Identifying demand with multidimensional unobservables

a random functions approach

  • 0 Ratings
  • 0 Want to read
  • 0 Currently reading
  • 0 Have read
Identifying demand with multidimensional unob ...
Jeremy T. Fox
Not in Library

My Reading Lists:

Create a new list

Check-In

×Close
Add an optional check-in date. Check-in dates are used to track yearly reading goals.
Today

  • 0 Ratings
  • 0 Want to read
  • 0 Currently reading
  • 0 Have read

Buy this book

Last edited by MARC Bot
October 17, 2020 | History

Identifying demand with multidimensional unobservables

a random functions approach

  • 0 Ratings
  • 0 Want to read
  • 0 Currently reading
  • 0 Have read

"We explore the identification of nonseparable models without relying on the property that the model can be inverted in the econometric unobservables. In particular, we allow for infinite dimensional unobservables. In the context of a demand system, this allows each product to have multiple unobservables. We identify the distribution of demand both unconditional and conditional on market observables, which allows us to identify several quantities of economic interest such as the (conditional and unconditional) distributions of elasticities and the distribution of price effects following a merger. Our approach is based on a significant generalization of the linear in random coefficients model that only restricts the random functions to be analytic in the endogenous variables, which is satisfied by several standard demand models used in practice. We assume an (unknown) countable support for the the distribution of the infinite dimensional unobservables"--National Bureau of Economic Research web site.

Publish Date
Language
English

Buy this book

Edition Availability
Cover of: Identifying demand with multidimensional unobservables
Identifying demand with multidimensional unobservables: a random functions approach
2011, National Bureau of Economic Research
Electronic resource in English

Add another edition?

Book Details


Edition Notes

Title from PDF file as viewed on 1/10/2012.

Includes bibliographical references.

Also available in print.

System requirements: Adobe Acrobat Reader.

Mode of access: World Wide Web.

Published in
Cambridge, MA
Series
NBER working paper series -- working paper 17557, Working paper series (National Bureau of Economic Research : Online) -- working paper no. 17557.

Classifications

Library of Congress
HB1

The Physical Object

Format
Electronic resource

ID Numbers

Open Library
OL25173148M
LCCN
2011657464

Community Reviews (0)

Feedback?
No community reviews have been submitted for this work.

Lists

This work does not appear on any lists.

History

Download catalog record: RDF / JSON
October 17, 2020 Edited by MARC Bot import existing book
January 18, 2012 Created by LC Bot import new book