scholarly journals Nonparametric identification of auction models with non-separable unobserved heterogeneity

2009 ◽  
Author(s):  
Matthew Shum ◽  
David McAdams ◽  
Yingyao Hu
Keyword(s):  
Unobserved Heterogeneity ◽  
Nonparametric Identification ◽  
Auction Models

scholarly journals NONPARAMETRIC IDENTIFICATION OF ACCELERATED FAILURE TIME COMPETING RISKS MODELS

2013 ◽  
Vol 29 (5) ◽  
pp. 905-919 ◽  
Author(s):  
Sokbae Lee ◽  
Arthur Lewbel
Keyword(s):  
Competing Risks ◽  
Failure Time ◽  
Nonparametric Identification ◽  
Accelerated Failure Time ◽  
Rank Condition ◽  
Survivor Function ◽  
Auction Models ◽  
Regression Functions ◽  
Accelerated Failure ◽  
Identification Strategy

We provide new conditions for identification of accelerated failure time competing risks models. These include Roy models and some auction models. In our setup, unknown regression functions and the joint survivor function of latent disturbance terms are all nonparametric. We show that this model is identified given covariates that are independent of latent errors, provided that a certain rank condition is satisfied. We present a simple example in which our rank condition for identification is verified. Our identification strategy does not depend on identification at infinity or near zero, and it does not require exclusion assumptions. Given our identification, we show estimation can be accomplished using sieves.

SEMI-NONPARAMETRIC INTERVAL-CENSORED MIXED PROPORTIONAL HAZARD MODELS: IDENTIFICATION AND CONSISTENCY RESULTS

2008 ◽  
Vol 24 (3) ◽  
pp. 749-794 ◽  
Author(s):  
Herman J. Bierens
Keyword(s):  
Legendre Polynomials ◽  
Unobserved Heterogeneity ◽  
Unit Interval ◽  
Hazard Models ◽  
Nonparametric Identification ◽  
Proportional Hazard ◽  
Proportional Hazard Models ◽  
Consistency Results ◽  
Interval Censored ◽  
Mixed Proportional Hazard Models

In this paper I propose estimating distributions on the unit interval semi-nonparametrically using orthonormal Legendre polynomials. This approach will be applied to the interval-censored mixed proportional hazard (ICMPH) model, where the distribution of the unobserved heterogeneity is modeled semi-nonparametrically. Various conditions for the nonparametric identification of the ICMPH model are derived. I will prove general consistency results for M-estimators of (partly) non-euclidean parameters under weak and easy-to-verify conditions and specialize these results to sieve estimators. Special attention is paid to the case where the support of the covariates is finite.

University Dropout

2008 ◽  
Vol 29 (3) ◽  
pp. 134-147 ◽  
Author(s):  
Manuel C. Voelkle ◽  
Nicolas Sander
Keyword(s):  
Grade Point Average ◽  
Structural Equation ◽  
Unobserved Heterogeneity ◽  
School Grade ◽  
Grade Point ◽  
High School Grade ◽  
Hands On ◽  
University Dropout ◽  
The Individual ◽  
A Prospective Study

University dropout is a politically and economically important factor. While a number of studies address this issue cross-sectionally by analyzing different cohorts, or retrospectively via questionnaires, few of them are truly longitudinal and focus on the individual as the unit of interest. In contrast to these studies, an individual differences perspective is adopted in the present paper. For this purpose, a hands-on introduction to a recently proposed structural equation (SEM) approach to discrete-time survival analysis is provided ( Muthén & Masyn, 2005 ). In a next step, a prospective study with N = 1096 students, observed across four semesters, is introduced. As expected, average university grade proved to be an important predictor of future dropout, while high-school grade-point average (GPA) yielded no incremental predictive validity but was completely mediated by university grade. Accounting for unobserved heterogeneity, three latent classes could be identified with differential predictor-criterion relations, suggesting the need to pay closer attention to the composition of the student population.

Migration and the Internet

2017 ◽  
Vol 14 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Thomas John Cooke ◽  
Ian Shuttleworth
Keyword(s):  
United States ◽  
Information And Communication Technologies ◽  
Unobserved Heterogeneity ◽  
Panel Study ◽  
The United States ◽  
Negative Effect ◽  
Information And Communication ◽  
Using Data ◽  
And Migration ◽  
Dynamics Models

It is widely presumed that information and communication technologies, or ICTs, enable migration in several ways; primarily by reducing the costs of migration. However, a reconsideration of the relationship between ICTs and migration suggests that ICTs may just as well hinder migration; primarily by reducing the costs of not moving.  Using data from the US Panel Study of Income Dynamics, models that control for sources of observed and unobserved heterogeneity indicate a strong negative effect of ICT use on inter-state migration within the United States. These results help to explain the long-term decline in internal migration within the United States.

Sign in / Sign up

Export Citation Format

Share Document