JSM 2005 - Toronto

Abstract #304334

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.



The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page
Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 101
Type: Contributed
Date/Time: Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor: Business and Economics Statistics Section
Abstract - #304334
Title: Bayesian Model Averaging with Instrumental Variables: An Application to Aid and Growth
Author(s): Roberto Leon Gonzalez*+ and Daniel Montolio and Paul Mosley
Companies: University of Leicester and Universitat de Barcelona and University of Sheffield
Address: University Road, Leicester, LE1 7RH, United Kingdom
Keywords: Bayesian Model Averaging ; Instrumental Variables ; Empirics of Growth ; Effectiveness of Aid
Abstract:

This paper provides a Bayesian analysis of instrumental variable models robust to (1) the set of instruments, (2) the set of explanatory variables in the model, and (3) the allocation of explanatory variables between endogenous and exogenous. In addition, the analysis has the appealing property of reporting a probability that the parameters are overidentified. Furthermore, this probability is robust to issues (1) to (3). Similarly, a robust probability for a regressor being exogenous is obtained. Building on previous studies, the analysis uses a Bayesian Model Averaging (BMA) approach with posterior model probabilities that are robust to local nonidentification. In addition, this paper uses posterior model probabilities that are implied by a Reference prior density on the parameters of an all-encompassing model. This avoids the difficult problem of specifying prior densities and prior model probabilities for nested models. This methodology is illustrated in an empirical application that aims to provide estimates of the effect of aid on economic growth that take into account model uncertainty.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2005 program

JSM 2005 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2005