Page 17 - Azerbaijan State University of Economics

Gorkhmaz Imanov, Asif Aliyev : Fuzzy Linguistic Forecasting of Social Mobility

If the elements of a discrete transition matrix in the formula (11) replaced with
linguistic variables, the following fuzzy linguistic transition matrix can be obtained:

4
5
3
1
2

1

2
‖
‖
2018 =
Место для уравнения.
‖
‖
3
4
5

The elements of the vector in the expression (10) are defined by the following
formula:
= U( ∧ ) (20)

By estimation of elements forecasted fuzzy linguistic vector is obtained:

2018 = (VL, L, H, M, L)
The elements of this vector are determined in the following order:

= U[(VL∧VL), (VL∧VL), (VL∧VL), (VL∧VL), (VL∧VL)] = VL
1
= U[(L∧VH), (L∧VH), (L∧VL), (L∧VL), (L∧VL)] = L
2
= U[(VH∧VL), (VH∧VL), (VH∧H), (VH∧VL), (VH∧VL)] = H
3
= U[(M∧VL), (M∧VL), (M∧VL), (M∧VH), (M∧VL)] = M
4
= U[(L∧VL), (L∧VL), (L∧VL), (L∧VL), (L∧H)] = M (14)
5

The results show that there has been a subtle change in the social mobility indices
for – group which denotes low satisfied people. Thus, the social mobility index
3
is going to descend from very high to high. The inexistence of change in other social
strata mobility indices is due to the fact that the transition matrix covers only recent
data.

CONCLUSIONS
In the article, the mobility indices of social groups were calculated based on the
methods proposed by Theil, Fields and Ok separately for 2009, 2013, and 2017. It
was found that the mobility indices for the low satisfied group were high, medium
for the moderate satisfied group, and low for other strata.

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