Inflation and Inflation Uncertainty in Nigeria: A Test of the Friedman's Hypothesis (original) (raw)
Related papers
Exponential GARCH Modelling of the Inflation-Inflation Uncertainty Relationship for Ghana
Modern Economy, 2014
This study examines the asymmetric effects of inflation on inflation uncertainty in Ghana for the period 1963:4 to 2014:2. Exponential Generalized Autoregressive Heteroscedasticity (EGARCH) model is employed on monthly inflation rates to estimate inflation uncertainty. Two complementary approaches are used to determine the empirical relationship between inflation and its uncertainty. In the first approach, inflation dummy is included in the variance equation and in the second, we employ the two-step procedure in which Granger causality test is performed on the monthly inflation rates and the conditional variance generated from the EGARCH model. We find strong support for both Friedman-Ball and Cukierman-Meltzer hypotheses for the full sample as well as the inflation targeting period. Given the current build-up in inflationary pressures in Ghana, our results warn of possible costs of not keeping inflation in check. The major policy implication that follows from this study is that the Bank of Ghana should strive to minimize the gap between actual and target inflation levels so the public will have consistent belief in all announced policy targets.
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.
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.
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.
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
Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models
2018
Based on time series data on inflation rates in Nigeria from 1960 to 2016, we model and forecast inflation using ARMA, ARIMA and GARCH models. Our diagnostic tests such as the ADF tests indicate that NINF time series data is essentially I (1), although it is generally I (0) at 10% level of significance. Based on the minimum Theil’s U forecast evaluation statistic, the study presents the ARMA (1, 0, 2) model, the ARIMA (1, 1, 1) model and the AR (3) – GARCH (1, 1) model; of which the ARMA (1, 0, 2) model is clearly the best optimal model. Our diagnostic tests also indicate that the presented models are stable and hence reliable. The results of the study reveal that inflation in Nigeria is likely to rise to about 17% per annum by end of 2021 and is likely to exceed that level by 2027. In order to address the problem of inflation in Nigeria, three main policy prescriptions have been suggested and are envisioned to assist policy makers in stabilizing the Nigerian economy.
Oil Price Volatility and Inflation Level in Nigeria: An Exponential Garch Approach
International Journal of Advanced Research, 2021
Over the years, expenditures of public and private sectors are regulated by the activities in the oil and gas industry. The budget of Nigeria is hinged on the international price of crude oil and any shock on oil price affects the general activities in the country. With quarterly data from the period of 1981Q1 to 2020Q2, the study uses an exponential generalized autoregressive conditional heteroscedasticity approach to examine oil price volatility and inflation level in Nigeria. An augmented Dicky-Fuller unit root test and bound test cointegration approach were used to test for stationarity and existence of long run association among the variables respectively. The study found that negative shocks in real oil price affects the volatility of the inflation level. Also, it was observed that aside real oil price volatility, interest rate and real gross domestic product volatilities affect the volatility of the inflation level. The study therefore recommends among other things that polic...
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...
Forecasting Inflation in Kenya Using Arima-Garch Models
2015
The aim of this study was to empirically develop ARIMA-GARCH models for Kenya inflation and to forecast the rates of inflation using the historical monthly data from 2000 to 2014. The empirical research employs time series analysis, ordinary least square and auto-regressive conditional heteroscedastic to find the estimators. The forecasting inflation analysis have been conducted using two models, the ARIMA (1, 1, 12) model was able to produce forecasts based on the stationarity test and history patterns in the data compared to GARCH (1,2) model. The empirical results of 180 monthly data series indicate that the combination between ARIMA(1,1,12)GARCH(1,2) model provide the optimum results and effectively improved estimating and forecasting accuracy compared to the other previous methods of forecasting.
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...