ROBUST REGRESSION IN MONTHLY BUSINESS SURVEY

There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several alternative techniques of estimation, less sensitive to outliers, have been proposed in the statistical literature. In this paper we attempt to apply and assess some robust regression methods (LTS, M estimation, S-estimation, MM-estimation) in the business survey conducted within the framework of official statistics

Census administration in Ukraine : insight into the Polish experience in the context of international indicators analysis

The latest National Population Census in Poland, like in many EU countries, was conducted in 2021. In Ukraine, during the entire period of independence, a national census was conducted only once, in 2001, while the following rounds kept being postponed. In 2019, a trial census was conducted in several regions of central Ukraine. The working hypothesis is that for the organisation and conduct of the All-Ukrainian Population Census in Ukraine, it is important to use the experience of EU countries in this field (and Poland’s experience in particular). The purpose of the article is to substantiate the theoretical foundations and comparative analysis of the processes of conducting censuses in Poland and Ukraine and to study the factors of increasing the level of respondent participation. The article reviews a number of socio-economic factors in the light of the comparison of data census organisation in Poland and Ukraine. Several international indicators were investigated that could have an impact on respondent participation in statistical surveys and censuses. By applying factor analysis, it was possible to identify the factors that could increase the level of respondent participation. To solve these demographic challenges, the following activity should be considered: financial support for the successful functioning of economic entities, improvement of social infrastructure, friendly environment for innovation and investment, and peace and political stability in Ukraine

Local Estimation in Small Business Research

There are many surveys of populations that contain a number of extreme values. This is particularly true in surveys of business enterprises. Outliers observations can have an important effect on work with estimation especially on low level of the aggregation. Although the values are extreme, they need not necessarily be false; extremely large observations are a natural component in survey populations. So we shall explore some alternative technique estimation less sensitive to outliers. In this paper we examine local regression which has ability to accommodate local departures from the underlying linear model in business statistics

ROBUST REGRESSION IN MONTHLY BUSINESS SURVEY

There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several alternative techniques of estimation, less sensitive to outliers, have been proposed in the statistical literature. In this paper we attempt to apply and assess some robust regression methods (LTS, M-estimation, S-estimation, MM-estimation) in the business survey conducted within the framework of official statistics

Robust regression in monthly business survey

There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several alternative techniques of estimation, less sensitive to outliers, have been proposed in the statistical literature. In this paper we attempt to apply and assess some robust regression methods (LTS, M-estimation, S-estimation, MM-estimation) in the business survey conducted within the framework of official statistics