A predictive model for inflation in Nigeria
Nse S. Udoh and Anietie S. Isaiah
The study estimates a dynamic model using quarterly data spanning 1995 to 2016. Four dynamic models: level lagged variables, differenced lagged variables, log-transformed lagged variables and differenced log-transformed lagged variables were considered. The best predictive model was selected based on the Schwarz Information Criterion (SIC) value. From the empirical results, the level form models performed better than the differenced form models. On the basis of model parsimony, the level lagged model was the preferred model among the set of selected models. Predictions obtained from the model indicate that the model is stable as actual interest rate (IR) values, fall well within the computed 95% prediction interval. The study concludes that previous values of IR and money supply (MS) are significant in predicting future ination rates in Nigeria.
Year of publication: |
2019
|
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Authors: | Udoh, Nse S. ; Isaiah, Anietie S. |
Published in: |
CBN journal of applied statistics. - Abuja : Central Bank of Nigeria, ISSN 2476-8472, ZDB-ID 2854997-1. - Vol. 9.2018, 2, p. 103-129
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Subject: | Autoregressive Distributed Lag Model | Inflation Rate | Predictive Model | Inflation | Prognoseverfahren | Forecasting model | Nigeria | Kointegration | Cointegration | Inflationsrate | Inflation rate | Zeitreihenanalyse | Time series analysis |
Saved in:
freely available
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.33429/Cjas.09218.5/6 [DOI] hdl:10419/219295 [Handle] |
Classification: | E52 - Monetary Policy (Targets, Instruments, and Effects) |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012031209
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