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AA10715861-00000164-0001.pdf
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Title |
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Inference on conditional moment restriction models with generated variables
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Kimoto, Ryo
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Department of Economics, The Pennsylvania State University
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大津, 泰介
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オオツ, タイスケ
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Ōtsu, Taisuke
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Department of Economics, London School of Economics; 慶應義塾大学産業研究所
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Keio Economic Observatory
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Keio Economic Observatory Sangyo Kenkyujo
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2022
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KEO discussion paper
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164
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2022
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1
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Abstract |
A seminal work by Domínguez and Lobato (2004) proposed a consistent estimation method for conditional moment restrictions, which does not rely on additional identification assumptions as in the GMM estimator using unconditional moments and is free from any userchosen number. Their methodology is further extended by Domínguez and Lobato (2015, 2020) for consistent specification testing of conditional moment restrictions, which may involve generated variables. We follow up this literature and derive the asymptotic distribution of Domínguez and Lobato's (2004) estimator that involves generated variables. Our simulation result illustrates that ignoring proxy errors in the generated variables may cause severer distortions for the coverage or size properties of statistical inference on parameters.
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History |
Jan 19, 2022 | | インデックス を変更 |
Jan 19, 2022 | | Creator Link,Creator Name,Creator Kana,Edition 版,Place 場所,Publisher Name,Publisher Kana を変更 |
Oct 16, 2023 | | JaLCDOI を変更 |
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Index |
/ Public / Keio Economic Observatory(KEO) / KEO discussion paper / 101-102, 104-108, 110-119, 121-144, 147-149, 152, 155-156, 158-162, 164-168, 170, 173, 175, 177-178 |
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