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The social and economic consequences of

unemployment

Valentina Nicoleta Musat

Matricola 1900045088

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Table of Contents

Abstract

1. Introduction

2. Economic impacts

2.1 The relation between unemployment and real GDP

2.1.1 Is Okuns Law stable over time?

2.1.2. Forecasting and Okuns law

2.2 Unemployment and the public expenditure

2.3 The Relationship between Growth and Unemployment

3. Social impacts

3.1 The impact of unemployment in the countries' populations

3.2 The social individual consequences of unemployment

4. Summary and conclusions

5. Bibliography

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Abstract

Unemployment is a great problem of modern economics and at the moment due to the global

financial crisis it has become an even greater problem. The purpose of this study is to examine

the social and economic consequences of unemployment through the examples of several

countries in the European Union.

First, connections between unemployment and real GDP are investigated, and then the

influence of unemployment on the budget of different countries is examined, by focusing on

labour market costs from GDP. The validity of Okun's Law is put to the test and a discussion

is made based on the efficiency of this law over short and long periods of time.

In the part of the study dealing with social consequences, the influence of unemployment on

the population is examined.

Finally the social and individual effects of unemployment are demonstrated.

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1. Introduction

In this project the topic of unemployment will be examined. Unemployment is one of the

great challenges of modern economics (of course unemployment also existed in previous

ages), and is currently in the shadow of the global economic crisis, making it an even bigger

and stringent problem.

However, there are countless disentanglements of the solutions and causes to unemployment,

and not enough work has been done to synthesize both the social and economic consequences.

This project therefore aims to examine the complex types of consequences of unemployment

and its social and economic impacts.

In the economic part, the relationship between unemployment and real GDP is examined, then

the labour expenses in terms of GDP are analysed.

In the social part of the study, relations between the rate of population reproduction and the

rate of unemployment are examined. In the last part the individual and social effects on

unemployment are described.

Data from 2000 to 2011 is used to examine the relationship between unemployment and GDP

growth.

To examine the effects, European countries were chosen, and to have a well-represented

model and more accurate results, countries form both the new entrants and from within the

founders of EU were chosen (Romania, Bulgaria, Slovakia, Germany, and United Kingdom).

The hypothesises:

1. According to Okuns law, in these countries the unemployment and the GDP has a close,

positive relation.

2. The proportional labour expenditures in the developed EU countries are higher than in the

new states.

3. The unemployment and the population reproduction rate (the average number of children of

a woman of childbearing age) are in close relation, so the increase of unemployment rate

decreases the reproduction rate.

Definition of 'Natural Unemployment'

Natural employment is the minimum rate for unemployment that can be maintained by the

economic for large timeframes. Theory (the Philips curve) states that more people can be

employed if the state can accept a larger inflation, but in practice it has been observed that, in

time, the rate of unemployment will rise again if the inflation rate is maintained at large

values. However there is a state of balance, where the minimum unemployment rate produces

a relatively invariable inflation.

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2. Economic impacts

2.1 The relation between unemployment and real GDP

Okuns law is a macroeconomic context which deals with the relationship between

unemployment and economic growth. The recession's most pressing consequence is the rise in

unemployment. As production declines in the companies, they need less work, so do not hire

new workers and also lay off many of the existing ones. Unemployment and the companys

output move together during the business cycle. These parallel movements and their

quantified relationship were first formulated by Okun, referred to in the future as Okuns law

[1].

,

where:

is potential GDP

is actual output

is the natural rate of unemployment

is actual unemployment rate

is the factor relating changes in unemployment to changes in output

Okuns Law describes the connection, from a statistical point of view, between the rate of

unemployment and the GDP (or its growth). The intention is to show the proportion of GDP

that can be lost if the rate of unemployment goes beyond the natural unemployment. The law

can be described in simple terms: in general, output is a function of labor used in production,

and the connection between output and unemployment is negative.

The numerical definition of the law is disregarded, because in other countries and other times,

the researchers had different results. Therefore the following wording is the most appropriate:

Between the current and the long-time stable unemployment rate and the income on potential

output, there is a quantified relationship.

In the following, the real GDP and unemployment are examined with econometrical and

statistical correlation method. First, Okuns law has to be reversed, since in the testing

unemployment will be the explanatory variable and the real GDP is the dependent variable.

After that, conversely Okun's Law reads as follows: If the unemployment increases, the

output decreases.

For the estimations Eviews 5 software was used, which is an econometric and statistics

software package. Data was collected from the websites of Eurostat and World Bank Data.

The following command was used for each country:

countrygdprate c countryunemploymentrate

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After the regressions were ran, tests were performed for heteroskedasticity, normality,

autocorrelation, multicolinearity and stability. The solutions of the tests were not satisfactory,

but its attributable to having only 48 observations that can be used, the quarterly data of 12

years. Data for the countries before 2000 could not be obtained.

The table below contains the results:

Country Fitting regression curve

Bulgaria 1,918 + 0,028*x

Romania -5,515 + 1,189*x

Slovakia 1,83 + 0,056*x

Germany 0,27 + 0,03*x

United Kingdom 0,121 + 0,05*x

Table 1: Fitted regression curve for the selected countries

As it can be seen in the table, all of the relations are positive, which refutes Okuns Law. Of

course the problem is not with the law, but with the regression used. After thoroughly

examining the data and the regression, the source of the problem is detected. The example of

Germany will be used, because it shows the problem better, more visibly than the others.

Table 2: Germanys results

As it can be seen on the trend lines of GDP and unemployment the correlation is negative

between them. So, if the unemployment is getting lower, the GDP growth rate will get higher.

Hereupon, the problem in the regression model is that thanks to the market crash in 2009, the

GDP growth rate has dropped, and this misfits our regression. Germany handled well the

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crisis, so its GDP growth rate normalized, but if one looks at a less developed country, for

example Romania, where the crisis management wasnt good enough, different results can be

seen.

Table 3: Romanias results

In this case it can be seen that the GDP growth rate isnt normalized, which means, to have a

correct regression more dummies need to be added, which means that degrees of freedom will

be lost.

To solve this problem dummy variables could be used for that period, but that would mean

loosing at least another 4 observations. Instead of trying to run a well fitted regression

model with only 44 observations (which is nearly impossible), a regression model that was

discovered in a Hungarian lecture note was used (konometria kzgazdszoknak

{Econometrics for economists}, Dr Ott Hajd, 2013). It contains many more observations,

so the result is more consequent.

The imported data from the note:

Country Fitting regression curve Correlation

Bulgaria 0,01*x + 1,34 0,16

Romania (-0,457)*x + 9,7 -0,28

Slovakia (-0,01)*x + 1,44 -0,59

Germany 0,417*x + (-2,738) 0,22

United Kingdom (-3,46)*x + 19,49 -0,8

Table 4: Fitted regression curve (konometria kzgazdszoknak Dr Ott Hajd, 2013)

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The results of the regression analysis clearly show that in the majority of countries, there is a

linear and positive relationship between the two criteria. It means that, if the unemployment

rate in Romania grows by 1 percent, the GDP growth rate will decrease by 0,457 percent. In

the next chart, the steepness of regression can be seen. This is a good way to illustrate the

differences between the countries' sensitivity to unemployment.

Table 5: Steepness of regression

The results of correlation indices are more varied, but the relationship is mostly negative. The

relationship is neutral in the case of Germany and Bulgaria. It means that in this period, the

correlation between unemployment rate and GDP growth rate is very low and the effect is

small.

There is a negative and very close relation in case of Slovakia and the United Kingdom. In

these countries the GDP is strongly dependent on the unemployment rate in the country.

In the majority of countries, the results of regression analysis show that there is a linear type

of connection. According to the correlation analysis, the growth of unemployment rate to

decline in real GDP is a linear relationship. This means that the law of Okun has been proven

with statistical and econometrical tools.

2.1.1 Is Okuns Law stable over time?

The issue with long time-series is that there are many events to account for during large time-

spans, and sometimes these events are hard to spot or go unnoticed, making it hard to detect

changes in relationships between economic factors, and Okun's law seems to have been

affected by this. While the general form of Okun's law stands true for long periods of time, for

shorter time-frames the connection between unemployment and output growth tends to be

variable[2].

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To determine this variability, a rolling regression (also known as sliding window regression)

can be used to improve the results, estimating the relationship for different same-length

periods of time. This would output a vector of coefficients for every time-window, allowing

one to determine if the relationship exhibits stability over time. By using rolling regressions

there is a lower chance for events that have happened in the distant past to cause the results to

be biased or corrupted.[2]

Splitting the data into smaller windows would mean working with intervals that are quite

short in terms of econometric analysis, but this could allow the investigation of Okun's law

separately for periods of unaffected growth or for periods of recession, and assess its

effectiveness as a law[2].

2.1.2. Forecasting and Okuns law

Even while considering the negative aspects of Okun's law, such as the variation of its

coefficients throughout history and the fact that its correlation has not always been very

strong, it can be quite useful for economic policymakers as a forecasting tool if the negative

aspects are accounted for.

The main idea is to compare the law with a stable forecasting model and to account for

instability. This turns Okun's law into a dynamic relationship that functions as an

autoregressive model, which means that future values for the coefficients of Okun's law can

be found or tuned by looking at and analysing past values and past coefficients. For example,

the change in the rate of unemployment in the current quarter could be forecast depending on

the change in unemployment in the last 4-8 quarters.[2]

To do this, a past timeframe up to the present must be selected (n-x n), and a forecast for

the next period (n+1) must be made based on the timeframe data and its frequency. Then, the

forecast can be included in the timeframe, extending the data to (n-x n+1) and a forecast

can be made for (n+2). The process can be repeated to simulate different scenarios and

directions that unemployment can take.

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2.2 Unemployment and the public expenditure (in labour market to GDP ratio)

The ongoing European debt crisis affects almost all European states. To solve the crisis, most

countries have proposed economic policy cutbacks in public spending, thereby reducing the

huge debt to GDP ratio. However, in times of crisis the State is responsible for the

management of unemployment, just like with the education and health care system. To

achieve its objectives, the State should contribute heavily from the budget to solve problems

in these areas.

Every country has employment expenditures, however, what differs from one country to

another is the period of time that the unemployment benefits are paid and the conditions under

which the payments/benefits are offered.

Analysis of the ratio of labour market spending to GDP is a more accurate, more comparable

picture of unemployment "prices". Public expenditure, therefore, in addition to unemployment

benefits includes according to the established practice in OECD:

- The cost of employment and unemployment relief apparatus,

- The re-training costs, youth programs etc.

- Expenses related to early retirement and disability retirement,

- As well as employment subsidies.

So the labour costs include not only unemployment benefits but also a number of other costs

and taxes that are related to the inner workings of the employment/benefits ecosystem.

Next, the findings of another project will be described, as not enough data for the regression

could be collected. These statements need to have a coherent, thorough research. This ratio is

lower in the newly joined countries (0.5-0.8%) like Romania, and also low in the UK

(0.56%), because of its very liberal politics. The ratio is much higher in Germany (2.5%), but

if the unemployment rates in these countries are compared, it can be seen that the high

expenditures in GDP ratio does not mean that the unemployment is low. But one interesting

thing is that Germany is the only country in the investigation whose unemployment rate didnt

get much higher during the global crisis.

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Table 6: Unemployment rate for the studied countries

2.3 The Relationship between Growth and Unemployment

The connection can be misleading or weak for short timeframes, with rate of unemployment

commonly exhibiting a lag with respect to other economic counter-measures that are put in

place, or after other economic indicators have shown amelioration. There are a number of

factors that cause this: for example, companies might not be making full use of their

workforce, since layoffs are costly and there is a risk of having to rehire once the demand

trend reverses. On the other side, companies can improve productivity at the beginning of a

recovery period to meet the demands of the market, but since this is only temporary, it is not a

true reflection of any average productivity increase. When the workforce is utilized to its

maximum, output cannot grow any faster than the increase in productivity unless the

workforce is expanded. Thus, final output growth will be a function of workforce growth and

productivity growth. Thus, while GDP grows faster than productivity, there will be a fall in

unemployment.

For longer time spans, the relationship between GDP growth and unemployment becomes

negative - the trend which is reflected in Okun's law. Okun's law implies that a country needs

a GDP growth that is roughly equal to the possible output growth in order to stabilize

unemployment. With this, one of the main connections between the growth of GDP and

unemployment is represented by potential output, which measures and probes the capability

of an economy to create goods and services while using all possible resources. Growth of

potential output is affected by the rises and falls in potential productivity and workforce

supply, under conditions of full employment.

In times of high unemployment, such as in the present, real GDP is lower than potential GDP,

also known as an output gap. With no or low growth of productivity, while every addition to

the workforce becomes employed, output growth will be the same as workforce growth.

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When GDP rate of growth is lower than the rate at which the workforce grows, not enough

new jobs will be made available to account for new job prospectors, which leads to higher

unemployment.

In the case in which growth of output is higher than the growth of the work force, new

positions will be filled from the ranks of the unemployed, thus lowering unemployment. In

the case in which the GDP increases the same amount as the workforce along with the growth

in productivity, there will be a surplus of employees with respect to the actual demands. Thus,

after a certain time unemployment will rise.

The unemployment will be reduced in the long run only if the growth of GDP is higher than

the sum of growths of both workforce and potential output. It is vital for policymakers to have

knowledge of the GDP growth rate if they are to implement reforms that will reduce

unemployment, but this is not trivial, as the workforce and productivity are constantly

changing.

There is, however, a weaker correlation between GDP per capita and these two factors. A

lower GDP per capita does not necessarily translate into higher unemployment numbers. The

low numbers might be due to underemployment or even self-employment yielding lower

returns than normal employment.

3. Social impacts

In the following chapters the social impacts of unemployment will be examined and

presented. Since all economic decisions, whether investments by the state, or decisions in a

company have social and environmental impacts, not only economic ones, it is very important

for the policy-makers to measure these impacts before making decisions. Consequently, it is

also important, to examine more than the economic results of the relationships and

phenomenon of economy. Therefore it was decided to make this part as important as the

previous one.

3.1 The impact of unemployment in the countries' populations

In the following chapters the relationship between demographics and unemployment will be

examined. The word demography is heard in the media every day. But what is demography

exactly?

Demography is the study of changes (such as the number of births, deaths, marriages, and

illnesses) that occur over a period of time in human populations.

From that definition, the number of births is the most important for the project, this

indicator being the one which has the highest relation with unemployment, so it must be

highlighted.

Nowadays, the largest problem of the European societies is the population decline and the

negative demographic trend. Before looking for a correlation between the unemployment and

fertility rate, the changing of population in the mentioned countries must be examined.

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Figure 1: Population structure, UK [3] and Romania [4]

The fertility rate is the number of birth per childbearing woman, so its not as a percentage. If

the fertility rate is under 2, the population is decreasing. It can be seen that the relation is

multiplicative. For example, if its 1.33, it means that its 66.5% so after 2 generations, for 2

base people it will be only around 45%.

Inside Europe, two main groups can be distinguished, by the extent of reproduction rate, one,

sharply declining population, and the other is the slowly shrinking group.

In Figure 1, the age construct diagrams of the United Kingdom and Romania are compared.

The difference is minor, but important. In the UK, the population is relatively evenly spread

between the age of 20 and 50 while in Romania its between the ages 35 and 50, because of

the migration. It is affecting the calculations, because in the UK, the immigration is much

higher, especially for the ages of 25+. It means that the children who are supposed to be born

in for example Romania will be born in the United Kingdom, but usually the immigrants

wont live their whole life there, eventually coming back with their children.

The relations between the fertility rate and the unemployment were examined by regression

analysis. In the examination, the unemployment is independent, and fertility rate is the

dependent variable.

Country R r2 (%)

Bulgaria -0,9038 81

Romania -0,4055 16,5

Slovakia -0,7026 49

Germany -0,4927 24

United Kingdom 0,6991 49

Table 7: Strength of correlation between unemployment and fertility rate

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The results of analysis are the following:

The connection is negative and close in the following countries: Germany, Bulgaria, Slovakia,

and Romania. It means that the increase in the unemployment rate leads to a decrease in

reproductive rate in these countries.

Table 8: Unemployment and fertility rate

The result can also be seen in the trend line in Table 8. As it can be seen, the higher the

unemployment, the lower the fertility rate.

A totally different result was obtained in the case of United Kingdom. It has a strong, positive

correlation. This statistically means, that if the unemployment increases, the fertility rate

increases as well. One can only speculate what can it causes this. In the authors opinion, the

higher the unemployment, the more immigrants will go to UK, because the unemployment

rate in the European Union basically has the same trend. So if the unemployment rate

increases in the EU, more people will go to the more developed countries to live and give

birth to their children.

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Table 9: Unemployment and fertility rate

Since only one from five countries has positive correlation, the interpretation of these results

can be dispensed, making only two comments on them.

The reproductive rate of population growth is not equal to the population growth, above the

index value of 2: for example, In case of Hungary, where the 2003 value of 1.28 increases to

1.33 by 2009, this figure does not mean an increase in population.

Furthermore, among the countries studied, Germany has the most serious demographic crisis.

With these statistical methods, the validity of the assumption is confirmed, the increase of

unemployment rate decreases the fertility rate in most of the countries, thus proving that there

is a correlation between the two variables and proving the adverse effects of unemployment in

this area as well.

3.2 The social individual consequences of unemployment

The effects of unemployment in economic books are mainly omitted. Economists focus on the

causes of unemployment, fiscal costs, and macro-economic consequences only. It cannot be

ignored that there are quantifiable effects on the individual, which, although indirectly, affects

the current and future economy of the countries. In this part the consequences in Hungary will

be examined.

In the project the outcome of a survey will be used, made by the Institute of Political Sciences

of the Hungarian Science Academy.

The following table depicts the perceived differences at social level between the employed

and the unemployed:

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The proportion of respondents who agree with the following

statements Employed Unemployed

Every day I meet a wide range of people 61,2% 50,6%

Throughout the day there is something to do 86,5% 60,3%

What I do is beneficial for the whole society 76,4% 32,6%

Society has respect for those like me 50,2% 28,4%

Table 10: A survey by the Institute of Political Sciences of the Hungarian Science

Academy

Analysing the table, it can be seen that the unemployed people are less self-confident and they

dont consider themselves as useful members of the community. The other problem is that

usually they dont meet with other people and they become introverted, which is not good if

they want to get a job again. A little over 30% agreed to the question Does society have

respect for those like me? The main problem is that they can easily get stuck in the vicious

circle of unemployment.

The further possible personal consequences of unemployment (the consequences likely to

result from each other and getting worse) especially in case of long-term unemployment:

- Depreciation of acquired knowledge,

- Social and cultural isolation,

- Psychological and health problems,

- Family tensions and conflicts,

- Alcoholism, drug abuse,

- Risk of debt,

- Aggressiveness.

Work to people is therefore not simply an earning activity, but also has social significance of

in modern societies.

Therefore, the unemployed are deprived of more fundamental things than the working income

when they dont have job. A changed life situation affects people's health, self-esteem, social

relationships and social and community activity.

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4. Summary and conclusions

In this project a full overview of the economic and social impacts of the unemployment was

attempted, by examining the economic effects and social effects in equal parts.

Negative consequences of unemployment are usually quick to appear as effects on the

economy, through changes in the output. Thus, the increase in unemployment will reduce in

direct proportion economic output.

Therefore, the higher unemployment rate will be detrimental to the economic output, which

further strengthens the growth of unemployment. The government gives unemployment

benefits to the people who lost their job and in case of mass unemployment this is heavy on

the budget. The labour market is not only spending unemployment benefits, but also the

creation of new jobs will increase the governmental and private spending.

When unemployment is persistent, it may have serious consequences, not only on economic,

but also on social and individual levels. The unemployed lose self-esteem, get in conflict with

their environment and, in severe cases, become addicted to alcohol or drugs.

For the state it is extremely difficult to cope with the problems caused by long-term

unemployment.

In this paper, another problem is linked to unemployment: the fact that in Europe, every

country, without exception, suffers from a drastic population decline. The assertion that there

is a strong correlation between unemployment and the decline in reproductive rate seems

logical.

According to the results of the calculations, this assumption is true in most of the countries

studied, with a moderately strong relationship in four out of five countries: Germany,

Bulgaria, Slovakia, and Romania. This means that the increase in unemployment leads to a

reduction in the rate of reproduction.

In this paper the direct and indirect adverse consequences of unemployment in long and short

term are shown. Of course, additional points can be made besides the economic and social

points, which may be the subject of a future research.

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5. Bibliography

[1] http://en.wikipedia.org/wiki/Okun%27s_law

[2] http://www.kc.frb.org/publicat/econrev/pdf/4q07knotek.pdf

[3] http://countrylicious.com/united-kingdom#!/people-and-society

[4] http://countrylicious.com/romania#!/people-and-society

5. http://www.bpb.de/themen/1XDG03,0,Folgen_der_Arbeitslosigkeit.html

6. ftp://ftp.repec.org/opt/ReDIF/RePEc/bbn/journl/2007_2_7_Gut.pdf

7. http://www.kas.de/wf/doc/kas_33244-1522-23-30.pdf?130110040302

8. http://www.insse.ro/cms/files/publicatii/Romania%20in%20figures_2011.pdf

9. Eurostat: http://epp.eurostat.ec.europa.eu/portal/page/portal/eurostat/home/

10. Meyer Dietmar - Solt Katalin (1999): Makrokonmia (Macroeconomics). Aula,

Budapest, 1999.

11. Samuelson P.A.Nordhaus W. D (1998): Kzgazdasgtan (Economics). Akadmiai,

Budapest, 2008.

12. Valkovics Vladimir, Demography, Osiris, Budapest. 2001.