Results 211 to 220 of about 76,914 (334)

Bayesian Model Averaging in the Context of Spatial Hedonic Pricing: An Application to Farmland Values [PDF]

open access: yes
Since 1973, British Columbia created an Agricultural Land Reserve to protect farmland from development. In this study, we employ GIS-based hedonic pricing models of farmland values to examine factors that affect farmland prices.
G. Cornelis van Kooten   +2 more
core  

Revisiting the Ancient Origins of Gender Inequality

open access: yesJournal of Applied Econometrics, EarlyView.
ABSTRACT This study re‐examines the long‐term effect of traditional plough use on contemporary gender roles, as originally advanced by Alesina, Giuliano and Nunn [Quarterly Journal of Economics (2013) Vol. 128, pp. 469–530]. The findings demonstrate that the reduced‐form relationship between historical plough adoption and female empowerment is robust ...
Trung V. Vu
wiley   +1 more source

Spatial econometrics (1, Spatial autocorrelation)

open access: yes, 2000
Les méthodes de l’économétrie spatiale visent à traiter les deux grandes particularités des données spatiales : l’autocorrélation spatiale qui se référé à l’absence d’indépendance entre observations géographiques et l’hétérogénéité spatiale qui est liée à la différenciation dans l’espace des variables et des comportements.
openaire   +1 more source

A Consistent Heteroskedasticity‐Robust LM‐Type Specification Test for Semiparametric Models

open access: yesJournal of Applied Econometrics, EarlyView.
ABSTRACT This article develops a heteroskedasticity‐robust Lagrange Multiplier‐type specification test for semiparametric regression models. The test is able to detect a wide class of deviations from the null hypothesis. The test statistic is based on the estimates from the restricted semiparametric model, can be computed in a regression‐based way, and
Ivan Korolev
wiley   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

open access: yesJournal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe   +2 more
wiley   +1 more source

Home - About - Disclaimer - Privacy