Unemployment as a Sorting Criterion Essay (Article)

Exclusively available on Available only on IvyPanda® Made by Human No AI

Empirical Work

Eriksson and Rooth developed an empirical study to evaluate the effect of the unemployment period and the level of employment stigma in the labor market. The main focus of the study is to develop a clear understanding of the attitudes associated with employers when contracting employees facing different periods of unemployment. It is apparent that the rate of unemployment in the society has been on a fluctuating trend over the past decades, and there is an indication that there is a rise in the coefficient of long-term unemployment (Erikson and Rooth 1015).

Additionally, the empirical study reveals that the current labor market has demonstrated an increase in stigmatization in employment, especially for individuals with more than nine months of unemployment functions. It is apparent that most employers are keen on analyzing the information about the past employment of job applicants, and this study reveals that there is a high likelihood of stigmatization for applicants with long-term experience with unemployment.

Methodology

The researchers developed a study to evaluate the relationship between the length of unemployment and the stigmatization attitude associated with employers when they handle the affected job applicants. The descriptive study relied on both primary and secondary data. The secondary data was retrieved from various studies from the past through a theoretical analysis process that revealed the findings from other researchers. The primary data was retrieved from an experimental process. The experiment entailed the collection of job applications in the Swedish labor market in selected jobs. The researcher considered 8,466 applications sent out to 3,786 employers (Erikson and Rooth 1019).

The large sample space provided a clear representation of the entire labor market to enhance the validity and reliability of the findings. The applications were designed to possess realistic attributes of job seekers with different levels of experience and unemployment periods. The attribute under consideration was the unemployment history, but it was not highlighted explicitly. The analysis process entailed the evaluation of the likelihood of the applicants being invited for a job interview based on the length and number of unemployment spells.

Identification and Estimation Strategy

The researchers had full control of the attributes of the applicants, and they were assigned randomly. The unemployment history attribute was estimated in a manner that would provide a realistic picture of the virtual applicants. The contemporary unemployment group involved estimation of between 0-9 months of unemployment. The applications also included graduates who had been unemployed for a year, and other applicants with varying numbers of unemployment spells, and different numbers of employees ranging from 1-3 employees. The main reason for having limits in the estimation process was to ensure that the attributes possessed by the respective applicants could be included in the analysis process.

One of the limitations of the identification and estimation strategy is that it did not provide a clear indication that the gaps in the employment experience skills were caused by unemployment; hence, it is possible that the recipients of the CVs would have assumed that the gaps were caused by other reasons. The baseline equation was estimated by determining the invitation of a job interview as a function of the standard deviation of the job advertisement attributes (Erikson and Rooth 1028).

Findings

The researchers found that the callback probability is a function of the unemployment history of the applicants. The higher the coefficient of unemployment spells the lower the probability of callback from the employers. Additionally, the frequency of the unemployment spells is also a major determinant of the callback function. The researchers clearly revealed that unemployment stigmatization exists in the labor market (Eriksson and Rooth 1036).

However, the results also revealed that other factors like skill levels and experience have an effect on the decisions made by employers. The research reveals that people with a long spell of unemployment before applying for a job have a lower probability of being called for an interview, especially if the job opportunity is a high-skill level opportunity. This implies that the employers associate the long unemployment spells with the erosion or lack of skills (Solga 160).

It is also apparent that job applicants with a long list of past employers experience a hard time getting a new job because in callback function is relatively lower, especially if the applicants have longer periods of unemployment between jobs (Karren and Sherman 849). The study validated the fact that employers look beyond the skills and experience possessed by the employees. The unemployment stigmatization is a concept that should be studied further to help in the development of an understanding of the factors that enhance the chances of getting a job for the unemployed members of society.

Works Cited

Carvalho, L., Stephan Meier, and Stephanie W. Wang. “Poverty and Economic Decision-Making: Evidence from Changes In Financial Resources At Payday.” American Economic Review 106.2 (2016): 260-284. Print.

Eriksson, Stefan, and Dan-Olof Rooth. “Do Employers Use Unemployment as a Sorting Criterion When Hiring? Evidence from a Field Experiment.” The American Economic Review 104.3 (2014): 1014-1039. Print.

Howlett, Elizabeth, Jeremy Kees, and Elyria Kemp. “The Role of Self‐Regulation, Future Orientation, and Financial Knowledge in Long‐Term Financial Decisions.” Journal of Consumer Affairs 42.2 (2008): 223-242. Print.

Karren, Ronald, and Kim Sherman. “Layoffs and Unemployment Discrimination: A New Stigma.” Journal of Managerial Psychology 27.8 (2012): 848-863. Print.

Shah, Anuj K., Sendhil Mullainathan, and Eldar Shafir. “Some Consequences of Having Too Little.” Science 338.6107 (2012): 682-685. Print.

Solga, Heike. “‘Stigmatization by Negative Selection’: Explaining Less‐Educated People’s Decreasing Employment Opportunities.” European sociological review 18.2 (2002): 159-178. Print.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2020, August 31). Unemployment as a Sorting Criterion. https://ivypanda.com/essays/unemployment-as-a-sorting-criterion/

Work Cited

"Unemployment as a Sorting Criterion." IvyPanda, 31 Aug. 2020, ivypanda.com/essays/unemployment-as-a-sorting-criterion/.

References

IvyPanda. (2020) 'Unemployment as a Sorting Criterion'. 31 August.

References

IvyPanda. 2020. "Unemployment as a Sorting Criterion." August 31, 2020. https://ivypanda.com/essays/unemployment-as-a-sorting-criterion/.

1. IvyPanda. "Unemployment as a Sorting Criterion." August 31, 2020. https://ivypanda.com/essays/unemployment-as-a-sorting-criterion/.


Bibliography


IvyPanda. "Unemployment as a Sorting Criterion." August 31, 2020. https://ivypanda.com/essays/unemployment-as-a-sorting-criterion/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
Privacy Settings

IvyPanda uses cookies and similar technologies to enhance your experience, enabling functionalities such as:

  • Basic site functions
  • Ensuring secure, safe transactions
  • Secure account login
  • Remembering account, browser, and regional preferences
  • Remembering privacy and security settings
  • Analyzing site traffic and usage
  • Personalized search, content, and recommendations
  • Displaying relevant, targeted ads on and off IvyPanda

Please refer to IvyPanda's Cookies Policy and Privacy Policy for detailed information.

Required Cookies & Technologies
Always active

Certain technologies we use are essential for critical functions such as security and site integrity, account authentication, security and privacy preferences, internal site usage and maintenance data, and ensuring the site operates correctly for browsing and transactions.

Site Customization

Cookies and similar technologies are used to enhance your experience by:

  • Remembering general and regional preferences
  • Personalizing content, search, recommendations, and offers

Some functions, such as personalized recommendations, account preferences, or localization, may not work correctly without these technologies. For more details, please refer to IvyPanda's Cookies Policy.

Personalized Advertising

To enable personalized advertising (such as interest-based ads), we may share your data with our marketing and advertising partners using cookies and other technologies. These partners may have their own information collected about you. Turning off the personalized advertising setting won't stop you from seeing IvyPanda ads, but it may make the ads you see less relevant or more repetitive.

Personalized advertising may be considered a "sale" or "sharing" of the information under California and other state privacy laws, and you may have the right to opt out. Turning off personalized advertising allows you to exercise your right to opt out. Learn more in IvyPanda's Cookies Policy and Privacy Policy.

1 / 1