATURE
OF
SIMULTANEOUS
EQUATIONS
MODELS
438
16.2
SIMULTANEITY
BIAS
IN
OLS
441
16.3
IDENTIFYING
AND
ESTIMATING
A
STRUCTURAL
EQUATION
443
IDENTIFICATION
IN
A
TWO-EQUATION
SYSTEM
443
ESTIMATION
BY
2SLS
448
16.4
SYSTEMS
WITH
MORE
THAN
TWO
EQUATIONS
450
IDENTIFICATION
IN
SYSTEMS
WITH
THREE
OR
MORE
EQUATIONS
450
ESTIMATION
451
16.5
SIMULTANEOUS
EQUATIONS
MODELS
WITH
TIME
SERIES
451
16.6
SIMULTANEOUS
EQUATIONS
MODELS
WITH
PANEL
DATA
455
SUMMARY
457
CHAPTER
17
LIMITED
DEPENDENT
VARIABLE
MODELS
AND
SAMPLE
SELECTION
CORRECTIONS
459
17.1
LOGIT
AND
PROBIT
MODELS
FOR
BINARY
RESPONSE
460
SPECIFYING
LOGIT
AND
PROBIT
MODELS
460
MAXIMUM
LIKELIHOOD
ESTIMATION
OF
LOGIT
AND
PROBIT
MODELS
463
TESTING
MULTIPLE
HYPOTHESES
464
INTERPRETING
THE
LOGIT
AND
PROBIT
ESTIMATES
465
17.2
THE
TOBIT
MODEL
FOR
CORNER
SOLUTION
RESPONSES
472
INTERPRETING
THE
TOBIT
ESTIMATES
474
SPECIFICATION
ISSUES
IN
TOBIT
MODELS
479
17.3
THE
POISSON
REGRESSION
MODEL
480
17.4
CENSORED
AND
TRUNCATED
REGRESSION
MODELS
485 |
| any_adam_object | 1 |
| author | Wooldridge, Jeffrey M. 1960- |
| author_GND | (DE-588)131680463 |
| author_facet | Wooldridge, Jeffrey M. 1960- |
| author_role | aut |
| author_sort | Wooldridge, Jeffrey M. 1960- |
| author_variant | j m w jm jmw |
| building | Verbundindex |
| bvnumber | BV041627821 |
| classification_rvk | QH 300 QH 310 |
| classification_tum | WIR 017f |
| ctrlnum | (OCoLC)873442081 (DE-599)BVBBV041627821 |
| discipline | Wirtschaftswissenschaften |
| edition | Europe, Middle East and Africa ed. |
| format | Book |
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| genre_facet | Lehrbuch |
| id | DE-604.BV041627821 |
| illustrated | Illustrated |
| indexdate | 2025-02-20T07:15:36Z |
| institution | BVB |
| isbn | 9781408093757 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027068790 |
| oclc_num | 873442081 |
| open_access_boolean | |
| owner | DE-521 DE-945 DE-1043 DE-1047 DE-19 DE-BY-UBM DE-706 DE-20 DE-188 DE-355 DE-BY-UBR DE-M49 DE-BY-TUM DE-862 DE-BY-FWS |
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| physical | XVIII, 603 S. graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Cengage Learning |
| record_format | marc |
| spellingShingle | Wooldridge, Jeffrey M. 1960- Introduction to econometrics Ökonometrie (DE-588)4132280-0 gnd |
| subject_GND | (DE-588)4132280-0 (DE-588)4123623-3 |
| title | Introduction to econometrics |
| title_auth | Introduction to econometrics |
| title_exact_search | Introduction to econometrics |
| title_full | Introduction to econometrics Jeffrey M. Wooldridge |
| title_fullStr | Introduction to econometrics Jeffrey M. Wooldridge |
| title_full_unstemmed | Introduction to econometrics Jeffrey M. Wooldridge |
| title_short | Introduction to econometrics |
| title_sort | introduction to econometrics |
| topic | Ökonometrie (DE-588)4132280-0 gnd |
| topic_facet | Ökonometrie Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027068790&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT wooldridgejeffreym introductiontoeconometrics |
Indexes
Sonderstandort Fakultät
| Call Number: |
2000 QH 300 W913 |
|---|---|
| Copy 1 | nicht ausleihbar Checked out – Due: 31.12.2099 Recall This |