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Quantile Regression with Classical Additive Measurement Errors [PDF]
This note derives the bias of the quantile regression estimator in the presence of classical additive measurement error, and show its connection to least squares models.
Gabriel Montes-Rojas
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Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Increased frequency of extreme weather events, particularly droughts, threatens grassland farming by destabilizing yields and farms' economic viability. We examine, theoretically and through numerical simulations, how sown plant diversity (natural insurance) influences the attractiveness of indemnity and drought index insurance (formal ...
Nicolas Alou +3 more
wiley +1 more source
Quantile Regression in Risk Calibration [PDF]
Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the ...
Wolfgang Karl Härdle +2 more
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Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification
Econometrics, 2015 Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
doaj +1 more source
Journal of the Operations Research Society of Japan, 1991 Summary: This study proposes a new use of goal programming for empirically estimating a regression quantile hyperplane. The approach can yield regression quantile estimates that are less sensitive to not only non- Gaussian error distributions but also a small sample size than conventional regression quantile methods.
openaire +2 more sources
Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Eggs are an inexpensive and sustainable source of proteins, but volatility in the U.S. egg prices has intensified in recent years, raising concerns over food affordability and market stability. This study examines the drivers of U.S. egg price dynamics over 2004–2025 using a two‐stage framework that combines LASSO‐based variable selection with
Xuemei Zhao +3 more
wiley +1 more source
REGRESI KUANTIL MEDIAN UNTUK MENGATASI HETEROSKEDASTISITAS PADA ANALISIS REGRESI
E-Jurnal Matematika, 2013 In regression analysis, the method used to estimate the parameters is Ordinary Least Squares (OLS). The principle of OLS is to minimize the sum of squares error. If any of the assumptions were not met, the results of the OLS estimates are no longer best,
IDA AYU PRASETYA UTHAMI +2 more
doaj +1 more source
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT This paper examines the relationship between participation in the EU Rural Development Program and the economic performance of Italian olive farms using a finite‐mixture model with inverse‐probability‐weighted regression adjustment. Based on 2010–2022 FADN panel data, it estimates heterogeneous treatment effects while correcting for selection ...
Francesco Caracciolo, Marilena Furno
wiley +1 more source
A Note on Implementing Box-Cox Quantile Regression [PDF]
The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques.
Wilke, Ralf A. +2 more
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Corrigendum: Modified quantile regression for modeling the low birth weight
Frontiers in Applied Mathematics and Statistics, 2023 Ferra Yanuar +2 more
doaj +1 more source