The Gender Gap in Stock Market Participation:

Evidence from Stock Gifting

Jennifer Itzkowitz, Jesse Itzkowitz, Andrew Schwartz*

March 8, 2024

Abstract

Using recent data from an American app-based consumer stock brokerage, we provide novel evidence about the gender gap in stock market participation. We find that

women receive less encouragement than men to participate in the stock market. However, equal encouragement mitigates the stock market participation gender gap. Stock

gift cards, a quantifiable measure of behavior, serve as our proxy for encouragement

and a nudge to participate in the stock market. We find that even among children

too young to express an interest in finance, boys receive more stock gift cards than

girls. Additionally, the stock gift gender gap is larger in communities with greater

gender inequity. We conclude that women receive less encouragement because of the

perception that women are less interested in finance than men.

Keywords: Gender; App-Based Investing; Stock Market Participation; Investment Decisions; Personal Finance

JEL Codes: J16; G11; G40; G51

*Itzkowitz, Jennifer (Corresponding Author): Seton Hall University, jennifer.itzkowitz@shu.edu;

Itzkowitz, Jesse: Ipsos Behavioral Science Center, jesse.itzkowitz@ipsos.com; Schwartz, Andrew: Seton

Hall University, andrew.schwartz@shu.edu. We thank Anca Cotet-Grecu, Clifton Green, Joel Houston, Dan

Ladik, Chi Liao, Brandon Lockhardt, Steven Malliaris, Kurt Rothoff, Wendy K. Smith, Hongfei Tang,

Eleanor Xu, Danielle Zanzalari, participants at the 2022 Research in Behavioral Finance Conference, and

participants at the 2023 Financial Managment Association Annual Conference for their insightful feedback

on this paper.

1
1 Introduction

Women are less likely to participate in the stock market than men (Agnew et al., 2003;

Almenberg and Dreber, 2015; Ke, 2021; Kaustia et al., 2023). When women do participate

in the stock market, they invest less money than their male counterparts (Neelakantan and

Chang, 2010). The price of non-participation (and under-participation) in the stock market

over long periods of time is staggering, placing women at significant financial disadvantage

compared to men.1

Why are women less likely to participate in the stock market than men? The reasons are

complex, multifaceted, and not entirely understood.2 In addition to known factors, it is

possible that there is a gender gap in stock market participation because women receive less

encouragement than men to participate. This may occur for two possible reasons, either

because we perceive that women are less interested in finance (Driva et al., 2016; Halko et

al., 2012; Ke, 2021), or because women are actually less interested. These possibilities are

not mutually exclusive. They, however, are not the same.

How can we foster gender-based equality in stock market participation? If women are as

interested as men in participating in the stock market, then a simple nudge to encourage

women to participate may be enough to help close the gender gap. However, if women

1For example, (Bovenberg et al., 2007) show that, compared to an optimal strategy, not participating in

the stock market for retirement and other savings yields a welfare loss of 12 percent.

2Some factors which are known to contribute to disparities in stock market participation include gender

gaps in wealth, income, time in the labor force (Blau and Kahn, 2017), financial literacy (Lusardi and

Mitchell, 2008; van Rooij et al., 2011), financial confidence (Bucher-Koenen et al., 2021; Jha and Shayo,

2024), and attitudes towards risk (Barber and Odean, 2001). Even after individual characteristics such as

age, education, income, net worth, risk aversion and even BMI have been considered, Kaustia et al. (2023)

finds that gender remains an important determinant of stock market participation.

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are not participating in the stock market because they are less interested than men, then

encouragement will not be enough to result in sustained stock market participation.

Jha and Shayo (2024) demonstrate in an experimental setting that a small nudge to begin

stock trading results in future stock market participation. We extend the study of the effect

of a small nudge to enter the stock market on future stock market participation beyond a

highly controlled experimental setting using a novel data set from a American app-based

discount stock brokerage firm. Our data set includes detailed stock trade and app log-in

data with the unique feature that people can give gift cards which are redeemable for stock

through the app. We observe people’s behavior after receiving a stock gift card, which serves

as a quantifiable, low-cost, naturally occurring, nudge to enter the stock market.

We find a significant gender gap in the likelihood of being encouraged to enter the stock

market. Women receive just 38.8% of all of stock gift cards. The average stock gift card

purchased for a female is for 21.9% less value than a gift card purchased for a male. The

gender gap also exists among minors. Among children under age 18, girls receive just 38.4%

of the stock gift cards.

These initial descriptive results support both the interest and perception hypotheses. Gift

givers usually tailor gifts to the recipient’s interests or at least their perceptions of the

recipient’s interests.3 If women are, on average, less interested in finance, then it rationally

follows that they will receive fewer stock gift cards. Additionally, if women are perceived to

3Research has demonstrated that “implicit biases,” such as the belief that women are less interested

in finance likely exist outside of conscious awareness and can persist even as our explicit attitudes evolve

(Greenwald and Banaji, 1995).

3
be less interested in finance, then it also follows that women will receiver fewer stock gift

cards.

To distinguish between the hypotheses, we observe gift giving to children under 8 years old

which is before an average child has the cognitive ability to understand investing and stock

trading (Friedline, 2015). In other words, all boys and girls under 8 are equally (un)interested

in purchasing stocks. Among the subsample of children who are under 8 years old, the pattern

remains consistent. Girls receive fewer stock gift cards than boys. To further distinguish

between the hypotheses, we observe differences in people’s expectations of gender norms.4

Not surprisingly, we find a correlation between a community’s gender role expectations and

the gift card gender gap. As the gender imbalance in a community grows, so does the gender

gift card gap.

Next, we turn to gift card value. We find that having received a gift card, on average, women

receive lower valued gift cards than men. To confirm that observed differences are not due

to confounding variables, we control for income, wealth, and age in several ways. First, we

include control variables in a multivariate setting. Next, we compare siblings who are both

under 18 years old and live in the same household. Even using paired tests among mixed

gendered siblings, we find the gender gift card value gap persists. Sisters receive smaller gifts

than their brothers.

4People’s beliefs about gender roles shape their perceptions of who is interested in finance. While every

community has gender role expectations, they differ from group to group. Following Duchin et al. (2020),

we create proxies for a community’s gender norms using gender imbalances in income, education, and labor

market participation.

4
Finally, we examine whether gift card redemption is an effective nudge to spur stock market

participation. We confirm that 90% of the people who open an account with a gift card

remain invested in the stock market after 1 year. Interestingly, although by a small margin,

a greater proportion of women (91%) than men (89%) remain invested in the stock market.

Next, using both subsequent stock purchases and app login behavior, we find that gift cards

do promote sustained stock market interest among both men and women.

Taken together the evidence provides strong support for the hypothesis that we act based

on our perception that men are more interested in finance than women. The results likely

generalize to other less easily quantifiable behaviors such as how parents speak to their

children about finance, and how teachers educate their students, and how financial advisors

plan for their clients. The results highlight the differences in how we interact with others

around financial inclusion in the informal “pathway” to stock market participation (Milkman

et al., 2015). Additionally, the evidence fits within the theory of cumulative disadvantage,

which describes how larger gender and racial gaps later in life are the result of many small

differences that occur at earlier stages (DiPrete and Eirich, 2006).

By introducing an antecedant, our work makes an important contribution to the literature

examining the gender gap in wealth accumulation (Ruel and Hauser, 2013). A gender gap

in encouragement to participate in the stock market may perpetuate long-run inequities in

stock market participation and wealth accumulation. Unlike prior work that explored innate

or learned characteristics like financial literacy, financial confidence, and risk tolerance, we

show that other people’s perceptions, a factor outside of one’s direct control, influence stock

5
market participation. In this way, our paper is more similar to Goldsmith-Pinkham and

Shue (2023) who show that women have a different investment experience than men.

2 Data

The primary data comes from an American app-based brokerage firm from January 2015

through September 2020.5 The brokerage data includes the complete records of every trade,

dividend payment, deposit, and withdrawal made with the broker. Additionally, we observe

how each trade was funded such as cash transfer, debit/credit, cash from the account, and

gift card. The data also includes the time and date for every time a user logs into the app,

regardless of whether they make a trade. We use this data to observe investor behavior.

The brokerage records include data for 697,465 accounts which represent a broad crosssection of the U.S. population. Account data includes investor-reported birth-year, zip code,

employment status, and gender, which must be reported in a binary formal as either male or

female. 59.0% of the users are male. As the brokerage operates via a new, app-based platform

with several features that encourage novices, investors skew younger than the population as

a whole. The average age of an investor is 32 years old. Investors of all ages, however,

are represented. 14.3% of accounts are custodial accounts for minors. 45.7% of users are

between 18-34, 32.1% are between 35-54, and 7.9% are 55 or older. Table 1 reports the full

breakdown of investors by age and gender.6 Our data is similar to other data sets which

5We use the same primary dataset as the one described by Itzkowitz et al. (2023).

6Between April, 2017 and March, 2018 the broker initiated a promotion whereby new users received a

bonus $5 gift card for joining the brokerage platform. We exclude users who opened their account using this

promotional giveaway since these investors may have different behaviors and characteristics than the overall

6
report individual investor behavior. An advantage of our data is that it includes a broader

range of investors. For example, in the original dataset used by Barber and Odean (2001)

the average age of an investor is 50 and approximately 20% of the accounts were opened by

women compared to an average age of 32 with women accounting for 41.0% of the accounts

in our dataset.

[Insert Table 1 Here]

The app-based trading platform has several advantages and unique features which we exploit

in our analysis. First, the app-based brokerage encourages novice investors by reducing the

barriers to trading. The app-based brokerage has no minimum account size, allows fractional

shares, and has a negligible $0.99 trade fee which encourages participation by minimizing

the fixed costs of stock market entry (Vissing-Jørgensen, 2002).

Another unique feature of the app is the ability to purchase and redeem stock gift cards.7

Gift cards are given for a specific dollar amount and must be used to purchase stock in one

company. Fractional share trading allows gift cards of any value to be purchased and fully

redeemed for a single stock regardless of how much the stock is trading for.8 Redeeming

a stock gift card is a common method of opening an account. 36.8% of users opened their

account through gift card redemption. Gift cards are also much more likely to be used to

customer base. We also exclude accounts transferred from another broker because we cannot observe market

entry.

7We use gift cards redeemed as a proxy for gift cards received. In informal conversations with appbased stock brokerage that provided us with this data, we learned that approximately 85% of all gift cards

purchased are eventually redeemed.

8Most of the stock gift cards are for the stock of a particular company. The user, however, has the option

of using the dollar amount to purchase stock in a different company. The amount, however, cannot be split

between multiple companies.

7
open an account as opposed to funding a subsequent stock purchase. Only 10.8% of second

purchases are funded via a gift card.

In addition to standard accounts, we also observe custodial accounts, which are accounts

created for minors. The user data includes an identifier which links each custodial account

to its parent (standard adult) account. By identifying multiple custodial accounts linked to

the same parent account, we construct a sample of siblings.

We supplement the primary data with data from the 2016 American Community Survey

(ACS) created by the U.S. Census Bureau. From the ACS, we add median income data and

the percent of residents who earn at least a college reported by zip code. Median income by

zip code is used as a proxy for user income (Bhattacharya and Lakdawalla, 2006; Morris et

al., 2017). The percentage of residents who earn at least a college degree is used a proxy for

whether the user is college educated. We include the population distribution of boys and

girls within a family as a basis for comparison. We also include median income by gender,

percentage of people employed by gender, and the percent of residents who earn at least a

college degree by gender in each zip code as a proxies for gender role expectations in each

community (Duchin et al., 2020).

We divide the sample the sample according to the U.S. Census Bureau’s geographic regions

and income measures based on user zip codes. We find that each of the four geographic

regions in the U.S. are well-represented in the sample. In addition, we divide the sample

according to the median zip code income quartile breakpoints from the 2016 American

Community Survey. Not surprisingly, the lowest income level is underrepresented in the

8
sample. However, all income levels are represented. Taken together, the evidence indicates

that the sample is well-diversified.

3 Empirical Results

We begin by showing two main results. We first establish that women receive fewer gift cards

than men. We then show that on average the value of the gift cards redeemed by women is

lower than those redeemed by men. Next, we turn to cross-sectional differences in cultural

attitudes towards gender roles. Here we show that there is a correlation between cultural

factors and the gender gap in stock gift card giving. Finally, we show that conditional on

receiving a gift card, women and men remain active investors in roughly equal proportions.

3.1 Number of Stock Gifts

According to the U.S. Census Bureau, 50.8% of the United States population is female.

If men and women are equally likely to receive stock gifts, then the proportion of females

redeeming stock gift cards should match the proportion in the overall U.S. population. Table

2 reports the number of redeemed gift cards by gender. Panel A reports the number of all gift

cards redeemed and Panel B reports the number of gift cards redeemed to open an account

(initial gift cards).

[Insert Table 2 Here]

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In the Percent Female column, we compare the percent of gift cards received by women

to the null hypothesis that women receive gift cards in proportion to their share of the

U.S. population (for the full sample). The results in Panel A indicate that women are

considerably less likely to receive gift cards than men. In our sample, only 38.8% of all gift

cards are redeemed by women. Thus, women are 12 points under-represented among those

gifted stocks as compared to the general U.S. population.

The initial data show that men receive more stock gift cards than women. It is possible

that the difference reflects expressed personal preferences. If men exhibit a greater interest

in investing in the stock market, then they should be more likely to receive stock gift cards.

It is also possible that the difference reflects our perception of people’s interest in investing.

A challenge in a study like this is that people’s preferences cannot be directly observed.

Instead, we identify two other ways distinguish between expressed and perceived personal

preference, gift receivers age and initial purchases.

Camerer (1988) notes that gifts are often given to children with the intent of educating or

shaping their tastes, rather than as the result of their expressed preferences. Table 2 reports

the number of gift cards given by gender to children under the age of 18. Here, we see that

only 38.0% of all gift cards to children under the age of 18 are to females. The results for

children under 18 are even stronger than the full sample. Girls receive fewer gift cards than

boys.

It is possible that this gender gap may arise because we only observe gift cards that have

been redeemed, rather than all of the cards that have been gifted. If this is the case, then

10
this provides support for the theory that the gift card gender gap measures a gender gap in

stock market interest. Looking at gifts to minors under 18 years old helps us to rule this

out as a possibility. First, the approximately 15% of gift cards which are not redeemed are

not enough to close the gender gap among minors under 18 years old.9 Additionally, minors

under 18 are not capable of redeeming a gift cards themselves. That parents may be more

likely to redeem a stock gift card for their son than their daughter contributes to the evidence

that the gender gap is the result perception of interest rather than actual stock interest.

To further control for gender differences in stock market interest, we look at gifts to children

under 8. Friedline (2015) shows that almost no children under 8 have any interest in or even

the cognitive ability to understand the stock market. Observing gift card giving behavior to

young children therefore reflects only perceived preferences rather than the stated preferences

of the receiver. Even among very young children, girls receive only 46.2% of all gift cards.

To help us further distinguish, we identify whether gift cards are used to open an account

(i.e. an initial gift card). While later gift cards may be the result of feedback from the gift

receiver, gift cards given to people who are not yet participants are more likely to reveal the

thoughts of the gift giver. As shown in Table 2 Panel B, when we consider only gifts used

for account initiation, women remain under-represented by 5.1 points.

9Assume that the 15% of cards gifted to minors but unredeemed were all given to girls. Then, if we

assign all of these cards to girls, while the gender gap would shrink it would still remain that 47% of gift

cards given to girls with the remaining 53% given to boys (where 47% = 38% of the 85% of cards redeemed

+ all 15% of unredeemed cards).

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3.1.1 The Gender Composition of Siblings in a Family

To further confirm that stock market interest is not the sole reason for the gender gap in gift

card giving we exploit a unique sub-sample in our data, siblings. It is unlikely that there are

gender gaps in awareness, knowledge, or interest of two young children raised in the same

home at the same time. Additionally, siblings share the same income, wealth, and living

conditions. Thus, gender differences in wages and wealth do not explain differences in stock

gift giving to siblings.

Table 3 shows the gender composition of families in our sample compared to the actual family

composition (shown in parentheses) in the United States where the population distribution

of boys and girls within a family is derived from the 2016 ACS.10 We can not observe actual

family make-up. Instead, we observe the distribution of initial gift cards within a family.

[Insert Table 3 Here]

If boys and girls are equally likely to be given a gift card, then the distribution of gift cards

should mirror the distribution of boys and girls for given family sizes in the overall population.

We find that families with more sons than daughters are significantly over-represented in our

brokerage data. For example, among single child families, only 51.4% should have a boy.

In the sample, however, among single child families, 64.5% have a boy. Similarly, among 2

child families, 23.4% of families in the U.S. are composed of two girls, however only 17.9% of

the two-child families in our sample are two-girl families. A χ2 goodness-of-fit test confirms

10We restrict our analysis to families with 4 or fewer children. Only 0.5% of families in the sample report

5 or more children.

12
that there is a statistically significant difference in observed family composition relative to

expected family composition in every family size. This result is consistent with Duchin et

al. (2020) who finds that family composition influences financial gender gaps.

There are two possible explanations for these results. Either families with boys are more

likely to receive stock gift cards, or only the male children in families are given stock gift

cards. Both of these explanations are consistent with the perception theory.

Observing the pattern of sibling giving allows us to reject another alternative hypothesis.

It is possible that some gift cards may be gifts given to married couples. If the husband is

more likely than the wife to redeem the gift card, it will appear that men receive more stock

gifts. By observing only siblings who are under age 18, we reject the hypothesis that gender

roles in a relationship merely give the appearance of a male dominated sample.

Additionally, observing siblings allows us to reject sample selection concerns as well. As we

are only able to observe the gift cards that are redeemed, it is possible that the gender gap

is the result of a gap in gift card redemption rather than a gender gap in gift cards received.

However, it is highly unlikely that once a parent has downloaded the app and created a

custodial account for one of their children, the same parent would redeem only a gift card

for their son but not their daughter. And, if a parent does only redeem their son’s gift card,

this provides support rather than refutes the theory that perceptions of stock market interest

influence who is encouraged to participate in the stock market.

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3.1.2 Cultural Differences

To further distinguish between hypotheses, we consider differences in community gender

norms. While every society, ethnic group, and culture has gender role expectations, they

differ from group to group. So far, we have operated under the broad assumption that gender

norms are consistent across the United States. Given the size and diversity of the United

States, this is not necessarily the case. Gender norms differ across communities.

People develop gender norms by inferring the relative social status of men and women in

their community, extrapolating from such cues as labor force participation, traditional occupations, and representation in positions of authority. For example, individuals brought up

by mothers who do not work outside the home are more likely to develop stereotyped gender

attitudes (Gold and Andres, 1978; Weinraub et al., 1984; Farr ́e and Vella, 2013). Similarly,

an individuals brought up by a mother with less formal education than their father develop

a less egalitarian gender attitude (Martin et al., 1980). Using empirical data, (Alesina et al.,

2013) confirm the causal effect of community norms on residents’ gender attitudes.

Following, Duchin et al. (2020) we introduce three proxies for the relative economic status of

men and women to measure the relative strength of community gender norms. First, Income

Imbalance is the difference between the average annual income of employed men and women,

scaled by the average income. Second, Education Imbalance is the difference between the

years of education for men and women, scaled by average education. Third, Labor Force

Participation Imbalance is the difference in the labor force participation rate between men

14
and women. Each proxy is from the 2016 ACS and measure the results in the zip code in

which the gift receiver lives.

If stock gifts are given based on the gift giver’s beliefs about gender roles around finance,

then we would expect to see a larger gender gap in stock gift cards in communities with

larger differences in gender role expectations. To understand the influence of gender norms

in the gift givers’ communities, we divide the sample into quartiles based on the with-in

sample percentile rank of each attribute.

Ideally, we would be able to distinguish between the community of the gift giver and receiver.

However, we only have information about the gift receiver. Given that our perceptions of

gender roles are shaped by our community, it is likely that the gift giver and receiver share

similar beliefs about gender norms. More specifically, anecdotal evidence from conversations

with the app-based brokerage’s CEO suggests that many of the gift cards given to children

are from immediate relatives such as grandparents, aunts, and uncles. As parents’ implicit

gender-role associations and observable behaviors are strong indicators of children’s attitudes

towards gender roles (Croft et al., 2014), it is likely that the gift givers and receivers have

similar beliefs about gender norms. We, therefore, use the community of the gift receiver as

a proxy for the community of the gift giver.

Table 4 presents statistics about various groups of gift card recipients. The sample is limited

to only investors who opened an account and made their first stock purchase by redeeming

a stock gift card. The statistics are based only on the first gift card redeemed.

[Insert Table 4 Here]

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Panel A of Table 4 includes all gift card recipients. In each quartile, if males and females

are equally likely to receive stock gifts, then the proportion of females redeeming stock

gift cards should match the proportion in the overall U.S. population which is 50.8%. The

first set of columns breaks up the sample according to Income Imbalance quartiles. In the

first quartile in which Income Imbalance is the smallest, women receive 49.2% of the gift

cards. The resulting gender gift card gap is just 1.6%. As the gender imbalance in income

grows, so does the proportion of gift cards which are given to men. In the quartile with the

largest gender income imbalance, the gift card gender gap grows to 15.0%. A two sample

test of proportions confirms that the difference in differences (15.0% - 1.6%) is statistically

significant.

In the following columns of Panel A, we use the Education Imbalance as a proxy for community norms of gender roles. In the last three columns, we use the Labor Force Participation

Imbalance as a proxy for community norms. Across all three measures, regardless of the

community proxy that we use, we observe similar patterns. In communities where there is a

larger gender role imbalance, there is a larger gift card gender gap.

In Panel B, we restrict the sample to only children who are younger than 8 years. In the

lowest Income Imbalance quartile, the gift card gender gap is 5.4%. As the gender imbalance

in income grows, so does the proportion of gift cards which are given to boys. In the quartile

with the largest Income Imbalance, the gift card gap nearly doubles to 10.7%. A two sample

test of proportions confirms that the difference in differences (10.7% - 5.4%)is statistically

significant. The results are consistent across the other measures of community attitudes

towards gender. As children under 8 years old are all uninterested in the stock market, the

16
results are consistent with the theory that a gift giver’s belief about a someone’s interest in

stock market investing is shaped by gender norms in their community.

In Panel D, we restrict the sample to only adults who are older than 18 years old. Here

the gift card gender gap in the lowest Income Imbalance quartile favors women at roughly

the same proportion as the number of women in the population. However, by the highest

income imbalance quartile the gender gift card gap has grows to 11.57%. The same is true

across other measures of gender role imbalances. This is consistent with the theory that a

gift giver’s belief about a woman’s interest in stock market investing is shaped by the gender

norms in their community. Among adults, it is also possible that interest in stock market

investing has been shaped by the community. In other words, women in communities with

a large differences in gender role expectations may also be less interested in stock market

investing. We investigate this further later.

3.2 Value of Stock Gifts

We have shown that women are given fewer stock gift cards than men. We next consider the

differences in the value of stock gifted to men and women. Table 5 reports the average value

of gift cards by gender. Panel A includes all gift cards while Panel B restricts the sample to

only gift cards used to open an account (initial gift cards).11

[Insert Table 5 Here]

11Both this study and Jha and Shayo (2024) endow participants with money to study the effect of a low

cost nudge on future stock market participation. In Jha and Shayo (2024) participants are endowed with

either $50 or $100 which is surprisingly similar to the average value of an initial gift card in our data set at

$42.67.

17
We find that, conditional on receiving a gift card, men receive larger gift cards than women.

On average, men receive gift cards that are $10.81 larger than women. Considering that the

average gift card is only $50.53 (with a median of $25) this difference is striking both economically and statistically. It represents a 21.4% difference in the average stock gift between

men and women. This result is consistent with prior work finds that female entrepreneurs

obtain less funding than their male peers (Brooks et al., 2014; Hebert, 2020). Female fund

managers have lower fund flows (Niessen-Ruenzi and Ruenzi, 2019), and there is a gender

gap in capital allocation to CEOs (Duchin et al., 2020). Consistent with this research we

show that the funding gap exists at a personal level too.

3.2.1 Controlling for Other Factors

Differences in gift card value may be the result of other factors unrelated to either perception

or interest in investing. The gender wage gap may contribute to men receiving larger stock

gifts. For example, the size of a gift may partially reflect the giver’s perception of what the

receiver would find a valuable gift. This perception is likely to be influenced by the receiver’s

financial standing. It is also possible that a user’s age or level of education influence the

value of a stock gift.

[Insert Table 6 Here]

Table 6 presents the results of the OLS regressions in which the dependent variable is the

value of a gift card. The primary independent variable of interest is Female, an indicator

variable for the user’s gender. Even after controlling for age, income, and education the

18
coefficient of the Female indicator variable, the primary variable of interest is both economically and statistically significant. Adding additional control variables lowers the coefficient

on the Female indicator variable suggesting that the age, income, and education do partially

explain our results. However, the gap in gift card amounts is not driven solely by these other

factors.

3.2.2 Differences in Sibling Pairs

The results in Table 5 indicate that among minors, there is only a small difference in the

value of gift cards given to boys compared to girls. To further investigate this, we look at

a subsample of sibling pairs. When gift cards are given to siblings on the same days, we

expect them to be for the same amount. For example, when an aunt buys holiday gifts for

a niece and nephew at the same time, they will likely be for the same amount. It is unlikely

that people are overtly choosing to gift less to girls, instead it is likely to be a non-conscious

action. Only when gift cards are given to siblings on different days do we expect that they

will be for different amounts since the amount of the first gift is not as immediately accessible

in the gift givers memory.12

Table 7 compares the values of gift cards given to pairs of brothers and sisters in the same

family. This subsample allows us to cleanly and clearly evaluate one sibling pair per family.

If a family has more than 2 children, we only consider the oldest child of each gender.

12For example, the gift card might be given on each child’s birthday. Thus, the gift giver might not

remember the exact amount given to the first child and will let unconscious bias impact the value of the gift

card given to the second child.

19
[Insert Table 7 Here]

The results in 7 provide evidence that there is a gender gap in capital allocation to boys and

girls. Paired t-tests indicate that when gift cards are given to pairs of mixed gender siblings

on the same day the amounts are indistinguishable. However, we find that even when siblings

within the same family are compared, brothers receive more money in the form of stock gift

cards than their own sisters provided they are gifted on different days. This supports the

theory that the gender differences in gift card giving is non-conscious, rather than explicit.

3.2.3 The Influence of Sibling Age

Even after controlling for many factors, it is still possible that older children receive larger

gift cards. In untabulated results, we compare the ages of the siblings in the matched sample

and confirm that the average difference in age among mixed sibling pairs is not statistically

different from 0. To further confirm the influence of age on the results, we subset the sample

of all siblings according to birth order. In Table 8, we report the mean initial gift card given

to the oldest child and the second oldest child. We then break down the results by the gender

of both the oldest and second oldest child.

[Insert Table 8 Here]

The results presented in Table 8 confirm that older siblings receive gift cards which are worth

more than younger siblings, on average. The difference between the amount given to the

oldest and second oldest child is always positive and statistically significant regardless of the

20
gender of the oldest and second oldest child. The difference is largest when the oldest child

is a boy and the second oldest child is a girl, whereas the difference is smallest when the

oldest child is a girl and the second oldest child is a boy.

We further investigate the interrelationships between sibling birth order, gender, and stock

gift value. Table 9 presents the results of regressions in which the dependent variable is

the value of a gift card and the independent variables are indicator variables for whether

the sibling is female and the first-born. The omitted category is first born, male siblings.

Coefficients can be interpreted as the difference between the average value of a gift card

received by a first born, male and their sibling in the given category.

[Insert Table 9 Here]

Similar to Table 8, Table 9 compares the results of gift cards given to siblings. Table 8

includes only the oldest sibling of each gender and can only compare one group of siblings

at a time. By contrast 9 provides more holistic results, including all siblings.

The results indicate that only when a younger sister receives a gift card on the same day as

her older brother is it likely to be for the same amount of money. Otherwise, younger sisters,

are given significantly smaller gift cards than their older brothers. Surprisingly, the results

in column (6) indicate that when a first-born sister receives a stock gift card on a different

day than her younger brother, she is still given $3.60 less, on average.

Overall, we find large and persistent gender differences in stock gift giving. When a woman

does receive a stock gift card, it is for less money. Comparing siblings allows us to rule

21
out alternative theories such as the influence of income or wealth on gift size. In addition,

comparing gift cards given to siblings on the same and different days confirms that the

difference is non-conscious rather than intentional.

3.3 Stock Market Participation

We now turn our attention to stock market participation. We observe patterns of behavior

after gift card redemption. We find support for the idea that gift cards serve as a nudge to

not only promote stock market entry, but also stock market participation. Next, we compare

the sustained participation rates of men versus women.

Redeeming a stock gift card is an effective way to encourage someone to enter the stock

market as gift cards help overcome inertial behavior (Bertaut and Haliassos, 1995). However,

a stock gift card does not necessarily result in future stock market participation beyond entry.

There is nothing stopping a gift card redeemer from cashing out their account. Additionally,

there is no guarantee that the recipient takes any further action.

If men are more interested in the stock market, then we expect men to continue participating

in the stock market after gift card redemption at a higher rate than women. However, if

men are given gift cards because of the perception that they are more interested, then we

do not expect to observe a gender participation gap following market entry.

We first measure stock market participation by using a simple indicator equal to 1 if someone

is still invested in stocks one year after their first stock purchase. This is the most common

22
measure of stock market participation and is similar to Almenberg and Dreber (2015), van

Rooij et al. (2011), and Ke (2021), among others. Additionally, we create two more measures

of sustained stock market participation. First, we observe whether investors make additional

stock purchases after their initial stock purchase. This measure of continued participation

is in the spirit of Jha and Shayo (2024) who measure market participation as an additional

stock trade following their initial intervention. Next, we observe whether investors continue

to login to the brokerage app to monitor their investments.

For all of the tests in this section, the data is restricted to samples of males and females over

18 years old who initiated their accounts by redeeming gift cards. There are several reasons

for using this subsample. Investors under 18 years old may not have discretionary income

to invest. Additionally, for investors who are under 18 years old, the data does not allow us

to distinguish whether subsequent purchases and logins are being made by the minor or the

parent.

We observe three patterns of behavior about stock market participation. First, following a

stock gift card redemption, account holders continue to participate in the stock market indicating that the nudge is successful. Second, the gender gap (or lack thereof) in participation

is consistent across varying community attitudes towards gender roles which suggests that

gender norms in a community influence our perception of who is interested in participating

in the stock market. Third, men and women continue to participate in the stock market

in relatively equal proportions. This is consistent with the idea that if we offer men and

women equal encouragement to enter the stock market then we can minimize the gender gap

in stock market participation.

23
3.3.1 Univariate Results

Table 10 reports the percentage of accounts that remain 1 year after account initiation.

Table 11 reports univariate statistics for subsequent stock trades and app logins as measures

of sustained stock market participation. As in Table 4, we present the results for the sample

broken up by quartiles based on Income Imbalance to determine if the prevailing culture

influences stock market participation. We repeat all of the tests in Table 10 and Table 11 for

the other cultural measures used in Table 4. For brevity, the results which are qualitatively

the same are not reported.

[Insert Table 10 Here]

The statistics presented in Table 10 indicate that on average 90% of accounts opened following the redemption of a gift card remain open after 1 year. This indicates that the small

nudge provided by receiving a gift card leads to sustained stock market participation. Interestingly, although by a small margin, a greater percentage of women’s accounts (91.1%)

remain open after 1 year compared to men’s accounts (89.1%).

Panel A of Table 11 reports subsequent stock purchases. In the first columns, we report the

average of the number of subsequent stock purchases made at any time after the initial stock

purchase. Men make an average of just over 3 more stock purchases than women. This is

consistent with the results of Barber and Odean (2001) that, on average, men trade more

frequently than women.

[Insert Table 11 Here]

24
However, many trades are not required to be an active stock market participant. In the

remainder of the columns in Panel A, we instead measure the percentage of women and the

percentage of men who continue to invest after their initial purchase made with a gift card.

First, participation is measured as making at least one additional stock purchase following

the initial purchase. In the last two columns, we measure the percentage of men and women

who make a subsequent stock purchase more than one year after their first stock purchase

to determine if gift card recipients remain active investors. Here, we restrict the subsample

to accounts initiated on or before September 30, 2019 to ensure enough time in the sample

period for investors to make a subsequent purchase.

Our first observation is that more than half of all gift card recipients continue investing after

redeeming their first gift card. The conclusion that we draw from these results is that stock

gift cards are an effective way to encourage stock market participation, which is consistent

with the results of Jha and Shayo (2024).

Second, the gender gap in continued investment at any time following the initial gift card

redemption is relatively small at just under 5%. This indicates that men and women continue

to participate in the stock market in relatively equal proportions.

Third, and perhaps most interestingly, the gender gap in participation remains both relatively small and consistent across changes in a community’s attitude about gender roles.

Specifically, 56.7% of females and 59.1% of males in the lowest Income Gender Inequity

quartile continue to participate in the stock market after gift card redemption. There is only

a 2.5% difference in stock market participation. Among the largest Income Imbalance quar25
tile, the gap in continued stock market participation increases to only 4.0%. By comparison,

for the same groups of people, the gap in the percentage of gift cards received increases to

11.6% from -1.8%. This is consistent with the theory that gift cards are given because of

perception of rather than actual stock market interest.

Panel B of Table 11 reports investor app logins as an additional proxy for stock market

interest. In the first columns, we report the average of the total number of all logins for

females and males. Consistent with our earlier results, males are more active users of the

app, logging in to the app more frequently than females.

In the remainder of columns of Panel B, rather than report the number of logins, we report

the percentage of females and the percentage of males who login more than 4 times after

their initial purchase. And, we report the percentage of females and males that login more

than 4 times after more than 1 year since their initial purchase for accounts.13 Here, we

again restrict the subsample to accounts initiated on or before September 30, 2019.

The results are consistent with those in Panel A. Regardless of gender, once people have

a stock account, they continue to remain engaged. Even after one year from market entry,

more than half of investors over 18 years old continue to login to their account. Additionally,

there is no discernible trend across Income Imbalance quartiles.

13In untabulated tests, we test for more than 1 subsequent login as opposed to 4 and the results remain

qualitatively unchanged.

26
3.3.2 Controlling for Other Factors

Differences in sustained stock market participation may be the result of other factors unrelated to either our perception of or interest in investing. The gender wage gap may contribute

to men being more able to participate in the stock market. For example, if men have more

discretionary income than women, then men may be more likely to make subsequent stock

purchases. Similarly, women may be more interested in withdrawing their initial investment

to spend as discretionary income, rather than continuing to invest in the stock market. As

in Table 6, in Tables 12 we use median income by zip code from the 2016 ACS as a proxy

for individual users income. Additionally, we use the percentage of residents who earn at

least a college graduates by zip code from the 2016 ACS as a proxy for the individuals level

of education. It is also possible that a user’s age and the size of the initial gift influence

whether an account holder continues to participate in the stock market.

[Insert Table 12 Here]

Table 12 Panel A presents the results of probit regressions in which the dependent variable

is an indicator for whether an account remains open one year after an account was opened.

After controlling for user age, income, and the initial gift card value, the coefficient of the

Female indicator variable in column (3) is indistinguishable from 0.

Table 12 Panel B presents the results of probit regressions in which the dependent variable

is an indicator for whether the account holder made at least one trade more than 1 year

after they redeemed a stock gift card. After controlling for user age, income, and the initial

27
gift card value, the coefficient of the Female indicator variable in column (3) is 0.017. In

contrast to our earlier results, this indicates that women are 0.6% more likely than men to

make a make a stock trade more than a year after their first trade.

Further, after controlling for other factors, in the 2nd, 3rd, and highest income inequity

quartiles, the gender gap in continued stock market participation is indistinguishable. That

is, men and women are equally likely to continue to trade in the future regardless of their

community’s gender norms. In the lowest income inequity quartile, women are, on average

1.8% (the marginal effect of the coefficient of 0.055) more likely to continue trading more

than a year after their first stock purchase.

Next, we turn to our final proxy for sustained stock market participation, app logins, measured in a multivariate setting. Panel C of Table 12 presents the results of probit regressions

in which the dependent variable is an indicator for whether the account holder logs into the

app more than 4 times after one year following account initiation.

We find that women and men are equally likely to remain active. For example, the coefficient

of Female in Panel C column (3) is not statistically or economically significant. Taken

together, the results indicate that the proportion of active men and the proportion of active

women are the roughly same. This offers strong support for the idea that having received

the same nudge, the same proportion of men and women participate in the stock market.

28
4 Conclusion

Stock gift cards encourage stock market entry and participation. However, women receive

only 38.3% of all stock gift cards. Additionally, conditional on receiving a gift card, women’s

gift cards are for $10.81, or 21.4%, less than men’s gift cards.

We conclude that the stock gift card gender gap is the result of people acting on the perception that men are more interested in investing than women. We do not find support for

the alternative hypothesis that men are more interested in finance than women. To distinguish between perceived interest and actual interest, we observe gift cards to children under

8 years old, before they have the cognitive ability to be interested in investing (Friedline,

2015). Even for children under 8 years old, the pattern remains consistent, girls under 8

receive just 45.7% of initial gift cards. To further distinguish between the hypotheses, we

consider community characteristics. We find that in communities where there is a larger

gender role imbalance, there is also larger stock gift card gender gap. This evidence is consistent with the theory that part of the gift card gap can be attributed to the gender norms

of a community.

We then turn to the value of gift cards received. It is possible that gift card value is related

to an individuals optimal level of investment, rather than either of our original hypotheses.

Even after we include control variables such as income, wealth, and age in a multivariate

setting, we find that men receive higher valued gift cards than women. Next, we compare

siblings who are both under 18 years old and part of the same household, which effectively

controls for income, wealth, quality of education, and family attitudes towards investing.

29
Even among pairs of mixed gendered siblings, sisters receive gift cards for less value than

their brothers.

Finally, we confirm that a stock gift card is an effective nudge to encourage stock market

participation. One year after a stock gift card redemption, 90% of people remain invested

in the stock market. Most importantly, roughly the same proportion of men and women

continue to participate in the stock market. Using subsequent stock purchases and app

logins as measures of sustained stock market interest and participation, we find that men

and women are equally likely to continue to participate in the stock market. This indicates

that if men and women were encouraged to enter the stock market in equal proportions then

the gender gap in stock market participation would fall.

We recognize that the data has limitations. The stakes of the financial decisions analyzed

in this paper are small. The average stock gift card amount is just $50.53. This app may

not be thought of as a vehicle for long-term investments. And, many investors likely have

other savings accounts prohibiting us from seeing the full picture. Despite the limitations

of the data set, our work provides a measurable way to evaluate the implications of our

non-conscious perceptions of stock market interest. In line with the theory of cumulative

advantage, even if the dollar amount is small, the impacts are large as stock market entry

and exposure contribute to financial confidence, financial literacy, and a life time of stock

market participation. We hope that the basic facts in this paper will encourage future work

to understand and ultimately reduce gender gaps in finance.

30
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Figure 1: Histogram of Number of Trades and Logins

Proportion of Users

0 10 20 30 40 50

Number of Trades

Proportion of Users

0 500 1000 1500

Number of Logins

(a) Trades (b) Logins

(a) presents the histogram of the proportion of users who make a given number of trades. Note that in this

figure the number of trades is top-coded to 50. (b) presents the histogram of the proportion of users who

have a given number of logins. Note that in this figure the number of logins is top-coded to 1,500.

34
Table 1: User Demographics

This tables reports the breakdown of unique users by demographic characteristics. Minors are users who

are younger than 18 years old. Male and Female are self-reported. Region is determined by the U.S. Census

Bureau’s geographic region by zip code. Median Income (Zip Code) is the median income of the user’s zip

code per the 2016 ACS.

Panel A: Users by Age & Gender

Age Male Female Total

Under 8 15,702 13,658 29,360

8-17 44,948 25,112 70,060

18-24 83,754 34,317 118,071

25-34 121,934 77,219 199,153

35-44 77,420 63,112 140,532

45-54 39,677 42,057 81,734

55-64 17,420 19,879 37,299

65+ 8,450 8,770 17,220

Total 409,305 284,124 693,429

Panel B: Users by Location & Income

Median Income (Zip Code)

Region < 30K 30K-70K 70K- >100K Total

100K

Northeast 7,244 68,848 32,829 17,282 126,203

South 13,123 201,281 51,346 19,834 285,584

Midwest 8,547 91,189 26,470 5,843 132,049

West 2,647 89,333 41,144 16,469 149,593

Total 31,561 450,651 151,789 59,428 693,429

35
Table 2: Number of Gift Cards Received by Gender

This table reports the number of gift cards given to males and females. Panel A includes all gift cards given.

Panel B restricts the sample to Initial Gift Cards, that is, gift cards used to open an account. Percent

Females column significance is based on a one proportion Z-test comparing the proportion of gift cards given

to females to the US population for each age group. ∗ < 0.10, ∗∗ < 0.05, ∗ ∗ ∗ < 0.01

Panel A: All Gift Cards

Sample Total Male Female Percent Females

Full Sample 423,861 259,203 164,658 0.388***

Children (Under 18) 98,147 60,898 37,249 0.380***

Children (Under 8) 32,843 17,671 15,172 0.462***

Panel B: Initial Gift Cards

Sample Total Male Female Percent Females

Full Sample 180,131 98,937 81,194 0.451***

Children (Under 18) 37,544 23,130 14,414 0.384***

Children (Under 8) 12,355 6,707 5,648 0.457***

36
Table 3: Distribution of Accounts for Female Children by Family Size

This table reports the distribution of accounts opened using a gift card for families of different sizes. Number

of Kids is the number of accounts opened using a gift card for minors linked to a single adult account. Number

of Families is the total number of unique parent accounts with at least one linked custodial account. In each

row, we report the proportion of families of a given size that have X number of girls. The expected proportion

of gender by family size is reported in parenthesis and is derived from the 2016 American Community Survey.

χ2 is the results of a χ2 goodness-of-fit test comparing the observed distribution of female children to the

expected distribution. *p < 0.10, **p < 0.05, ***p < 0.01.

Number of

Kids

Number of

Families 0

Number of Girls

1 2 3 4 χ2

1 21,196 0.645

(0.514)

0.355

(0.486) 1,472.11***

2 4,476 0.330

(0.257)

0.491

(0.509)

0.179

(0.234) 230.02***

3 908 0.191

(0.142)

0.401

(0.379)

0.310

(0.354)

0.098

(0.125) 45.72***

4 190 0.084

(0.084)

0.309

(0.252)

0.358

(0.359)

0.203

(0.236)

0.046

(0.068) 9.19*

37
Table 4: Cultural Factors and the Stock Gift Card Gender Gap

This table reports the proportion of gift cards given to females versus males across the cultural spectrum.

The sample is divided into quartiles based on cultural measures of differences between men and women within

the user’s zip code. Income Imbalance is measured as differences between the median wage of males and

females, scaled by the average wage within each zip code. Education Imbalance is defined as the difference

between the proportion of males and females who have a bachelor’s degree or higher, scaled by the average

proportion of people who have a bachelor’s degree or higher in the zip code. Labor Force Participation

Imbalance is measured as the difference between the male and female labor participation rate within the zip

code.

Panel A: All Investors

Income Imbalance Education Imbalance Labor Participation Imbalance

Female Male Difference Female Male Difference Female Male Difference

Lowest 0.492 0.508 0.016 0.493 0.507 0.014 0.476 0.525 0.049

2nd 0.457 0.543 0.087 0.455 0.545 0.091 0.453 0.547 0.094

3rd 0.438 0.562 0.124 0.435 0.565 0.131 0.446 0.554 0.107

Highest 0.417 0.583 0.166 0.423 0.577 0.155 0.429 0.571 0.142

Difference (High-Low) 0.150*** 0.141*** 0.093***

Panel B: Under 8 Years Old

Income Imbalance Education Imbalance Labor Participation Imbalance

Female Male Difference Female Male Difference Female Male Difference

Lowest 0.473 0.527 0.054 0.475 0.525 0.051 0.457 0.543 0.086

2nd 0.456 0.544 0.088 0.458 0.542 0.083 0.457 0.543 0.086

3rd 0.456 0.544 0.088 0.439 0.561 0.123 0.461 0.539 0.078

Highest 0.447 0.553 0.107 0.446 0.554 0.108 0.439 0.561 0.123

Difference (High-Low) 0.052*** 0.058*** 0.037***

Panel C: 8-18 Years Old

Income Imbalance Education Imbalance Labor Participation Imbalance

Female Male Difference Female Male Difference Female Male Difference

Lowest 0.385 0.615 0.230 0.409 0.591 0.182 0.359 0.641 0.281

2nd 0.349 0.651 0.302 0.383 0.618 0.235 0.342 0.658 0.316

3rd 0.332 0.668 0.337 0.370 0.630 0.260 0.323 0.677 0.354

Highest 0.324 0.676 0.352 0.361 0.639 0.278 0.334 0.666 0.332

Difference (High-Low) 0.122*** 0.097*** 0.051***

Panel D: Older than 18 Years Old

Income Imbalance Education Imbalance Labor Participation Imbalance

Female Male Difference Female Male Difference Female Male Difference

Lowest 0.509 0.491 -0.018 0.510 0.490 -0.021 0.494 0.506 0.012

2nd 0.475 0.525 0.051 0.474 0.526 0.052 0.472 0.528 0.057

3rd 0.458 0.542 0.084 0.456 0.544 0.087 0.470 0.530 0.060

Highest 0.442 0.558 0.116 0.445 0.555 0.111 0.451 0.549 0.097

Difference (High-Low) 0.133*** 0.131*** 0.086***

38
Table 5: Average Gift Card Amount Received by Gender

This table reports the mean value of gift cards in dollars by gender. Panel A reports all gift cards given,

and Panel B restricts the sample only to gift cards used to open an account (i.e. initial gift cards). The

difference column reports the differences between the average amount given to males and females. Standard

errors are report in parenthesis. In the difference column, significance is determined by a two sample t-test.

∗ < 0.10, ∗∗ < 0.05, ∗ ∗ ∗ < 0.01

Panel A: All Gift Cards

Sample Overall Male Female Difference

Full Sample 50.53

(0.16)

54.73

(0.23)

43.92

(0.23)

10.81***

(0.34)

Minors Only 54.50

(0.29)

54.75

(0.37)

54.11

(0.46)

0.64

(0.59)

Panel B: Initial Gift Cards

Sample Overall Male Female Difference

Full Sample 42.67

(0.21)

46.74

(0.31)

37.72

(0.27)

9.02***

(0.42)

Minors Only 56.34

(0.45)

56.82

(0.59)

55.57

(0.70)

1.25

(0.93)

39
Table 6: The Influence of Gender on Gift Card Value

This table reports OLS regressions in which the dependent variable is the dollar amount of a gift card.

Female is an indicator for whether the account registered to a female user. User Age is the age of the person

who received the gift card. Income is defined as the median income (in thousands) for the user’s zip code.

% College is the The percentage of residents who earn at least a college degree in the user’s zip code. In

columns (1) & (2) we report the results for all gift cards. In columns (3) & (4) we include only initial gift

cards. Standard errors are reported in parenthesis. *p < 0.10, **p < 0.05, ***p < 0.01.

Female

All Gift Cards

(1) (2)

-10.812∗∗∗ -9.810∗∗∗

(0.336) (0.337)

Initial Gift Cards

(3) (4)

-9.020∗∗∗ -6.450∗∗∗

(0.421) (0.423)

User Age 0.014

(0.010)

-0.257∗∗∗

(0.012)

Log(Income) 0.050∗∗∗

(0.009)

0.091∗∗∗

(0.012)

% College 44.251∗∗∗

(1.421)

48.133∗∗∗

(1.853)

Constant

Observations

Adjusted R-Sq.

54.731∗∗∗

(0.209)

423,861

0.002

34.786∗∗∗

(0.564)

421,916

0.009

46.740∗∗∗

(0.283)

180,131

0.003

31.169∗∗∗

(0.730)

179,418

0.019

40
Table 7: Comparison of Gift Cards Given to Mixed Gender Siblings

This table reports the dollar amount of the initial gift card given to mixed gender sibling pairs. Only families

with at least one male and one female child are included. If a family includes multiple children of a given

gender, only the eldest child of each gender is included. The first row contains all families with both a male

and female child. Same day refers to families where the male and female child opened their account on the

same day. Different Days include families where the two children opened their accounts on different days.

Paired standard errors are included in parenthesis. *p < 0.10, **p < 0.05, ***p < 0.01.

Male Female Difference Pairs

Overall 40.70

(0.81)

39.31

(0.81)

1.40**

(0.65) 4,859

Same Day 40.33

(1.34)

40.40

(1.33)

-0.07

(0.50) 1,746

Different Days 40.91

(1.02)

38.69

(1.02)

2.22**

(0.97) 3,113

Table 8: Comparison of Initial Gift Cards Given to Sibling Pairs

In this table, we report the difference in the initial gift card given to the oldest and second oldest child in a

family. The first row contains all families with at least two children. Rows two through five then breakdown

the results by the gender of the oldest and second oldest child. Paired standard errors are included in

parenthesis. *p < 0.10, **p < 0.05, ***p < 0.01.

Gender of Gender

Oldest Child Second Child

Amount to

Oldest Child

Amount to

Second Child Difference Pairs

Overall 41.83

(0.61)

37.95

(0.61)

3.31***

(0.48) 8,126

Male Male 41.83

(1.06)

37.95

(1.04)

3.88***

(0.79) 2,706

Male Female 42.99

(1.28)

38.18

(1.27)

4.82***

(1.11) 1,998

Female Male 40.29

(1.23)

38.70

(1.28)

1.59**

(0.91) 1,902

Female Female 40.47

(1.37)

38.03

(1.35)

2.44**

(1.02) 1,520

41
Table 9: The Influence of Gender and Birth Order on Initial Gift Card Amount

This table reports the coefficients of regressions in which the dependent variable is the initial gift card dollar

amount. The main variables of interest are the interaction between gender (male vs. female) and firstborn

status (first born vs. non-first born). The omitted base category is male firstborn. Columns (1) & (2)

include the full sample. Columns (3)-(4) include only families where all of the families children opened their

account on the same day, whereas columns (5)-(6) include families where accounts were opened for different

children on different days. Standard errors are clustered by family and reported in parenthesis. *p < 0.10,

**p < 0.05, ***p < 0.01.

Female×Non-First Born

Full Sample

(1) (2)

-8.817∗∗∗ -6.517∗∗∗

(1.422) (1.568)

Same Day

(3) (4)

-6.796∗∗∗ -0.732

(2.232) (0.785)

Different Days

(5) (6)

-13.521∗∗∗ -8.767∗∗∗

(2.153) (2.163)

Male×Non-First Born -7.056∗∗∗

(1.315)

-5.142∗∗∗

(1.237)

-5.077∗∗

(2.065)

-0.783

(0.954)

-11.171∗∗∗

(1.824)

-6.808∗∗∗

(1.675)

Female×First Born -3.294∗

(1.681)

-2.782∗∗

(1.191)

-4.155

(2.711)

-0.784

(0.895)

-3.213

(2.135)

-3.602∗∗

(1.709)

User Age -0.077

(0.072)

-0.271

(0.179)

0.017

(0.020)

0.241

(0.184)

-1.107∗∗∗

(0.231)

-0.416∗

(0.223)

Constant

Family FE

Observations

Adjusted R-Sq.

48.142∗∗∗

(1.473)

No

21,439

0.002

48.367∗∗∗

(2.305)

Yes

20,490

0.709

48.779∗∗∗

(1.979)

No

7,448

0.001

42.623∗∗∗

(2.065)

Yes

6,499

0.923

58.633∗∗∗

(3.346)

No

13,991

0.006

49.923∗∗∗

(2.943)

Yes

13,991

0.624

42
Table 10: Keeping Account Open for at least One Year after a Gift Card

This table reports the proportion of males and females who keep their account open for at least one year

after redeeming a gift card to open their account. The sample is divided into quartiles (Lowest, 2nd, 3rd,

and Highest) based on the Income Imbalance as measured by the differences between the median wage of

males and females, scaled by the average wage in each zip code.

Female Male Differece

Lowest 0.906 0.893 -0.013

2nd 0.911 0.896 -0.015

3rd 0.916 0.896 -0.020

Highest 0.912 0.880 -0.032

Overall 0.911 0.891 -0.020

Table 11: Ongoing Stock Market Participation after a Gift Card

This table reports the stock market participation of males and females older than age 18 who opened their

account by redeeming a gift card before 2020. Average number of trades is the average number total number

of trades a person makes at any time following account initiation. Percent who Continue to Trade after

Initial Purchase is the percentage of people who make more than one stock purchase at any time after their

initial stock purchase. Percent who continue to trade after 1 year is the percentage of people who make at

least one stock purchase more than a year after their initial stock purchase. This subsample is limited to

people who opened their account prior to 2019. Average number of log-ins is the average of the number of

times a person opens the stock trading app and logs into their account. Percent who log in more than 4

times is the percentage of people who log in 4 or more times any time after their initial purchase. Percent

who log in more than 4 times after 1 year is the percentage of people who log in 4 or more times after 1

year following their initial purchase. This subsample is limited to people who opened their account prior to

2019. The sample is divided into quartiles (Lowest, 2nd, 3rd, and Highest) based on the Income Imbalance

as measured by the differences between the median wage of males and females, scaled by the average wage

in each zip code.

Panel A: Trade Data

Average Number Percent who Continue to Trade Percent who Continue to Trade

of Trades after Initial Purchase after 1 Year

Female Male Difference Female Male Difference Female Male Difference

Lowest 9.41 12.47 3.06 0.567 0.591 0.025 0.046 0.059 0.013

2nd 9.40 12.46 3.06 0.558 0.603 0.044 0.046 0.065 0.018

3rd 9.81 12.93 3.12 0.558 0.609 0.051 0.052 0.067 0.015

Highest 9.76 12.92 3.17 0.559 0.599 0.040 0.055 0.075 0.019

Panel B: Login Data

Average Number Percent who Login more than Percent who Login more than

of Logins 4 Times 4 Times after 1 Year

Female Male Difference Female Male Difference Female Male Difference

Lowest 96.42 141.56 45.14 0.855 0.865 0.010 0.533 0.510 -0.023

2nd 97.60 148.81 51.21 0.852 0.871 0.019 0.521 0.522 0.001

3rd 98.64 150.04 51.39 0.852 0.869 0.016 0.530 0.523 -0.007

Highest 97.19 147.83 50.64 0.848 0.861 0.013 0.531 0.528 -0.003

43
Table 12: Stock Market Participation and Gender after Receiving a Gift Card

This table reports the relationship between stock market participation after the redemption of a gift certificate. Panel A reports a probit regression in which the dependent variable is an indicator for whether the

account remains open for at least 1 year after opening of the account. Panel B reports probit regressions

in which the dependent variable is whether an account holder purchased a stock more than 1 year after

opening their account. Panel C reports a probit regression in which the dependent variable is an indicator

for whether the user logged in at least four times to their account more than a year after the account’s

opening. In columns (4) - (7), the sample is divided into quartiles (Lowest, 2nd, 3rd, and Highest) based

on the Income Imbalance as measured by the differences between the median wage of males and females,

scaled by the average wage in each zip code. Age is the age of the person who received the gift card. Income

is defined as the median income (in thousands) for the user’s zip code. % College is the The percentage of

residents who earn at least a college degree in the user’s zip code. Initial Gift Card Value is the amount of

money that the first gift card was redeemed for. Marginal average effects are included in square brackets.

Standard errors are reported in parenthesis. *p < 0.10, **p < 0.05, ***p < 0.01.

Panel A: Account Open for at least 1 Year

(1) (2) (3) (4) (5) (6) (7)

Female 0.090∗∗∗ 0.069∗∗∗ 0.008 0.006 -0.013 0.005 0.054∗∗

(0.010) (0.010) (0.010) (0.020) (0.020) (0.022) (0.022)

[0.014] [0.011] [0.001] [0.001] [-0.002] [0.001] [0.008]

User Age 0.006∗∗∗ 0.006∗∗∗ 0.005∗∗∗ 0.006∗∗∗ 0.006∗∗∗ 0.007∗∗∗

(0.000) (0.000) (0.001) (0.001) (0.001) (0.001)

Log(Income) -0.013 -0.063∗ -0.031 -0.028 -0.101∗∗

(0.020) (0.038) (0.039) (0.046) (0.048)

% College -0.048 0.156∗ 0.103 -0.152 -0.147

(0.044) (0.089) (0.082) (0.094) (0.094)

Log(Initial GC Value) -0.450∗∗∗ -0.451∗∗∗ -0.459∗∗∗ -0.462∗∗∗ -0.428∗∗∗

(0.005) (0.010) (0.010) (0.011) (0.010)

Constant 1.307∗∗∗ 1.098∗∗∗ 2.702∗∗∗ 2.819∗∗∗ 2.771∗∗∗ 2.870∗∗∗ 3.025∗∗∗

(0.007) (0.015) (0.073) (0.140) (0.150) (0.173) (0.182)

Observations 134,193 134,193 133,703 35,107 35,737 32,201 30,658

Psuedo R-Sq. 0.001 0.004 0.109 0.103 0.109 0.114 0.118

Sample Full Full Full Lowest 2nd 3rd Highest

44
Table 12 (Continued)

Panel B: Trader After 1 Year

Female

(1)

0.040***

(0.007)

[0.013]

(2)

0.007

(0.007)

[0.002]

(3)

0.017**

(0.008)

[0.005]

(4)

0.055***

(0.015)

[0.018]

(5)

-0.003

(0.015)

[-0.001]

(6)

0.000

(0.015)

[0.000]

(7)

0.011

(0.016)

[0.004]

User Age 0.009***

(0.000)

0.009***

(0.000)

0.010***

(0.001)

0.009***

(0.001)

0.009***

(0.001)

0.008***

(0.001)

Log(Income) 0.042***

(0.014)

0.075***

(0.028)

0.053*

(0.029)

0.094***

(0.033)

-0.017

(0.034)

% College -0.157***

(0.032)

-0.111*

(0.067)

-0.060

(0.061)

-0.279***

(0.070)

-0.129*

(0.068)

Log(Initial GC Value) 0.107***

(0.004)

0.105***

(0.008)

0.118***

(0.008)

0.120***

(0.008)

0.085***

(0.008)

Constant

Observations

Psuedo R-Sq.

Sample

-0.660***

(0.005)

134,193

0.000

Full

-0.981***

(0.012)

134,193

0.006

Full

-1.432***

(0.053)

133,703

0.011

Full

-1.625***

(0.102)

35,107

0.013

Lowest

-1.520***

(0.109)

35,737

0.011

2nd

-1.647***

(0.124)

32,201

0.013

3rd

-1.078***

(0.129)

30,658

0.008

Highest

Panel C: More than 4 Logins after 1 Year

Female

(1)

0.038***

(2)

0.003

(3)

0.007

(4)

0.041***

(5)

-0.013

(6)

-0.008

(7)

0.008

(0.007)

[0.015]

(0.007)

[0.001]

(0.007)

[0.003]

(0.014)

[0.016]

(0.014)

[-0.005]

(0.014)

[-0.003]

(0.015)

[0.003]

User Age 0.009***

(0.000)

0.009***

(0.000)

0.010***

(0.001)

0.009***

(0.001)

0.011***

(0.001)

0.008***

(0.001)

Log(Income) 0.058***

(0.013)

0.085***

(0.026)

0.101***

(0.027)

0.107***

(0.030)

-0.053*

(0.032)

% College -0.176***

(0.030)

-0.161***

(0.062)

-0.102*

(0.056)

-0.287***

(0.064)

-0.065

(0.064)

Log(Initial GC Value) 0.058***

(0.004)

0.064***

(0.007)

0.064***

(0.007)

0.064***

(0.008)

0.040***

(0.007)

Constant -0.102*** -0.435*** -0.789*** -0.949*** -0.970*** -1.005*** -0.266**

Observations

Psuedo R-Sq.

Sample

(0.005)

134,193

0.000

Full

(0.011)

134,193

0.006

Full

(0.049)

133,703

0.008

Full

(0.094)

35,107

0.008

Lowest

(0.101)

35,737

0.007

2nd

(0.114)

32,201

0.010

3rd

(0.120)

30,658

0.006

Highest

45