I. Introduction
Substantial cross-country disparities in asset participation and allocation remain largely unexplained even after accounting for factors such as demographics, education, income, and wealth. Surprisingly, there is considerable variation also among similarly developed and geographically proximate countries (Badarinza, Campbell, and Ramadorai (Reference Badarinza, Campbell and Ramadorai2016), Christelis, Georgarakos, and Haliassos (Reference Christelis, Georgarakos and Haliassos2013)).
We argue that cultural heritage may play a crucial role in understanding these disparities.Footnote 1 Extensive evidence has demonstrated the profound impact of culture on shaping beliefs, preferences, and individual decision-making, influencing various domains such as labor force participation, education, fertility, corruption, and violence (Alesina, Giuliano, and Nunn (Reference Alesina, Giuliano and Nunn2013), Fernández (Reference Fernández2011), Fernandez and Fogli (Reference Fernandez and Fogli2009), Fernández, Fogli, and Olivetti (Reference Fernández, Fogli and Olivetti2004), Figlio, Giuliano, Özek, and Sapienza (Reference Figlio, Giuliano, Özek and Sapienza2019), Fisman and Miguel (Reference Fisman and Miguel2007), Guiso, Sapienza, and Zingales (Reference Guiso, Sapienza and Zingales2003), (Reference Guiso, Sapienza and Zingales2006), Miguel, Saiegh, and Satyanath (Reference Miguel, Saiegh and Satyanath2011), and Voigtländer and Voth (Reference Voigtländer and Voth2012)). Given the influence of preferences on financial behavior, it is plausible that cultural heritage, transmitted from parents to children, helps explain some of the cross-country differences in portfolio compositions. This article examines this idea by assessing the effect of a distinct culturally transmitted attribute central to any theory of investment behavior – risk preferences – on the composition of financial portfolios.
Although previous research has not directly tested this hypothesis, existing evidence points to the potential influence of cultural traits on the formation of financial portfolios.Footnote 2 For example, Guiso, Sapienza, and Zingales (Reference Guiso, Sapienza and Zingales2008) find that trust, a cultural attribute with deep historical roots, affects households’ willingness to participate in the stock market. Haliassos, Jansson, and Karabulut (Reference Haliassos, Jansson and Karabulut2017) use data on first-generation European migrants in Sweden, grouping them into six-country clusters based on their genetic proximity to native Swedes, and study the role of cultural differences in asset market participation.
A key challenge in the existing literature is to disentangle the effect of culturally transmitted preferences on investment behavior from the influence of other institutional and economic factors. A particular culture, which might drive specific investment behaviors, could also give rise to institutions and policies that accommodate or incentivize such behaviors (Guiso et al. (Reference Guiso, Sapienza and Zingales2006)). In such cases, it becomes difficult to distinguish whether a certain investment behavior can be attributed to institutional features or individuals’ cultural attributes.
We overcome these concerns by relating the investment behavior of second-generation migrants in Sweden—a subsample of the Swedish population who were born in Sweden but have both parents born in a different country—with the ancestral culture of risk taking in their parents’ countries of origin.Footnote 3 By considering the inter-generational transmission of attitudes from parents to children (Dohmen, Falk, Huffman, and Sunde (Reference Dohmen, Falk, Huffman and Sunde2012)), our identification strategy exploits the opportunity to observe this subsample with diverse parental cultural backgrounds in a common environment. This approach allows us to isolate the impact of cultural factors from other influences, such as institutional and aggregate economic factors. Furthermore, the spatial separation of migrants from their countries of origin rules out reverse causality and any other omitted factor must be intergenerationally transmissible. Thus, none of the usual confounders—such as institutions, the economic environment, technology, and geography—can plausibly explain away our estimates.Footnote 4
To investigate individuals’ investment behavior, we start by looking at equity market participation and the share of financial wealth invested in equities, conditional on participation. For our main analysis, we combine administrative data on the investment behavior and portfolio composition of the population of second-generation migrants in Sweden with information on risk preferences in their parents’ countries of origin, obtained from the Global Preference Survey (GPS; Falk, Becker, Dohmen, Enke, Huffman, and Sunde (Reference Falk, Becker, Dohmen, Enke, Huffman and Sunde2018)). GPS is an experimentally validated survey data set of economic (risk and time preferences) and social preferences (reciprocity, altruism, and trust) from 76 countries, representing approximately 90% of the global population. The extensive global coverage of GPS allows us to assign second-generation migrants in Sweden to the measures of risk preferences in the country of ancestry.
We find that culturally transmitted risk preferences significantly increase the likelihood of participation in risky asset markets. While participation in risky asset markets is influenced by risk preferences, as well as other characteristics—such as wealth, access to information, and cognitive capacity influencing individuals’ ability to overcome fixed costs of participation—the share of financial wealth invested in equities conditional on participation is usually considered to be mainly a reflection of risk-taking tendencies. We find that, among those who participate in equity markets, the descendants of those from more risk-loving cultures assign a larger share of their financial wealth to equities. A 1-standard-deviation increase in the culture of risk-taking (0.29) leads to a 1.4 percentage points increase in the risky asset share, compared to the mean of 48%.
A potential threat to our identification is the possibility that migration from different source countries and across time may occur for various reasons that could affect the investment behavior of children of immigrants beyond the average cultural characteristics of source countries or that risk preferences in the country of ancestry might merely capture indirect parental characteristics.
However, our findings are robust to controlling for parental characteristics, such as education, wealth, or income. This mitigates the aforementioned concern, as parental features pick up the effect of selection of migrants from specific countries and across time to a large extent.Footnote 5 Nevertheless, we go beyond this to explicitly address this concern in a number of ways. First, we show that our findings remain unchanged when we control for source continents. Additionally, the findings are robust to controlling for the source countries’ GDP per capita or life expectancy. Furthermore, trust has been shown to influence financial market behavior, especially among migrants (Guiso, Sapienza, and Zingales (Reference Guiso, Sapienza and Zingales2004), Guiso et al. (Reference Guiso, Sapienza and Zingales2008)). If culturally transmitted risk preferences we study are correlated with trust, one might suspect children of migrants from different countries to behave differently due to varying levels of trust. We show that our results are robust to controlling for trust. Finally, institutional features may be confounding the influence of culture. Yet, the estimates on the effects of culture on risk taking remain significant when we control for the rule of law as a measure of institutions in the origin country – even though institutions are arguably endogenous to culture. These exercises suggest that variations in some of the most important economic and social indicators of the source countries are unlikely to derive our findings.Footnote 6
Another concern regarding the proposed interpretation is that children’s investment behavior may not be directly shaped by their cultural heritage, but instead it reflects indirect influences from their other outcomes, such as cognitive ability, education, income, and wealth—all of which are linked to investment behavior. However, we find that the relations between cultural attributes and the investment behavior of children of immigrants remain strong even after controlling for children’s education, income, wealth, and IQ.Footnote 7
Having established that cultural risk preferences affect the most basic indicators of risk taking in financial markets, we shift our attention to understanding whether a culture of risk taking influences the composition of risky asset portfolios, conditional on participation. More specifically, we aim to understand if those from risk-loving cultures take more idiosyncratic risks and form portfolios with higher volatility or risk taking in financial markets induced by cultural background is just manifested in the share of financial wealth designated to risky assets. The former hypothesis is arguably plausible because the literature typically measures risk-taking culture—whether measured using GPS or other measures employed in this article—by framing risk in lottery-type frameworks or choices resembling gambling scenarios.
Compared to investments in mutual funds, direct investments in stocks typically exhibit greater volatility with potentially more extreme returns, characteristics particularly appealing to investors with a preference for taking idiosyncratic risk. Previous research has shown that individuals who invest in stocks, rather than mutual funds, tend to view trading as a form of gambling and may switch between the two activities as substitutes.Footnote 8 Also, survey respondents often equate investing in stocks to gambling, purchasing lottery tickets, or visiting a casino (Chopra and Haaland (Reference Chopra and Haaland2023), Henkel and Zimpelmann (Reference Henkel and Zimpelmann2023)). Dorn, Dorn, and Sengmueller (Reference Dorn, Dorn and Sengmueller2015) demonstrate that variation in lottery prizes in Germany affects trading behavior in individual stocks and options, while mutual fund trading fails to provide the desired gambling experience sought by gambling-motivated investors. Gao and Lin (Reference Gao and Lin2015) find that higher lottery jackpot prizes in Taiwan lead to a decrease in trading volume among stocks preferred by individual investors. Kumar (Reference Kumar2009) discovers that individual investors prefer stocks with lottery-like features, such as low prices, high idiosyncratic volatility, and high idiosyncratic skewness.
We show that, conditional on participation in the equity market, individuals with immigrant parents from countries with a greater willingness to take risks are more likely to directly hold stocks (less likely to invest in mutual funds), allocate a larger portion of their risky portfolio to direct stock holdings, and hold portfolios with higher volatility.
Importantly, our findings remain robust even after controlling for parental characteristics (education, wealth, or income) or country-level characteristics (GDP per capita, life expectancy, trust, or the rule of law). This suggests that our findings are not merely capturing indirect parental or country characteristics, and that cultural risk preferences plausibly have a direct effect on children’s portfolio composition. In addition, individual-level outcomes of education, income, or wealth are not strong enough mediators to fully account for the total effect of cultural risk preferences.
Furthermore, we provide evidence on the mechanisms of cultural persistence and demonstrate that we indeed pick up the role of cultural heritage in our analysis. First, we corroborate our findings on portfolio composition by examining risk-taking heritage that predates our outcomes by a very long time. While our primary focus in this study is on the impact of cultural heritage on risk taking in financial markets, rather than how cultural values are formed, this exercise provides an intuitive understanding of the origins of differing cultural norms and whether similar results are obtained when using characteristics of ancestral tribes or communities before any modernization occurred. To accomplish this, we use a separate data set from the Ethnographic Atlas of Murdock (Reference Murdock1965), which contains information gathered by ethnographers reflecting various cultural and socioeconomic characteristics of pre-modern societies before industrialization and European contact.Footnote 9 We proxy the long-term ancestral culture of risk-taking in the parents’ countries of origin with the prevalence of chance games in societies, as opposed to games relying on physical skills or strategies. Consistent with our baseline findings, we find that individuals whose ancestors participated in games with a significant element of chance are more likely to own stocks instead of mutual funds, allocate more of their portfolio to directly held stocks, and have more volatile portfolios. This addresses the unlikely concern that our main cultural preferences obtained from the GPS might have been influenced (even partially) by contemporaneous institutional and economic policies that could have affected the parents of immigrants in ways not reflected in their wealth, income, and education. By incorporating this additional evidence from pre-modern societies, we further strengthen the argument that cultural characteristics play a vital role in shaping investment behavior.
Second, we show that the relationships between ancestral and cultural risk preferences and financial behavior are stronger for individuals who descend from more persistent cultures. Giuliano and Nunn (Reference Giuliano and Nunn2021) argue that in environments characterized by greater stability across generations, traits that have evolved up to the previous generation are more likely to be beneficial for the current generation. Hence, it becomes advantageous to maintain existing customs and cultural norms. We test this idea in our setting by approximating cultural persistence with exogenous measures of cross-generational climatic variability of the environment. We confirm our hypothesis, supporting the idea that the influence of cultural background on investment behavior is more pronounced when individuals come from cultures with higher levels of persistence.
Third, in line with the arguments for the role of socialization in cultural transmission (Dohmen et al. (Reference Dohmen, Falk, Huffman and Sunde2012)), we explore whether a stronger vertical or horizontal transmission of culture enhances the effect of culture on financial behavior. We find that the role of cultural background in investment behavior is stronger when parents share the same country of origin (vertical transmission of culture). This suggests that the transmission of cultural values and preferences within the family plays a significant role in shaping the investment decisions of their children. Furthermore, we find that when individuals have greater opportunities to interact with others from a similar cultural background in their municipalities (horizontal transmission of culture) the impact of cultural risk preferences on investment behavior becomes even stronger.
We make three main contributions to the literature. First, this article contributes to our understanding of the determinants of cross-country variation in risk taking in financial markets (Badarinza et al. (Reference Badarinza, Campbell and Ramadorai2016), Christelis et al. (Reference Christelis, Georgarakos and Haliassos2013)). We demonstrate that cultural differences in risk taking can help explain the disparities in risk taking and portfolio composition.
Second, our findings have important implications for understanding under-diversification and lack of delegation among investors. Evidence suggests that household portfolios in many countries are poorly diversified (Roussanov (Reference Roussanov2010)). Moreover, portfolio diversification has often been viewed as a by-product of investors’ trading decisions rather than a deliberate objective (Dorn and Huberman (Reference Dorn and Huberman2010), Goetzmann and Kumar (Reference Goetzmann and Kumar2008)), since equity portfolio diversification is highly correlated with the propensity to delegate equity investments. The reduced willingness to delegate equity investment decisions leads to lower investments in mutual funds – which are generally better diversified (Alessie, Hochguertel, and Soest (Reference Alessie, Hochguertel and Soest2004), Calvet, Campbell, and Sodini (Reference Calvet, Campbell and Sodini2009), and Gaudecker (Reference Gaudecker2015)) – and, consequently, to more concentrated equity portfolios (Dorn and Weber (Reference Dorn and Weber2013)). Our findings suggest that descending from more risk-loving cultures could result in under-diversified portfolios with larger volatility by investing less in mutual funds and more in directly held stocks. This cultural explanation of under-diversification could also help explain why we observe persistence of this behavior across time.
Third, this article adds to the best of our knowledge of the importance of family background in shaping individual investment behavior. Previous literature has primarily focused on the direct influence of the family on children’s genetic traits, human capital, wealth or income (Barnea, Cronqvist, and Siegel (Reference Barnea, Cronqvist and Siegel2010), Calvet and Sodini (Reference Calvet and Sodini2014), Cesarini, Johannesson, Lichtenstein, Sandewall, and Wallace (Reference Cesarini, Johannesson, Lichtenstein, Sandewall and Wallace2010), and Charles and Hurst (Reference Charles and Hurst2003)), as well as the potential for parents to influence children’s behavior (Black, Devereux, Lundborg, and Majlesi (Reference Black, Devereux, Lundborg and Majlesi2017)), all of which could in turn impact financial decisions. In this article, we go beyond these existing explanations to show that the family could serve as a pathway for the influence of cultural heritage. More importantly, while it may be argued that the role of risk preferences in financial decision-making has long been established, we demonstrate that cultural heritage is a crucial determinant of individual risk preferences and it has direct effects on financial decision-making, emphasizing its significance in shaping individuals’ approach to risk and their subsequent financial choices.
II. Data
A. Outcome Variables
Our outcome variables are various measures of asset allocation of the population of second-generation migrants in Sweden. These data come from the Swedish Wealth Registry (Förmögenhetsregistret) and were collected by Statistics Sweden (the government’s statistical agency) for tax purposes. The data include all financial assets held outside retirement accounts at the end of a tax year, Dec. 31, reported by a variety of different sources, including the Swedish Tax Agency, welfare agencies, and financial institutions. Importantly, nontaxable securities and securities owned by investors below the wealth tax threshold were included in the reports (Calvet, Campbell, and Sodini (Reference Calvet, Campbell and Sodini2007)). With information based on statements from financial institutions and the full coverage of the population, issues of measurement error and selection bias (which are frequently substantial concerns) are negligible in our setting. We have data on assets (linked with the holders’ country of birth) from 1999 to 2006.
In our analysis of second-generation migrants, we focus on wealth in the year 2006. Between 1999 and 2005, banks were not required to report small bank accounts to the Swedish Tax Agency unless the account accrued more than 100 SEK (about 11 USD) in interest during the year. From 2006 onward, banks were required to report all bank accounts above 10,000 SEK.Footnote 10 Also, focusing on 2006 allows us to have more second-generation migrant children to be old enough to participate in the stock market than earlier in the sample.Footnote 11
We look at five outcome variables in total. The first is an indicator of participation in the risky asset market, through stocks or mutual funds, and the second is the share of risky assets in financial assets conditional on participation. Since market participation may be influenced by both preferences and other individual characteristics, such as wealth and cognitive ability, which can help overcome entry barriers into the markets, we are most interested in analyzing portfolio composition conditional on participation that could best reveal the role of culturally transmitted preferences in investment behavior.Footnote 12
Outcomes that we use to analyze portfolio composition conditional on risky asset market participation include: i) an indicator for whether the individual owns stocks directly, which we refer to as stock market participation; ii) the share of directly held stocks out of the total value of mutual funds and directly held stocks, which we refer to as stock share; iii) a proxy for portfolio volatility.
Investment data from the wealth register that is linked with country of birth for the population of Sweden is only available to us at the aggregated level, meaning that we observe the total value of individuals’ directly held stocks, fixed-income funds, and equity funds but not the composition of stocks and fund portfolios.Footnote 13 Therefore, we cannot precisely measure portfolio volatility and instead follow the approach of Calvet et al. (Reference Calvet, Campbell and Sodini2007), where they devised an approach to proxy portfolio diversification with more limited data.Footnote 14
B. Variable of Interest
Our variable of interest is a measure of risk-taking culture captured by the risk preferences associated with second-generation migrants’ ancestral countries (i.e., the country of origin of their parents). These data come from the GPS; an experimentally validated survey data set of the global variation in preferences (Falk et al. (Reference Falk, Becker, Dohmen, Enke, Huffman and Sunde2018)).Footnote 15 GPS provides us with measures specifically designed to capture economic and social preferences from 80,000 people in 76 countries that represent approximately 90% of the world population.Footnote 16 The surveys are carried out on representative samples within each country and exhibit substantial heterogeneity in preferences across countries.Footnote 17
Risk preferences (risk taking) were elicited through a series of related quantitative questions as well as one qualitative question (see Falk et al. (Reference Falk, Becker, Dohmen, Enke, Huffman and Sunde2018) for details). The quantitative survey measure consists of a series of five interdependent hypothetical binary choices, a format commonly referred to as a “staircase” (or “unfolding brackets”) procedure (Cornsweet (Reference Cornsweet1962)). Choices were between a fixed lottery, in which the individual could win x or zero, and varying sure payments, y.Footnote 18
The qualitative item asks for the respondents’ self-assessment of their willingness to take risks on an 11-point Likert scale, “In general, how willing are you to take risks?” This qualitative subjective self-assessment has previously been shown to be predictive of risk-taking behavior in the field in a representative sample (Dohmen, Falk, Huffman, Sunde, Schupp, and Wagner (Reference Dohmen, Falk, Huffman, Sunde, Schupp and Wagner2011)) as well as of incentivized experimental risk taking across countries in student samples (Vieider, Chmura, Fisher, Kusakawa, Martinsson, Thompson, and Sunday (Reference Vieider, Chmura, Fisher, Kusakawa, Martinsson, Thompson and Sunday2015)). The qualitative item and the outcome of the quantitative staircase measure were combined through roughly equal weights.
Figure 1 shows the distribution of risk taking measure by quartiles across countries in our sample. Risk taking measure ranges between −0.79 and 0.97. For a complete list of countries and their risk taking scores, see Supplementary Material Table A.1. Risk preferences vary substantially geographically, as well as within a set of countries with similar levels of development. For example, within Europe, while the Netherlands are in the top risk-taking quartile, Spain and Germany are in lower quartiles.Footnote 19
Figure 1 Risk Taking Across Countries
The data in Figure 1 come from Falk et al. (Reference Falk, Becker, Dohmen, Enke, Huffman and Sunde2018)
C. Controls
In our baseline regressions, we control for gender, year of birth, and time preferences from GPS. In our robustness exercises, we go further by taking into account parents’ years of birth, education, income ranks and parental financial wealth ranks (both within parental birth cohort).Footnote 20 We also investigate the mediating role of individuals’ education level, income rank, and financial wealth rank. All of the variables are provided by Statistics Sweden and are derived from administrative records, primarily from the Swedish tax authority.Footnote 21
Our final sample for the main analysis conditional on equity participation contains 38,702 observations (64,466 observations for unconditional outcomes). Table 1 provides summary statistics. Conditional on participation in equity markets, 45 percent directly hold stocks.
Table 1 Summary Statistics
In the same sample, stock holdings make up 29 percent of risky assets (stocks and mutual funds).Footnote 22
III. Empirical Strategy
Our main specification relates an outcome of interest for the children of migrants in Sweden to the parents’ cultural heritage. We estimate the following specification:
$$ {Y}_{ic}=\alpha +{\beta}_R\mathrm{RISK}\_\mathrm{TAKING}\_{\mathrm{CULTURE}}_c+\gamma {X}_i+{\varepsilon}_{ic}, $$
where
$ {Y}_{ic} $
denotes an outcome of interest for individual
$ i $
from a heritage of origin
$ c $
, where
$ c $
is a mnemonic for country.
$ \mathrm{RISK}\_\mathrm{TAKING}\_{\mathrm{CULTURE}}_c $
is to capture children of migrants’ cultural heritage of risk preferences in their parents’ country of origin. Where parents come from two different countries, this variable indicates the average preferences of those countries.
$ {X}_i $
refers to the set of control variables, which in the baseline regressions includes a dummy variable for the gender of the individual, year-of-birth dummies for the individual, and time preferences in parents’ country of origin.
$ {X}_i $
also includes parental, country of origin, and individual characteristics in subsequent regressions.
$ {\varepsilon}_{ic} $
is the error term, two-way clustered at the level of parental countries of birth.
Identifying Assumption
The key assumption of our empirical strategy is that, by including the risk preference measure in parents’ countries of origin, we capture the effect of cultural preferences and not that of potentially omitted variables. By observing second-generation immigrants in a common environment, we are able to distinguish cultural factors from institutional and economic ones, as these latter ones do not vary, while cultural heritage does. The assumption will be violated if cultural preferences are systematically correlated with other factors that affect financial behavior. One such example is if migrants from relatively risk-loving countries are wealthier (for other reasons than their high risk tolerance) and children of wealthier parents are more likely to participate in equity markets. The fact that we can observe and control for parental characteristics greatly mitigates these concerns. In Sections IV and V, we address the issue of confounding variables in detail and perform a number of robustness analyses.
IV. Baseline Results
A. Risky Asset Market
We start our analysis by showing the effects of country of origin risk preferences on risky asset market participation, regardless of whether participation is through mutual funds or directly owned stocks, in Panel A of Table 2, and the share of financial wealth invested in risky assets conditional on participation in Panel B. In all specifications, we control for year-of-birth and gender fixed effects. We do this because the previous literature has documented that the life cycle has important implications for equity-market participation (Fagereng, Gottlieb, and Guiso (Reference Fagereng, Gottlieb and Guiso2017)), and men and women could behave differently in their investment behavior. As explained before, we also control for the country of origin time preferences, although the results are very similar without those.
Table 2 Risky Asset Participation, Conditional Risky Asset Share, and Cultural Risk Preferences
While in the literature the decision to participate in risky asset markets is partly ascribed to overcoming fixed costs, we would expect those with higher risk preferences to be more likely to own equities. Column 1 in Panel A of Table 2 shows that culturally transmitted preferences for risk increase the likelihood of participation in risky asset markets. The coefficient estimate indicates that a 1-standard-deviation increase in ancestral risk preferences (0.29) increases the probability of risky-asset-market participation by 2.2 percentage points, compared to the mean of 60%.
Similarly in column 1 in Panel B of Table 2, we observe that, for those who participate in the risky asset market, individuals who come from more risk-loving cultural backgrounds designate more of their financial wealth to risky assets. A 1-standard-deviation increase in the culture of risk-taking (0.29) leads to an increase of 1.4 percentage points in the risky asset share, compared to the mean of 48%.
1. Selection of Migrating Parents
The baseline analysis for both outcomes reveals that the cultural heritage of second-generation migrants matters for risky investment behavior. The most important concern in interpreting these coefficients of interest as the effects of ancestral and cultural traits is the selection of migrant parents—those who migrate from certain countries in which people have been historically more risk-loving could display specific characteristics that affect their children’s investment behavior. In other words, cultural traits could be correlated with the socioeconomic status of parents, which might in turn determine children’s financial-market behavior.
To the extent that parental characteristics are shaped by cultural traits, they do not pose a threat to our identification, as those characteristics can be thought of as mechanisms through which cultural traits affect children’s behavior. If a parent is wealthy due to her risk-taking and wealth leads to more investment in equities, then wealth is not a confounder but a channel. Put differently, taking into account parental characteristics would reveal the controlled direct effect (compared to the total effect of culture), after filtering out the indirect effect operating through parents’ characteristics.
Nevertheless, parental characteristics that cause children to behave in a certain way in the financial markets could co-vary with ancestral cultural traits in a nonrandom way without having been caused by those cultural traits. To address this concern, we control for the most important parental features that could arguably affect children’s financial behavior and investigate how the coefficient estimates change.Footnote 23
The results are shown in columns 2–4 in both panels of Table 2. Column 2 starts with taking into account parental fixed effects for eight education levels and parental year of birth fixed effects.Footnote 24 The following two specifications add controls for parents’ income rank (added separately) and their wealth ranks within their birth cohorts. Compared to column 1, the coefficients of interest remain largely intact in both panels when we control for parental characteristics.Footnote 25
Importantly, we also assess the degree of omitted variable bias by studying the stability of the estimates by comparing baseline estimates to fully controlled specifications with parental characteristics. The method of Altonji, Elder, and Taber (Reference Altonji, Elder and Taber2005) allows us to evaluate how large selection on unobservables would have to be relative to the selection on observables in order to entirely explain away our result by an unobservable selection effect. For example, let us compare the baseline estimates in column 1 of Table 2 to the ones in column 4 when controlling for all of the parental characteristics.Footnote 26 In the risky asset participation and risky share regressions, Altonji ratios are 5.1 and 11.6, respectively. This suggests that selection on unobservables would have to be much stronger than selection on observables for our main result to be explained away by unobservable selection.
Given that these ratios are well above the rule of thumb of one (Altonji et al. (Reference Altonji, Elder and Taber2005)), our results are very unlikely to be biased by selection on omitted unobservables.Footnote 27
Overall, the findings presented in both panels of Table 2 suggest that it is unlikely that parental selection is driving our baseline results.
Moreover, in Supplementary Material Table A.3, we control for the corresponding financial behavior of parents in 1999 in addition to the other parental controls we have in column 4 of Table 2. Accounting for parental financial behavior addresses concerns about whether parents may transmit not only their culture but also their financial literacy, experiences, and attitudes in financial matters.
For example, in column 1 of Supplementary Material Table A.3, we control for the risky asset market participation of parents, and, in column 2, we control for their conditional risky asset share. Since parental financial behavior itself is a function of their culture and is also affected by their wealth and income, including it in the regressions is a clear case of having “bad controls” and we do not keep it in our regressions for the rest of the analysis. Nonetheless, it is noteworthy that including parental financial behavior does not have any significant effect on our findings. This could, of course, be the case partly because some of the effect of culture is already captured by parental income and wealth. But, importantly, this rules out the possibility that what we pick up in our analysis is the effect of bequest or inter-vivo transfers from parents to children, and also indicates that the effect of culture goes beyond children simply imitating parents’ financial behavior.Footnote 28
2. Role of Other Child Outcomes as Mediating Variables
We have so far documented that the cultural legacy of the country of origin is related to, and could have a direct influence on, second-generation migrants’ financial behavior even after controlling for some of the most consequential parental characteristics. One other possibility is that the investment behavior of children is simply an indirect reflection of their other outcomes and is not directly affected by their cultural heritage. From the previous literature, we know that cognitive ability, education, income, and wealth are directly related to investment behavior. If cultural heritage affects these outcomes (on top of the parental characteristics that we analyzed before), one might argue that the coefficient estimates for cultural heritage could reflect indirect effects via these other individual features and not a direct cultural effect on investment behavior.
To formally assess this possible scenario, we discuss potential mediating factors that could affect investment behavior directly and also be affected by culturally transmitted preferences, and investigate whether adding those controls sequentially changes the estimates we have found so far in Table 2. We acknowledge that since these variables, by construction, are potentially influenced by culturally transmitted risk-taking, they could be described as “bad controls” in the terminology of Angrist and Pischke (Reference Angrist and Pischke2009), as the ceteris paribus assumption could be violated. Note, though, that this is a standard mediation analysis, as our goal is to see how the risk-taking coefficient changes when we control for these variables. If adding a particular control changes the estimated coefficients considerably, it suggests that the effects on financial market behavior might be mediated by the effects of cultural traits on the variable included.
Columns 5–8 in both panels of Table 2 show the results for risky participation and conditional risky shares, respectively. In column 5, we add controls for children’s education, since the literature suggests that education could affect financial market behavior (Black et al. (Reference Black, Devereux, Lundborg and Majlesi2017), Cole, Paulson, and Shastry (Reference Cole, Paulson and Shastry2014), and Cooper and Zhu (Reference Cooper and Zhu2016)). However, our coefficients of interest in both panels barely change and they are not statistically different from those in column 4. Therefore, the effect of our cultural preference variable on participation in risky markets and conditional risky share does not seem to be mediated through education.Footnote 29
Higher earnings could affect financial behavior by acting as a higher stable return to human capital that can partially substitute for bond holding and increase risk-taking. In column 6 of Table 2, we add earnings rank (constructed within cohorts) as a control. This has very little to no effect on the estimates.
Also, the literature suggests that wealth affects the extent of risk-taking (Calvet and Sodini (Reference Calvet and Sodini2014)), as it helps overcome the fixed cost of participation and reduce relative risk aversion. In column 7 of Table 2, we add the financial wealth rank. This reduces the coefficient estimates in both panels and makes the effect of cultural risk-taking on participation statistically insignificant.Footnote 30
Given that risky share is a more direct measure of risk-taking in financial markets, this suggests that individuals descending from more risk-taking cultures are generally wealthier (influencing participation barriers), but the effect of cultural risk-taking still persists beyond the wealth effect. Controlling for all three variables at the same time in column 8 produces estimates very similar to controlling for wealth.
Therefore, a large portion of the associations found before remain intact to conditioning on individual characteristics, suggesting that these child outcomes are not large enough mediators (except in the case of market participation), and the direct effect of ancestral risk-taking on financial behavior remains important.
Before we move on, we exploit an additional source of information on a subsample of individuals, which allows us to carry out an exercise to investigate the role of cognitive ability by controlling for IQ test scores. We have access to IQ test scores from the military enlistment data that takes place at the age of 18 or 19 for enlisted men. We do not have this test score for all men in our sample of analysis, since it became less and less common over time for men to enlist in military service. The IQ test consists of four different parts, graded separately and transformed into a general measure of cognitive ability with values ranging from 1 to 9. The findings in columns 1 and 2 of Supplementary Material Table A.4 paint a very similar picture to those found in Table 2 and the results are not driven by cognitive ability.
3. Further Robustness to Alternative Country of Origin Characteristics
A possible scenario is that countries with higher measures of cultural risk-taking might be different in other ways that affect the investment behavior of children of immigrants from those countries. One should note that, for this to be a threat to our identification, these potential effects should be in addition to their impact on the socioeconomic characteristics of the first-generation immigrants themselves, which we account for.
To investigate this, in Table 3, in addition to baseline controls and parental controls (as in column 4 of Table 2), we add further controls to proxy for many aspects of heterogeneity across countries from which first generation migrants descend. In column 1, we add continent fixed effects, allowing us to use within continent variation. This has no discernible effect on either participation (Panel A) or conditional risky share (Panel B). These suggest that a few country clusters do not drive the results.Footnote 31
Table 3 Risky Asset Participation, Conditional Risky Asset Share, and Cultural Risk Preferences
$ \mid $
Robustness to Other Cross-Country Controls
Next, we control for GDP per capita and life expectancy of the source countries in columns 2 and 3. Data on GDP per capita are from the Penn World Tables, measured in 1995, and data on Life Expectancy are from the World Bank, WDI, measured in 2016. Estimates of the coefficients of interest in the following 2 columns are very similar to the previous estimates. GDP per capita and life expectancy coefficient estimates are both economically and statistically insignificant. This suggests that the level of development of the source countries is unlikely to drive our findings and it is not confounding the cultural variable of interest.
Alternatively, one could argue that the selection of immigrants from countries with differential levels of development is not what we are picking up in our regressions, but, rather, economic preferences could correlate with social preferences affecting financial behavior. This is not an argument against the role of culturally transmissible traits in general, but the coefficient estimates on our variable of interest could be biased. More specifically, Guiso et al. (Reference Guiso, Sapienza and Zingales2004), (Reference Guiso, Sapienza and Zingales2008) suggest that trust (or social capital in general) is a cultural factor shaping financial behavior. To address this, in column 4, we account for the trust measure from the GPS, which could potentially affect our outcomes independently. Results suggest that controlling for trust has no effect on the coefficients of interest.
Lastly, one may be concerned about institutional characteristics of the origin countries confounding the influence of culture. It is worth noting that institutions are arguably endogenous to culture, and therefore, controlling for their quality would make for adding bad controls. Nevertheless, in column 5, we control for the rule of law as a measure of institutional quality in the origin country, extracted from the Worldwide Governance Indicators (Kaufmann, Kraay, and Mastruzzi (Reference Kaufmann, Kraay and Mastruzzi2010)).Footnote 32 While the estimate for market participation becomes statistically insignificant, the estimate of the effect of risk-taking culture on risky shares remains meaningful and statistically significant, indicating that culture plays a distinct role not explained by institutional differences. In column 6, we control for all the characteristics of countries of origin discussed before. The estimates are very close to the ones in column 5, and even stronger in the risky asset share regression of Panel B.
B. Compositional Effects
So far, we have documented that those from more risk-loving cultures are more likely to participate in risky asset markets and, conditional on that, designate a larger share of their financial wealth to equities. While participation is not necessarily attributed to risk-taking preferences, as in classical models everyone is expected to participate and nonparticipation is usually attributed to an inability to overcome fixed costs, it is predicted that a more risk-loving individual chooses a higher risky share.
However, our findings do not indicate whether more risk-taking in financial markets induced by cultural background is manifested in a mean–variance efficient portfolio with the best possible Sharpe ratio, as predicted in the canonical model of investment behavior, or a portfolio with high idiosyncratic risk and high volatility, where the expected return might be low. In other words, it is not clear if there are compositional effects whereby cultural background induces taking on more idiosyncratic risk or if it is just about a larger mean–variance efficient portfolio.
Compared to investments in mutual funds, direct investments in stocks typically exhibit greater volatility with potentially more extreme returns, characteristics particularly appealing to investors with an appetite for idiosyncratic risk. Previous research suggests that individuals who invest in stocks rather than mutual funds often perceive trading as a form of gambling and may substitute between the two activities (Barsky et al. (Reference Barsky, Juster, Kimball and Shapiro1997)). Additionally, survey respondents frequently equate stock investing with gambling, buying lottery tickets, or visiting a casino (Chopra and Haaland (Reference Chopra and Haaland2023), Henkel and Zimpelmann (Reference Henkel and Zimpelmann2023)).Footnote 33
Dorn et al. (Reference Dorn, Dorn and Sengmueller2015) show that fluctuations in lottery prizes in Germany influence trading behavior in individual stocks and options, whereas mutual fund trading does not provide the same gambling experience for such gambling-motivated investors. Similarly, Gao and Lin (Reference Gao and Lin2015) find that larger lottery jackpots in Taiwan lead to a decline in trading volume for stocks favored by individual investors. Further supporting this connection, Kumar (Reference Kumar2009) finds that individual investors are drawn to stocks with lottery-like characteristics, such as low prices, high idiosyncratic volatility, and high idiosyncratic skewness.
In Table 4, we investigate how culturally inherited risk preferences affect the composition of risky portfolios. The sample is restricted to risky asset market participants. Specifically, we try to understand if those from more risk-loving cultures take on more idiosyncratic risk by investing (relatively) more in directly held stocks as opposed to investing in mutual funds and if they form risky portfolios with higher volatility.
Table 4 Stock Participation, Stock Share, Portfolio Volatility Proxy, and Cultural Risk Preferences
The outcome of interest in Panel A of Table 4 is an indicator of whether participants directly own stocks. The baseline estimate in column 1 indicates that, conditional on participation, those from more risk-loving cultures are more likely to directly hold stocks. A 1-standard-deviation increase in ancestral risk-taking preferences leads to a 6.1 percentage point increase in the likelihood of owning stocks (compared to a mean of 45%). An alternative way to get a sense of the quantitative significance of the effect is to compare individuals from countries in the top and bottom quartiles of risk-taking. For example, if a market participant with a Portuguese heritage (−0.79) had the risk-taking preferences of someone with an Algerian heritage (0.39), her probability of stock-market participation would go up by 25 percentage points.
As in Table 2, columns 2–4 of Table 4 control for parental characteristics. None of these has any discernible effect on the coefficient estimate. Comparing columns 1 and 4 reveals an Altonji ratio of 13.1, which rules out selection on unobservables to a great extent.Footnote 34
Again, as previously, in columns 5–8, we add individual characteristics. The coefficient estimate survives even controlling for these, suggesting that the effect of cultural heritage might work beyond the mediating effect of other personal outcomes.
These findings suggest that culturally transmitted risk-taking preferences have a compositional effect on individuals’ portfolios by inducing people to hold stocks directly and take more idiosyncratic risk.
In Panel B of Table 4, we investigate the intensive margin by exploring whether those who descend from more risk-loving cultures would also invest (relatively) more in directly held stocks than mutual funds, which presumably would also lead to the formation of less diversified portfolios. The outcome is the share of directly held stocks when the denominator is the total value of funds and stocks. Estimates suggest that those from more risk-loving cultures assign a larger share of their portfolio to directly held stocks. A 1-standard-deviation increase in ancestral risk-taking preferences leads to a 4.8 percentage point increase in the share of stocks among risky assets (compared to a mean of 29%). Also, comparing the baseline coefficient in column 1 with that in column 4 reveals that taking into account parental characteristics barely changes anything, with a high Altonji ratio of 26.5.Footnote 35
Instead, the rest of the table suggests that individual characteristics are not strong enough mediating factors to make a difference in the direct effect of cultural risk preferences (columns 5–8).
While these exercises provide suggestive evidence, they do not, on their own, establish that individuals with a more risk-tolerant cultural background take on greater idiosyncratic risk. To strengthen our evidence, we attempt to approximate individuals’ portfolio volatility. Because we do not have information on the exact portfolio of assets held by individuals, we create a portfolio volatility proxy using the methodology detailed in Appendix 2.12 of Calvet et al. (Reference Calvet, Campbell and Sodini2007) and explained in Section II. The results are presented in Panel C of Table 4. The findings in column 1 indicate that a standard deviation increase in cultural risk-taking raises portfolio volatility by almost 7% of a standard deviation. Adding parental background characteristics in columns 2–4 and individual characteristics in columns 5–8 does not have any recognizable effect.
Importantly, in additional exercises in Supplementary Material Tables A.3 and A.4, we observe that the findings in all 3 panels of Table 4 are robust to taking into account parental investment behavior and individual cognitive ability. This rules out the possibility that the influence of cultural risk preferences on portfolio composition is driven by parental influence (e.g., due to differential parental financial sophistication) or individuals’ ability (e.g., better understanding of financial markets).
Finally, we further check the sensitivity of our findings in Table 4 to previously mentioned country-level controls. Table 5 shows that the results are robust and that the previous conclusions carry over.
Table 5 Stock Participation, Stock Share, Portfolio Volatility Proxy, and Cultural Risk Preferences
$ \mid $
Robustness to Other Cross-Country Controls
Overall, the findings suggest a large effect of cultural heritage on portfolio composition by increasing the level of idiosyncratic risk, which indicates a departure from mean–variance efficiency for those born into more risk-loving cultures. While this may suggest that the cultural component of risk-taking, at least as measured by GPS, induces both greater aggregate and idiosyncratic risk, it is also consistent with the possibility that individuals from more risk-loving cultural backgrounds are less sophisticated investors. However, the latter possibility is very unlikely since one would expect investor sophistication to be highly correlated with individual and parental characteristics, and we have shown that the effects survive not only controlling for (arguably) influential parental background, but also individual characteristics (such as cognitive ability).
All estimates shown in Tables 4 and 5 are economically meaningful and statistically significant, indicating that the largest effects of cultural heritage seem to be on portfolio composition and taking idiosyncratic risk. With this in mind, in the rest of the article, we focus our attention on portfolio composition and the mechanisms through which culture influences portfolio composition.Footnote 36
V. Mechanisms of Cultural Persistence
In Sections III and IV, we have argued that risk preferences extracted from countries of the parents of second-generation immigrants capture the effect of cultural heritage, and we have tried to rule out potential competing narratives. Here, we provide additional evidence in support of our hypothesis by generating predictions that are compatible with the role of culture and by testing those predictions in our setup.
A. Ancestral Risk-Taking Culture Proxied by Ethnographic Chance Games in Parental Birth Country
Part of the literature that studies the impact of cultural values on economic outcomes has focused on cultural variables that are measured before modernization and industrialization and that predate economic outcomes by a very long time (Alesina et al. (Reference Alesina, Giuliano and Nunn2013), Giuliano and Nunn (Reference Giuliano and Nunn2013), Michalopoulos (Reference Michalopoulos2012), and Nunn and Wantchekon (Reference Nunn and Wantchekon2011)). The advantages of using cultural variables measured very far back in time are twofold. First, it rules out reverse causality (e.g., gender norms today cannot have caused plough usage centuries ago (Alesina et al. (Reference Alesina, Giuliano and Nunn2013))). Second, it provides an intuitive understanding of where the differing cultural norms come from, as these measures capture characteristics of ancestral tribes or communities before any modernization and industrialization took place.
In our setup, with the spatial separation that our identification strategy relies on, reverse causality is already ruled out; there is no plausible mechanism by which cross-sectional variance in financial decision-making in Sweden has a material impact on measured average risk preferences across countries. Furthermore, as we are mainly concerned with the impact of cultural values on financial decision-making, and not how those cultural values are formed, we prefer using a direct measure of risk preferences as our baseline. Nevertheless, using a “deeper” measure of cultural risk-taking provides an intuitive justification for where these differences may come from. Also, this addresses the unlikely concern that our main cultural preferences, obtained from the GPS, might have been formed (even partly) by contemporaneous institutional and economic policies that could have also affected parents of immigrants in ways not reflected in their wealth, income, and education.Footnote 37
We draw on the Ethnographic Atlas from Murdock (Reference Murdock1965) which allows us to approximate ancestral risk-taking culture.Footnote 38 It further buttresses the interpretation of the GPS measure of risk-taking as capturing deeper cultural differences with an actual bearing on economic decisions, as opposed to solely reflecting some economic or institutional differences across countries that induce differences in survey respondents’ lottery certainty-equivalence.
The Ethnographic Atlas includes information gathered by ethnographers reflecting various cultural and socio-economic characteristics of pre-modern societies before industrialization and European contact.Footnote 39 The Atlas provides us with information on what types of games a given society had in their cultures. It classifies societies’ games when any combination of the following three elements were present: i) chance, ii) physical skills, and iii) strategy.Footnote 40 We proxy the ancestral culture of risk taking in the parents’ country of origin with the share of people whose ancestors played chance games.Footnote 41
In Panel A of Table 6, we present our findings on the effects of the long-term ancestral cultural measure of risk-taking described above on portfolio composition. Namely, we investigate to what extent children from cultures in which their ancestors’ games were more heavily based on chance, rather than strategy or physical activities, are more likely to take more idiosyncratic risks in their portfolio, keeping the institutional setting constant.
Table 6 Mechanisms of Cultural Persistence
Consistent with the baseline findings, in columns 1 to 3 we find that, conditional on equity market participation, children with an ancestral culture of risk taking are more likely to participate in the stock market, have a greater share of their financial wealth directly in stocks, and form portfolios with higher volatility.
This analysis reassures that cultural traits, defined in this analysis based on those passed down from centuries ago, influence individuals’ financial behavior today and the effect is similar to traits drawn from contemporary societies.
B. Cultural Persistence
The next analysis is based on the idea that cultural transmission is stronger for individuals whose parents come from countries in which maintaining cultural norms has been more beneficial across generations. Giuliano and Nunn (Reference Giuliano and Nunn2021) study cultural persistence and change and argue that the similarity of the environment across generations matters for cultural transmission. When the environment is more stable across generations, traits that have evolved up to the previous generation are more likely to be beneficial for the current one, and hence, the more beneficial it is to maintain existing customs. They empirically show that populations whose ancestors lived in environments with more cross-generational instability exhibit less cultural persistence.
Based on this, we expect the relations we find between culturally transmitted preferences and financial behavior to be weaker for those from more unstable places, as cultural persistence is weaker. We test this idea by interacting two measures of risk-taking culture—i) ancestral risk-taking based on the ethnographic data and ii) modern risk-taking from the GPS—with an exogenous measure of cross-generational climatic variability of the environment built by Giuliano and Nunn (Reference Giuliano and Nunn2021). Giuliano and Nunn (Reference Giuliano and Nunn2021) calculate cross-generational climatic instability of the ancestors of individuals living in each country today by measuring the average temperature variation over 70 generations (20 years to a generation) from years 500 to 1900 using sources of paleoclimatic data.Footnote 42
Panel B of Table 6 depicts a general pattern for individuals whose ancestors come from more unstable countries. The effects of culturally transmitted preferences on financial decision-making are mitigated. In the first 3 columns, we use the ancestral culture of risk-taking extracted from the Ethnographic Atlas and, in columns 4–6, we use the measure of cultural risk-taking from the GPS. The estimates on the interaction terms are more precise in the case of ancestral risk-taking. This is expected as the measure of environmental instability is built for the ancestors of current generations.
Overall, the results are consistent with the idea that our variables of interest indeed capture the cultural transmission of economic preferences. For instance, if we look at the share of directly held stocks as the outcome of analysis in column 5, the net effect of risk-taking for those from highly unstable countries (90th percentile = 0.41) is low at 3.7 percentage points. Whereas, the net effect of risk-taking for those from highly stable countries (10th percentile of instability measure = 0.12) is quite substantial at 21.4 percentage points (compared to the mean share of 29%). This reiterates the importance of cultural persistence in the transmission of cultural traits.
C. The Role of Socialization
Bisin and Verdier (Reference Bisin and Verdier2000) argue that socialization is one of the main channels of cultural transmission. In this section, we explore additional channels of cultural transmission via socialization, namely, vertical and horizontal transmission.
Dohmen et al. (Reference Dohmen, Falk, Huffman and Sunde2012) find that the correlation between parents’ and children’s cultural attitudes is stronger when parents are from similar cultures (i.e., the vertical transmission of culture is stronger). To test this idea, we create a Same Country indicator—a binary variable equal to 1 if both parents originate from the same country—and interact it with our risk-taking measure. If cultural transmission is stronger when parents are from the same country, the relationship between risk preferences and investment behavior should be accentuated. The results in Panel C of Table 6 are consistent with this idea—the association between risk-taking and outcome variables are much stronger for those with both parents from the same country. For instance, column 4 indicates that the positive effect of risk-taking culture on the likelihood of participating in the stock market is 14.3 percentage points higher for those with both parents from the same country.
At the same time, parents’ cultural transmission might be weaker or stronger depending on the region they live (Dohmen et al. (Reference Dohmen, Falk, Huffman and Sunde2012)). For example, peers at school or neighbors in the same community may also play a role in cultural transmission (horizontal transmission). Therefore, to capture the horizontal transmission of culture, we also look at the shares of people from the same region as parents who live within the same municipality as the individuals and interact this with the risk-taking variable.Footnote 43 If cultural transmission is stronger when individuals have more opportunities to interact with others from a similar cultural background, then, the relationship between risk preferences and investment behavior should be even more pronounced. The evidence in Panel D of Table 6 aligns with this idea. For example, if we increase the share of people in a municipality with a similar culture from 0 to 10 percent, the positive effect of risk-taking on the share of stocks more than doubles and goes from 3.1 to 8.5 percentage points (see column 5).
In sum, this section provides evidence on the role of socialization in cultural transmission and both vertical and horizontal transmissions of culture seem to matter.
VI. Supplementary Robustness Checks
A. Excluding Finnish Parents
As mentioned in Section II, since we need our sample of analysis to be adults when we observe them in the wealth register and we do not have financial outcomes after 2006, parents of the individuals in our sample must have migrated to Sweden far back in time for their children to have been born in Sweden early enough to be in our sample. Also, we require parents to be in the data set in 1999 (the earliest year of the wealth register), so that we have information on their wealth and financial behavior.
Historically, Finland was part of the Swedish Kingdom and has maintained a significant Swedish-speaking population, leading to substantial migration and exchange between the two countries. Consequently, because migration of non-Nordics to Sweden was not a widespread phenomenon before the 1990s, parents from Finland are over-represented in our sample. While it is clear from Supplementary Material Table A.1 and Figure 1 that variation in risk preferences across European countries is almost as large as variation in the whole sample, we formally investigate how our findings change if we limit our sample to second-generation immigrants whose parents come from outside Finland. Coefficient estimates in Supplementary Material Table A.6 are very similar to our baseline findings, indicating that the large set of immigrants from Finland are not driving our results.
B. Outcome Data from an Earlier Year
For our outcome variables so far, we have used data from the year 2006. As discussed before in Section II, there are two main reasons for that. One is that we want our sample of second-generation immigrants to be as old as possible when we observe them and make decisions about financial market behavior during their adult lives. The second is that, between 1999 and 2005, banks were not required to report small bank accounts to the Swedish Tax Agency unless the account accrued more than 100 SEK (about 11 USD) in interest during the year. For 2006, banks were required to report all bank accounts above 10,000 SEK and, as a result, we have more complete information on financial wealth when we study risky share and stock share in our analysis. Nevertheless, in Supplementary Material Table A.7, we present the findings when we instead use data from the year 2000. Note that, because we have more people with reported financial wealth of zero, our sample of analysis is smaller. However, we get very similar results to our baseline, indicating that our analysis is not sensitive to the sample year.
VII. Conclusion
This article investigates the cultural origins of risk-taking in financial markets. More specifically, by combining Swedish wealth registry data on second-generation immigrants with risk preferences in their parents’ countries of origin, we examine the influence of culturally transmitted risk preferences on individual investments in the equity market and portfolio composition. Children of immigrants from more risk-loving cultures are more likely to participate in equity markets. Moreover, conditional on participation, they allocate a larger share of their financial wealth to risky assets, are more likely to hold stocks directly, invest a higher proportion of their risky assets in stocks, and hold more volatile portfolios.
We show that our results are not driven by the selection of migrating parents and culturally transmitted preferences have an independent and direct effect on individuals’ financial decisions beyond their potential impact on parental and individual socio-economic characteristics.
Beyond advancing our understanding of the vast cross-country differences in investment behavior, our findings have important implications for understanding under-diversification and the lack of delegation among investors. We also emphasize the role of culture, and its intergenerational nature, as an explanation for how risk preferences are formed at the individual level and as a mechanism through which parents influence their children’s economic behavior and outcomes: cultural attitudes toward risk, (partially) shaped by transmission from parents, have economically and statistically significant effects on investment behavior.
This article remains silent about the possibility that some cultural traits might be associated with better expected returns on investment. For instance, more risk averse individuals might have a more diversified portfolio that could generate higher returns over the longer run. However, so far, we do not observe individual assets and their prices in our data and cannot judge whether individuals from more risk-loving cultures are more or less successful in their investment decisions. Thus, whether certain cultural characteristics are more conducive to financial success is a question left for future research.
Supplementary Material
To view supplementary material for this article, please visit http://doi.org/10.1017/S0022109025102263.
Funding statement
We acknowledge funding from the Swedish House of Finance.
Open access
