Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

GMM with Many Moment Conditions

Chirok Han and Peter C. B. Phillips
Econometrica
Vol. 74, No. 1 (Jan., 2006), pp. 147-192
Published by: The Econometric Society
Stable URL: http://www.jstor.org/stable/3598926
Page Count: 46
  • Read Online (Free)
  • Download ($10.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
GMM with Many Moment Conditions
Preview not available

Abstract

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or uninformed) instruments and some panel data models that cover moderate time spans and have correspondingly large numbers of instruments. Under certain regularity conditions, the GMM estimators are shown to converge in probability but not necessarily to the true parameter, and conditions for consistent GMM estimation are given. A general framework for the GMM limit distribution theory is developed based on epiconvergence methods. Some illustrations are provided, including consistent GMM estimation of a panel model with time varying individual effects, consistent limited information maximum likelihood estimation as a continuously updated GMM estimator, and consistent IV structural estimation using large numbers of weak or irrelevant instruments. Some simulations are reported.

Page Thumbnails

  • Thumbnail: Page 
147
    147
  • Thumbnail: Page 
148
    148
  • Thumbnail: Page 
149
    149
  • Thumbnail: Page 
150
    150
  • Thumbnail: Page 
151
    151
  • Thumbnail: Page 
152
    152
  • Thumbnail: Page 
153
    153
  • Thumbnail: Page 
154
    154
  • Thumbnail: Page 
155
    155
  • Thumbnail: Page 
156
    156
  • Thumbnail: Page 
157
    157
  • Thumbnail: Page 
158
    158
  • Thumbnail: Page 
159
    159
  • Thumbnail: Page 
160
    160
  • Thumbnail: Page 
161
    161
  • Thumbnail: Page 
162
    162
  • Thumbnail: Page 
163
    163
  • Thumbnail: Page 
164
    164
  • Thumbnail: Page 
165
    165
  • Thumbnail: Page 
166
    166
  • Thumbnail: Page 
167
    167
  • Thumbnail: Page 
168
    168
  • Thumbnail: Page 
169
    169
  • Thumbnail: Page 
170
    170
  • Thumbnail: Page 
171
    171
  • Thumbnail: Page 
172
    172
  • Thumbnail: Page 
173
    173
  • Thumbnail: Page 
174
    174
  • Thumbnail: Page 
175
    175
  • Thumbnail: Page 
176
    176
  • Thumbnail: Page 
177
    177
  • Thumbnail: Page 
178
    178
  • Thumbnail: Page 
179
    179
  • Thumbnail: Page 
180
    180
  • Thumbnail: Page 
181
    181
  • Thumbnail: Page 
182
    182
  • Thumbnail: Page 
183
    183
  • Thumbnail: Page 
184
    184
  • Thumbnail: Page 
185
    185
  • Thumbnail: Page 
186
    186
  • Thumbnail: Page 
187
    187
  • Thumbnail: Page 
188
    188
  • Thumbnail: Page 
189
    189
  • Thumbnail: Page 
190
    190
  • Thumbnail: Page 
191
    191
  • Thumbnail: Page 
192
    192