A Text Mining Analysis of Central Bank Monetary Policy Communication in Nigeria

This paper employs text-mining techniques to analyse the communication strategy of the Central Bank of Nigeria (CBN) during the period 2004-2019. Since the policy communique released after each meeting of the CBN’s monetary policy committee (MPC) represents an important tool of central bank communication, we construct a corpus based on 87 policy communiques with a total of 123, 353 words. Having processed the textual data into a form suitable for analysis, we examined the readability, sentiments, and topics of the policy documents. While the CBN’s communication has increased substantially over the years, implying increased monetary policy transparency; the computed Coleman and Liau readability index shows that the word and sentence structures of the policy communiques have become more complex, thus reducing its readability. In terms of monetary policy sentiments, we find an average net score of -10.5 per cent, reflecting the level of policy uncertainties faced by the MPC over the sample period. In addition, our results indicate that the topics driving the linguistic contents of the communiques were influenced by the Bank’s policy objectives as well as the nature of shocks hitting the economy per period

Economic policy uncertainty index for Nigeria

We construct an index of economic policy uncertainty (EPU) for Nigeria following the news-based approach developed by Baker et al. (2016). The index is based on news articles published by five Nigerian newspapers over the period April 2016 – June 2023.The computed index tracks major events in the country, increasing during periods of higher uncertainties around key economic and political developments. For instance, the economic recession of 2016, the COVID-19 pandemic, and the country’s election cycles were associated with higher levels of the index. The computed index is useful for economic and policy analyses

Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques

The recent economic conundrum arising from the fall in the international oil price has threatened the maintenance of price stability, a key function of the central bank, therefore the need to investigate predictors of inflationary measures arises. The model averaging method considers uncertainty as part of the model selection, and include information from all candidate models. We analysed a wide spectrum of inflation predictors and all the possible models for Nigeria CPI inflation using the Bayesian Model Averaging and Weighted Average Least Squares. The study uses fifty-nine (59) predictor variables cutting across all sectors of the Nigerian economy and three (3) measures of inflation, namely; all items consumer price index, core consumer price index and food consumer price index. The results from both model averaging techniques showed that maximum lending rate, world food price index and Bureau de change exchange rate are the significant drivers of inflationary measures among focus variables, while foreign assets, credit to private sectors, net credit to government and real effective exchange rate are the drivers of inflationary measures, for the auxiliary variables, strongly supporting the monetarist and open economy views on inflation. The structuralist view is reported to be relatively weaker because government expenditure is only significant at 10.0 per cent.

Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques

The recent economic conundrum arising from the fall in the international oil price has threatened the maintenance of price stability, a key function of the central bank, therefore the need to investigate predictors of inflationary measures arises. The model averaging method considers uncertainty as part of the model selection, and include information from all candidate models. We analysed a wide spectrum of inflation predictors and all the possible models for Nigeria CPI inflation using the Bayesian Model Averaging and Weighted Average Least Squares. The study uses fifty-nine (59) predictor variables cutting across all sectors of the Nigerian economy and three (3) measures of inflation, namely; all items consumer price index, core consumer price index and food consumer price index. The results from both model averaging techniques showed that maximum lending rate, world food price index and Bureau de change exchange rate are the significant drivers of inflationary measures among focus variables, while foreign assets, credit to private sectors, net credit to government and real effective exchange rate are the drivers of inflationary measures, for the auxiliary variables, strongly supporting the monetarist and open economy views on inflation. The structuralist view is reported to be relatively weaker because government expenditure is only significant at 10.0 per cent.

Forecasting Nigerian Inflation using Model Averaging methods: Modelling Frameworks to Central Banks

As a result of the adverse macroeconomic effect of inflation on welfare, fiscal budgeting, trade performance, international competitiveness and the whole economy, inflation still remains a subject of utmost concern and interest to policy makers. The traditional Philips curve as well as other methodologies have been criticized for their inability to track correctly the pattern of inflation, particularly, these models do not allow for enough variables to be included as part of the regressors, and judgment is often made by a single model. In this work, model averaging techniques via Bayesian and frequentist approach were considered. Specifically, we considered the Bayesian model averaging (BMA) and Frequentist model averaging (FMA) techniques to model and forecast future path of CPI inflation in Nigeria using a wide range of variables. The results indicated that both in-sample and out-of-sample forecasts were highly reliable, judging from the various forecast performance criteria. Various policy scenarios conducted were highly fascinating both from the theoretical perspective and the prevailing economic situation in the country

Forecasting Nigerian Inflation using Model Averaging methods: Modelling Frameworks to Central Banks

As a result of the adverse macroeconomic effect of inflation on welfare, fiscal budgeting, trade performance, international competitiveness and the whole economy, inflation still remains a subject of utmost concern and interest to policy makers. The traditional Philips curve as well as other methodologies have been criticized for their inability to track correctly the pattern of inflation, particularly, these models do not allow for enough variables to be included as part of the regressors, and judgment is often made by a single model. In this work, model averaging techniques via Bayesian and frequentist approach were considered. Specifically, we considered the Bayesian model averaging (BMA) and Frequentist model averaging (FMA) techniques to model and forecast future path of CPI inflation in Nigeria using a wide range of variables. The results indicated that both in-sample and out-of-sample forecasts were highly reliable, judging from the various forecast performance criteria. Various policy scenarios conducted were highly fascinating both from the theoretical perspective and the prevailing economic situation in the country

Economic policy uncertainty index for Nigeria

We construct an index of economic policy uncertainty (EPU) for Nigeria following the news-based approach developed by Baker et al. (2016). The index is based on news articles published by five Nigerian newspapers over the period May 2009 – June 2023.The computed index tracks major events in the country, increasing during periods of higher uncertainties around key economic and political developments. For instance, the terrorist activities of 2011, negative oil price shocks of 2014, the economic recession of 2016, the COVID-19 pandemic, and the country’s election cycles were associated with higher levels of the index. The computed index is useful for economic and policy analyses

Climate change and fossil fuel prices : a GARCH-MIDAS analysis

In this study, we investigate the connection between climate change and the volatility of fossil fuel prices using the GARCH-MIDAS framework which accommodates mixed data frequencies and by extension circumvents information loss due to splicing or aggregation of one variable for the other. We conduct a battery of robustness tests that allow for nominal and real prices of fossil fuels as well as global financial crises (GFC). We show a strong connection between climate change and the volatility of fossil fuel prices albeit with stronger evidence in the post-GFC period. The outcome is positive in the recent period and therefore climate change seems to have heightened the volatility in the fossil fuel market. Even when the real prices are considered, results remain consistent, indicating that inflationary pressures do not diminish the effect of climate change on fossil fuel price volatility. We also show that own market risk positively impacts the volatility of fossil fuel prices and the volatility tends to persist when there is a shock to the fossil fuel market. More conscious efforts are needed to effectively discourage increased investments in environmentally-degrading assets.https://www.elsevier.com/locate/eneeco2025-06-17hj2023EconomicsSDG-08:Decent work and economic growthSDG-13:Climate actio

Disentangled oil shocks and stock market volatility in Nigeria and South Africa : a GARCH-MIDAS approach

In this study, we investigate the effects of disentangled oil shocks on the volatility of the stock markets of Nigeria and South Africa using the Mixed Data Sampling variant of the Generalized Autoregressive Conditional Heteroscedasticity (GARCH-MIDAS) model. The disentangled oil shocks involve oil supply shock, economic activity shock, oil consumption demand shock, and oil inventory demand shock covering January 2010 and July 2022. Overall, we find that the stock market volatilities of Nigeria and South Africa respond similarly to oil supply shock and oil consumption demand shock but differently to economic activity shock and oil inventory demand shock. The unusual increase in the volatility of Nigeria’s stock market has been attributed to the loss of investors’ confidence which takes a too long time to be restored. Our results are robust to alternative forecast sampling techniques, particularly fixed and rolling windows.https://www.elsevier.com/locate/eap2025-04-24hj2023Economic

Oil-growth nexus in Nigeria : an ADL-MIDAS approach

In this study, we investigate the effect of oil price on the real GDP growth of Nigeria. We contribute to the extant literature on oil price-growth nexus in three ways. First, we employ one of the recently developed Mixed Data Sampling models owing to its ability to accommodate both high and low data frequencies in the same predictive model. Second, we examine the impact of crude oil price on aggregate as well as sectoral output growth, with focus on agriculture, industry and service sectors. Third, we account for the role of macroeconomic/control variables and crude oil price asymmetry. Our results show that accounting for crude oil price asymmetry and macroeconomic determinants increases the predictability of the ADL-MIDAS model for the oil price-growth nexus. On the aggregate, we find that negative oil price changes significantly reduce economic growth while positive oil price changes do not increase economic growth significantly. The sectoral analyses show that the service and industry sectors are more affected by the negative oil price changes than the agriculture sector. Overall, we conclude that the impact of government participation in the economy remains huge and the situation whereby recurrent to capital expenditure ratio of government is about 80/20 percent dampens the growth potential of the Nigerian economy. More investment in capital infrastructure relative to recurrent expenditure is recommended, to reduce the adverse effect of negative crude oil price on economic growth in Nigeria.https://www.elsevier.com/locate/resourpol2025-05-11hj2022Economic