Worker Absences and Demand for Flexible Contracts

Last registered on September 12, 2024

Pre-Trial

Trial Information

General Information

Title
Worker Absences and Demand for Flexible Contracts
RCT ID
AEARCTR-0014289
Initial registration date
September 02, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 12, 2024, 5:37 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation
Paris School of Economics

Other Primary Investigator(s)

PI Affiliation
National University of Singapore
PI Affiliation
Stockholm School of Economics

Additional Trial Information

Status
On going
Start date
2024-09-02
End date
2025-07-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Worker absenteeism and high turnover remain common problems in developing labor markets, even while the unemployment rate is high (Allen 1981, Leigh 1983, Benavides et al. 2000). In India, the absence rate stands at 8% of worker-days among permanent manufacturing employees, and a majority of unskilled workers continue to be employed in informal casual labor. We hypothesize that worker demand for flexibility affects labor supply decisions, both in terms of absence and selection into informal work arrangements.

We test for the existence of a demand for flexible work among unskilled casual laborers in Odisha, India, and investigate the underlying motivations. We use an incentive-compatible choice experiment, which elicits preferences over pairs of contracts which vary in levels of flexibility, attendance bonus, and distance to local network. This allows us to empirically document workers’ willingness to pay for flexibility in terms of forgone wage earnings, when they are proximate (or not) to the network.

We combine this with attendance data from random implementation of contracts and collect detailed survey data on the causes of absences, social network and practices, as well as risk and time preferences. We plan to: 1) estimate the share of workers who have demand for flexibility that exceeds what is permitted in a typical formal contract; 2) distinguish the main reasons why workers demand flexibility, including the role of social duties; and 3) examine consequences for contract selection and earnings.
External Link(s)

Registration Citation

Citation
Goraya, Sampreet, Suanna Oh and Yogita Shamdasani. 2024. "Worker Absences and Demand for Flexible Contracts." AEA RCT Registry. September 12. https://doi.org/10.1257/rct.14289-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-09-02
Intervention End Date
2025-07-31

Primary Outcomes

Primary Outcomes (end points)
The main outcome variable is willingness to pay for a flexible contract in terms of foregone wage earnings, measured across different pairs of contracts.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We also collect detailed survey data on household characteristics, past work experience and absences in the last 30 days, network size and dependence, social practice and attitudes, risk and time preferences.

We randomize a subset of workers into rigid vs. more flexible contracts to examine the impacts on take-up, absenteeism and productivity.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
** Setting and Recruitment:

We propose to test our hypothesis with low-income workers in rural Odisha, one of India's least developed states. We selected the initial target villages using the following process. We sample participants from different social groups and analyze if the needs for flexibility differ across them. We aim to survey up to 10 participants from each of the two main social categories living in different hamlets in a village. Using the 2011 Census data, we identify villages with at least 40 households across two major social categories and at least 15 households in each of those social categories. In addition, we restrict our sample to those villages that have no more than 250 households, more than 15 km away from urban centers, and have more than 10 households that are engaged in casual labor.

After the initial selection, the recruiting team visits the target villages to verify and update the above information. Provided that the two major social categories are living in separate hamlets, we further restrict to villages that have physical demarcation dividing the two. We identify suitable work site locations that are close to a large cluster of target villages.
We conduct the study in villages that are within 10km of the worksites. In each sample village, local staff members visit every household in the two largest hamlets and explain that there is the opportunity for one male member to participate in a survey. Using a short screening questionnaire, we identify all male household heads who are aged 18-55 and currently residing in the village, who are not in regular employment (e.g. salaried work) , and who are interested in a six-week casual wage job. We randomly select a maximum of 10 people per hamlet (20 per village) to participate in the survey.

** Procedures:

Identifying the Willingness to Pay (WTP) for Flexibility: The choice experiment consists of two parts. The first part begins with survey questions about household characteristics and work experience over the past 30 days, including reasons for work absences. We will document the number of workdays missed by participants and categorize reasons for these absences into the following categories:

- Social duties (e.g., weddings, funerals, festivals, helping neighbors)
- Household duties (e.g., household business, child-rearing, firewood collection)
- Farm work (e.g., on their own or for close relatives)
- Illness

Thereafter, we will conduct a Becker-Degroot-Marschak (BDM) exercise involving a real 6-week employment opportunity. All job offers involve producing a basic household item at a manufacturing worksite, with a prevailing daily wage and a lump-sum attendance bonus at the end of six weeks. The offers vary only in terms of the attendance requirement, bonus amount, and distance to the village, as described in detail below. All participants will be informed that one of their choices will be implemented with a small probability, meaning there are real stakes associated with their decisions.

In the second part, we will conduct a survey module that captures norms around attending social events, such as the size and frequency of events, participation rates, and the participants’ dependence on social networks to further explore the role of social duties. Network dependence may stem from needs such as financial distress insurance or concerns related to reputation or self-image. We will assess the relative importance of these factors, noting the potential differences across agricultural lean vs. peak seasons. In addition, we will conduct various incentivized exercises to measure risk aversion and present bias to understand how behavioral factors unrelated to the four main categories outlined above affect WTP for flexibility.

** Illustration of the BDM Exercise:

* Contract Type 1 - Fixed Contract
This work arrangement requires the worker to show up every day, except for some fixed days. The worker can specify one day per week (e.g., Sunday) to take off without consequence. They can still work on these fixed holidays and earn wages, but if they take off any other day, they will not receive the lump-sum bonus at the end.
An alternative version of the fixed contract allows workers to pre-specify all the days they are willing to take off at the beginning of the work period. These pre-specified holidays do not have to fall on the same day of each week. This version helps us gauge the importance of expected versus unexpected causes of absences.

* Contract Type 2 - Flexible Contract
This work arrangement allows workers to take off days flexibly, up to a certain number, without having to pre-specify which days they want to take off. For example, a flexible contract with 6 days off allows them to take any 6 days off without consequence. If they exceed this limit, they will not receive the lump-sum bonus at the end.

* Worksite Type - Close vs. Distant
The same job and pairs of contracts are offered at two types of worksites. The close worksite is within commuting distance from the participants’ villages, while the distant worksite requires more than 3 hours of travel, preventing daily commuting. For the distant worksite, the employer provides transportation, lodging, and a lump-sum relocation payment. By comparing workers’ contract choices across the two worksites, we can determine whether workers value flexibility more when they are physically closer to their networks.

** Contract Choice
Workers will review multiple pairs of contracts and choose their preferred option. The main comparisons include:

* Close Worksite
- Fixed contract with 6 days off vs. Flexible contract with 6 days off
- Fixed contract with 6 days off vs. Fixed contract with 12 days off
- Fixed contract with 6 days off vs. Flexible contract with 12 days off
- Pre-specified leaves (6 or 12) at the beginning of the contract vs. Flexible contract with (6 or 12) days off)

* Distant Worksite
- Fixed contract with 6 days off vs. Flexible contract with 6 days off
- Fixed contract with 6 days off vs. Flexible contract with 12 days off

The offers are structured such that one contract offers the same fixed bonus amount (e.g., USD 40), while the other contract involves a price list with different bonus levels (ranging from USD 1 to USD 40). The order of contracts and bonus amounts (ascending or descending) will be randomized across participants. After the choices are made, we will determine if a participant receives a job offer through a lottery. If selected, there is a small chance that the offer chosen by the participant during the BDM exercise will be implemented. The choice experiment allows us to address the first two questions by measuring workers’ true WTP for flexibility and investigating factors that determine their decisions.

** Job Implementation
During the job implementation phase, we randomize participants into different types of contracts to understand the impact of work arrangements on workers’ job take-up, attendance, and productivity. For a subset of selected workers, instead of implementing their choices during the BDM exercise, we initially offer them a fixed contract which allows them to take off one fixed day per week (e.g., every Sunday) without losing the bonus, and measure their contract take-up.

Next, for a randomly selected 50% of participants, we upgrade their contract to a flexible one, allowing them to take off any 12 days. For those who refuse the rigid contract in the first place, we still upgrade them to a flexible job and again measure take-up. At the worksite, we measure daily attendance and productivity over six weeks, and administer weekly questionnaires to understand reasons for any absences.
This procedure allows us to (1) estimate the impact of contract type on job take-up in order to understand worker selection into formalized jobs; and (2) estimate the treatment effect of flexibility on productivity and earnings among those who were willing to take up the fixed contract, meaning the unobservable worker type is held constant. The job implementation phase will inform trade-offs firms face when offering different contract types.
Experimental Design Details
Not available
Randomization Method
During the job implementation phase, we assign participants into different types of contracts using computer randomization.
Randomization Unit
Individual randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We aim to collect survey data with at least 600 workers (up to 10 workers per hamlet, 2 hamlets per village, 30-50 villages).
Sample size: planned number of observations
600 workers with WTP for 6 contract types
Sample size (or number of clusters) by treatment arms
For the job implementation phase, we plan to assign at least 54 workers to each of fixed and flexible contract.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
NUS-IRB
IRB Approval Date
2024-08-05
IRB Approval Number
NUS-IRB-2022-381