Applied nonparametric econometrics:
The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2015
|
| Links: | https://doi.org/10.1017/CBO9780511845765 |
| Summary: | The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls. |
| Physical Description: | 1 Online-Ressource (xii, 367 Seiten) |
| ISBN: | 9780511845765 |
Staff View
MARC
| LEADER | 00000nam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-20-CTM-CR9780511845765 | ||
| 003 | UkCbUP | ||
| 005 | 20151021141943.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 101029s2015||||enk o ||1 0|eng|d | ||
| 020 | |a 9780511845765 | ||
| 100 | 1 | |a Henderson, Daniel J. | |
| 245 | 1 | 0 | |a Applied nonparametric econometrics |c Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2015 | |
| 300 | |a 1 Online-Ressource (xii, 367 Seiten) | ||
| 336 | |b txt | ||
| 337 | |b c | ||
| 338 | |b cr | ||
| 520 | |a The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls. | ||
| 700 | 1 | |a Parmeter, Christopher F. | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9780521279680 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9781107010253 |
| 966 | 4 | 0 | |l DE-91 |p ZDB-20-CTM |q TUM_PDA_CTM |u https://doi.org/10.1017/CBO9780511845765 |3 Volltext |
| 912 | |a ZDB-20-CTM | ||
| 912 | |a ZDB-20-CTM | ||
| 049 | |a DE-91 | ||
Record in the Search Index
| DE-BY-TUM_katkey | ZDB-20-CTM-CR9780511845765 |
|---|---|
| _version_ | 1827038447433416704 |
| adam_text | |
| any_adam_object | |
| author | Henderson, Daniel J. |
| author2 | Parmeter, Christopher F. |
| author2_role | |
| author2_variant | c f p cf cfp |
| author_facet | Henderson, Daniel J. Parmeter, Christopher F. |
| author_role | |
| author_sort | Henderson, Daniel J. |
| author_variant | d j h dj djh |
| building | Verbundindex |
| bvnumber | localTUM |
| collection | ZDB-20-CTM |
| format | eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01860nam a2200265 i 4500</leader><controlfield tag="001">ZDB-20-CTM-CR9780511845765</controlfield><controlfield tag="003">UkCbUP</controlfield><controlfield tag="005">20151021141943.0</controlfield><controlfield tag="006">m|||||o||d||||||||</controlfield><controlfield tag="007">cr||||||||||||</controlfield><controlfield tag="008">101029s2015||||enk o ||1 0|eng|d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780511845765</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Henderson, Daniel J.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Applied nonparametric econometrics</subfield><subfield code="c">Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xii, 367 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Parmeter, Christopher F.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9780521279680</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9781107010253</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-91</subfield><subfield code="p">ZDB-20-CTM</subfield><subfield code="q">TUM_PDA_CTM</subfield><subfield code="u">https://doi.org/10.1017/CBO9780511845765</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CTM</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CTM</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield></datafield></record></collection> |
| id | ZDB-20-CTM-CR9780511845765 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-19T15:54:02Z |
| institution | BVB |
| isbn | 9780511845765 |
| language | English |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource (xii, 367 Seiten) |
| psigel | ZDB-20-CTM TUM_PDA_CTM ZDB-20-CTM |
| publishDate | 2015 |
| publishDateSearch | 2015 |
| publishDateSort | 2015 |
| publisher | Cambridge University Press |
| record_format | marc |
| spelling | Henderson, Daniel J. Applied nonparametric econometrics Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami Cambridge Cambridge University Press 2015 1 Online-Ressource (xii, 367 Seiten) txt c cr The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls. Parmeter, Christopher F. Erscheint auch als Druck-Ausgabe 9780521279680 Erscheint auch als Druck-Ausgabe 9781107010253 |
| spellingShingle | Henderson, Daniel J. Applied nonparametric econometrics |
| title | Applied nonparametric econometrics |
| title_auth | Applied nonparametric econometrics |
| title_exact_search | Applied nonparametric econometrics |
| title_full | Applied nonparametric econometrics Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami |
| title_fullStr | Applied nonparametric econometrics Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami |
| title_full_unstemmed | Applied nonparametric econometrics Daniel J. Henderson, University of Alabama, Christopher F. Parmeter, University of Miami |
| title_short | Applied nonparametric econometrics |
| title_sort | applied nonparametric econometrics |
| work_keys_str_mv | AT hendersondanielj appliednonparametriceconometrics AT parmeterchristopherf appliednonparametriceconometrics |