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A Joint Specification Test for Response Probabilities in Unordered Multinomial Choice Models
http://hdl.handle.net/10252/00005947
http://hdl.handle.net/10252/00005947ff2fc1f4-bab0-4084-80b1-a76a334d8855
名前 / ファイル | ライセンス | アクション |
---|---|---|
Econometrics3-667-698-2015 (500.7 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2019-11-29 | |||||
タイトル | ||||||
タイトル | A Joint Specification Test for Response Probabilities in Unordered Multinomial Choice Models | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | specification test | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | multinomial choice models | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | parametric bootstrap | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | nonparametric methods | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Iwasawa, Masamune
× Iwasawa, Masamune |
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著者別名 | ||||||
姓名 | 岩澤, 正宗 | |||||
書誌情報 |
Econometrics 巻 3, 号 3, p. 667-697, 発行日 2015 |
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ISSN / EISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 22251146 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.3390/econometrics3030667 | |||||
権利表記 | ||||||
権利情報 | ©2015 by the author | |||||
出版社版URI | ||||||
権利情報 | https://www.mdpi.com/2225-1146/3/3/667 | |||||
テキストバージョン | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
日本十進分類法 | ||||||
主題Scheme | NDC | |||||
主題 | 417 | |||||
NIIサブジェクト | ||||||
主題Scheme | Other | |||||
主題 | 経済学 | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Estimation results obtained by parametric models may be seriously misleading when the model is misspecified or poorly approximates the true model. This study proposes a test that jointly tests the specifications of multiple response probabilities in unordered multinomial choice models. The test statistic is asymptotically chi-square distributed, consistent against a fixed alternative and able to detect a local alternative approaching to the null at a rate slower than the parametric rate. We show that rejection regions can be calculated by a simple parametric bootstrap procedure, when the sample size is small. The size and power of the tests are investigated by Monte Carlo experiments. |