Search Results - subject:"kernel-regularized least squares"

Estimation of empirical models for margins of exports with unknown nonlinear functional forms: A Kernel-Regularized Least Squares (KRLS) approach

Wagner, Joachim - 2024

for the first time the Kernel-Regularized Least Squares (KRLS) estimator to deal with this issue in empirical models for …

Persistent link: https://www.econbiz.de/10014466971

Cloud computing and extensive margins of exports: Evidence for manufacturing firms from 27 EU countries

Wagner, Joachim - 2024

this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least … Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various …

Persistent link: https://www.econbiz.de/10014493164

Estimation of empirical models for margins of exports with unknown nonlinear functional forms : a Kernel-Regularized Least Squares (KRLS) approach

Wagner, Joachim - 2024 - This version: January 17, 2024

for the first time the Kernel-Regularized Least Squares (KRLS) estimator to deal with this issue in empirical models for …

Persistent link: https://www.econbiz.de/10014464962

Cloud computing and extensive margins of exports : evidence for manufacturing firms from 27 EU countries

Wagner, Joachim - 2024 - This version: March 5, 2024

Persistent link: https://www.econbiz.de/10014485550

Firm characteristics of two-way traders : evidence from Probit vs. Kernel-Regularized Least Squares regressions

Wagner, Joachim - 2025 - This version: May 23, 2025

all possible non-linear relationships are taken care of. A solution is provided by Kernel Regularized Least Squares (KRLS …

Persistent link: https://www.econbiz.de/10015407786

Machine-learning-based semiparametric time series conditional variance: Estimation and forecasting

Dang, Justin; Ullah, Aman - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-12

, known as the kernel-regularized least squares estimator, is used to estimate the nonparametric component. We discuss how to …

Persistent link: https://www.econbiz.de/10013201342

Machine-learning-based semiparametric time series conditional variance : estimation and forecasting

Dang, Justin; Ullah, Aman - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-12

, known as the kernel-regularized least squares estimator, is used to estimate the nonparametric component. We discuss how to …

Persistent link: https://www.econbiz.de/10012814196

Generalized kernel regularized least squares estimator with parametric error covariance

Dang, Justin; Ullah, Aman - In: Empirical economics : a quarterly journal of the … 64 (2023) 6, pp. 3059-3088

Persistent link: https://www.econbiz.de/10014329024

Re-estimating the pollution haven-halo hypotheses for Brazil via a machine learning procedure

Uche, Emmanuel; Omoke, Philip Chimobi; Silva-Opuala, Charles - In: Journal of international development : the journal of … 36 (2024) 2, pp. 1274-1292

Persistent link: https://www.econbiz.de/10014516040

Environment and development : penalized non-parametric inference of global trends in deforestation, pollution and carbon

Andrée, Bo Pieter Johannes; Spencer, Phoebe; Chamorro, … - 2019

This paper revisits the issue of environment and development raised in the 1992 World Development Report, with new analysis tools and data. The paper discusses inference and interpretation in a machine learning framework. The results suggest that production gradually favors conserving the...

Persistent link: https://www.econbiz.de/10012008015