Abstract: 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 clas...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
Variables are often measured subject to error, whether they are collected as part of an experiment o...
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 stru...
Estimation of standard errors of Engel elasticities within the framework of a linear structural mode...
Though the common default maximum likelihood estimator used in structural equa-tion modeling is pred...
Estimation of demand elasticities using LA-AIDS model with Stone's Price Index and bootstrapping sta...
Standard errors of parameter estimates are widely used in empirical work. The bootstrap can often pr...
Elasticities are often estimated from the results of demand analysis. However, drawing inferences fr...
Bootstrapping is a nonparametric approach for evaluating the distribution of a statistic based on ra...
This paper examines the sensitivity of the distributions of OLS and 2SLS estimators to the assumptio...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consi...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
This study empirically investigated bootstrap bias estimation in the area of structural equation mod...
Abstract. In applied econometrics, the researcher typically has two recourses for conducting inferen...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
Variables are often measured subject to error, whether they are collected as part of an experiment o...
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 stru...
Estimation of standard errors of Engel elasticities within the framework of a linear structural mode...
Though the common default maximum likelihood estimator used in structural equa-tion modeling is pred...
Estimation of demand elasticities using LA-AIDS model with Stone's Price Index and bootstrapping sta...
Standard errors of parameter estimates are widely used in empirical work. The bootstrap can often pr...
Elasticities are often estimated from the results of demand analysis. However, drawing inferences fr...
Bootstrapping is a nonparametric approach for evaluating the distribution of a statistic based on ra...
This paper examines the sensitivity of the distributions of OLS and 2SLS estimators to the assumptio...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consi...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...
This study empirically investigated bootstrap bias estimation in the area of structural equation mod...
Abstract. In applied econometrics, the researcher typically has two recourses for conducting inferen...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
Variables are often measured subject to error, whether they are collected as part of an experiment o...
The possible discrepancy between a hypothesized model and the observed data is measured by so called...