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. 2019 Jun 27;8:123. doi: 10.4103/jehp.jehp_453_18

Table 4.

Optimal lags in the VAR model for variables

Row Variable name Lag LogL FPE AIC HQC SBC
1 Health expenditure 1* −224.783 1.37e+10 23.871 23.888 23.971
2 GNP 1* −277.114 3.37e+11 29.38 29.397 29.479
3 GDP 1* −275.701 2.90e+11 29.231 29.248 29.331
4 National income 1* −274.550 2.57e+11 29.110 29.127 29.210
5 Consumption 1* −60.026 40.123 6.529 6.545 6.628
6 Liquidity 1* −234.603 3.84e+09 24.905 24.922 25.005
7 Inflation rate 1* −61.043 44.661 6.636 6.653 6.735
8 Budget deficit 1* −205.93 2.46e+09 24.461 24.471 24.559
9 Gini coefficient 1* 62.693 0.000 −6.388 −6.372 −6.289
10 Unemployment rate 6* −16.916 1.077 2.910 2.892 2.997
11 Population rate 1* −106.506 5348.848 11.421 11.438 11.521

The SBC, AIC, and HQC in these lagshave the minimum value and these lags are optimal. *=These lags are optimal, FPE=Final prediction error, LR=Likelihood ratio, SBC=Schwarz-Bayesian criteria, AIC=Akaike criteria, HQC=Hannan-Quinn criteria, GNP=Gross national production, GDP=Gross domestic production