Volunteering in the banking sector

Last registered on June 30, 2020


Trial Information

General Information

Volunteering in the banking sector
Initial registration date
June 27, 2020
Last updated
June 30, 2020, 12:15 PM EDT


Primary Investigator

Bocconi University

Other Primary Investigator(s)

PI Affiliation
PI Affiliation

Additional Trial Information

On going
Start date
End date
Secondary IDs
Volunteering is a way through which employees can create positive social impact, whilst simultaneously developing professional skills and connecting to the communities they serve. While it is natural to think this should have positive spillovers in the workplace, there is almost no evidence that this is the case. We hypothesize that the take-up of volunteering triggers the individual accumulation of altruism, which in turn affects employees’ willingness to contribute to the common good both inside and outside the workplace. Our collaboration with the Volunteering team of a large bank whilst it launches its new volunteering platform tests this hypothesis. We send an email to a random sample of the bank’s UK-offices, informing employees of a new volunteering platform that the bank is launching. We also randomize the intensity of the treatment – that is, the percent of teams within an office that are treated. The random assignment of the email should create exogenous variation in employees’ participation in volunteering, which allows us to estimate the causal effect of volunteering on a variety of outcomes, including employees capacity to connect to their colleagues, the bank as a company, their customers, and society at large. We decided to also randomize the intensity of treatment across offices in order to measure additional social multiplier effects. If individuals in offices that receive high-intensity treatments see significantly different long-run outcomes than those in receive low-intensity treatment office, this provides evidence that social dynamics are important in the individual propensity of being altruistic.
External Link(s)

Registration Citation

Ashraf, Nava , Oriana Bandiera and Alexia Delfino. 2020. "Volunteering in the banking sector." AEA RCT Registry. June 30. https://doi.org/10.1257/rct.6091-1.0
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Registration on the volunteering platform, Volunteering, Repeated volunteering, Type of volunteering activity (e.g., individual or team-based, personal or through organization, fund-raising or other activity), organising volunteering activities, social spillovers in volunteering, engagement with teams, cooperation within team, alignment in values with other colleagues and managers, performance (measure through HR variables as well as business variables, if available), work satisfaction, well-being, customer service, relationship with clients.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Inclusion of others in self, trust in others, attitudes towards diversity. If possible, we will also collect data on volunteering, fund-raising and altruistic behavior outside of the workplace.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Teams assigned to the treatment group receive an email informing all the employees within the team of the launch of the new volunteering platform and making explicit that the bank allows for paid-leave during one day of volunteering. We also randomize the intensity of the treatment – that is, the percent of teams within an office that are treated.

First, each office is assigned randomly into one of five treatment groups:
group 1 = no departments are treated
group 2 = 25% of departments are treated
group 3 = 50% of departments are treated
group 4 = 75% of departments are treated
group 5 = 100% departments are treated
Departments within an office correspond to teams. All the people within a treated department receive the experimental email.
Then, within offices, each department (=team) is randomly assigned to receiving the email or not, according to the given intensity.

We use 10 strata, which are defined based on the number of departments within an office.
Experimental Design Details
Assignment to groups is weighted as follows:
- for 1 Dept Offices: 1/4 Control, 3/4 100% Treated
- for 2 Dept Offices : 1/4 Control, 3/4 50% Treated
- for 3 Dept Offices: 1/4 Control, 3/8 25% Treated, 3/8 75% Treated
- for 4+ Dept Offices: 1/4 Control, 3/16 each of the Treatment Arms

Strata 1 to 6 are for offices with 1 to 6 departments, respectively. Stratum 7 is for offices with 7 or 8 departments. Stratum 8 for offices with 9 or 10 departments. Stratum 9 for offices with between11 and 18 departments and stratum 10 for offices with more than 18 departments.
Randomization Method
Randomisation done in office using Stata.
Randomization Unit
Office level (identified by a unique postcode)
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
752 offices
Sample size: planned number of observations
36851 employees
Sample size (or number of clusters) by treatment arms
17089 employees received the email, 19762 did not receive the email.
In terms of intensity of treatment, 8966 people are in offices with no treated team, 4362 in offices with 1/4 of teams treated, 13142 are in offices with 1/2 treated teams, 2967 are in offices with 3/4 of teams treated and 7414 people in offices with all people treated.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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Institutional Review Boards (IRBs)

IRB Name
LSE Research Ethics Committee
IRB Approval Date
IRB Approval Number
REC ref. 000727


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials