Page 10 - Azerbaijan State University of Economics
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THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.80, # 2, 2023, pp. 4-13
Table 4: ARIMA model for household expenses on food
Dependent Variable: D(EXPONFOOD)
Method: Least Squares
Date: 01/08/23 Time: 12:21
Sample (adjusted): 8 14
Included observations: 7 after adjustments
Failure to improve SSR after 11 iterations
MA Backcast: 2 7
Variable Coefficient Std. Error t-Statistic Prob.
C 6.787033 2.967827 2.286869 0.0841
AR(6) 0.549085 0.450273 1.219449 0.2897
MA(6) -0.946182 0.342401 -2.763377 0.0507
R-squared 0.990023 Mean dependent var 5.585714
Adjusted R-squared 0.985034 S.D. dependent var 2.927700
S.E. of regression 0.358159 Akaike info criterion 1.081849
Sum squared resid 0.513112 Schwarz criterion 1.058668
Log likelihood -0.786472 Hannan-Quinn criter. 0.795332
F-statistic 198.4574 Durbin-Watson stat 2.036730
Prob(F-statistic) 0.000100
Using ARIMA models in tables 2-4 Engel curve components: household income,
expenses, expenses on food were forecasted for the next five years (table 5). Expenses
on food are calculated based on obtained data.
Table 5: Forecast results for Engel Curve components between 2022-2026
Expenses on food (%
№ Years Income Expenses Expenses on food
in total)
1 2022 309.10 315.76 141.71 0.45
2 2023 317.00 319.79 150.54 0.47
3 2024 324.36 325.76 154.98 0.48
4 2025 331.26 325.57 160.44 0.49
5 2026 337.73 330.36 166.44 0.50
According to table 5 it can be inferred that household income, expenses, and expenses
on food forecast for 2022-2026 will show relatively gradual increment in comparison
with factual data dinamics which markedly increased till 2021. It can also be derived
that expenses on food will increase from 45% to 50%. The trend patterns of forecasted
items are illustrated in figure 1.
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