dr. T. (Tom) Boot

Associate Professor

Faculty of Economics and Business

Telephone:

+31 50 36 34001

E-mail:

t.boot rug.nl

Homepage Research Portal

Publications

Grouped heterogeneity in linear panel data models with heterogeneous error variances

Aguilar Loyo, J. & Boot, T., 2025, In: Journal of Business & Economic Statistics. 43, 1, p. 68-80 13 p.

Research output: Contribution to journal › Article › Academic › peer-review

Uniform inference in linear error-in-variables models: Divide-and-conquer

Boot, T. & Juodis, A., 2025, In: Econometric Reviews. 44, 3, p. 335-355

Research output: Contribution to journal › Article › Academic › peer-review

Unbiased estimation of the OLS covariance matrix when the errors are clustered

Boot, T., Niccodemi, G. & Wansbeek, T., 2024, Advanced Studies in Theoretical and Applied Econometrics. Kumbhakar, S. C., Sickles, R. C. & Wang, H.-J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 47-69 23 p. (Advanced Studies in Theoretical and Applied Econometrics; vol. 55).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

Where's Waldo? A framework for quantifying the privacy-utility trade-off in marketing applications

Ponte, G. R., Wieringa, J. E., Boot, T. & Verhoef, P. C., Sept-2024, In: International Journal of Research in Marketing. 41, 3, p. 529-546 18 p.

Research output: Contribution to journal › Article › Academic › peer-review

Joint inference based on Stein-type averaging estimators in the linear regression model

Boot, T., Aug-2023, In: Journal of Econometrics. 235, 2, p. 1542-1563 22 p.

Research output: Contribution to journal › Article › Academic › peer-review

Unbiased estimation of the OLS covariance matrix when the errors are clustered

Boot, T., Wansbeek, T. & Niccodemi, G., 2023, In: Empirical Economics. 64, p. 2511-2533 23 p.

Research output: Contribution to journal › Article › Academic › peer-review

Corrigendum: Wang and Leng (2016), High-dimensional ordinary least-squares projection for screening variables, Journal of the Royal Statistical Society Series B, 78, 589–611

Wang, X., Leng, C. & Boot, T., 22-Sept-2021, In: Journal of the Royal Statistical Society. Series B: Statistical Methodology. 83, 4, p. 880-881 2 p.

Research output: Contribution to journal › Erratum

All (12) publications

Press/media

Veni-beurzen voor veertien Groningse onderzoekers

Mitzinneck, B. C., van der Kwaak, C. & Boot, T.

05/11/2020

Press/Media: Expert Comment › Popular

Jonge RUG-onderzoekers slepen tien VENI’s in de wacht

Mitzinneck, B. C., van der Kwaak, C. & Boot, T.

05/11/2020

Press/Media: Expert Comment › Popular

All (2) press/media

View full research profile

dr. T. (Tom) Boot

Publications

Grouped heterogeneity in linear panel data models with heterogeneous error variances

Uniform inference in linear error-in-variables models: Divide-and-conquer

Unbiased estimation of the OLS covariance matrix when the errors are clustered

Where's Waldo? A framework for quantifying the privacy-utility trade-off in marketing applications

Joint inference based on Stein-type averaging estimators in the linear regression model

Unbiased estimation of the OLS covariance matrix when the errors are clustered

Corrigendum: Wang and Leng (2016), High-dimensional ordinary least-squares projection for screening variables, Journal of the Royal Statistical Society Series B, 78, 589–611

Does modeling a structural break improve forecast accuracy?

Subspace Methods

Confidence Regions for Averaging Estimators

Press/media

Veni-beurzen voor veertien Groningse onderzoekers

Jonge RUG-onderzoekers slepen tien VENI’s in de wacht