چکیده:
This paper investigates the relationship between inflation and growth uncertainty in Iran for the period of 1988-2008 by using quarterly data. We employ Generalized Autoregressive Conditional Heteroscedasticity in Mean (GARCH-M) model to estimate time- varying conditional residual variance of growth, as a standard measures of growth uncertainty. The empirical evidence shows that growth uncertainty affects the level of inflation. This result is in line with Feizi Yengjeh (2010), supporting Deveraux (1989) hypothesis.
خلاصه ماشینی:
"We employ Generalized Autoregressive Conditional Heteroscedasticity in Mean (GARCH-M) model to estimate time- varying conditional residual variance of growth, as a standard measures of growth uncertainty.
To investigate the relationship between growth uncertainty and inflation in Iran we report the estimation result of the GARCH-M model in Table 8.
Table 8: The Estimation Result of GARCH-M(1,1) Model for Inflation به تصویر صفحه مراجعه شود)) The coefficient of conditional variance in the mean equation (λ) is positive and significant, which means that growth rate uncertainty affects inflation positively.
0000 prob To investigate the relationship between growth uncertainty and inflation, we use EGARCH-M model as follows: 2 t 0 1 t −1 2 t −4 3 t −6 Tεt t (15) 2 2 2 σ = φ1 + φ2υt −1 + θσ υ (16) We report the estimation result of this model in Table 14.
Table 14: The Estimation Result of EGARCH-M model of inflation به تصویر صفحه مراجعه شود)) The coefficient of conditional variance in the mean equation (λ) is positive and significant, which means that growth uncertainty affects on inflation.
5. Conclusion: In this paper, we have investigated empirically the relationship between growth uncertainty and inflation in Iran for the period of 1988- 2008 by using quarterly data and applying GARCH-M model.
"The relationship between Inflation and Inflation Uncertainty in Iran, Evidence from GARCH and State-Space Modeling (1961-2003)", Journal of Economic Research, 74, 25-55."