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| Format: Ms Word | 1-5 Chapters | Table of Content|


Study Level: BTech, BSc, BEng, BA, HND, ND or NCE

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Table of Contents

Chapter One: Introduction

1.1       Background of the Study

1.2       Statement of Research Problem

1.3       Research Questions

1.4       Objectives of the Study

1.5       Significance of the Study

1.6       Scope of Limitation of the Study

1.7       Definition of Key Concepts


2.1       Introduction

2.2       Macroeconomic theories of Inflation

2.2.1    The Purchasing Power Parity Theory

2.2.2    The Monetarist Theory

2.2.3    The Structuralist Theory

2.2.4    The Structuralist – Monetarist  (hybrid) Theory

2.3       Empirical Literature



3.1       The Study Area

3.2       Data

3.3       Instrument for Data Collection

3.4       Methodology

3.5       Macroeconomic Dynamics and the General Dynamic Regression Model

3.6       Classical (static) Linear Regression Model and the Dynamic Variant

3.7       Estimation Methods for Dynamic Regression Models

3.7.1    Direct Application of OLS

3.7.2    Difference form Estimation

3.8       Model Selection Criteria

3.8.1    The R-squared (R2) Criterion

3.8.2    The Adjusted R-squared (R2) Criterion

3.8.3    The Akaike’s Information Criterion (AIC)

3.8.4    The Bayesian Information Criterion (BIC)

3.9       Model Diagnostics and Evaluation

3.9.1    Descriptive Analysis of Residuals

3.9.2    Examination of Residuals through Formal Tests

Test of normality (Jarque – Bera)

Test autocorrelation (The Breusch – Godfrey)

Test of heteroskedasticity (White)

Test of Model Specification (Ramsey Reset)

Test of Parameter Stability (Cusum)




4.1       Introduction

4.2       Exploratory Analysis

4.2.1    Descriptive Statistics of Series

4.2.2    Correlation Matrix (properties of series)

4.2.3    Time Series plots of Series (raw series)

4.2.4    Time series plot of series (log-transformed series)

4.2.5    Unit roof tests of individual series (raw

4.2.6    Unit roof tests of individual series (log-transformed series)

4.3       Model Specification

4.4       Model Estimation (GreH 1.9.91)

4.4.1    Least Squares Estimation Model I

4.4.2    Least Squares Estimation Model II

4.4.3    Least Squares Estimation Model III

4.4.4    Least Squares Estimation Model IV

4.5       Model Estimation (SPSS Version 20)

4.5.1    Least Squares Estimation Model I

4.5.2    Least Squares Estimation Model II

4.5.3    Least Squares Estimation Model III

4.5.4    Least Squares Estimation Model IV

4.6       Prediction

4.6.1    Prediction Results: Model I

4.6.2    Prediction Results:  Model II

4.6.3    Prediction Results:  Model III

4.6.4    Prediction Results: Model IV

4.7       Post Predictive Analysis

Chapter Five: Summary, Conclusions and Recommendations

5.1      Summary

5.2       Conclusion

5.3       Recommendations




This study builds a model for predicting inflation in Nigeria by exploiting the dynamic properties of Consumer Price Index (CPI), broad Money Supply (MS), real effective exchange rate (REER), and real gross domestic product (RGDP) between 1995 and 2015. CPI, MS, and REER were used as surrogates for inflation rate; stock of money in the economy after deflating with CPI; and import price respectively, while RGDP was used as a surrogate for real income of economic agents in the economy within the sample period. Guided by real-world macroeconomic conditions and considered theories of inflation, we developed a dynamic regression model expressing current value of CPI as a linear function of lagged values of itself plus lagged values of MS, REER, and RGDP. The methodology produced a multivariate time series model which was viewed as standard multiple regression model, except that in this case the independent variables were lagged values of CPI, MS, REER, and RGDP. Relying on evidence from exploratory analysis, we formulated four classes of models. Appropriate lag orders included in the dynamic models were determined by trial and error. Model estimation was carried out using the dynamic regression function in Gretl 1.9.91 which was compared with the backward selection algorithm in SPSS version 20. The final models obtained from SPSS compared favourably well with the first comprehensive dynamic regression equations obtained from Gretl for the four classes of models, except that models at levels pointed towards autocorrelated residuals, though not decisively so, using the backward selection algorithm in SPSS. The study identified past inflation rates (proxied by CPI) as the dominant predictor of inflation in Nigeria. Previous values of broad money supply (MS), real gross domestic product (RGDP) also provide substantial information in inflation prediction in Nigeria. The role of past values of real effective exchange rate in predicting inflation is negligible, though statistically significant in all the models. Prediction equations were selected based on the principle of parsimony, and the parsimonious equation that generated inflation rates that were close to the actual inflation rates was selected as the most preferred prediction equation, hence was used in predicting one year ahead inflation rates for Nigeria.






1.1       Background of the Study

An economy is regarded as suffering from inflation if it is experiencing a period of continuous rising prices resulting in loss of monetary purchasing power. Consequently, inflation has been defined as a persistent or continuous rise in the general price level or, alternatively, as a persistent or continuous fall in the value of money. When the price level increases, each unit of currency buys fewer goods and services; consequently, inflation is also the erosion in the purchasing power of money, a loss of real value in the internal medium of exchange and unit of account in the economy. In an inflationary economy, it is difficult for the national currency to act as a medium of exchange and a store of value without having adverse effect on income distribution, output and employment.

There is widespread agreement that high and volatile inflation can be damaging both to individual businesses as well as to consumers, hence, to the economy as a whole. Persistent inflation in goods and services can result in high social costs, too. In Nigeria, major afflictions that have persisted in the economy are inflationary trends and devaluation in the value of the naira. The problem of inflation has been with us for some time now and indeed, the rate of inflation Nigeria has worsened.

Maintaining price stability while ensuring an adequate expansion of credit to assist economic growth have been the primary goals of monetary policy in Nigeria. The concern about inflation emanates not only from the need to maintain overall macroeconomic stability, but also from the fact that inflation hits the poor particularly hard as they do not possess effective inflation hedges.

Low and stable inflation, high economic growth and low employment rate are the three most important objectives of macroeconomic policy. Hence, governments put a significant amount of effort in monitoring and addressing trends and deviations of gross domestic product (GDP), employment and inflation compared to what is perceived to be full-capacity level. In this context, the primary goal of macroeconomic policy makers in Nigeria is achieved of sustainable, low and predictable level of inflation. It is considered that this goal contributes towards the broader national objectives of sustainable economic growth and development. When the general level of prices is relatively stable, uncertainties of time-related activities such as investment diminish. This helps to promote full employment and strong economic growth. When price stability is achieved and maintained, monetary policy makers have done their job well (Sobel, Stroup, Macpherson and Gwartney, 2006). Conceivably, one of the most important responsibilities of every government is fostering a healthy economy, which benefits all her citizens. The government through its ability to tax, spend and control money supply, attempts to promote full employment, price stability and economic growth.

According to modern central banking practices, maintaining economic stability has become one of the core objectives of Central Bank of Nigeria as in many other developing countries. The concern with maintaining price stability stems not only from the need to maintain overall macroeconomic stability, but also from the fact that price stability forms a better environment for investment, output, employment and other vital macroeconomic indicators. Experiences of many countries over the decades, suggest that price stability promotes economic growth. Therefore, policy makers believe when inflation crosses a reasonable threshold in the economy, that it can adversely affect other macroeconomic variables and in turn undermine the steady level of the economy.

The importance of price stability is also stressed in the Maastrict agreement, which defined the framework for a single European Currency, Euro, and identified price stability as the main objective of the new European Central Bank  (McEachern, 2006). When inflation is volatile from year to year, it becomes difficult for individuals and businesses to correctly predict the rate of inflation in the near future. When economic agents are able to make accurate prediction of inflation, they can anticipate what is likely to happen and take steps to protect themselves. Therefore, identifying factors that influence and drive inflation and predicting these factors accurately becomes vital for economic agents. Accurate prediction of inflation could also enable macroeconomic policy makers conduct monetary policy effectively and efficiently to achieve the objective of price stability.

They are many measures of inflation, because they are many price indices relating to different sections of the economy. Two widely known indices for which inflation rates are reported in many countries are the Consumer Price Index (CPI), which measures the rate of change in the prices of goods and services bought by consumers, and the GDP deflator, which measures prices of locally-produced goods and services. In Nigeria, raw inflation figures are reported monthly using the CPI by the National Bureau of Statistics (NBS). The CPI is an estimation of price changes for a typical basket of goods. In other words, the prices of everyday goods such as housing, food, education, clothing  and so forth, are computed from one month to the next and the difference represents the CPI. The strength of the CPI compared to other measures of inflation lies on the facts that: It is simple to compute; it has large population coverage; it includes many products and services and it is the most commonly used measure of inflation in Nigeria. Hence, the CPI is used in this study to proxy the inflation rate.

1.2       Statement of Research Problem

Inflation is viewed as being undesirable because of some serious economic and social effects. Regrettably, in Nigeria we are now reaching levels of inflation which seem to be highly volatile and which poses a much greater threat to the economy. Despite efforts by government to curb the inflationary trend in Nigeria, inflation continues to cause serious distortion in real income redistribution, impact negatively on the growth rate of the living standard of most Nigerians, especially fixed income earners, for example, pensioners and beneficiaries, whose incomes are usually not adjusted upwards fast enough to compensate for the effect of continually rising prices. Producers are confronted with higher unit costs of production, low capacity utilization and out right shop closure. The high cost of production has reduced output which affects the unit cost. The consumers bear the burden of higher prices which diminishes the value of their disposable income. The workers tend to demand higher wages even without a corresponding increase in marginal productivity of labour. The average propensity to save and invest are continuously on the decline thereby stagnating economic growth.

Nigeria has a long history of high and variable inflation. According to Folorunso and Abiola (2000) a general increase in the price level was first noticed in the 1970s.  This was propelled by fiscal dominance and severe macroeconomic imbalances brought about by a sharp increase in government revenue from crude oil exports. The government injected massive public expenditure into the economy through the enormous post war reconstruction of the early 1970s and expenditure on gigantic capital projects embarked upon by all governments under the Third National Development Plan. This increased the entire currency in circulation with the financial sector having to contend with a serious liquidity crisis due to deposit runs. During the sample period (1995-2015), inflation reached an all-time high of 73% in 1995 easing off to 17.9% in 2005. The inflation rate further declined to its historical low of 5.3% in 2007. However, from 2008, signs of appreciation in the inflation rate became obvious averaging 9.7% in 2015 (see Table 1.1)      Insert Table.

Inflation in Nigeria has been linked to rapid growth in money supply caused mostly large deficit budgeting by the federal government over the years. These deficits are financed by printing money through the Ways and Means Advances of the Central Bank of Nigeria (Folorunso et al, 2000). During the period under review, 1995-2015, money supply, broadly defined, has been on the increase. Money supply (M2)  was N291.5 billion (1995), N2,767.9 billion (2005) N11,154.8 billion (2010) and N19,142.5 billion in 2015 (see Table 1.1).

In an attempt to identify the determinants of inflation in Nigeria, money growth, income and exchange rate movements have remained the focal issues. Indeed, most studies have concluded that excess domestic demand, generated by expansionary fiscal and monetary policies have been the key factors underlying inflation in Nigeria (Akinnifesi, 1984; Darat, 1985 and Ikhide, 1993). Others have tended to stress structural factors such as rapid exchange rate depreciation, agricultural supply bottlenecks, fragmentation between supply and demand in and between different sectors of the economy and inadequate food supply (Adeyeye and Fakiyesi, 1980; Asogu, 1991; Aigbokhan, 1991).

The question that agitates the mind after considering issues raised in this section concern factors that determine inflation in Nigeria. Relatedly, is there an economically interpretable and statistically valid functional relationship between the inflation rate and its suspected causative factors in the Nigerian economy? It is hoped that this research will yield a theoretically plausible and statistically robust model which could be used in predicting inflation rates in Nigeria. This it is believed will aid sound macroeconomic policy formulation and implementation in order to achieve the objective of price stability.

Table 1.1: Inflation Rate and some other macroeconomic indicators in Nigeria                        (1995-2015)

Year Inflation (%) Money Supply (Nm) GDP



Official Exchange Rate (N1)
1995 72.8 291,467.17 1,933,211.55 21.8861
1996 29.3 351,242.75 2,702,719.13 21.8861
1997 10.7 415,186.72 2,801,972.58 21.8861
1998 7.9 499,499.4 2,708,430.86 21.8861
1999 6.6 649,829.15 3,194,014.97 92.6934
2000 6.9 924,626.57 4,582,127.29 102.1052
2001 18.9 1,322,040.40 4,725,086.00 111.9433
2002 12.9 1,656,473.50 6,912,381.25 120.9702
2003 14.0 2,049,203.6 8,487,031.57 129.3565
2004 15.0 2,275,442.6 11,411,066.91 133.5004
2005 17.8 2,767,892.5 14,572,239.12 132.1470
2006 8.2 3,892,015.5 18,564,594.73 128.6516
2007 5.4 5,362,270.4 20,657,317.67 125.8381
2008 11.6 8,518,430.7 24,296,329.29 118.5669
2009 12.4 9,578,490.0 24,794,238.66 148.9017
2010 13.7 11,154,782.5 33,984,754.13 150.2980
2011 10.8 12.436,823.5 37,543,654.70 153.8616
2012 11.3 13,618,080.3 41,239,120.84 158.3214
2013 10.4 14,303,494.5 43,713,115.72 180.5679
2014 9.5 14,670,373.2 45,543,022.16 180.7893
2015 9.5 15,202,489.3 47,947,564.18 190.9274

Source: 1. CBN Statistical Bulletin (various issues)       

  1. NBS Statistical News (April 2016, pp. 7-12) 



1.3       Research Questions

–           Is there a statistically valid, theory consistent predictive inflation function in the Nigerian economy?

–           Do different predictors of inflation have different dynamic effects on the inflation rate?

1.4       Objectives of the Study

Our primary interest in this research work is to empirically investigate whether or not the inherent dynamics in CPI, MS, REER and RGDP can be employed in formulating a predictive model for inflation in Nigeria given data constraints on key conventional variables such as wages, disposable income, unemployment and import prices which are traditionally employed in building functional relationships for inflation. CPI, MS, REER, and RGDP as economic indicators embody expectations by economic agents regarding the performance of the economy in general with respect to economic growth, the level of interest rate and inflation among other variables. To the extent that these expectations are largely correct, these indicators could be used as indicators of future economic activity of interest. When these economic indicators can reliably signal changes in inflation rate several months or quarters into the future, they facilitate the conduct of macroeconomic policies which must anticipate the future and take corrective action in order to keep the economy growing at, or close to, capacity with price stability.

1.5       Research Hypothesis

The following hypotheses are made:

–           A statistically valid, theory consistent predictive inflation function in the Nigerian economy does exist.

–           Different predictors of inflation have different dynamic effects on the inflation rate.

1.6       Significance of the Study

Inflation is a regressive form of taxation and among the most vulnerable to the inflation tax are the poor and fixed income group. It causes efficiency losses and lower the productive base of the economy. Furthermore, inflation can discourage savings if the rate of return on savings does not reflect the increase in the level of prices. The uncertainty about future prices can also cause unexpected gains and losses in trade and industry, and thus, discourage long term contracts and investment channeling resources into speculation. Hence, this study is motivated by the need for further empirical analysis of the inflationary process in Nigeria to support sound macroeconomic policy management.

Using quarterly time series data from 1995 to 2015, this research models the dynamic influences of broad money supply, real gross domestic product on consumer price index which in this case is used as a proxy variable for inflation using dynamic regression modelling approach. Money supply, real gross domestic product, real effective exchange rate and consumer price index; like most macroeconomic variables are known to exhibit strong serial dependence. This research seeks to visualize and model these dependencies and exploit them for generating future inflation rates using past observations of the series. The advantage of this modelling approach is its ability to deliver results based on underlying economic theories, which are also consistent with data characteristics, and real world conditions.

Indepth knowledge of how inflation behaves; what influences and drives it over time is needed because macroeconomic policy efficiency is challenged by the fact that its effects are often lagged. This can be an alternative method to model and forecast inflation by macroeconomic policy makers given that various instruments deployed to tackle inflation only yield results after a certain period of time, hence, a preemptive strike strategy seems like a reasonable choice for monetary authorities.

1.7       Scope and Limitations of the Study

A major drawback of this study is the length of the data. Attempts to extend the sample size beyond 1995 were not fruitful. Also, variables like disposable income, wages, unemployment which directly or indirectly feed into the inflationary processes are not included in the study. The reason for excluding these variables from the study is difficulty in obtaining them.

1.8       Definition of Key Concepts

  1. Autocorreltion function

The autocorrelation of a time series measures the correlation between values of the time series at different points in time, as a function of the two times. Mathematically, the autocorrelation between any two time series observations, say, Yt and Yt+h, separated by h intervals of time is defined by


                         for h = 1, 2, …

The formula for the autocorrelation is just the usual correlation formula, specialized to the correlation between Yt and Yt+h.

If the process is convariance stationary, the variance of Yt at any other time Yt+h is a constant, so that

for h = 1, 2, ….

Relevant to this, we define the sample autocorrelation

, at lag h as

for h = 1, 2, …





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