Forecasting inflation in a small open developing economy

ABSTRACT

The transition to a model-based forecasting environment is encountered by hurdles in a small open developing economy. An attempt is made to validate the benefits of model-based inflation forecasting for central banks in small open developing economies. Despite data limitations, two distinct VARs are designed to project near-term inflation. Batteries of tests (such as sequential forecasts, out-of-sample forecasting errors, equal-weight forecasting errors and decomposition) are performed on the two models to assess their predictive ability. The main finding is that model-based forecasts are reliable for use by central banks in small open developing economies, as substantiated by the relatively low forecasting errors.

KEYWORDS:

• Inflation
• forecasting
• BVAR
• BVECM
• small open economy

JEL CLASSIFICATION:

• E17
• E27
• E37
• E52

Disclaimer

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The views expressed in this paper are those of the author(s) and do not necessarily represent those of the Central Bank of Mauritius. Any errors are the authors’ responsibility.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ See Gupta and Sichei (2006) for a detailed exposition of VECM.

² See Gupta and Sichei (2006) and Madhou et al. (2017) for a detailed description of BVAR.

³ The ‘curse of dimensionality’ is triggered by the use of equal number of lags for each variable, adding to the coefficients to be estimated and exhausting the degrees of freedom.

⁴ Three lag selection criteria are used: Akaike, Schwartz and Hannan-Quinn.

⁵ The cointegrating relationships are illustrated in Figures 1 and 2. Co-movements between global oil prices and domestic oil prices and between global food prices and domestic food prices are depicted in Figures 1 and 2, respectively. The co-movements show the long-term relationship between foreign and domestic variables. The oil and food gaps, calculated as the difference between global and domestic prices, are mean reverting.

⁶ Private sector credit is treated as an endogenous variable in the BVAR model and as an exogenous variable in the BVECM.

⁷ Imported CPI is proxied by the Eurozone CPI in US Dollars.

⁸ Seasonal adjustment is performed using the X-13 technique.

⁹ Supply shocks, such as unfavourable climatic conditions affecting vegetables and disease ravaged meat products, are the main drivers influencing inflation in Mauritius, typically in the first quarter of the year.