Every market has buyers and sellers, and the labour market is no exception: the buyers are employers, and the sellers are workers. Some of this participant may not be active at any given moment in the sense of seeking new employees or new jobs, but on any given day, thousands of firms and workers will be “in the market” trying to transact.
The Labour Force and Unemployment
The term labour force refers to all those over 16 years of age who are either employed, actively seeking work, or expecting recall from a layoff. Those in the labour force who are not employed for pay are the unemployed. [1]
People who are not employed and are neither looking for work nor waiting to be recalled from layoff by their employers are not counted as part of the labour force. The total labour force thus consists of the employed and the unemployed.
The number and identities of people in each labour market category are always changing; the flows of people from one category to another are considerable. There are four major flows between labour market states:
employed workers become unemployed by quitting voluntarily or being laid off (being involuntarily separated from the firm, either temporarily or permanently),
unemployed workers obtain employment by being newly hired or being recalled to a job from which they were temporarily laid off,
those in the labour force, whether employed or unemployed, can leave the labour force by retiring or otherwise deciding against taking or seeking work for pay (dropping out),
those who have never worked or looked for a job expand the labour force by entering it, while those who have dropped out do so by re-entering the labour force.
The ratio of those unemployed to those in the labour force is the unemployment rate. While this rate is crude and has several imperfections, it is the most widely cited measure of labour market conditions.
The relation among unemployment, employment, and labour force
Analytically, to access the unemployment rate we can use the following equality:
where , , and designate respectively the working-age population, the level of employment, the number of unemployed, and the participation rate at period t. Defining the unemployment as , we have
Using this equation in logarithm terms at time t and t-1, we get:
Assuming that u is a small number, this relation allows us to express the variation of unemployment rate as a function of the growth rates of working-age population, employment, and participation:
This decomposition shows that the variation in the rate of unemployment come from variations in the employment rate, the size of the working-age population, and participation rate.
Chapter 2 – Some facts
The different unemployment experience
During the last 20 years, the industrialized countries have evolved in very different direction with respect to unemployment. In contradiction to Japan, or the United States, most of European countries showed a high proportion of unemployment.
Table 1.1 Rates of unemployment, participation, and employment in 20 OECD countries in 2011
Country
Unemployment Rate
Participation Rate
Employment Rate
Australia
5,10
78,8
72,70
Austria
4,14
75,79
72,13
Belgium
7,14
68,88
61,93
Canada
7,45
80,25
71,98
Denmark
7,57
83,19
73,15
Finland
7,77
75,43
69,03
France
9,26
69,34
63,80
Germany
5,92
81,04
72,53
Greece
17,66
68,57
55,55
Ireland
14,39
70,96
59,20
Italy
8,40
63,01
56,98
Japan
4,57
80,61
71,20
Luxembourg
4,90
70,57
64,63
Netherlands
4,44
80,13
74,88
Norway
3,21
80,22
75,30
Portugal
12,74
77,42
64,20
Spain
21,64
75,28
57,68
Sweden
7,54
31,00
74,10
Switzerland
4,04
86,60
79,35
United Kingdom
8,01
76,75
69,48
United States
8,95
64,21
66,65
Euro area (17 countries)
10,07
26,20
64,25
EU (27 countries)
9,59
…
64,30
OECD – Total
7,92
27,80
64,85
Source: OECD Data
Table 1.1 summarises the unemployment, participation and employment rates in 20 OECD countries for 2011. We see that unemployment is a phenomenon that touches all the countries, but in different proportions. There are some countries such as Austria, Japan, Luxemburg, the Netherlands, Norway, and Switzerland, have an unemployment rate below 5 per cent. But other countries, such as Greece, Ireland, Portugal, and Spain, have an unemployment rate higher than 10 per cent. For the European Union as a whole (27 countries), the average unemployment rate is the neighbourhood of 10 per cent, 2 points greater than the overall OECD unemployment rate.
Get Help With Your Essay
If you need assistance with writing your essay, our professional essay writing service is here to help!
The third column reports the employment rate, i.e. the ratio of the number of persons employed to the number of person in the population (working-age from 15 to 64 years old). This indicator is very important for the analysis since it can be used as a complement to the data of unemployment, given that the definition of unemployment is necessarily objective. As we can see from table 1.1 countries with high employment rate are also the ones who have low rates of unemployment. So there is a negative relationship among them.
The second column also shows that participation rates are highly dispersed, since they vary from 63.01 per cent in Italy to 86.60 per cent in Switzerland. Moreover, countries that face high unemployment rate generally have relatively a weak participation rate.
This rapid overview of the rates of unemployment, participation, and employment in different OECD countries suggest that certain countries face a relatively high unemployment rate because of insufficient job creation. Examination of changes over time since the beginning of 1950s in unemployment and employment rate in the United States and selected OECD countries will throw further lights on the origins of unemployment.
The US unemployment experience in comparative perspective
Table 1.2 summarises the unemployment experience of the United States, selected other countries, and the OECD as a whole from 1950 to 2011. The OECD unemployment rate averaged about 3 per cent during the 1950s and 1960s unemployment throughout the OECD increased sharply in the aftermath of the oil shocks of the 1970s and continued rising the worldwide recession of the early 1980s. The overall OECD unemployment rate more than doubled from 2.8 per cent in the 1960s to 7.0 per cent in the 1980s, and has remained at an even higher rate in the 1990s. Last year the overall OECD unemployment rate was 8.2 per cent.
Table 1.2 Unemployment rates in selected OECD countries
Country
1950
1960
1970
1980
1990
2000
2011
Australia
1,50
2,00
3,90
7,50
9,10
6,28
5,20
Canada
3,80
4,70
6,60
9,30
9,90
6,82
7,50
France
1,50
1,70
3,80
9,00
11,10
9,4
9,30
Germany
4,90
0,60
1,90
5,70
6,50
7,76
6,00
Italy
7,20
3,80
4,70
7,50
10,20
10,59
8,50
Japan
2,10
1,30
1,70
2,50
2.7
4,72
4,80
Netherlands
1,50
0,90
4,00
9,60
6,90
2,95
4,40
Norway
1,70
1,70
1,60
2,80
5,30
3,33
3,30
New Zeland
0,90
0,90
1,50
4,10
8,10
9,00
6,70
Portugal
2,20
2,40
1,60
7,30
5,80
4,04
13,40
Spain
2,10
2,30
4,20
17,50
20,30
13,92
21,80
Sweden
1,70
1,50
1,80
2,20
7,00
5,4
7,60
United Kingdom
1,70
2,00
4,40
10,10
8,70
5,58
8,00
United States
4,40
4,70
6,10
7,20
6,00
4,00
9,10
OECD
3,50
2,80
4,30
7,00
7,30
6,1
8,2
Source: OECD Data
Table 1.2 indicates that major OECD nations shared a pattern of rising unemployment from the 1960s to the 1970s to the 1980s, but the magnitude of the increases vary widely across countries, with the largest increase in Spain. In the 1990s the unemployment experience diverge somewhat, with continued increases from the 1980s in most European countries and Australia, but decline in the United States, United Kingdom, and Portugal. In the 2000s there is a general decrease of unemployment rate among all the countries, except in Italy and Japan. From 2000 to 2011 unemployment is a phenomenon that touches all the countries but in different proportion, with the largest increase in Spain and Portugal.
The table highlights the distinctive aspects of the evolution of US unemployment. The United States has moved from having a consistently higher unemployment rate than the OECD as a whole in the 1950s, 1960s and 1970s to having a much lower rate in the 1990s and 2000s, but again a higher unemployment in 2011. The United States is the only major OECD economy with a lower average unemployment rate in 2000s than in 1980s: 4.0 per cent in the 2000s versus 7.2 per cent in 1980s. But the current US unemployment rate of 9.1 per cent is the highest experienced since 1980.
The composition of US unemployment also differs substantially from many other OECD nations. The United States has much larger month-to-month flows into and out of employment than most of OECD economies and a much lower incidence of long-term unemployment than any advanced OECD economy. Long-term unemployment (six months and less than one year) as a percentage of total unemployment in 2011 stood at 12.43 per cent in the United States as compared with 9.8 per cent in Canada, 13.48 per cent in Australia, 18.65 per cent in France, 14.71 in Germany, 15.03 in Italy, 17.68 in Greece and 18.66 in Spain. US unemployment rates for the working-age population are particularly low (and employment/population ratios are particularly high) for young workers (those aged to 15 to 24), women and older workers (those aged 55 to 64). Overall, the US labour market does a relatively good job of moving new entrants and women into employment. European labour market institutions (especially employment protection laws) seem geared to keeping married males in work, but appear to make it tougher for new entrants to gain steady employment.
Cyclical versus Structural unemployment
The analytical discussion of unemployment since Friedman (1968) and Phelps (1968) start with the hypothesis that at any given time, a national economy is characterized by a natural rate of unemployment. Aggregate demand expansions can (at least temporarily) push the economy below this rate of unemployment, but at the cost of accelerating inflation. Similarly, shocks that raise unemployment above the natural rate lead to deceleration inflation. As long as the policy-maker avoids explosive inflation or deflation, the economy cannot remain persistently above or below the natural rate of unemployment, but it may fluctuate around it.
This hypothesis suggests separating changes in unemployment into cyclical fluctuation around the natural rate and structural movement in the natural rate itself.
Figure 1 Unemployment in the US, Australia, Europe and OECD
Figure 1 illustrates the time patterns of the unemployment rates for the United States, Australia, Europe, and OECD countries from 1970 to 2011. The figure suggests cyclical unemployment fluctuation around a relatively stable natural rate in the United States until 2008, and a possible upward drift in the natural rate in Europe and Australia. The acceleration in inflation in most European economies in late 1980s, despite much higher unemployment rate than in the 1960s and 1970s, indicates a large rise in natural rate of unemployment. The deceleration of inflation in the 1990s and early 2000s suggests that some cyclical component has played a role in recent high European unemployment.
2 – Data and Descriptive statistics
I next explore in a more depth, the extent to which a relatively stable natural rate of unemployment since 1970 or so is consistent with the experience of the flexible US labour market. The data for this analysis are taken from Bureau of Labour Statistics from 1970 to 2012 (monthly data).
3 – Empirical Methodology and Results
For estimating the natural rate of unemployment (un) I am going to use the expectations-augmented (or accelerationist) Phillips Curve (EAPC) in which the rate of growth of price inflation (or more generally the difference between current inflation and expected inflation) depends on the deviation of the unemployment rate from the natural rate:
where p is the log of the price level, u is the unemployment rate, is a positive coefficient, equals, and is an error term. Expected inflation is assumed to equal the lagged inflation rate (). A regression of the change in the inflation rate on the unemployment rate yields estimates of the natural rate of unemployment ( = -. The basic idea behind this equation is that price inflation increases when unemployment is below the natural rate and decreases when it is above.
Table 2.1 Price inflation and unemployment in the United States, Europe and OECD countries
United States
Europe
OECD
(1)
(2)
(3)
(4)
(5)
Constant
0.397562
0.519119
0.142052
11.87027
12.00131
[6.163198]
[8.568430]
[1.910330]
[7.503319]
[5.137325]
D80
-0.348037
[0.929960]
D90
-0.355382
[0.950040]
D00
-0.369512
[0.986341]
Unemployment rate (u)
-0.006995
-0.026207
0.032498
-0.596646
-0.906432
[0.669781]
[2.835975]
[2.918381]
[3.129660]
[2.544017]
Observations (n)
511
511
511
41
41
Durbin-Watson Statistic
0.798394
0.828986
0.833514
0.233627
0.304103
R2
0.006191
0.015555
0.016457
0.200734
0.142330
Notes: The US regressions cover 1970 to 2012. The dependent variable in all regressions is the inflation rate (Dp).The numbers in parenthesis are standard errors. p=100*log(CPI), using the Consumer Price Index for the United States and Europe; u is the unemployment rate measured in percentage, D80=1 for the 1980- and 0 otherwise; D90=1 for the 1990- and 0 otherwise; D00=1 for the 2000- and 0 otherwise.
Estimation for US unemployment
Dependent Variable: P
Method: Least Squares
Date: 10/04/12 Time: 17:04
Sample (adjusted): 1970M02 2012M08
Included observations: 511 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.397562
0.064506
6.163198
0.0000
UNEMP
-0.006995
0.010444
-0.669781
0.5033
D80
-0.348037
0.374250
-0.929960
0.3528
D90
-0.355382
0.374071
-0.950040
0.3425
D00
-0.369512
0.374629
-0.986341
0.3244
R-squared
0.006191
Mean dependent var
0.353720
Adjusted R-squared
-0.001665
S.D. dependent var
0.373392
S.E. of regression
0.373702
Akaike info criterion
0.879023
Sum squared resid
70.66469
Schwarz criterion
0.920475
Log likelihood
-219.5904
F-statistic
0.788056
Durbin-Watson stat
0.798394
Prob(F-statistic)
0.533265
Estimation for US male unemployment
Dependent Variable: P
Method: Least Squares
Date: 10/04/12 Time: 17:05
Sample (adjusted): 1970M02 2012M08
Included observations: 511 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.519119
0.060585
8.568430
0.0000
UNEMPMALE
-0.026207
0.009241
-2.835975
0.0048
R-squared
0.015555
Mean dependent var
0.353720
Adjusted R-squared
0.013621
S.D. dependent var
0.373392
S.E. of regression
0.370840
Akaike info criterion
0.857814
Sum squared resid
69.99885
Schwarz criterion
0.874395
Log likelihood
-217.1715
F-statistic
8.042753
Durbin-Watson stat
0.828986
Prob(F-statistic)
0.004751
Estimation for US female unemployment
Dependent Variable: P
Method: Least Squares
Date: 10/04/12 Time: 17:07
Sample (adjusted): 1970M02 2012M08
Included observations: 511 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.142052
0.074360
1.910330
0.0567
UNEMPFEMALE
0.032498
0.011136
2.918381
0.0037
R-squared
0.016457
Mean dependent var
0.353720
Adjusted R-squared
0.014525
S.D. dependent var
0.373392
S.E. of regression
0.370670
Akaike info criterion
0.856897
Sum squared resid
69.93471
Schwarz criterion
0.873478
Log likelihood
-216.9373
F-statistic
8.516946
Durbin-Watson stat
0.833514
Prob(F-statistic)
0.003674
Estimation for Europe unemployment
Dependent Variable: P2
Method: Least Squares
Date: 10/04/12 Time: 17:08
Sample (adjusted): 1970M02 1973M06
Included observations: 41 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
11.87027
1.582002
7.503319
0.0000
UNEMPEURO
-0.596646
0.190642
-3.129660
0.0033
R-squared
0.200734
Mean dependent var
7.164938
Adjusted R-squared
0.180240
S.D. dependent var
3.481375
S.E. of regression
3.152057
Akaike info criterion
5.181538
Sum squared resid
387.4831
Schwarz criterion
5.265127
Log likelihood
-104.2215
F-statistic
9.794774
Durbin-Watson stat
0.233627
Prob(F-statistic)
0.003308
Estimation for Europe unemployment
Dependent Variable: P3
Method: Least Squares
Date: 10/04/12 Time: 17:09
Sample (adjusted): 1970M02 1973M06
Included observations: 41 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
12.00131
2.336102
5.137325
0.0000
UNEMPOECD
-0.906432
0.356299
-2.544017
0.0150
R-squared
0.142330
Mean dependent var
6.186970
Adjusted R-squared
0.120338
S.D. dependent var
3.301618
S.E. of regression
3.096597
Akaike info criterion
5.146035
Sum squared resid
373.9676
Schwarz criterion
5.229624
Log likelihood
-103.4937
F-statistic
6.472025
Durbin-Watson stat
0.304103
Prob(F-statistic)
0.015033
Conclusion
References
Literature
Ronald G. Ehrenberg, Robert S. Smith “Modern Labour Economics. Theory and Public Policy” – Pearson International Edition, 2009, Tenth Edition
Internet Sources
http://www.tradingeconomics.com
http://www.indexmundi.com/
http://www.statcan.gc.ca/daily-quotidien/120907/dq120907a-eng.htm
Eurostat Website: http://ec.europa.eu/eurostat
I have a problem with the regression of this model:
I have monthly data. But when I estimate it on Eviews, the results I get are not that expected: R-squared is very small (near to zero), the standard errors are all smaller than 1.
In order to estimate the model first I have done this: P=100*log(CPI), but I’m not sure if is right or not.
I can send the data after if this description is not enough.
Cite This Work
To export a reference to this article please select a referencing style below:
