Estimation of standard errors of Engel elasticities within the framework of a linear structural model formulated on two-wave panel data is considered. The complete demand system is characterized by measurement errors in total expenditure and by latent preference variation. The estimation of the parameters as well as the standard errors of the estimates is based on the assumption that the variables are normally distributed. Considering a concrete case it is demonstrated that normality does not hold as a maintained assumption. In the light of this standard errors are estimated by means of bootstrapping. However, one obtains rather similar estimates of the standard errors of the Engel elasticities no matter whether one sticks to classical norm...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
We conduct Monte Carlo experiments to investigate the biases of assuming a misspecified demand model...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
Abstract: Estimation of standard errors of Engel elasticities within the framework of a linear struc...
Estimation of demand elasticities using LA-AIDS model with Stone's Price Index and bootstrapping sta...
Elasticities are often estimated from the results of demand analysis. However, drawing inferences fr...
Though the common default maximum likelihood estimator used in structural equa-tion modeling is pred...
Standard errors of parameter estimates are widely used in empirical work. The bootstrap can often pr...
Empirical studies of consumer demand or of factor demand have now moved far beyond the Cobb-Douglas ...
This paper examines the sensitivity of the distributions of OLS and 2SLS estimators to the assumptio...
Bootstrapping is a nonparametric approach for evaluating the distribution of a statistic based on ra...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
Variables are often measured subject to error, whether they are collected as part of an experiment o...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consi...
This study empirically investigated bootstrap bias estimation in the area of structural equation mod...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
We conduct Monte Carlo experiments to investigate the biases of assuming a misspecified demand model...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
Abstract: Estimation of standard errors of Engel elasticities within the framework of a linear struc...
Estimation of demand elasticities using LA-AIDS model with Stone's Price Index and bootstrapping sta...
Elasticities are often estimated from the results of demand analysis. However, drawing inferences fr...
Though the common default maximum likelihood estimator used in structural equa-tion modeling is pred...
Standard errors of parameter estimates are widely used in empirical work. The bootstrap can often pr...
Empirical studies of consumer demand or of factor demand have now moved far beyond the Cobb-Douglas ...
This paper examines the sensitivity of the distributions of OLS and 2SLS estimators to the assumptio...
Bootstrapping is a nonparametric approach for evaluating the distribution of a statistic based on ra...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
Variables are often measured subject to error, whether they are collected as part of an experiment o...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consi...
This study empirically investigated bootstrap bias estimation in the area of structural equation mod...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
We conduct Monte Carlo experiments to investigate the biases of assuming a misspecified demand model...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...