Data for: Oil Price Shocks and Domestic Inflation in Thailand

Published: 03-11-2019| Version 1 | DOI: 10.17632/yyxvf477wr.1
Contributor:
Komain Jiranyakul

Description

Estimations 1. Perform unit root tests to determine the order of integration of each variable. 2. Estimate long-run equation using Gregory and Hansen (1996) algorithm. 3. Obtain the residual series from the estimated long-run equation. 4. When the ADF* of Gregory and Hansen (1996) indicates the absence of long-run relationship, non-linear cointegration tests (TAR and MTAR) of Enders and Siklos (2001) can be performed. 5. Use OLS to estimate short-run dynamic or error correction model to examine whether the long-run relationship is stable. 6. In the short-run analysis, a bivariate VECH-GARCH(1,1) model can be estimated for oil price shock and inflation series to obtain 2 volatility series. 7. Perform Granger causality tests of four variables and use unrestricted VAR model to analyze impulse response functions (IRFs) and variance decompositions (VDCs). 8. Separate oil price shock series to negative and positive components, and test for asymmetric causality using VAR and Granger causality/block exogeniet Wald tests. Then analyze IRFs for positive and negative oil price shocks and inflation rate.

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