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Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we offer several contributions. Manski and Tamer (2002) propose two estimation approaches in this context, focusing on general results....
Persistent link: https://www.econbiz.de/10013107857
Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we offer several contributions. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general...
Persistent link: https://www.econbiz.de/10013066961
Quadratic functions are often used in regression to infer the existence of an extremum in a relationship although tests of the location of the extremum are rarely performed. We investigate the construction of the following confidence intervals: Delta, Fieller, estimated first derivative,...
Persistent link: https://www.econbiz.de/10012733206
In the literature, although many studies are describing the structural break in the linear regression model with time-series data, studies investigating this issue with cross-sectional data are limited. In this study, the performance evaluation of some approaches used to determine the structural...
Persistent link: https://www.econbiz.de/10012115148
We propose marginal integration estimation and testing methods for the coefficients of varying coefficient multivariate regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence as univariate function estimation. For the...
Persistent link: https://www.econbiz.de/10012966219
We present a fundamentally unique method of nonparametric regression using clusters and test it against classically established methods. We compare two nonlinear regression estimation packages called ‘NNS', Viole (NNS: nonlinear nonparametric statistics, 2016), and ‘np', Hayfield and Racine...
Persistent link: https://www.econbiz.de/10012967797