Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples
The asymptotic distribution is presented for the linear instrumental variables model estimated with a ridge penalty and a prior where the tuning parameter is selected with a holdout sample. The structural parameters and the tuning parameter are estimated jointly by method of moments. A chi-squared s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Stats |
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| Online Access: | https://www.mdpi.com/2571-905X/4/3/43 |
| _version_ | 1797517108723056640 |
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| author | Fallaw Sowell Nandana Sengupta |
| author_facet | Fallaw Sowell Nandana Sengupta |
| author_sort | Fallaw Sowell |
| collection | DOAJ |
| description | The asymptotic distribution is presented for the linear instrumental variables model estimated with a ridge penalty and a prior where the tuning parameter is selected with a holdout sample. The structural parameters and the tuning parameter are estimated jointly by method of moments. A chi-squared statistic permits confidence regions for the structural parameters. The form of the asymptotic distribution provides insights on the optimal way to perform the split between the training and test sample. Results for the linear regression estimated by ridge regression are presented as a special case. |
| first_indexed | 2024-03-10T07:12:08Z |
| format | Article |
| id | doaj.art-050dff38d57f44c6a60a6e6cf3b51e48 |
| institution | Directory Open Access Journal |
| issn | 2571-905X |
| language | English |
| last_indexed | 2024-03-10T07:12:08Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Stats |
| spelling | doaj.art-050dff38d57f44c6a60a6e6cf3b51e482023-11-22T15:18:26ZengMDPI AGStats2571-905X2021-09-014372574410.3390/stats4030043Inference for the Linear IV Model Ridge Estimator Using Training and Test SamplesFallaw Sowell0Nandana Sengupta1Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213, USASchool of Public Policy, Indian Institute of Technology Delhi, New Delhi 110016, IndiaThe asymptotic distribution is presented for the linear instrumental variables model estimated with a ridge penalty and a prior where the tuning parameter is selected with a holdout sample. The structural parameters and the tuning parameter are estimated jointly by method of moments. A chi-squared statistic permits confidence regions for the structural parameters. The form of the asymptotic distribution provides insights on the optimal way to perform the split between the training and test sample. Results for the linear regression estimated by ridge regression are presented as a special case.https://www.mdpi.com/2571-905X/4/3/43ridge regressionholdout samplemethod of momentsasymptotic distributionconfidence region |
| spellingShingle | Fallaw Sowell Nandana Sengupta Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples Stats ridge regression holdout sample method of moments asymptotic distribution confidence region |
| title | Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples |
| title_full | Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples |
| title_fullStr | Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples |
| title_full_unstemmed | Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples |
| title_short | Inference for the Linear IV Model Ridge Estimator Using Training and Test Samples |
| title_sort | inference for the linear iv model ridge estimator using training and test samples |
| topic | ridge regression holdout sample method of moments asymptotic distribution confidence region |
| url | https://www.mdpi.com/2571-905X/4/3/43 |
| work_keys_str_mv | AT fallawsowell inferenceforthelinearivmodelridgeestimatorusingtrainingandtestsamples AT nandanasengupta inferenceforthelinearivmodelridgeestimatorusingtrainingandtestsamples |