Inference in Linear Regression Models with Many Covariates and Heteroskedasticity

The linear regression model is widely used in empirical work in Economics, Statistics, and many other disciplines. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results are obtained using high-dimensional approximations, where the number of included covariates are allowed to grow as fast as the sample size. We find that all of the usual versions of Eicker-White heteroskedasticity consistent standard error estimators for linear models are inconsistent under this asymptotics. We then propose a new heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional)\ heteroskedasticity of unknown form and the inclusion of possibly many covariates. We apply our findings to three settings: parametric linear models with many covariates, linear panel models with many fixed effects, and semiparametric semi-linear models with many technical regressors. Simulation evidence consistent with our theoretical results is also provided. The proposed methods are also illustrated with an empirical application

Alternative Asymptotics and the Partially Linear Model with Many Regressors

Non-standard distributional approximations have received considerable attention in recent years. They often provide more accurate approximations in small samples, and theoretical improvements in some cases. This paper shows that the seemingly unrelated "many instruments asymptotics" and "small bandwidth asymptotics" share a common structure, where the object determining the limiting distribution is a V-statistic with a remainder that is an asymptotically normal degenerate U-statistic. We illustrate how this general structure can be used to derive new results by obtaining a new asymptotic distribution of a series estimator of the partially linear model when the number of terms in the series approximation possibly grows as fast as the sample size, which we call "many terms asymptotics"

Circle of Friends, an Encouraging Intervention for Alleviating Loneliness

Non peer reviewe

Magnetic and mechanical effects of Mn substitutions in AlFe2B2

The mechanical and magnetic properties of the newly discovered MAB-phase class of materials based upon AlFe2B2 were investigated. The samples were synthesised from stoichiometric amounts of all constituent elements. X-ray diffraction shows that the main phase is orthorhombic with an elongated b-axis, similar to AlFe2B2. The low hardness and visual inspection of the samples after deformation indicate that these compounds are deformed via a delamination process. When substituting iron in AlFe2B2 with manganese, the magnetism in the system goes from being ferro- to antiferromagnetic via a disordered ferrimagnetic phase exhibited by AlFeMnB2. Density functional theory calculations indicate a weakening of the magnetic interactions among the transitions metal ions as iron is substituted by manganese in AlFe2B2. The Mn-Mn exchange interactions in AlMn2 B2 are found to be very small

Exploring response inhibition, the behavioral inhibition system and possible sex differences in athletes and non-athletes

Background: The objective of this study was to revisit the question concerning whether athletes are better than non-athletes at fundamental cognitive abilities, such as inhibitory control, in addition to also focusing on motivational dispositions and possible sex differences. Adding the latter could be crucial since both inhibitory control and motivational dispositions, such as approach and avoidance, are central to goal-directed behavior. Methods: This study’s sample was composed of 93 participants (40 males): 29 biathletes; 30 alpine skiers; and 34 non-athletes. A non-sport-specific stop-signal task was used for the assessment of inhibitory control in terms of response inhibition, and the motivational dispositions were assessed with the BIS/BAS scales. Results: The results showed that there were no differences between the two different sports or non-athletes with regard to response inhibition. However, females showed significantly slower response inhibition than males (p = 0.018) and scored significantly higher on the trait variable BIS (p < 0.001). Conclusions: The results from this study suggest that it might be meaningful to explore the contribution of sex differences and motivational dispositions on response inhibition in conjunction with different types of sports.info:eu-repo/semantics/publishedVersio

Reconstructing phylogenetic level-1 networks from nondense binet and trinet sets

Binets and trinets are phylogenetic networks with two and three leaves, respectively. Here we consider the problem of deciding if there exists a binary level-1 phylogenetic network displaying a given set T of binary binets or trinets over a taxon set X, and constructing such a network whenever it exists. We show that this is NP-hard for trinets but polynomial-time solvable for binets. Moreover, we show that the problem is still polynomial-time solvable for inputs consisting of binets and trinets as long as the cycles in the trinets have size three. Finally, we present an O(3^{|X|} poly(|X|)) time algorithm for general sets of binets and trinets. The latter two algorithms generalise to instances containing level-1 networks with arbitrarily many leaves, and thus provide some of the first supernetwork algorithms for computing networks from a set of rooted 1 phylogenetic networks