University of Groningen
Methods for High-Dimensional Data in Econometrics
Koning, Nick
DOI:
10.33612/diss.168716962
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Publication date: 2021
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Citation for published version (APA):
Koning, N. (2021). Methods for High-Dimensional Data in Econometrics. University of Groningen, SOM research school. https://doi.org/10.33612/diss.168716962
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Propositions
accompanying the PhD thesis
Methods for High-Dimensional Data in Econometrics by Nick W. Koning
1. Employing regularization in the presence of a sum restriction on the parame-ters in a linear model should be done with caution, as this can interfere with the interpretation of the regularization and may also lead to more complica-ted computation (Chapter 2).
2. Mixing `0- and `1-regularization in unit-sum regression leads to substantially
sparser solutions than `1-regularization, and can guarantee a unique solution
that may not exist when only using `1-regularization (Chapter 2).
3. In a ‘many moment inequalities’ setting, ignoring all but the largest t statis-tic leads to a test with low power against alternatives with multiple violated moment inequalities. This can be improved by maximizing over additional t statistics corresponding to moment inequalities that are implied by the origi-nal set of inequalities (Chapter 3).
4. In a ‘many moment inequalities’ setting, a test on symmetry randomization may lead to considerable performance improvements compared to bootstrap methods in small samples (Chapter 3).
5. Compared to a quadratic statistic, a test based on a conic statistic requires a weaker existence condition at the cost of dependence of the alternative on the covariance structure of the parameter estimators (Chapter 4).
6. With a well-constructed cone, one can focus the power of a test based on a conic statistic towards a specific subset of the alternatives (Chapter 4). 7. The asymptotic analysis of tests, where the level converges to zero is
unde-rappreciated in the current literature.
8. The noise produced by an office as a function of the number of its number of occupants has a local maximum at 2.
9. “If you chase two rabbits, you will lose them both.” – Erasmus in Adagia.
// De magenta omlijning geeft de netto maat aan en zal niet zichtbaar zijn in het eindproduct // // Let op: Dit proef bestand is niet geschikt om correcties in te maken //
