@ARTICLE{26543120_26558330_2006, 
	author = {Tatyana Ratnikova}, 
	keywords = {, econometric analysis, model with qualitative dependent variablesmodel with limited dependent variables},
	title = {Introduction to Econometric Analysis of Panel Data},
	journal = {HSE Economic Journal },
	year = {2006},
	month = {4},
	volume = {10},
	number = {4},
	pages = {638-669},
	url = {https://ej.hse.ru/en/2006-10-4/26558330.html},
	publisher = {},
	abstract = {In previous number of the journal eight lectures from a course «Introduction to econometric analysis of panel data» has been published. Its have presented a gene­ral information on the panel data, the basic models estimations methods, estimators property and specification tests. Then there were discussed the estimation problems under conditions of heteroskedasticity and autocorrelation of the error term, correlation between some of the explanatory variables and the individual effects and the estimation problems, which take place in dynamic models and models with measurement errors.In this publication two last lectures are offered your attention. The first one considers estimation of the models with qualitative and limited dependent variables. The second one will be discussed some measures for sample attrition consequences decreasing.},
	annote = {In previous number of the journal eight lectures from a course «Introduction to econometric analysis of panel data» has been published. Its have presented a gene­ral information on the panel data, the basic models estimations methods, estimators property and specification tests. Then there were discussed the estimation problems under conditions of heteroskedasticity and autocorrelation of the error term, correlation between some of the explanatory variables and the individual effects and the estimation problems, which take place in dynamic models and models with measurement errors.In this publication two last lectures are offered your attention. The first one considers estimation of the models with qualitative and limited dependent variables. The second one will be discussed some measures for sample attrition consequences decreasing.}
}