Results 101 to 110 of about 30,733 (250)
Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation
International Statistical Review, EarlyView.Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo +3 more
wiley +1 more source
Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors [PDF]
We consider nonparametric estimation of the conditional qth quantile for stationary time series. We deal with stationary time series with strong time dependence and heavy tails under the setting of random design.
Toshio Honda
core
Heterogeneity in Manufacturing Growth Risk
Journal of Money, Credit and Banking, EarlyView.Abstract We analyze differences in output growth risk with respect to financial conditions across U.S. manufacturing industries. Using a multilevel quantile regression approach, we find that industries exhibit heterogeneous increases of downside risk in times of tight financial conditions, while upside potential remains stable.
DAAN OPSCHOOR +2 more
wiley +1 more source
გლობალიზაცია და ბიზნესიThis research attempts to investigate how uncertainty in fiscal policy (FPU) and monetary policy (MPU) affects the US energy transition. While previous literature took the total renewable energy consumption (REC) as an indicator for the energy transition,
Mohammed Amine Mouffok +3 more
doaj +1 more source
Penalizing function based bandwidth choice in nonparametric quantile regression [PDF]
In nonparametric mean regression various methods for bandwidth choice exist. These methods can roughly be divided into plug-in methods and methods based on penalizing functions.
Klaus Abberger
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Mixing It Up: Inflation at Risk
Journal of Money, Credit and Banking, EarlyView.Abstract Understanding how risk factors shape the economic outlook is essential for guiding policy decisions. This paper develops a flexible framework that decomposes distributional risk forecasts of macro‐economic variables into underlying contributions and supports the construction of interpretable risk measures.
MAXIMILIAN SCHRÖDER
wiley +1 more source
Quantile Treatment Effects in the Regression Discontinuity Design [PDF]
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design (RDD) and proposes simple estimators.
Frölich, Markus, Melly, Blaise
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Local bilinear multiple-output quantile/depth regression
, 2015 A new quantile regression concept, based on a directional version of Koenker and Bassett's traditional single-output one, has been introduced in [Ann. Statist. (2010) 38 635-669] for multiple-output location/linear regression problems.
Hallin, Marc +3 more
core +1 more source
Do robots boost productivity? A quantitative meta‐study
Journal of Economic Surveys, EarlyView.ABSTRACT This meta‐study analyzes the productivity effects of industrial robots. More than 1800 estimates from 85 primary studies are collected. The meta‐analytic evidence suggests that robotization has so far provided, at best, a small boost to productivity. There is strong evidence of publication bias in the positive direction.
Florian Schneider
wiley +1 more source
Inequality constrained quantile regression: Working paper series--03-08 [PDF]
, 2003 An algorithm for computing parametric linear quantile regression estimates subject to linear inequality constraints is described. The algorithm is a variant of the interior point algorithm described in Koenker and Portnoy (1997) for unconstrained ...
Koenker, Roger, Ng, Pin
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