About this project
This statistics project fits time series models to historical monthly inflation data. It tests for stationarity, identifies and estimates ARIMA specifications, validates them with diagnostic checks, and evaluates out-of-sample forecast accuracy against naive benchmarks, producing a twelve-month inflation forecast with confidence intervals.
Methodology
Time series analysis
Chapters 1–5 outline
Chapter 1
Introduction: background to inflation forecasting, statement of the problem (policy and business planning need reliable short-term inflation forecasts), aim and objectives, research questions, scope, significance of the study, and definition of terms.
Chapter 2
Literature Review: theoretical framework, review of related works on inflation forecasting, gaps in existing studies, and a summary positioning this project.
Chapter 3
Methodology / System Analysis and Design: time series design; Box-Jenkins methodology; forecast evaluation. Includes data collection method, system requirements, use-case and architecture diagrams (or population, sample size, and instrument).
Chapter 4
Implementation and Results: a validated ARIMA model and twelve-month forecast. Presentation of findings, testing, evaluation, and discussion of results.
Chapter 5
Summary, Conclusion and Recommendations: key findings, contribution to knowledge, limitations, and recommendations for further research.
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