Analysis of the relationship between economic growth and

unemployment

CHAPTER ONE

Introduction

Growth is a matter of extreme importance for countries in the developed

and developing world. Growth is considered to be a pathway to decrease

the level of unemployment Sustained growth with employment

generating polices eventually trims down the critical problems of

unemployment. Growth is an essential component for the progress and

prosperity of mankind. Growth helps in upgrading the living standards of

people. In classical and neoclassical economics, unemployment is due to

rigidities imposed on the labour market from the outside, such as wage

laws, taxes, and other regulations that may be the reason of hiring of

minimum workers.

Keynesian economics explains unemployment as a result of to

insufficient effective demand for goods and services in the economy.

Unemployment is a social and political issue. It is a phenomenon issue

where resources are wasted leading to a deacceleration in growth.

AIM

The study aim to investigate the casual relationship between

unemployment and economic growth.

OBJECTIVES

Determining the relationship between unemployment and economic

growth.

To provide an insight into the development of alternatives to improve

the economic growth.

Problem statement

After almost more than two and half decades of political independence,

Zimbabwe’s economic growth leads to a lot to be desired. This is borne

out by indicators such as high levels of inflation, higher levels of

unemployment being caused by various factors such as low wages.

According to World Bank Statistics (2006), Zimbabwe’s real per capita

income fell to levels below –7% between 2005 and 2006.

Unemployment levels continue to be woefully high and income

disparities are still glaringly large. Inflation rate continues on its upwards

spiraled up to levels above 6500% (Central Statistical Office: October

2007) leaving the employed failing just to maintain the minimum

consumption basket.

Only negligible industrialization has occurred since 1980. It seems

economic growth has since independence failed to keep pace with

population growth. Post-independence development efforts such as the

Economic Structural Adjustment Program (ESAP; 1991) amoung other

things lead to the removal of price and wage control (sichone,2003:1).

This lead to a huge increase in unemployment. Also in an attempt to spur

growth of the economy the plans were to redistribute wealth both public

and private, from the minority of whites controlling the economy to

majority of blacks that made up the economy. However these policies

had serious implications on several white settlers who started to walk out

of Zimbabwe and their enterprises collapsed. This also led to the increase

in unemployment. From these policies we can deduce that policy makers

were not mainly focusing on unemployment as a factor that has an effect

on economic growth. Therefore the rate at which the economy is

growing in relation to the rate of unemployment is the motive behind this

research. Of significance in this research is to see whether

unemployment has a negative or a positive contribution on the worsening

of the growth of the economy in the period 1985 to 2005.

Significance of the study

This research provides an empirical investigation of the relationship

between unemployment and economic growth in Zimbabwe. The

research provides a base for the policy makers to develop alternatives to

improve the growth of the economy.

CHAPTER TWO

LITERATURE REVIEW

Economic growth is the increase of per capita gross domestic product or

other measures of aggregate income. Economic growth is primarily

driven by improvements in productivity which involves producing more

goods and services with the same inputs of labor, capital energy and

materials. There has been extensive literature on the issue of growth and

unemployment.

Blanchard elaborated in conventional theories of growth and

unemployment that neither unemployment influence growth nor that long

run growth effects equilibrium unemployment. Romer also found out

that growth brought about unemployment due to increase in technology.

He stated that economic growth bring about unemployment through skills

obsolescence and new machinery.

Kurz and Salavdori exposited that classical economists focussed on the

long period growth and paid a little attention to shot period. Neoclassical

economists also started with the same style but soon realised the

problems and focussed on intertemporary analysis. Neoclassical

economists focused in investment in physical and human capital which

will then lead to a decrease in the rate of unemployment. Influential work

is done by Herrod and Domar about growth and unemployment.

Technological innovation had dual effects on the economy.

Technological innovation can lead to high economic growth. Also it can

lead to high unemployment rate. Two different types of effects were

elaborated by economists. Pissarides Postel Vinay found that

technological progress helped to reduce unemployment due to

capitalization effect. Rapid growth raised the returns of firms and new

firms were launched to share the profit and in turn more jobs were

created. Quick innovation made the labourers unemployed. Growth and

technological progress had significant role in minimizing unemployment

but this growth remain limited to a few areas and regional disparities

emerged.

Inflation is the rise in the general level of prices of goods and services in

an economy over a period of time. Economists generally agree that

higher rates of inflation and hyper inflation are caused by an excessive

growth in the money supply. Keynesian view inflation as constructive to

a faster rate of economic growth since the excess demand and favorable

market conditions will simulate investment and expansion.

CHAPTER THREE

METHODOLOGY

3.0 Introduction

This section proceeds to an econometric investigation. It endeavors to

outline, specify and develop the empirical model. The strategy is to

consider regressions of Economic Growth on a set of economic variables

that affects the growth rate of the economy. The set of variables are

unemployment and inflation. This chapter explains and justifies variables

to be used. It also reveals the data collecting techniques used in this

study.

3.1 Model Specification

To discover whether and how economic growth can be explained by

economic variables, the model in this study is based on the following

equation.

Economic growth =B0 + B1unempl + B2inflatoin + Ui

Where

Economic growth = gross domestic product at constant price in

percentages.

Unempl = unnual unemployment rate as a percentage.

Inflation=annual inflation rate

U = Error Term

B = regression coefficients

Therefore, the model with which the econometric phenomenon will

be empirically tested can be stated as follows

G = f (P, U,) Where

G = Annual Economic growth

P = Annual inflation rate

U = Annual unemployment rate

To come up with a mathematical equation explaining the behaviour of

economic growth as any of the above determinants change, the method of

Ordinary Least Squares (OLS) will be used. With this method, the

mathematical equation can be stated as

G = β0 + β1P + β 2U + ε

Where ε is the error term, which captures all other variables not included

in the model.

.3.2 Justification of Variables

3.2.1 Dependent Variable

Economic Growth

It measures the rate of increase in an economy’s real output overtime. An

increases in unemployment rate lead to a decrease in economic growth..

As such, economic growth is used in this model as an explanatory

variable.

3.2.2 Independent variables

Unemployment

It means failure to secure a job resulting in deprivation of income. The

spillover effects of unemployment are low productivity and low living

standards of people which may lead to decrease in economic growth.

Unemployment affects the demand side of the economy. If people have

no money to spend, local businesses may find it difficult to sell their

products and this spiraling effect can affect the growth of the economy.

Inflation

It is the sustained rise in the general level of prices overtime. High rates

of inflation reduce the growth rate of the economy. Inflation thus

increases the cost of buying machinery by companies resulting in low

productivity. Inflation also result in retrenchment which result in low

labour force. Low labor force results in low productivity. Inflation also

affects the business fraternity since it makes planning and budgeting very

difficult resulting in business closures, low output, and commodity

shortage.

.3.3 Data Characteristics3.3.1 Data Choice

This research relied heavily on secondary data sources. This is because

secondary data has the following advantages:

Secondary data is less expensive to get as compared to primary data,

which requires huge financial resources in survey taking.

The data is based on nationally representative samples taken by

responsible organizations

However, secondary data has the limitation that it may loose some

important information during its processing.

Data Sources-GDP data at constant price is obtained from the national accounts section

-annual employment rate is obtained from the employment and education

sector.

-annual inflation rate is obtained from the prices section.

Tabular and Graphical presentation.

-Constructed tables to display data on the annual rate of unemployment,

annual inflation rates and the annual economic growth in percentages.

-line graphs represent the economic growth trend for the period 1986-

2005

Two-way ANOVA

-tables for hypothesis testing

-calculation of the F-value

Hypothesis

H0 –There is a positive relationship between economic growth and

unemployment

H1 –there is an inverse relationship between economic growth and

unemployment

YEAR P (annual inflation rate in

%)

U (annual unemployment

rate in %)

G (economic Growth in

%)

1986 14.2 6.3 2.11987 11.9 7.8 1.11988 7.1 11 7.61989 11.6 12.8 5.21990 15.5 13.4 71991 23.3 12.5 7.11992 42.09 15 -8.41993 27.6 16.2 2.11994 22.3 17 5.81995 22.6 18.6 0.21996 21.4 19.5 9.7

1997 18.9 20.2 1.41998 31.7 20.1 0.81999 58.5 21.2 -4.12000 55.8 22 -8.2

2001 71.9 22.4 -0.2

2002 133.2 22.2 -5.9

2003 365 23.1 -7.4

2004 350 23.4 -3.6

2005 237.8 23.8 -4

CHAPTER FOUR

PRESENTATION AND INTERPRETATION OF RESULTS

4.0 Introduction

It would be unrealistic to say that unemployment and inflation are related

to economic growth without carrying out proper empirical tests. This

chapter therefore provides the presentation and interpretation of results

obtained from the regression of time series data of economic growth,

unemployment and inflation. It highlights findings on the relationship

between economic growth, unemployment and inflation. Appropriate

tests will be carried out to ensure that the model satisfies all Ordinary

Least Squares (OLS) assumptions as well as to establish stationarity of

variables.

Model Summary

Model R

R Squar

e

Adjusted R

Square

Std. Error of

the Estimate

1.609(a) .371 .297 4.69003

a Predictors: (Constant), Unemployment, Inflation

ANOVA TABLE

Model

Sum of Square

s DfMean

Square F Sig.1 Regre

ssion220.40

7 2 110.203 5.010 .019(a)

Residual

373.939 17 21.996

Total 594.346 19

a Predictors: (Constant), Unemployment, inflationb Dependent Variable: economic growth

Coefficients(a)

Model Unstandardized

Standardized

t Sig.

CoefficientsCoefficien

ts

BStd. Error Beta

1 (Constant) 7.445 4.044 1.841 .083

inflation -.019 .012 -.377 -1.568 .135 Unempl

oyment -.319 .252 -.303 -1.263 .224

a Dependent Variable: VAR00003

Therefore using the results in the table above , the model will be

economic growth = 7.445-0.19P-0.319U+ε. The equation shows that unemployment is negatively related to economic

growth. This means that a decrease in unemployment also increases the level

of economic growth.

From the equation also, a unit increase in unemployment leads to a

decrease in economic growth. Also from the table, inflation is negatively

related to economic growth. This means that a unit decrease in inflation

increases economic growth but not as much as unemployment.

The DW Test

The Durbin Watson (DW) test is used to test for autocorrelation.

Values of the test ranges from 0 to 4 where values close to 0

indicate strong positive correlation and those close to 4 indicate

strong negative correlation. Values close to 2 indicate no serial

correlation. As a rule of thumb d should be between 1.5 and 2.5 to

indicate independence of error terms. The DW statistic of 1.969

thus lies in the zone of no autocorrelation satisfying the ordinary

least squares (OLS) assumption that successive values of the

random error term should be independent. The Durbin Watson

statistic is also greater than R2 hence ruling out the possibility of

spurious regression.

4.3 Interpretation of Results

To test the goodness of fit of the overall model, we consider the F-

statistic and R2. The computed F-statistic of 5.010 exceeds the critical F-

value of 0.019 at 5% level of significance. As a rule of thumb the F-

statistic should be greater than 5.We can therefore conclude that the

model is statistically significant.

The coefficient of determination (R2) shows the proportion of total

variation explained by changes in any of the independent variables

included in the model. The R2 value of 0.371 shows that 37.1% of the

variation in economic growth is explained by the levels of inflation and

unemployment. The remaining 62.9% is explained by other factors not

included in the model, which may be captured by the error term.

The significance of each explanatory variable is measured by the t-

statistic values. Each explanatory variable is said to be significant if the

absolute value of the t-statistic greater than 2 or approximately equal to 2.

From the results obtained, all absolute t –statistic values are greater than

2 showing that all the explanatory variables included are significant in

explaining economic growth.

Correlations

inflationunemployment

Economic growth

inflation Pearson Correlation 1 .599(**) -.558(*)

Sig. (2-tailed) . .005 .010

N 20 20 20unemployment

Pearson Correlation .599(**) 1 -.529(*)

Sig. (2-tailed) .005 . .016

N 20 20 20Economic growth

Pearson Correlation -.558(*) -.529(*) 1

Sig. (2-tailed) .010 .016 .

N 20 20 20** Correlation is significant at the 0.01 level (2-tailed).* Correlation is significant at the 0.05 level (2-tailed).

CHAPTER FIVE

CONCLUSIONS

CHAPTER SEVEN