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LNYF
± 2 S.E.
Forecast: LNYF
Actual: LNY
Forecast sample: 2008 2020
Included observations: 13
Root Mean Squared Error
0.347302
Mean Absolute Error
0.305399
Mean Abs. Percent Error
7.460016
Theil Inequality Coefficient
0.041696
Bias Proportion
0.000000
Variance Proportion
0.478784
Covariance Proportion
0.521216
Theil U2 Coefficient
0.790199
Symmetric MAPE
7.366845
Figure 1. of parameter X1 and X2Result of MAPE and TIC criteria 1st p. abovebased on the information provided in the nameSince MAPE=7.46<10 and
TIC=0.042<1X1 and X2 parameters were proved to be significant. Now, the significance of the
regression equation based on the Fisher criterion is determined when α=0.05, k1=8; at
k2=3
𝐹
жад
=
8.81from the equality to .and from the equality according to the condition
𝐹
жад
<
𝐹
ҳисоб
𝐹
ҳисоб
= 65,4
Since DW=1.96 there is no autocorrelation(---)-regression equation defined
below:
𝐿𝑛𝑌 = 0,35𝐿𝑛𝑋3 − 0,01𝐿𝑛𝑋1 − 0,01445𝐿𝑛𝑋2 + 1,4
(---)
is reliable and adequate, this (---)-regression equation is exponentiated to get rid of the logarithm,
and the (---)-regression equation becomes:
𝑌 =
𝑋3
0,35
∗𝑒
1,4
𝑋1
0,01
∗𝑋2
0,01445
(--) If we give an economic interpretation to this (--)-regression equation, it was found that if
production costs and energy consumption in the enterprise are reduced by 100%, the efficiency of
enterprise management will increase by 0.014% and 0.02%, respectively. However, if the raw
material consumption is increased by 100%, the management efficiency is found to increase by
0.47%. In turn, it is appropriate to provide the enterprise with raw materials as much as possible
while promoting the relations of economic cooperation in the management of the enterprise, and
in this regard, any available opportunity should be used.
Now we will carry out an econometric analysis of the influence of factors such as
production costs - X1, energy consumption - X2 and raw material consumption - X3 on the change
of management efficiency - Y, calculated using the statistical data of "Koqon oil-oil" JSC for the
years 2008-2020. First, we can check the correlation coefficient between these factors and the
resulting factor (strong or weak) by conducting econometric analyzes and the order of selection of
factors (Table 3).
1x1>10>