Improved Over-identifying restriction test in GMM with many moment conditions
Project/Area Number |
25780153
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Economic statistics
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Research Institution | Hiroshima University |
Principal Investigator |
|
Project Period (FY) |
2013-04-01 – 2017-03-31
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Project Status |
Completed (Fiscal Year 2016)
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Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
Keywords | 一般化モーメント法 / 過剰識別検定 / パネルデータ / 共分散構造分析 / 定式化検定 / GMM / 計量経済学 |
Outline of Final Research Achievements |
In this project, I discussed how to improve the performance of the over-identifying restriction test in GMM when many moment conditions are available. Two new approaches are proposed. The first is to use a block diagonal weighting matrix, and the second is to use the principal components of the optimal weighting matrix. Using these two alternative weighting matrices, I proposed two new tests, and derived their asymptotic properties. I carried out Monte Carlo simulation in the context of dynamic panel data models and it is found that the test with a block diagonal weighting matrix is more powerful than that based on the principal components of the optimal weighting matrix.
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Report
(5 results)
Research Products
(20 results)