Inflation Rate Volatility and Household Final Consumption Expenditure: Evidence from Cameroon

Abstract

Aims: The study aims to examine the effects of inflation rate volatility on household final consumption expenditure in Cameroon. Studies on inflation rate and household final consumption expenditure in Cameroon are limited. This study provides a new insight into how inflation rate fluctuations affect household consumption expenditure in Cameroon.
 Study Design: The study made use of an ex-post facto research design as the researcher has no control over the variables.
 Place and Duration of the Study: The study was conducted in Cameroon using World Bank data from 1980-2020.
 Methodology of the Study: The objectives of the study were accomplished using the autoregressive distributive lag (ARDL) bound test and error correction model (ECM) based on the conclusion of the unit root test.
 Results: The findings indicate that the inflation rate has a positive and significant effect on household final consumption expenditure in both the short and long run.
 Conclusion: The study concludes that an unstable inflation rate has a great impact on household final consumption expenditure in Cameroon.

Financial Development and Economic Growth in Cameroon: An Ardl Bound Test and Multivariate Granger Causality Framework

“…A key ingredient in time series data is to make sure that the series is not serially correlated, there is no heteroscedasticity, the model is correctly specified, and the residual term is normally distributed (Ewane & Abonongi 2022). The diagnostic results in Table 1.7 confirmed there is no autocorrelation and heteroscedasticity.…”

“…Thus, GDP, liquid liabilities, and financial development index have a long-run relationship. Hence, it is imperative to run two tests in this study; the ARDL which will capture the short run and ECM which capture the long run (Ewane & Abonongi 2022).…”

“…To tackle structural breaks, it is usually imperative to also conduct a unit root test that accounts for possibilities of structural breaks especially in time series data which usually suffer from structural breaks (see Figure 1.1 and 1.2). This is also to make sure none of the variables are integrated of order 2 in order not to render the autoregressive distributive lag (ARDL) invalid (Ewane & Abonongi 2022). In this case, the Zivot-Andrews unit root test with a single structural breakpoint is applied (Andrews & Zivot 1992).…”

“…Once the calculated F-statistics is greater than the critical values for the upper bound, cointegration is assumed. If there is cointegration, it is an indication that the series are related and would merge with time in the long run (Ewane & Abonongi 2022).…”