Principles of econometrics: theory and applications
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2024]
|
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xvii, 406 Seiten Diagramme |
| ISBN: | 9783031525346 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV049635379 | ||
| 003 | DE-604 | ||
| 005 | 20240517 | ||
| 007 | t | ||
| 008 | 240404s2024 |||| |||| 00||| eng d | ||
| 020 | |a 9783031525346 |9 978-3-031-52534-6 | ||
| 035 | |a (OCoLC)1426285986 | ||
| 035 | |a (DE-599)BVBBV049635379 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-355 |a DE-N2 | ||
| 084 | |a QH 310 |0 (DE-625)141567: |2 rvk | ||
| 100 | 1 | |a Mignon, Valérie |e Verfasser |0 (DE-588)171421817 |4 aut | |
| 245 | 1 | 0 | |a Principles of econometrics |b theory and applications |c Valérie Mignon |
| 264 | 1 | |a Cham |b Springer |c [2024] | |
| 264 | 4 | |c © 2024 | |
| 300 | |a xvii, 406 Seiten |b Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-3-031-52535-3 |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034979114&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034979114 | |
Datensatz im Suchindex
| _version_ | 1809976529476648960 |
|---|---|
| adam_text |
Contents 1 Introductory Developments. 1.1 What Is Econometrics? Some Introductory Examples. 1.1.1 Answers to Many Questions. 1.1.2 The Example of Consumption and Income. 1.1.3 The Answers to the Other Questions Asked. 1.2 Model and Variable. 1.2.1 The Concept of Model. 1.2.2 Different Types of Data. 1 1 1 2 4 7 7 9 Explained Variable/Explanatory Variable . 9 1.2.4 Error Term . 1.3 Statistics Reminders . 1.3.1 Mean. 1.3.2 Variance. Standard Deviation, and Covariance. 1.3.3 Linear Correlation Coefficient. 1.3.4 Empirical Application. 1.4 A Brief Introduction to the Concept of Stationarity. 1.4.1 Stationarity in the Mean. 1.4.2 Stationarity in the
Variance. 1.4.3 Empirical Application: A Study of the Nikkei Index. 1.5 Databases and Software. 1.5.1 Databases. 1.5.2 Econometric Software. Conclusion. The Gist of the Chapter. Further Reading. 10 11 11 11 13 15 17 18 20 21 23 23 25 26 26 26 2 The Simple Regression Model. 2.1 General . 2.1.1 The Linearity Assumption. 2.1.2 Specification of the Simple Regression Model and Properties of the Error Term . 2.1.3 Summary: Specification of the Simple Regression Model. 2.2 The Ordinary Least Squares (OLS)Method. 2.2.1 Objective and Reminder of Hypotheses. 27 27 27 1.2.3 29 32 33 33 xi
xii Contents 2.2.2 The OLS Principle. 2.2.3 The OLS Estimators. 2.2.4 Properties of OLS Estimators. 2.2.5 OLS Estimator of the Variance of the Error Tenn. 2.2.6 Empirical Application. 2.3 Tests on the Regression Parameters. 2.3.1 Determining the Distributions Followed by the OLS Estimators. 53 2.3.2 Tests on the Regression Coefficients. 2.3.3 Empirical Application. 2.4 Analysis of Variance and Coefficient of Determination. 34 35 47 49 50 53 Analysis of Variance (ANOVA). 64 2.4.1 2.4.2 Coefficient of Determination. 2.4.3 Analysis of Variance and Significance Test of the Coefficient ß. 69 2.4.4 Empirical Application. 2.5 Prediction. 2.6 Some Extensions of the Simple Regression Model . 2.6.1 Log-Linear
Model. 2.6.2 Semi-Log Model. 2.6.3 Reciprocal Model. 66 71 72 75 76 77 79 Log-Inverse or Log-Reciprocal Model . SO Conclusion. The Gist of the Chapter. Further Reading. Appendix 2.1: Demonstrations. Appendix 2.2: Normal Distribution and Normality Test. Appendix 2.3: The Maximum Likelihood Method. SI S2 S2 S3 97 100 The Multiple Regression Model. 3.1 Writing the Model in Matrix Form. 3.2 The OLS Estimators . 3.2.1 Assumptions of the Multiple Regression Model . 3.2.2 Estimation of Coefficients. 3.2.3 Properties of OLS Estimators. 3.2.4 Error Variance Estimation. 3.2.5
Example. 3.3 Tests on the Regression Coefficients. 3.3.1 Distribution of Estimators. 3.3.2 Tests on a Regression Coefficient. 3.3.3 Significance Tests of Several Coefficients. 3.4 Analysis of Variance (ANOVA) and Adjusted Coefficient of Determination. 123 3.4.1 Analysis-of-Variance Equation. 3.4.2 Coefficient of Determination. 105 105 107 107 110 112 114 I 14 117 117 11S 120 2.6.4 3 57 61 64 123 125
Contents xïii 3.4.3 Adjusted Coefficient of Determination. 3.4.4 Partial Correlation Coefficient. 3.4.5 Example. 3.5 Some Examples of Cross-Sectional Applications. 3.5.1 Determinants of Crime. 3.5.2 Health Econometrics. 3.5.3 Inequalities and Financial Openness. 3.5.4 Inequality and Voting Behavior. 3.6 Prediction. 3.6.1 Determination of Predicted Value and Prediction Interval. 3.6.2 Example. 3.7 Model Comparison Criteria. 3.7.1 Explanatory Power/Predictive Power of a Model. 3.7.2 Coefficient of Determination and Adjusted Coefficient of Determination. 144 3.7.3 Information Criteria. 3.7.4 The Mallows Criterion . 3.8 Empirical Application . 3.8.1 Practical
Calculation of the OLS Estimators . 3.8.2 Software Estimation. Conclusion. The Gist of the Chapter. Further Reading. Appendix 3.1: Elements of Matrix Algebra. Appendix 3.2: Demonstrations. 4 126 127 128 134 134 135 137 139 140 140 142 143 143 144 146 147 148 150 152 153 153 153 160 Heteroskedasticity and Autocorrelation of Errors. 171 4.1 172 4.2 4.3 The Generalized Least Squares (GLS) Estimators. 4.1.1 Properties of OLS Estimators in the Presence of Autocorrelation and/or Heteroskedasticity. 172 4.1.2 The Generalized Least Squares (GLS) Method. 4.1.3 Estimation of the Variance of the Errors. Heteroskedasticity of Errors. 4.2.1 The Sources of Heteroskedasticity. 4.2.2 Estimation When There Is Heteroskedasticity . 4.2.3 Detecting Heteroskedasticity. 4.2.4 Estimation Procedures When There Is Heteroskedasticity
. 4.2.5 Empirical Application. Autocorrelation of Errors. 4.3.1 Sources of Autocorrelation. 4.3.2 Estimation When There Is Autocorrelation . 4.3.3 Detecting Autocorrelation. 4.3.4 Estimation Procedures in the Presence of Error Autocorrelation. 211 4.3.5 Prediction in the Presence of Error Autocorrelation. 173 175 176 176 177 178 186 189 194 194 198 201 216
xiv 5 6 Contents 4.3.6 Empirical Application. Conclusion. The Gist of the Chapter. Further Reading. 217 220 221 221 Problems with Explanatory Variables. 5.1 Random Explanatory Variables and the Instrumental Variables Method. 223 5.1.1 Instrumental Variables Estimator. 5.1.2 The Hausman (1978) Specification Test. 5.1.3 Application Example: Measurement Error. 5.2 Multicollinearity and Variable Selection. 5.2.1 Presentation of the Problem. 5.2.2 The Effects of Multicollinearity. 5.2.3 Detecting Multicollinearity. 5.2.4 Solutions to Multicollinearity . 5.2.5 Variable Selection Methods. 5.3 Structural Changes and Indicator Variables. 5.3.1 The Constrained Least
Squares Method. 5.3.2 The Introduction of Indicator Variables . 5.3.3 Coefficient Stability Tests. Conclusion. The Gist of the Chapter. Further Reading. Appendix: Demonstration of the Formula for Constrained Least Squares Estimator. 263 223 Distributed Lag Models. 6.1 Why Introduce Lags? Some Examples. 6.2 General Formulation and Definitions of Distributed Lag Models. 268 6.3 Determination of the Number of Lags and Estimation. 6.3.1 Determination of the Number of Lags. 6.3.2 The Question of Estimating Distributed Lag Models. 6.4 Finite Distributed Lag Models: Almon Lag Models . 6.5 Infinite Distributed Lag Models. 265 265 The Koyck Approach . 273 6.5.2 The Pascal Approach
. 6.6 Autoregressive Distributed Lag Models. 6.6.1 Writing the ARDL Model. 6.6.2 Calculation of ARDL Model Weights . 6.7 Empirical Application . Conclusion. The Gist of the Chapter. Further Reading. 279 281 281 282 283 285 285 285 6.5.1 224 226 226 228 228 229 231 236 238 241 242 243 251 261 262 262 270 270 271 271 273
Contents 7 An Introduction to Time Series Models. 287 Some Definitions. 7.1.1 Time Series. 7.1.2 Second-Order Stationarity. 7.1.3 Autocovariance Function, Autocorrelation Function, and Partial Autocorrelation Function. 289 7.2 Stationarity. Autocorrelation Function and Unit Root Test. 7.2.1 Study of the Autocorrelation Function. 7.2.2 TS and DS Processes. 7.2.3 The Dickey-Fuller Test. 7.3 ARMA Processes. 7.3.1 Definitions . 7.3.2 The Box and Jenkins Methodology. 7.3.3 Empirical Application. 7.4 Extension to the Multivariate Case: VAR Processes. 7.4.1 Writing the Model. 7.4.2 Estimation of the Parameters of a VAR(p) Process and Validation. 329 7.4.3 Forecasting VAR
Processes. 7.4.4 Granger Causality . 7.4.5 Empirical Application. 7.5 Cointegration and Error-Correction Models. 7.5.1 The Problem of Spurious Regressions. 7.5.2 The Concept of Cointegration. 7.5.3 Error-Correction Models. 7.5.4 Estimation of Error-CorrectionModels and Cointegration Tests: The Engle and Granger (1987) Approach. 7.5.5 Empirical Application. Conclusion. The Gist of the Chapter. Further Reading. 7.1 8 XV Simultaneous Equations Models. The Analytical Framework. 8.1.1 Introductory Example . 8.1.2 General Form of Simultaneous EquationsModels . 8.2 The Identification
Problem. 8.2.1 Problem Description. 8.2.2 Rank and Order Conditions for Identification. 8.3 Estimation Methods. 8.3.1 Indirect Least Squares. 8.3.2 Two-Stage Least Squares. 8.3.3 Full-Information Methods. 8.4 Specification Test. 8.1 287 287 289 293 293 297 302 312 313 317 321 327 327 330 331 332 336 336 338 339 340 344 348 348 349 351 351 353 355 357 357 358 362 363 363 365 367
xvi Contents 8.5 Empirical Application . 8.5.1 Writing the Model. 8.5.2 Conditions for Identification . 8.5.3 Data. 8.5.4 Model Estimation. Conclusion. The Gist of the Chapter. Further Reading. 368 368 364 370 370 376 377 377 Appendix: Statistical Tables. 379 References. 395 Index. 401 |
| adam_txt | |
| any_adam_object | 1 |
| any_adam_object_boolean | |
| author | Mignon, Valérie |
| author_GND | (DE-588)171421817 |
| author_facet | Mignon, Valérie |
| author_role | aut |
| author_sort | Mignon, Valérie |
| author_variant | v m vm |
| building | Verbundindex |
| bvnumber | BV049635379 |
| classification_rvk | QH 310 |
| ctrlnum | (OCoLC)1426285986 (DE-599)BVBBV049635379 |
| discipline | Wirtschaftswissenschaften |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV049635379</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240517</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">240404s2024 |||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783031525346</subfield><subfield code="9">978-3-031-52534-6</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1426285986</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049635379</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-N2</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 310</subfield><subfield code="0">(DE-625)141567:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mignon, Valérie</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)171421817</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Principles of econometrics</subfield><subfield code="b">theory and applications</subfield><subfield code="c">Valérie Mignon</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer</subfield><subfield code="c">[2024]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xvii, 406 Seiten</subfield><subfield code="b">Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-3-031-52535-3</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Regensburg - ADAM Catalogue Enrichment</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034979114&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034979114</subfield></datafield></record></collection> |
| id | DE-604.BV049635379 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:38:56Z |
| indexdate | 2024-09-12T08:02:09Z |
| institution | BVB |
| isbn | 9783031525346 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034979114 |
| oclc_num | 1426285986 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-N2 |
| owner_facet | DE-355 DE-BY-UBR DE-N2 |
| physical | xvii, 406 Seiten Diagramme |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | Springer |
| record_format | marc |
| spelling | Mignon, Valérie Verfasser (DE-588)171421817 aut Principles of econometrics theory and applications Valérie Mignon Cham Springer [2024] © 2024 xvii, 406 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Erscheint auch als Online-Ausgabe 978-3-031-52535-3 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=034979114&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mignon, Valérie Principles of econometrics theory and applications |
| title | Principles of econometrics theory and applications |
| title_auth | Principles of econometrics theory and applications |
| title_exact_search | Principles of econometrics theory and applications |
| title_exact_search_txtP | Principles of econometrics theory and applications |
| title_full | Principles of econometrics theory and applications Valérie Mignon |
| title_fullStr | Principles of econometrics theory and applications Valérie Mignon |
| title_full_unstemmed | Principles of econometrics theory and applications Valérie Mignon |
| title_short | Principles of econometrics |
| title_sort | principles of econometrics theory and applications |
| title_sub | theory and applications |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=034979114&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT mignonvalerie principlesofeconometricstheoryandapplications |