Exponential GARCH Modelling of the Inflation-Inflation Uncertainty Relationship for Ghana (original) (raw)
Related papers
In the present study, we examine the relationship between inflation and inflation uncertainty in Ghana from 1964Ghana from :04 to 2012 At the first step, GARCH(1,2)-M model of monthly inflation data is estimated and the conditional variance from these estimates is used to as proxy for inflation uncertainty. Then, the Granger causality tests between actual inflation and our generated inflation uncertainty series are performed. Two main results follow from this paper. First, we find strong statistical support for the Friedman-Ball hypothesis: inflation significantly raises inflation uncertainty in Ghana over the full sample period and two subsamples at different lag lengths. Second, we also find evidence of inflation uncertainty affecting inflation in the long run as suggested by the Cukierman and Meltzer Hypothesis. Thus, results of this study have significant implications for Ghanaian Inflation Targeting (IT) efforts as well as the literature focusing on the relationship between inflation and inflation uncertainly in developing countries that are contemplating adopting inflation targeting. The policy implication is to aim at low average inflation rates in order to reduce the negative consequences of inflation uncertainty.
INFLATION UNCERTAINTY AND INFLATION TARGETING IN NIGERIA: EVIDENCE FROM GARCH MODELING
Nigerian Journal of Economies and Social Science , 2008
This paper examines the empirical relationship between inflation, inflation uncertainty and inflation targeting over time (1970-2003) using the Nigerian consumer price index. Uncertainty was measured using the Generalized Autoregressive Conditional Heteroscedasticity (AR GARCH) model. Our results suggest that there exists a positive relationship between the trend inflation and the measure of uncertainty. This linear relationship breaks down, however, when the time series data are sorted in ascending order of trend inflation and disaggregated into low and high inflation sub periods. In general, the relationship is negative at low inflation but significantly positive at high inflation. We conclude that the monetary authority in Nigeria should conduct the inflation policy in the range of the threshold level at which the tendency of structural change is highest.
Inflation and Inflation Uncertainty in Nigeria: A Test of the Friedman's Hypothesis
2016
This paper examines the relationship between inflation and inflation uncertainty in Nigeria. It attempts to test whether the Friedman’s hypothesis – that a rise in the average rate of inflation leads to more uncertainty about future rate of inflation - holds for the country. The monthly inflation data spanning the period 1960:1 to 2014:07 was used. Inflation uncertainty was modeled as a time varying process using a GARCH framework. Exponential Generalized Autoregressive Heteroscedasticity (EGARCH) complemented by seasonal ARIMA (2, 0, 2) (0, 0, 1) was employed to model the inflation uncertainty. Given that inflation series display structural breaks, this was tested and found to be significant which was accounted for in the model. The EGARCH fitted our data better than the symmetric GARCH model. The bivariate Granger Causality test was performed on inflation and its uncertainty; it showed that inflation causes inflation uncertainty in Nigeria. The fitted EGARCH model found strong sup...
Modeling Inflation and Exchange Rates in Ghana: Application of Multivariate GARCH Models
This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana. Keywords: DCC, BEKK, GARCH, Ghana, volatility, inflation, exchange, interest rates
Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models
This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana.
2013
This paper describe an empirical study of modeling financial time series data with application to inflation rate data for Nigeria. The theory of univariate non-linear time series analysis is explored and applied to the inflation data spanning from January, 1995 to December, 2011. The diagnostic checking has shown that the fitted model (GARCH(1,0) + ARMA(1,0)) is appropriate. A two-year (24 months) forecast from January 2012 to December 2013 was made. This empirical results have more general implications for small scale macroeconomics and will also be helpful for policy makers and citizens of the Federal Republic of Nigeria.
Understanding the Dynamics of Inflation Volatility in Nigeria: A GARCH Perspective
GARCH) family with a view to providing a parsimonious approximation to the dynamics of Nigeria's inflation volatility between 1996 and 2011. Of the competing models, the asymmetric TGARCH (1,1) provides an appropriate paradigm for explaining the dynamics of headline and core CPI volatilities in Nigeria, while the symmetric GARCH (1,1) was found to be adequate for food CPI. The results are quite revealing. Firstly, model outcomes indicate high persistence parameters for the core and food CPI, implying that the impacts of inflation shocks on their volatilities die away very slowly. However, the impact of inflation shocks on headline volatility die out rather quickly. Secondly, substantial evidence of asymmetric effect was found for both headline and core inflation types while the contrary was confirmed for food inflation. Thirdly, positive inflationary shocks yielded higher volatilities in headline and core inflation than negative innovations, implying the absence of leverage effect in them. The paper finds that periods of high inflation volatility are associated with periods of specific government policy changes, shocks to food prices and lack of coordination between monetary and fiscal policies. JEL Classification: C22, C51, C52, E31
Modelling Rates of Inflation in Ghana: An Application of ARCH Models
This study sought to model rates of inflation in Ghana using the Autoregressive Conditional Heteroscedastic models. In particular, the ARCH, GARCH and EGARCH models were compared. Monthly rates of inflation from January 2000 to December 2013 were used in the study with the rates from January 2000 to December 2012 serving as the training set and January 2013-December 2013 serving as the validation set. The result revealed that the EGARCH (1, 2) model with a mean equation of ARIMA (3, 1, 2) × (0, 0, 0)12 was appropriate for modelling Ghana’s monthly rates of inflation. A one year out-of-sample forecast for the year 2014 shows that Ghana would experience double digit inflation with an end of year inflation rate of 15.0% and a margin of error of 0.9%. This study would inform and guide policy-makers as well as investors and businessmen on management of expected future rates of inflation.
On the Inflation-Uncertainty Hypothesis in The Gambia: A Multi-Sample View on Causality Linkages
2018
The connection between inflation and inflation-uncertainty hypothesis has been tested in so many countries, yet in The Gambia testing the relationship and accounting for structural changes as not been given serious attention to the literature. This paper modelled the inflation-uncertainty hypothesis using monthly inflation series from 1970(1)-2017(5). The GJR-GARCH model was used to generate the conditional variance of the inflation proxied as inflation uncertainty. Then the Pearson correlation was employed across the various samples, and the results vary in sign and magnitude reflecting structural changes within The Gambia’s economy. Finally, Toda Yamamoto (1995) causality test was employed. The results show strong support of a feedback relationship for both the Friedman-Ball and Cukierman-Meltzer hypothesis for the full sample as well as the post Economy Reform Program (ERP) sample; while during the Inflation Targeting Era (ITE) sample; the results indicate strong support of the F...
Modelling Rates of Inflation in Kenya: An Application of Garch and Egarch Models
Mathematical theory and modeling, 2017
The purpose of this study was to determine an effective Arch-type model for forecasting Kenya’s inflation. Using Kenya monthly inflation data from January 1990 to December 2015, the performance of GARCH and EGARCH type models was analyzed to come up with the best model for forecasting Kenyan inflation data. Since the inflation series is non-stationary, the Consumer Price Index (CPI) was first transformed to return series by logarithmic transformation. Afterwards, the data was tested for the presence of ARCH effects and serial correlation using both Ljung Box Pierce Q test and Engle Arch test. The test showed presence of heteroscedasticity and correlation in the inflation return series which is a key feature of a financial time series data. The project adopted AIC and BIC in selecting the the best model. From the fitted models EGARCH (1,1) had the smallest AIC and BIC values followed by the GARCH(1,1) model. Model diagnostic test was conducted on the selected model EGARCH (1,1) model...