HOW UNEMPLOYMENT RATE AFFECT LABOR FORCE PARTICIPATION RATE IN DIFFERENT GROUPS OF PEOPLE
Introduction
Employment of individuals has been identified as one factor that counts in the determination of the extent to which people participate in various groups in a population. It is believed that the unemployment rate in any given population is known to be very influential in determining the labor force participation in different groups of a population (Peter & Dennis 2004). Labor force participation rate refers to the group of population between 16 years and 64 years in which some people are employed while others are not but looking for job (Farmer 1999). On the other hand, unemployment rate refers to the number of people who are not working at a given time. It is obtained by dividing the number of the people who are not employed by the total number of people in the labor force. It is worth noting that there are various attitudes towards employment in different group of people. The things that motivate people to look for employment are totally different.
To carry out this research, I will collect data which will be able to assist me in answering the research question of how unemployment rate affect labor force participation rate in different groups of people. The data will be analyzed and broken down in specific components so as to be able to come up with a piece that is understandable.
The issue of gender is very useful in understanding the issue of labor force participation rate. The research will be able to show the movement in the number of people participating in labor force across the male and female gender. The impact of the movements to the overall labor force participation rate will be of interest.
It is important to note that there are people who are not employed but do not look for a job. This group of people in the population are usually not considered when talking about the unemployment and labor force participation rate.
The economic or financial impact of the various labor situations will be looked at. This is aimed at showing the need to have well managed labor markets for all organizations. The issue of making better decisions regarding a company’s labor force will be briefly touched on.
Literature Review
Over the years, studies have been carried out regarding the issue of how unemployment rate affect labor force participation rate in different groups of people. This has been able to give an interesting insight into the effect of unemployment rate on the labor force participation in different groups of people.
Jorgen Elmeskov and his compatriot Karl Pichelman came up with a study on the trends and cycles involved in labor force participation with relation to the unemployment rate. Additionally, Dale Bremmer and his colleague Randall Kesselring also did a study on this issue. All these people were able to come up with findings which can be relied upon by people interested in this topic.
In their work titled ‘The Relationship between Aggregate Unemployment and the Labor Force Participation Rate: New Evidence on Divorced Women and the Discouraged Worker Effect’, Dale Bremmer and his colleague Randall Kesselring came up with several issues regarding unemployment rate and labor force participation in different populations. Firstly, their study showed that the rate at which people workers get determines the direction the labor force participation rate will take. The authors observed that whenever people are looking for jobs which become elusive, they get to a point of discouragement. This means that they stop taking part in looking for job. This means that the labor force participation rate goes down. These scholars used the vector auto regressions (VAR) and impulse functions in analyzing the relationship between unemployment rate and labor force participation rate. The study also handles the issue of people staying unemployed for long. The findings indicate that those who stay unemployed for long slow down. According to their study, the slowing down of workforce reverses the positive movement in labor force participation in a population. This means that the chances of unemployment persisting become higher. With this happening, the unemployment rate goes higher than before, while the labor force participation rate goes down.
The second work by Jorgen Elmeskov and his compatriot Karl Pichelman titled ‘unemployment and labor force participation-trends and cycles’, a good presentation of how these two factors relate is given. The study clearly shows how the unemployment rate behaves so as to cause an effect to the labor force participation rate. The scholars bring out several interesting factors regarding the things that affect labor force participation in a population. One of the things identified is school attendance. The study points out that an increase in the rate t which people attend school leads to a fall in the labor force participation rate in a population. This is because people are not focusing on working but schooling. Another factor cited by this study is the increase in the number of female individuals in the labor force. The scholars show that labor force participation increased as a result of unemployed female population taking up jobs. Jorgen Elmeskov and Karl Pichelman also show how male participation in labor force has been on the decline. They indicate that the decline has not been sharp recently. However, the decline does not count much in the labor force participation rate since it has been replaced by the increase in the level of female participation. These scholars also touch on the differences observed in the different countries. The two show that the different populations in the various countries exhibit totally difference in the unemployment rate and labor force participation. Additionally, these two scholars have been able to bring out an aspect of workforce management in companies. Their aim is to show how companies can manage their workforce by making decisions which support their financial status as well as boosting the economy. This is important since it also helps in making the labor participation rate in populations reasonable. Wells (1891) observed that proper workforce management in organizations is a good tool for ensuring that the output of an organizations remains at reasonable levels.
Economic/financial Theory
From the study, it is important to learn that the unemployment rate is very influential to the economy of countries. This is because it largely tells the output to expect. Additionally, there is usually an economic consideration in the labor force participation. This can be viewed by looking at a case where companies want to lay off employees. According to Whaples (1991), the companies may opt to reduce the hours worked by the employees so as to cut costs without letting them jobless. This is one thing that is likely going to make the economy move without taking nose dives. With people earning something, their spending will not be affected much. Output in the companies will also be at the desired level thus fostering economic stability especially during hard times (Rothbard 1963).
It is worth noting that labor force participation improves the output in companies. This is because people fear being in the labor force under the unemployed category. This means that the people who have been able to get employment opportunities are willing to work well. This is because in most cases, workforce supply is usually higher than the demand. According to Tachibanaki & Sakurai 1992, with low labor force demand employment opportunities are few. This means that individuals are usually competing for the minimal chances available. In the process of making a name in employment, the individuals deliver beyond expectations. This leads to good performance of the companies.
Data and Methodology
The Data for the study is obtained from secondary sources. The data gives details regarding the number of individuals in different categories and relation within the genders.
| FULL- OR PART-TIME STATUS | Number | ||||||||
| Full-time workers(2) | 10,155 | 9,693 | 9,243 | 8.1 | 7.6 | 7.6 | 7.6 | 7.7 | 7.3 |
| Part-time workers(3) | 1,810 | 1,579 | 1,632 | 6.2 | 6.2 | 5.6 | 5.8 | 5.5 | 5.6 |
Augmented Dickey-Fuller Unit Root Tests: Sample 1976:6 – 2011:2
Level Data
Variable Test Statistic Constant Trend Lag
Single Female Labor -71.7820* Yes No 25
Force Participation Rate (0.0001)
Married Female Labor -66.3142* Yes Yes 0
Force Participation Rate (0.0001)
Divorced, Separated, or Widowed -176.0965* Yes Yes 14
Female Labor Force Participation Rate(0.0001)
Single Male Labor -1.2943 Yes Yes 13
Force Participation Rate (0.8878)
Married Male Labor -2.5277 Yes Yes 4
Force Participation Rate (0.3145)
Divorced, Separated, or Widowed -2.9909 Yes Yes 12
Male Labor Force Participation Rate (0.1361)
Overall Unemployment Rate -2.6313*** Yes No 15
(0.0875)
First Differences of the Data
Variable Test Statistic Constant Trend Lag
Single Female Labor -19.8829* Yes Yes 0
Force Participation Rate (0.0000)
Married Female Labor -20.5808* Yes Yes 0
Force Participation Rate (0.0000)
Divorced, Separated, or Widowed -20.6227* Yes Yes 0
Female Labor Force Participation Rate (0.0000)
Single Male Labor -6.2895* Yes Yes 12
Force Participation Rate (0.0000)
Married Male Labor – 15.4538* Yes No 3
Force Participation Rate (0.0000)
Divorced, Separated, or Widowed -7.3785* Yes Yes 12
Male Labor Force Participation Rate (0.0000)
Overall Unemployment Rate -4.9429* Yes Yes 11
(0.0000)
Pair wise Granger-Casualty Tests: The Relationship between Labor Force Participation Rates and the Overall Unemployment Rate
Null Hypothesis: Sample 1976:6 – 2011:2
| Population subsample | Labor force participation rate does not granger cause overall unemployment rate | Overall unemployment rate does not granger cause labor force participation rate | Lags in VAR |
| Single Females | 5.141 | 3.889 | 16 |
| Married Females | 2.535 | 5.018 | 13 |
| Divorced, separated and windowed Females | 0.96 | 3.577 | 16 |
| Single Males | 5.159 | 4.291 | 16 |
| Married males | 1.75 | 5.741 | 13 |
| Divorced, separated and windowed males | 1.519 | 2.078 | 13 |
| VECTOR AUTO REGRESSION (VAR) Estimation Results |
| Explanatory Variables |
| Variables SFt MFt DFt SMt MMt DMt Ut |
| SFt-1 0.6909 -0.0113 0.0795 0.0810 -0.0284 -0.0123 -0.0112 |
| SFt-2 -0.2174 0.0530 -0.0 127 -0.3789 0.0003 0.0686 -0.0001 |
| SFt-3 0.1178 0.0559 0.0475 0.1366 -0.0106 -0.0237 0.0137 |
| SFt-4 0.4445 -0.1355 -0.0525 0.4674 0.0050 -0.0312 -0.0514 |
| SFt-5 -0.1837 0.0129 0.0267 -0.3078 0.0216 -0.0238 0.0072 |
| MFt-1 0.1185 0.7000 -0.0256 0.3255 0.0124 -0.0651 -0.0106 |
| MFt-2 -0.1910 0.1454 0.2991 -0.4347 -0.0511 -0.0349 0.0002 |
| MFt-3 0.4564 -0.0417 -0.0970 0.5674 0.0391 0.1088 0.1308 |
| MFt-4 0.0068 -0.1623 -0.0728 0.0497 -0.0244 -0.0003 0.0208 |
| MFt-5 -0.0077 0.2254 -0.0341 -0.0158 0.0055 0.0242 -0.1563 |
| DFt-1 0.0870 -0.0451 0.7239 -0.0986 -0.0174 -0.0007 -0.0482 |
| DFt-2 -0.4226 0.0130 0.0865 -0.2994 0.0150 -0.1880 0.0752 |
| DFt-3 0.0963 0.0001 0.0813 0.0306 -0.0218 0.1459 0.0392 |
| DFt-4 0.0087 0.1112 -0.2734 -0.0516 -0.0087 -0.0023 0.0473 |
| DFt-5 -0.1379 -0.0221 0.1598 -0.1471 0.0086 0.0046 -0.01676 |
| SMt-1 0.1635 -0.0254 -0.0984 0.8356 0.0223 0.0426 -0.0182 |
| SMt-2 -0.1562 0.0161 0.0791 -0.0921 0.0037 -0.1078 -0.0343 |
| SMt-3 -0.2445 0.0624 -0.0120 -0.3099 0.0084 0.0491 0.1056 |
| SMt-4 -0.0791 0.0568 0.0237 -0.1140 0.0087 0.0705 -0.0862 |
| SMt-5 -0.2242 0.0386 -0.0746 -0.1522 -0.0374 -0.0300 0.0582 |
| MMt-1 1.3042 -0.0170 -0.0649 1.3697 0.7711 -0.1404 0.1006 |
| MMt-2 -0.3057 -0.1326 0.1101 -0.7056 0.0211 0.2315 -0.1556 |
| MMt-3 0.1637 -0.0462 -0.0440 0.4741 0.0638 -0.1608 0.3504 |
| MMt-4 -0.1136 -0.0761 -0.0892 0.0102 -0.1785 0.3321 -0.2189 |
| MMt-5 -0.5192 -0.0100 0.0658 -0.4927 0.2284 -0.1792 -0.0250 |
| DMt-1 0.4527 -0.1045 0.0013 0.5628 -0.0023 0.8640 -0.0273 |
| DMt-2 -0.0317 0.0873 -0.0148 -0.0612 -0.0094 0.0591 0.0351 |
| DMt-3 -0.0775 -0.0051 0.0223 -0.0458 0.0013 -0.0395 0.0260 |
| DMt-4 0.1081 -0.0179 -0.0145 0.1200 0.0183 -0.1281 0.0064 |
| DMt-5 0.0926 -0.0625 0.0005 0.1648 -0.0030 0.1788 -0.0405 |
| Ut-1 -0.2658 0.1074 0.0408 -0.4060 -0.0090 -0.0744 0.9625 |
| Ut-2 -1.0420 0.1219 0.1581 -1.1468 0.0099 0.1305 -0.0538 |
| Ut-3 -0.3201 0.0272 -0.2216 -0.3859 -0.0213 -0.0034 -0.2023 |
| Ut-4 1.1707 -0.1722 -0.0344 1.5595 0.0439 0.2194 0.2579 |
| Ut-5 0.3503 -0.1167 0.03578 0.2468 -0.0643 -0.2838 0.0431 |
| Intercept -32.6879 25.0163 8.7943 -40.3253 9.8596 -2.3334 -6.8069 |
| R2 0.88 0.99 0.98 0.88 0.99 0.91 0.97 |
| Adjusted R2 0.85 0.99 0.98 0.87 0.99 0.90 0.97 |
| F-statistic 69.38 2810.94 531.72 78.76 1062.95 103.83 368.83 |
Empirical results
The number of unemployment cases in for full time workers have shown a drop in the last month of 2013. An increase in employment indicates a strong work environment (Rifkin 1995). This shows that full time employment has been improved for the last month. However, the part-time unemployment cases have been increasing over the months of 2013. In the last month of 2013, the unemployment stood at 5.6 up from 5.5 of the previous month. This shows that a large number of individuals in the labor force may have opted for full time jobs to the expense of part time ones. That explains the increase in the full time employment cases in 2013.
The data obtained and analyzed gives regression analysis with a specific assumption. The assumption is that the model relies heavily on some past data values. The model gives an analysis on the basis that the variables are related to past variables. From the seven estimated variables, the null hypothesis gives slopes equal to zero, which is simultaneous. The null hypothesis is rejected at 1% level.
From the regression figures, there seems to be causality between the unemployment rate and the labor force participation for divorced females and males which is not directional. The previously obtained values related to unemployment rate showed that they affected the labor participation rate but they did not flow in reverse in terms of causality.
Additionally, carrying out regression in relation to the extend one variable granger causes the other is useful. The Granger cause F tests done on the data above shows that the unemployment rate and labor participation rate of single and married females had a pair wise bi lateral causality.
Conclusion
It is worth noting that unemployment rate plays a big role in an existing labor force participation rate. As found out, the number of female to male workers is almost balancing. This shows a change in attitude regarding gender considerations in the job market. More women are getting into the job market more than before.
According to Romer (2011), discouragement of workers is a very key thing in the determination of the labor force participation rate. Therefore, for governments to ensure that the labor participation rate of a country remains high, it is important to ensure that the job market does not discourage the participants. It is worth noting that having a high labor participation rate is good since it keeps the economy vibrant.
The increase in the number of women taking up jobs has been identified as an important thing in increasing the labor force participation rate in a population. This means that the change in attitude regarding gender roles has made a big impact on the labor participation rate many populations.
The differences in trends across the different countries show a very important thing regarding labor force participation. The culture and attitude of the populations in the various countries explains the differences in the labor force landscape (Mincer 1966).
It is always important to make a wise decision regarding the employees of an organization. The management of companies should ensure that the best steps are taken when deciding on the fate of employees. Only the decisions that will maintain the financial stability and economic protection should be made (Borjas 2008). This will be able to boost an organizations financial welfare while assisting the economy of a country in maintaining stability and growth. It is always important for every player in the economy to ensure that he or she carries out actions which are capable of propelling a countries economy.
References
Borjas, G 2008, labor Economics, Mcgraw-Hill Irwin
Mincer, J 1966, Labor Force Participation and Unemplyment.John Wiley & Sons.
Tachibanaki, T & Sakurai, K 1992, Labor supply and Unemployment in Japan.
Romer, D 2011, “Unemployment”. Advanced Macroeconomics (Fourth ed.). New York: McGraw-Hill
Farmer, RA. 1999, “Unemployment”. Macroeconomics (Second ed.). Cincinnati
Rifkin, J 1995, The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era. Putnam Publishing Group.
Wells, DA. (1891). Recent Economic Changes and Their Effect on Production and Distribution of Wealth and Well-Being of Society. Appleton and Co.
Rothbard, M 1963, America’s Great Depression. Van Nostrand.
Peter, B and Dennis, H 2004 “Taking Apart Taking Part: Local Labor Force Participation Rates” University of Connecticut.
Whaples, R 1991, “The Shortening of the American Work Week: An Economic and Historical Analysis of Its Context, Causes, and Consequences”. Journal of Economic History 51 (2): 454–457.
