Improving Nigeria’s Inflation Forecast with Oil Price: The Role of Estimators

In this study, we propose a supply-side augmented Phillips curve for an oil dependent (Nigerian) economy. We argue for the role of oil price as a good proxy for the supply side of inflation given the structure of the Nigerian economy, which essentially relies on oil revenue. Thus, we compare the forecast results of the oil-based augmented Phillips curve with the traditional variant, as well as time series models such as ARIMA and ARFIMA. We also test for any probable asymmetric response of Nigeria’s inflation forecast to oil price changes. The forecast analyses are conducted for both in-sample and out-of-sample periods using alternative forecast measures. We employ the estimators of Lewellen (J Financ Econ 74:209–235, 2004) and Westerlund and Narayan (J Financ Econ 13(2):342–375, 2015) in order to account for relevant statistical properties of the predictors, and their results are compared with the standard OLS estimator. In addition, we follow the extended version of Westerlund and Narayan, constructed into a linear multi-predictive form by Makin et al. (J Int Money Financ 40:63–78, 2014) and Salisu et al. (Energy Econ, 2018), and a nonlinear (asymmetric) multi-predictive model by Salisu and Isah (Econ Model, 2018). We find that the augmented (oil-based) Phillips curve outperforms its traditional version, as well as time series models for both forecast samples. However, oil price asymmetric effects become evident when large samples are employed. Also, we find that the choice of estimator does matter for accurate inflation forecasts and by implication, accounting for the salient features of the predictors, if they exist, has implications on the forecast performance. Our results are robust to alternative oil price proxies and forecast measures.