The Labour Force And Unemployment Economics Essay

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. [] 

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.

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.