Simultaneous Confidence Intervals for High-dimensional Linear Models with Many Endogenous Variables [PDF]
arXiv, 2017 High-dimensional linear models with endogenous variables play an increasingly important role in recent econometric literature. In this work we allow for models with many endogenous variables and many instrument variables to achieve identification.
arxiv
The role of technology, organisation, and demand in growth and income distribution [PDF]
, 2012 The paper proposes a model that explains cross-country growth divergences over time for different aspects of structural change. The model formalises the links between production technology, firm organisation (functional composition of employment) on the ...
Ciarli, Tommaso +3 more
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Stochastic Convergence of Persistence Landscapes and Silhouettes
, 2013 Persistent homology is a widely used tool in Topological Data Analysis that encodes multiscale topological information as a multi-set of points in the plane called a persistence diagram.
Chazal, Frédéric +4 more
core +3 more sources
Appendix VI: Multipliers used in the construction of confidence intervals based on the Normal distribution, for selected levels of confidence [PDF]
, 2018 Michael Thrusfield +9 more
openalex +1 more source
A more robust definition of multiple priors [PDF]
This paper provides a multiple-priors representation of ambiguous beliefs à la Ghirardato, Maccheroni, and Marinacci (2004) and Nehring (2002) for any preference that is (i) monotonic, (ii) Bernoullian, i.e.
Marciano Siniscalchi, Paolo Ghirardato
core
Dependent multiplier bootstraps for non-degenerate $U$-statistics under mixing conditions with applications [PDF]
arXiv, 2014 The asymptotic validity of a resampling method for two sequential processes constructed from non-degenerate $U$-statistics is established under mixing conditions. The resampling schemes, referred to as {\em dependent multiplier bootstraps}, result from an adaptation of the seminal approach of \cite{GomHor02} to mixing sequences.
arxiv
Local and Global Inference for High Dimensional Nonparanormal Graphical Models [PDF]
arXiv, 2015 This paper proposes a unified framework to quantify local and global inferential uncertainty for high dimensional nonparanormal graphical models. In particular, we consider the problems of testing the presence of a single edge and constructing a uniform confidence subgraph.
arxiv
Inference with Weak Instruments [PDF]
This paper reviews recent developments in methods for dealing with weak instruments (IVs) in IV regression models. The focus is more on tests (and confidence intervals derived from tests) than estimators. The paper also presents new testing results under
Donald W.K. Andrews, James H. Stock
core
Bootstrapping Upper Confidence Bound [PDF]
arXiv, 2019 Upper Confidence Bound (UCB) method is arguably the most celebrated one used in online decision making with partial information feedback. Existing techniques for constructing confidence bounds are typically built upon various concentration inequalities, which thus lead to over-exploration.
arxiv
Simultaneous Confidence Bands for Functional Data Using the Gaussian Kinematic Formula
, 2019 This article constructs simultaneous confidence bands (SCBs) for functional parameters using the Gaussian Kinematic formula of $t$-processes (tGKF). Although the tGKF relies on Gaussianity, we show that a central limit theorem (CLT) for the parameter of ...
Schwartzman, Armin +1 more
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