Executive summary Introduction Current Unemployment status in UK
The unemployment rate in UK in June 2013 was 7.7 percent among the economically active population which is 0.1 percent lower from march 2013 and 0.2 percent lower from the year 2012.Moreover, there were 2.49 million unemployed people at the age of 16-64 of whom 1.42 million was male and 1.07 million was female in united kingdom in June 2013 which is 18000 lower from march in the same year and 40000 lower from earlier year. However, the inactivity rate of the age from 16 to 64 was 22.2 percent which is 0.2 percent lower than that in March of the respective year and 0.3 percent lower than that in previous year. The total number of economically inactive people aged from 16-64 was 8.95 million which is lowered by 83 thousands from March in the same year and is also lower than 88 thousands from previous year. Chart: Unemployment rate (aged 16+)
Source: Labour Force Survey Surve y - Office for National Statistics
Chart: Unemployment by duration for June to August 2013
Source: Labor Force Survey - Office for National Statistics
On the other hand, in case of international comparison, the unemployment rate in European Union (EU) 10.9 percent of the economically active population in august 2013.however, the highest unemployment rate in EU countries is 27.9 percent in Greece and 26.2 percent in Spain. The lowest unemployment rate in EU countries is 4.9 percent in Austria. Moreover, unemployment rate in Japan was 4.1 percent in august 2013 where the rate in United States was 7.3 percent in the same duration.
However, the employment in UK from the beginning of 2008 to early 2010 reduced by 80 thousands because of economic (Mimeo, 2010) recession. This was not a large decline because at the time of recession in 1980, employment decline by 1.8 million. In addition, the male loss their job more than female where male employment reduced by 3 percent and female employment was declined by only 0.7 percent at the time of recession. Though young are 19.5 percent of the working population in united kingdom, they have to suffer discriminately. Among the employment deduction in 2008 and 2010, 74 percent was between the age from 16 to 24.there was also gender biasness in job losses where 44 percent were male and 30 percent was female
among the job loser. Furthermore, unemployment rate of young people is also high with 35.6 percent for 16-17 years old as well as 17.1 percent for 18-24 years old. There is also a declining trend in employment to population rate of the young. Moreover, unemployment rate for young is higher than adults whereas the ratio of unemployment rate of young and adults is 2.53.the reason behind the increase in unemployment rate is decline in demand for labor as product demand is declining.
Economic Growth and Unemployment: It is widely accepted that there is a negative relationship between economic growth rates and the unemployment rate (Mitra, 2007). In the short term, there is no such strong connection between economic growth and an employment rate. It is very usual for unemployment rate to show a declining trend, if the overall activities of economy have shown a positive turned. For this reason, this is known as lagging economic indicator. It can be explained further by an example. Unemployment may not decrease at the same time when a recession ends. It may happen because some firms may have underutilized human resource on their payroll. It is because of laying-off workers when demand decreases and again hiring them again when the demand of products and services increases (Farsio and Quade, 2003). If employer keeps the extra employee during downtrend of economy, he can raise the production level at the very beginning of recovery stage of economic cycle without hiring additional employee. He can respond the increasing demand by raising productivity level. This le will push up the productivity level temporarily. Here a table showing the trend of economic growth rate and unemployment rate is give. Year
Growth Rate (%)
Unemployment Rate
2002
2.3
5.199
2003
2.82
5.048
2004
2.89
4.788
2005
2.34
4.799
2006
2.94
5.406
2007
2.72
5.4
2008
-0.14
5.558
2009
-4.96
7.458
2010
1.7
7.858
2011
1.1
2012
0.3
2013
1.9
7.7 8 7.2
Source: BBC: Economic Tracker: 2014 This data reveal the relationship between economic growths and unemployment. If we look at the growth and unemployment rate in 2009, it is seen that the unemployment rate is the highest and the growth rate is the lowest among the years presented here. The relationship between this two factors are analyzed further bellow Output will not grow faster than the rate of productivity growth until the employer begins adding workers, after the labor on hand is fully utilized. By the combined rate of growth in labor supply and labor productivity output can be measured, as the economy expand is progression. The unemployment rate will decline, as long as growth in real gross domestic product is more than the growth in labour productivity. Employment condition will improves, if the employment growth is more than that of labor force. The long run relationship these two economic variables can be described best by the “Law of Okun”.
The “Low of Okun” is propounded by Arthur
Okun. This theory propounds that the potential output rate which is equal to the real GDP growth, is necessary to maintain a stable unemployment rate. So it is recognized that the rate of potential output rate is the key point to maintain the relationship between changes in the rate of GDP growth and unemployment rate. If the unemployment rate is high as it is now in UK, the real GDP has some shortage of potential GDP and this is known as output gap. As there is no
productivity growth, labor supply growth rate will be equal to the growth in output, as long as there is an addition to the labor force. There will be shortage of employment opportunities, if the labor force growth rate is larger than the GDP growth rate (Tatom). As a consequence, the proportion of number of people with employment will fall. In the presence of productivity growth rate, if the GDP growth is equal to labor supply growth rate, it will create job opportunity for more people. This is because of rising demand which will motivate the employer to employ more people. The policymakers are trying heart and soul to cut off the unemployment rate by providing stimulus policies. Bu it is true that to bring down the unemployment rate, it is necessary to maintain a output growth.
Inflation Rate and Unemployment: Inflation is a bane for an economy and at the same time employment is boon for an economy. But the true fact is that there is a negative relationship between these two variables of an economy (Phillips, 1958). If the policy makers want to cut off the unemployment rate, there must be a high inflation rate. But this notion is applicable for short term. So there must be a trade-off between inflation and unemployment rate. If the goal is to maintain a low unemployment rate, the economy is required bear a high inflation rate. On the other hand, if the purpose is to maintain a low inflation rate, there may be a high unemployment rate (Tobin, 1972). It is mater of hope that a reasonable rate for both for this variables achievable. The relationship between inflation and variables in the context of UK‟s economy can be illustrated with the help of “Philips Curve”. Philips Curve: Philip‟s curve describes the relationship inflation and unemployment. Phillips showed that unemployment and inflation shared an inverse relationship inflation rose as unemployment fell, and inflation fell as unemployment rose. To create employment opportunity, the government is following stimulus policies. Due to these stimulus policies, more employment opportunities are created which raise the demand of labour. It creates more demand for products which raise the level of employment further. So the people have money in hand to spend, which creates demand for product and thus raise the level of price ultimately. This is the mechanism how more employment creates more inflation.
The Philips‟s curve has been created with data of the economy of UK for the years 20022013. Year
Inflation Rate (%)
2002
1.3
Unemployment Rate
5.199 2003
1.4
5.048 2004
1.3
4.788 2005
2.1
4.799 2006
2.3
5.406 2007
2.3
5.4 2008
3.6
5.558 2009
2.1
7.458 2010
3.29
2011
4.48
7.858 7.7
2012
2.83
8
2013
2.5
7.2
Source: International Monetary Fund - 2013 World Economic Outlook
9 8 7 6 5 4 3 2 1 0 2000
2002
2004
2006 Infaltion
2008
2010
2012
2014
Unemployment
Source: Author Here we see some discrepancy of theory propounded by Philip‟s. We see in 2011 unemployment rate and inflation rates both are high. Again in 2012, while the unemployment rate is high but the inflation rate is high. This is not always true that inflation and unemployment are inversely related. If the policy maker can come up with a number tools to control inflation while curving the unemployment rate, it is possible to achieve low inflation rate and low unemployment rate. For example, if the production can be raised along with the raising the income level of the, it can be possible to curve the inflation rate.
Impact of Technology on Unemployment: The technological advancement may affect the unemployment negatively for very short term. Technology both eliminates jobs and creates jobs (Nordhaus, 2007). Generally it destroys lower wage, lower productivity jobs, while it creates jobs that are more productive, high-skill and better paid. Historically, the income-generating effects of new technologies have proved more powerful than the labour-displacing effects: technological progress has been accompanied not only by higher output and productivity, but also by higher overall employment (OECD, 1994). Almost all types of technological development create new demand for labor in some labor markets and reduce the demand for labor in other labor markets (Mokyr, 1990). For example, there is a substantial increase in labor productivity because of the introduction of assembly line
production methods and the production of interchangeable parts resulted in production. This sort of technological innovation also creates demand for unskilled workers and at the same time decrease in the demand for skilled artisans. On the contrary, the introduction of automation in manufacturing processes reduces the demand for unskilled workers and has created demand for quality control technicians and computer programmers. Usually, the mix of the demand for labor will be changed by technological change, raising the demand for some types of labor and reducing the demand for other types of labor (Mantoux, 2006). The people who will lose jobs as a consequence of technological change that reduces the demand for that particular category of labor are known as structurally unemployed. So it appears that technological change may affect the demand for labor negatively in a particular labor market but the aggregate effect of technology on unemployment is positive. It can be cleared with an example from UK labor history. For example, in 1800, the majority of British workers were employed in agriculture. Labour saving technology meant that food could be produced with fewer workers and so some agricultural laborers lost their jobs as farms used more machines. However, as jobs were lost in agriculture, new jobs were created in producing machines. Still technological change can raise the unemployment level, if the labor market is inflexible. It means the labor force has only one skill and they are stick to this.
Consequence of unemployment Unemployment may lead to psychological disorder, social crime as well as economic downturn. However, there are other consequences of unemployment those are mention below:
During the period of unemployment, the skills and ability of the workers reduces that leads to the loss of human capital and ultimately to the loss of economic output.
A group of economists believe that unemployment leads to stressful life which makes an unemployed man unhappy (Winkelmann and Winkelmann, 1998; Clark and Oswald, 1994; Frey and Stutzer, 2002; Ahn et al., 2004).
Another team of economic analysts mentioned that unemployment leads to malnutrition, illness, mental stress and loss of self esteem and hence ultimately to depression (Linn et al., 1985; Frese and Mohr, 1987; Jackson and Warr, 1987; Banks and Jackson, 1982; Darity and Goldsmith, 1996; Goldsmith et al., 1996; Brenner and Mooney, 1983).
Goldsmith et al. (1996, 1997) found out that joblessness destroy self esteem and creates a feelings of externality and helplessness among the youths. In addition, they also found that based on the empirical evidence that joblessness leads to psychological disorders.
Te most important thing is that a group of socio-economists (Platt, 1984; Pritchard, 1992; Blakeley et al., 2003; Hamermesh and Soss, 1974; Daly et al. 2008) found that there if positive relationship between the rate of unemployment and the rate of suicide. That indicates, suicide rate rises with the increase in unemployment rate. Moreover, a long unemployed person has higher propensity to commit suicide.
(Brenner and Mooney, 1983; Moser et al., 1987, 1990) mentioned that unemployment may also cause to decline in life expectancy of workers.
Moreover, the probability of poor physical health and complex disease like heart attacks increases with the level of unemployment reported by Beale and Nethercott, 1987; Iverson and Sabroe 1988; Mattiasson et al., 1990.
However, the effect of unemployment depends on the duration of joblessness of person. The longer the period of joblessness, the greater the impact of unemployment. Long term unemployment leads to people‟s moral sinks (Layard, 1986,).
Ellwood, (1982) told that being unemployed for long duration especially at the age of youth leads to permanent scars.
An empirical research shows that there is positive relationship between unemployment rate and crime rate especially property crime. Thornberry and Christensen (1984) found that engagement in crime decrease employment prospects that ultimately increase the probability of involvement in crime. Fougere et al. (2006) mentioned that burglaries, thefts and drug offences increase with the rise in unemployment rate of young. However, Hansen and Machin (2002) mentioned that there is substantially negative relationship between the number of crime reported by police for property and vehicles crime and the proportion of worker payment beyond the minimum.
Carmichael and Ward (2001) mentioned that there is significant positive relationship between burglary, theft, fraud and forgery and total crime rates and young and adult unemployment. However the relationship between each category of crime and youth unemployment is stronger. Carmichael and Ward (2000) also found that burglary rates and male unemployment regardless of age are positively correlated.
Finally, there is positive relationship between unemployment rate and happiness of everybody in the society (Di Tella et al., 2001, 2003; Blanchflower, 2007; Knabe and Rätzel, 2008).In addition; rise in aggregate unemployment rate reduces national well being.
Conclusions: Unemployment is one of the key variables. Demand for a product and thus investment is directly related. Again the level of employment or unemployment is also affected by several as explained previously. The conclusions that can be drawn from the previous discussion that some variable have direct effect on unemployment in short and long terms. Some others have indirect effect on unemployment. The growth rate has a direct bearing on unemployment. If the growth rate is high, it will generate more economic activities and thus creates more employment opportunities. The effect of technology on unemployment is positive. It offsets the unemployment; it creates by increasing the deman d of labor in any other sector.
References
1. Mitra, A. and H. Sato (2007); Agglomeration economies in Japan: Technical Efficiency, Growth and Unemployment; Review of Urban and Regional Development Studies; Vol. 19, No. 3, pp. 197-209; 2. Nordhaus, W.D. (2007). Two centuries of productivity growth in computing.The Journal of Economic History, vol. 67, no. 1, p. 128. 3. Mokyr, J. (1990). The lever of riches: Technological creativity and economic progress. Oxford University Press. 4. Mantoux, P. (2006). The industrial revolution in the eighteenth century: An outline of the beginnings of the modern factory system in England. Taylor & Francis US. 5. OECD, "The OECD Jobs Study: Facts, Anal ysis, Strategies" http://www1.oecd.org/sge/min/job94/part2c.htm 6. "BBC News - Economy tracker: GDP". Bbc.co.uk. 2014-01-28. Retrieved 2014-02-08. 7. Farsio, F. and S. Quade, 2003. An empirical analysis of the relationship between GDP and unemployment. Humanomics, 19: 1-6. DOI: 10.1108/eb018884 8. Tatom, J.A., 1978. Economic Growth and Unemployment: A Reappraisal of the Conventional View, Federal Reserve Bank of St. Louis. pp: 16-23. 9. Phillips, A.W. (1958) „The Relation Between Unemployment and the Rate of Change of Money Wages in the United Kingdom, 1861-1957,‟ Economica, New Series, Vol. 25, Nos. 97-100, pp. 283-99. 10. Tobin, J. (1972) „Inflation and Unemployment,‟ American Economic Review, Vol. 62, No. 1, May, pp. 26-37.