Semiparametric and Nonparametric Methods in Econometrics

Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally dist...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Horowitz, Joel L. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer US, 2009.
Σειρά:Springer Series in Statistics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03689nam a22004335i 4500
001 978-0-387-92870-8
003 DE-He213
005 20151103121921.0
007 cr nn 008mamaa
008 100710s2009 xxu| s |||| 0|eng d
020 |a 9780387928708  |9 978-0-387-92870-8 
024 7 |a 10.1007/978-0-387-92870-8  |2 doi 
040 |d GrThAP 
050 4 |a QA276-280 
072 7 |a PBT  |2 bicssc 
072 7 |a K  |2 bicssc 
072 7 |a BUS061000  |2 bisacsh 
082 0 4 |a 330.015195  |2 23 
100 1 |a Horowitz, Joel L.  |e author. 
245 1 0 |a Semiparametric and Nonparametric Methods in Econometrics  |h [electronic resource] /  |c by Joel L. Horowitz. 
264 1 |a New York, NY :  |b Springer US,  |c 2009. 
300 |a X, 276 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Springer Series in Statistics,  |x 0172-7397 
505 0 |a Single-Index Models -- Nonparametric Additive Models and Semiparametric Partially Linear Models -- Binary-Response Models -- Statistical Inverse Problems -- Transformation Models. 
520 |a Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally distributed. Such assumptions simplify estimation and statistical inference but are rarely justified by economic theory or other a priori considerations. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. These methods are applicable to a wide variety of estimation problems in empirical economics and other fields, and they are being used in applied research with increasing frequency. The literature on nonparametric and semiparametric estimation is large and highly technical. This book presents the main ideas underlying a variety of nonparametric and semiparametric methods. It is accessible to graduate students and applied researchers who are familiar with econometric and statistical theory at the level taught in graduate-level courses in leading universities. The book emphasizes ideas instead of technical details and provides as intuitive an exposition as possible. Empirical examples illustrate the methods that are presented. This book updates and greatly expands the author’s previous book on semiparametric methods in econometrics. Nearly half of the material is new. Joel L. Horowitz is the Charles E. and Emma H. Morrison Professor of Market Economics at Northwestern University. He is the author of over 100 journal articles and book chapters in econometrics and statistics, a winner of the Richard Stone prize in applied econometrics, a fellow of the Econometric Society and American Statistical Association, and a former co-editor of Econometrica. 
650 0 |a Statistics. 
650 1 4 |a Statistics. 
650 2 4 |a Statistics for Business/Economics/Mathematical Finance/Insurance. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9780387928692 
830 0 |a Springer Series in Statistics,  |x 0172-7397 
856 4 0 |u http://dx.doi.org/10.1007/978-0-387-92870-8  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
950 |a Mathematics and Statistics (Springer-11649)