Zobrazeno 1 - 10
of 269
pro vyhledávání: '"Moon, Hyungsik Roger"'
Autor:
Gao, Zhan, Moon, Hyungsik Roger
This paper addresses the robust estimation of linear regression models in the presence of potentially endogenous outliers. Through Monte Carlo simulations, we demonstrate that existing $L_1$-regularized estimation methods, including the Huber estimat
Externí odkaz:
http://arxiv.org/abs/2408.03930
We incorporate a version of a spike and slab prior, comprising a pointmass at zero ("spike") and a Normal distribution around zero ("slab") into a dynamic panel data framework to model coefficient heterogeneity. In addition to homogeneity and full he
Externí odkaz:
http://arxiv.org/abs/2310.13785
We derive optimal statistical decision rules for discrete choice problems when payoffs depend on a partially-identified parameter $\theta$ and the decision maker can use a point-identified parameter $P$ to deduce restrictions on $\theta$. Leading exa
Externí odkaz:
http://arxiv.org/abs/2204.11748
We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of h
Externí odkaz:
http://arxiv.org/abs/2110.14117
We use a decision-theoretic framework to study the problem of forecasting discrete outcomes when the forecaster is unable to discriminate among a set of plausible forecast distributions because of partial identification or concerns about model misspe
Externí odkaz:
http://arxiv.org/abs/2011.03153
For an $N \times T$ random matrix $X(\beta)$ with weakly dependent uniformly sub-Gaussian entries $x_{it}(\beta)$ that may depend on a possibly infinite-dimensional parameter $\beta\in \mathbf{B}$, we obtain a uniform bound on its operator norm of th
Externí odkaz:
http://arxiv.org/abs/1905.01096
We prove a central limit theorem for network formation models with strategic interactions and homophilous agents. Since data often consists of observations on a single large network, we consider an asymptotic framework in which the network size diver
Externí odkaz:
http://arxiv.org/abs/1904.11060
In this paper, we investigate seemingly unrelated regression (SUR) models that allow the number of equations (N) to be large, and to be comparable to the number of the observations in each equation (T). It is well known in the literature that the con
Externí odkaz:
http://arxiv.org/abs/1811.05567
Autor:
Moon, Hyungsik Roger, Weidner, Martin
In this paper we investigate panel regression models with interactive fixed effects. We propose two new estimation methods that are based on minimizing convex objective functions. The first method minimizes the sum of squared residuals with a nuclear
Externí odkaz:
http://arxiv.org/abs/1810.10987
This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coefficients under a corr
Externí odkaz:
http://arxiv.org/abs/1709.10193