Professional Investor Use of Human Capital Management Information

Last registered on April 22, 2024
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Pre-Trial

Trial Information

General Information

Title
Professional Investor Use of Human Capital Management Information
RCT ID
AEARCTR-0011552
Initial registration date
September 07, 2023

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 15, 2023, 8:48 AM EDT

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

Last updated
April 22, 2024, 5:02 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name
Jason Sandvik
Affiliation
University of Arizona
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Other Primary Investigator(s)

PI Name
Lisa LaViers
PI Affiliation
Tulane University
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PI Name
Ethan Rouen
PI Affiliation
Harvard Business School
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PI Name
Rob Jennings
PI Affiliation
University of Arizona
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Additional Trial Information

Status
In development
Start date
2024-05-13
End date
2024-06-14
Keywords
Behavior, Finance & Microfinance, Gender, Labor
Additional Keywords
Disclosure, Diversity
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We examine whether and how professional investors use human capital information in their investment decisions. Human capital has become a vital component of firms’ operations, with annual expenses related to employees as a share of revenue increasing by more than 50% since 1990, compared to no growth for physical capital expenditures. Despite the increasing financial materiality of human capital investments, U.S. firms are required to disclose only two metrics related to non-executive employees, the total number of employees and the median wage. As a result, investors have demanded more information from firms and regulators. We will conduct an experiment among professional investors to determine whether and how details about a firm’s human capital management impact their valuations of the firm.
External Link(s)

Registration Citation

Citation
Jennings, Rob et al. 2024. "Professional Investor Use of Human Capital Management Information." AEA RCT Registry. April 22. https://doi.org/10.1257/rct.11552-1.1
Sponsors & Partners

Partner

Name
Certified Financial Analyst (CFA) Institute
Type
ngo
URL
https://www.cfainstitute.org/
Experimental Details

Interventions

Intervention(s)
See Intervention (Hidden)
Intervention Start Date
2024-05-13
Intervention End Date
2024-06-14

Primary Outcomes

Primary Outcomes (end points)
The answers to Question 2 are our primary outcomes of interest.
Primary Outcomes (explanation)
The answers to Question 2 will be the discount rates estimated by respondents given the required return on equity that they estimate via the CAPM and the additional firm-specific information provided to them. These outcomes will be numbers from 0% to 30%, in intervals of 0.1%.

Secondary Outcomes

Secondary Outcomes (end points)
The answers to Question 1, Question 3, Question 4, and additional survey questions.
Secondary Outcomes (explanation)
Question 1: Answers to this question will provide a data quality check to determine (i) whether respondents are thoughtfully and carefully responding to questions and (ii) whether respondents have the practical knowledge necessary to provide meaningful answers to Question 2 and 3. These outcomes will be numbers from 0% to 30%, in intervals of 0.1%.

Question 3: Answers to this question will provide an alternative means to estimating treatment effects based on respondents’ perceptions of how other CFA members would use the firm-specific information in their valuation decisions. These outcomes will be numbers from 0% to 30%, in intervals of 0.1%.

Question 4: This question will explicitly ask participants how influential each individual piece of firm-specific information was in their estimation of a discount rate in Question 2. They will be asked the following: “When using the Expanded CAPM to determine ABC's required return on equity in Question #2, by incorporating the additional company-specific information, how did each of the following pieces of information influence your estimate of ABC's required return on equity?” They will answer using a five-point Likert scale from “Large Negative Influence” to “Large Positive Influence.” We will also ask participants how they felt each piece of information influenced others’ estimates of ABC’s required return on equity.

We will also ask respondents how certain they are of their answers to Questions 1-3, which will help us gauge the quality of each individual’s response data.

Regarding the questions about the sources of information they use (or would use, hypothetically, if accessible) when they perform financial analysis and make investment decisions, these will be presented as statements to which respondents will indicate their level of agreement/disagreement.

Regarding the types of human capital management information that they would most want regulators to require firms to disclose, we will present them with different types of disclosures that they can vote on (allocating 100 votes however they’d like).

Responses to the remaining questions will be used to estimate treatment effect heterogeneity across particular groups. Specifically, based on respondent age, gender, race/ethnicity, and work experience.

Experimental Design

Experimental Design
See Experimental Design (Hidden)
Experimental Design Details
Not available
Randomization Method
Qualtrics randomization functionality
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,000 CFA Members
Sample size: planned number of observations
2,000 CFA Members
Sample size (or number of clusters) by treatment arms
2,000 CFA Members
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Using Stata command power x, diff(y) sd1(s1) sd2(s2), which computes the total sample size required to detect an experimental-group mean that’s y units different from the control-group mean of x. This test assumes that the standard deviations of the two groups are s2 and s1, respectively, that a two-sided test with a 5% significance level will be used, a power of 80%, and that both groups will have the same number of observations (the defaults). In this case, x would capture the average required return on equity reported in Question 2 by individuals in the control group, and y would capture the difference from this mean among agents in a particular treatment group. power twomeans .09, diff(.03) sd1(.050) sd2(.050): N per group = 45 power twomeans .09, diff(.03) sd1(.045) sd2(.045): N per group = 37 power twomeans .09, diff(.03) sd1(.040) sd2(.040): N per group = 29 power twomeans .09, diff(.03) sd1(.035) sd2(.035): N per group = 23 power twomeans .09, diff(.02) sd1(.050) sd2(.050): N per group = 100 power twomeans .09, diff(.02) sd1(.045) sd2(.045): N per group = 81 power twomeans .09, diff(.02) sd1(.040) sd2(.040): N per group = 64 power twomeans .09, diff(.02) sd1(.035) sd2(.035): N per group = 50 power twomeans .09, diff(.01) sd1(.050) sd2(.050): N per group = 394 power twomeans .09, diff(.01) sd1(.045) sd2(.045): N per group = 319 power twomeans .09, diff(.01) sd1(.040) sd2(.040): N per group = 253 power twomeans .09, diff(.01) sd1(.035) sd2(.035): N per group = 194 Note: these power calculations hold for different values of x, e.g., x = 6, 7, 8, 9, 10, 11, 12, etc.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Harvard University Area Committee on the Use of Human Subjects
IRB Approval Date
2023-07-20
IRB Approval Number
IRB23-0889
Analysis Plan