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Field
Intervention (Public)
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Before
We conduct a field experiment in Addis Ababa, Ethiopia, to study the impact of different aspects of vacancy design on the pool of applicants. For this purpose, we collect real vacancies from firms and exogenously vary the content of these job adverts.
We vary the following information on the job adverts:
1. Whether the advert includes information about the offered monthly salary or wage. When collecting the vacancies from firms, we ask about the monthly wage or salary that they expect to pay for this position. We then randomly vary whether we include this information in the vacancy advert.
2. Whether the advert includes a gender inclusivity statement. When collecting the vacancies from firms, we ask which gender they expect the majority of applicants to be off. Based on this information, we then randomly include a gender-specific inclusiveness statement that reads: "We encourage candidates of all genders to apply for this position, including [GENDER].", where [GENDER] is the expected minority gender. If the respondent does not know, which gender will be prevalent, we instead include the following statement: "We encourage candidates of all genders to apply for this position."
3. Whether the advert includes information about the "general skill" most demanded by this vacancy. Based on this information we randomly include a "Desired skills" category in the job advert that lists the top-ranked skill.
For each vacancy, we will create three different versions of each job advert with each of the above-mentioned components cross-randomized (i.e. independently randomized). We will post each vacancy on three different channels (i) offline job boards across the city, ii) Facebook adverts, and iii) the major online job board (www.ezega.com). We then randomize which version of the vacancy is posted on which channel.
The randomization is thus at the vacancy level and all treatment components are cross-randomized. Assuming a total of 400 different vacancies, we end up with the following treatment and control groups in this experiment:
Wage information treatment:
- 200 treated vacancies with wage information
- 200 control vacancies without wage information
Gender inclusivity information treatment:
- 200 treated vacancies with gender inclusivity information
- 200 control vacancies without gender inclusivity information
Skill requirements information treatment:
- 200 treated vacancies with skill requirement information
- 200 control vacancies without skill requirement information
Since the three different information treatments are independently randomized, we will obtain the following distribution of pieces of information over the 400 vacancies:
- 12.5% of vacancies will contain all three information treatments
- 37.5% of vacancies will contain two information treatments (either wage-gender, gender-skill, or wage-skill)
- 37.5% of vacancies will contain one information treatment (either wage only, gender only, or skill only)
- 12.5% of vacancies will contain no information treatments (pure control)
Our main outcomes of interest are the number and composition of applicants to these differentially treated vacancies.
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After
We conduct a field experiment in Addis Ababa, Ethiopia, to study the impact of different aspects of vacancy design on the pool of applicants. For this purpose, we collect real vacancies from firms and exogenously vary the content of these job adverts.
We vary the following information on the job adverts:
1. Whether the advert includes information about the offered monthly salary or wage. When collecting the vacancies from firms, we ask about the monthly wage or salary that they expect to pay for this position. We then randomly vary whether we include this information in the vacancy advert.
2. Whether the advert includes a gender inclusivity statement. When collecting the vacancies from firms, we ask which gender they expect the majority of applicants to be off. Based on this information, we then randomly include a gender-specific inclusiveness statement that reads: "We encourage candidates of all genders to apply for this position, including [GENDER].", where [GENDER] is the expected minority gender. If the respondent does not know, which gender will be prevalent, we instead include the following statement: "We encourage candidates of all genders to apply for this position."
3. Whether the advert includes information about the "general skill" most demanded by this vacancy. Based on this information we randomly include a "Desired skills" category in the job advert that lists the top-ranked skill.
For each vacancy, we will create three different versions of each job advert with each of the above-mentioned components cross-randomized (i.e. independently randomized). We will post each vacancy on three different channels (i) offline job boards across the city, ii) Facebook adverts, and iii) the major online job board (www.ezega.com). We then randomize which version of the vacancy is posted on which channel.
The randomization is thus at the vacancy level and all treatment components are cross-randomized. Assuming a total of 400 different vacancies, we end up with the following treatment and control groups in this experiment:
Wage information treatment:
- 200 treated vacancies with wage information
- 200 control vacancies without wage information
Gender inclusivity information treatment:
- 200 treated vacancies with gender inclusivity information
- 200 control vacancies without gender inclusivity information
Skill requirements information treatment:
- 200 treated vacancies with skill requirement information
- 200 control vacancies without skill requirement information
Since the three different information treatments are independently randomized, we will obtain the following distribution of pieces of information over the 400 vacancies:
- 12.5% of vacancies will contain all three information treatments
- 37.5% of vacancies will contain two information treatments (either wage-gender, gender-skill, or wage-skill)
- 37.5% of vacancies will contain one information treatment (either wage only, gender only, or skill only)
- 12.5% of vacancies will contain no information treatments (pure control)
Our main outcomes of interest are the number and composition of applicants to these differentially treated vacancies.
We plan to write separate papers for each of the treatments.
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