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DIVERSIFICATION OF EXPENDITURE DISTRIBUTIONS IN THE HOUSEHOLDS OF FARMERS AND EMPLOYEES USING FARMS

100%
Dudek H.
Zagadnienia Ekonomiki Rolnej
|
2006
|
issue 2(307)
68-78
EN
The distribution of equivalent expenditures in the households of farmers and the employees using farms were studied in the article. The analysis of irregularity in these distributions was conducted using Lorenz's curves as well as different measures of concentration of the expenditure values. The scope and the depth of relative objective poverty in the households of farmers and the employees using farms were also determined. The results obtained for this group of households have been compared with the data concerning the whole population of the households in Poland.
2
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Quantitative analysis of the household’s expenditure for food

100%
Dudek H.
Problemy Rolnictwa Światowego
|
2011
|
vol. 11(26)
|
issue 3
EN
The paper deals with the dependence of the share of households’ food expenditure on the total expenditure and the household’s size. This problem is important in applied welfare economics. According to the Engel’s law, the poorer household, the greater proportion of its total expenditure is devoted to the food consumption. In the study, the Working-Leser model was applied to Polish households microeconomic data from 2000, 2005 and 2009.
3

The Relationship between a Condition Number and Coefficients of Variation

100%
Dudek H.
|
2005
|
vol. 52
|
issue 1
75-85
EN
A linear model with constant term Y = X(beta) + (eta) is considered in this paper. The problem of near linear dependencies between column 1 (referring to constant term) and remaining columns of X matrix is analysed. It is a special case of multicollinearity. For measuring multicollinearity a condition number of X(T)X (after scaling each column so that it has unit length) is applied. It is the square root ratio of the largest eigenvalue of this matrix to the smallest. Values in excess of 20 are suggested by some of researches as indicative of the multicollinearity. In a model with one regressor collinearity may be caused only by near linear dependence between the column 1 and the column of values of explanatory variable. It means that values of the explanatory variable have small variation. For measuring variability of values of this variable coefficient of variation is applied. In this paper a formula defining the relationship between the condition number and the coefficient of variation is derived. Values of a condition number greater then 20 correspond with the coefficient of variation less then 0,1. In multiple regression model relationships between columns of X matrix are more complex. It is demonstrates by using examples, that even in the cases, when all coefficients of variation exceed 0,20 and dependencies between columns of values of explanatory variables are weak, there is a possibility of multicollinearity. It is therefore claimed that, in order to avoid this problem, one should not only examine separately dependencies between column 1 and each column of X. The analysis of whole X matrix is required. The application of the two-staged procedure of the selection of the explanatory variables, which first eliminates quasi-constant variables and then uses centered correlation coefficients does not exclude multicollinearity.
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