Mathematical Problems in Engineering / 2014 / Article / Tab 11

Research Article

Modelling Inflation Uncertainty with Structural Breaks Case of Turkey (1994–2013)

Table 11

Most appropriate obtained GARCH-type of models and their constraints for inflation series.

ParametersSymmetricAsymmetric
ARCH EGARCH

0.014242 (0.0002)0.013473 (0.0017)
0.476255 (0.0000)0.470196 (0.0000)
0.132779 (0.0197)0.152300 (0.0000)
0.457314 (0.0000)0.483289 (0.0000)
0.127269 (0.0088)0.151228 (0.0001)
0.009516 (0.0000)0.009930 (0.0000)
0.005730 (0.0053)0.004573 (0.0066)
−0.007033 (0.0002)−0.007627 (0.0000)
0.010459 (0.0000)0.010297 (0.0000)
0.014071 (0.0000)0.014152 (0.0000)

Variance equation

(0.0000)−14.69140 (0.0000)
0.161211 (0.0381)0.231022 (0.0973)
−0.418258 (0.0335)
0.215865 (0.0127)
(0.0004)1.855822 (0.0000)

Constraints

Mean reverting level0.000039
Stationarity0.161211
Nonnegativity
0.015157
0.446887

Criteria

Adjusted 0.8319300.830115
Log-likelihood805.4523809.2823
ARCH-LM (-statistics)0.903991 (0.3427)0.212247 (0.6454)
Stationarity of residuals*StationaryStationary
Selected modelARCH(1)EGARCH(1, 1)

Stationarity of selected the model residuals has been diagnosed using ADF, PP, and KPSS unit root tests with 5% significance level.
Values between brackets represent the significant P level.