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A project submitted to the Department of Statistics

Time Series Analysis and Forecasting of Inflation Rates

By

Halima Abdullahi

U/2014/ABC/0208

In partial fulfilment of the requirements for the award of a Bachelor's degree

Supervisor:

2024

Abstract

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. The study is organised into five chapters covering the introduction, review of related literature, research methodology, data presentation and analysis, and the summary, conclusion and recommendations.

Table of Contents

Chapter One: Introduction

  1. 1.1 Background to the Study4
  2. 1.2 Statement of the Problem6
  3. 1.3 Aim and Objectives of the Study8
  4. 1.4 Research Questions10
  5. 1.5 Research Hypotheses12
  6. 1.6 Scope of the Study14
  7. 1.7 Limitations of the Study16
  8. 1.8 Operational Definition of Terms18

Chapter Two: Literature Review

  1. 2.1 Conceptual Review16
  2. 2.2 Theoretical Framework18
  3. 2.3 Empirical Review of Related Studies20
  4. 2.4 Gap in Literature22
  5. 2.5 Summary of Literature Review24

Chapter Three: Research Methodology

  1. 3.1 Research Design28
  2. 3.2 Area of the Study30
  3. 3.3 Population of the Study32
  4. 3.4 Sample and Sampling Technique34
  5. 3.5 Instrument for Data Collection36
  6. 3.6 Validity and Reliability of the Instrument38
  7. 3.7 Method of Data Collection40
  8. 3.8 Method of Data Analysis42

Chapter Four: Data Presentation and Analysis

  1. 4.1 Data Presentation40
  2. 4.2 Test of Hypotheses42
  3. 4.3 Discussion of Findings44

Chapter Five: Summary, Conclusion and Recommendations

  1. 5.1 Summary of Findings52
  2. 5.2 Conclusion54
  3. 5.3 Recommendations56
  4. 5.4 Suggestions for Further Studies58

References

Appendices

Final YearPreview only

Chapter One: Introduction

1.1 Background to the Study

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.

1.2 Statement of the Problem

Fits ARIMA models to historical inflation data and evaluates forecast accuracy. Existing approaches remain limited in reach, accuracy and ease of use, which creates the gap this study addresses.

1.3 Aim and Objectives

The aim of this study is to time series analysis and forecasting of inflation rates. The specific objectives are to:

  1. review existing literature and systems related to the study;
  2. collect and analyse data using Time series analysis;
  3. evaluate the results against the stated problem;
  4. make recommendations for practice and further research.

1.4 Scope of the Study

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 Two: Literature Review

Literature Review: theoretical framework, review of related works on inflation forecasting, gaps in existing studies, and a summary positioning this project. Literature Review: theoretical framework, review of related works on inflation forecasting, gaps in existing studies, and a summary positioning this project.

Chapters 2–5 are not part of this preview.