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Securities regulation, household equity ownership, and trust in the stock market

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Abstract

Using aggregate data from national accounts, we study whether strengthening and harmonizing securities regulation across the European Union increases household equity ownership. We find a significant increase in the proportion of liquid assets invested in equity, both when a household’s own country adopts the regulation and when other countries adopt the regulation. To directly explore the mechanism through which households’ willingness to directly invest in the equity market increases, we show that the effect of securities regulation is stronger in countries where trust is low and between countries where cultural biases are most pronounced.

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Notes

  1. Along with EU member countries, we also include Iceland, Liechtenstein, and Norway in our sample, countries which are not in the European Union but belong to the EEA. We include these countries because they have agreed to adopt the EU capital market directives, among other things, in exchange for access to the single market. For simplicity, we refer to all countries in our sample as EU countries.

  2. Giannetti and Koskinen (2010) separate investor protection into its public and private enforcement components and find that the association between investor protection and stock-market participation is primarily driven by investors’ ability to privately enforce their own rights (i.e., through the court system). Our results suggest that public oversight is an important determinant of household equity ownership.

  3. PROSP pertains primarily to the preparation of prospectuses for public securities offerings by issuers and only applies to primary market trading—a relatively limited subset of total trading in the stock market. TPD focuses on enhancing corporate disclosures by establishing new requirements and strengthening the enforcement of existing requirements for periodic financial reports. While these directives likely enhance the credibility of corporate disclosures, they focus on improving transparency and are not directly aimed at enhancing retail investor confidence. Nevertheless, we control for the adoption of both PROSP and TPD in our empirical analyses.

  4. We only disclose the country-specific MiFID adoption years because we obtained the country-specific MiFID adoption dates from Jean-Marie Meier with the agreement that we would not disclose the exact dates in the paper. These dates will be publicly available upon the publication of Meier (2019).

  5. Another observable aspect of the directives is their subsequent enforcement. There is evidence that both MAD and MiFID were actively enforced (e.g., Christensen et al. 2016 document that nine out of the 22 sample countries in our main analysis had taken at least one enforcement action under MAD by the end of 2009). However, at a conceptual level, it not clear that households should delay their reaction to new regulation until an enforcement action is taken, particularly if they trust that the government will implement and enforce the laws on the books. (We examine the role of trust in the government in Table 5 Panel C.)

  6. Studies have also used brokerage account data (e.g., Scularbaum et al. 1978; Barber and Odean 2000) or government tax records (e.g., Blume and Friend 1975, 1978; Kopczuk and Saez 2004). Internationally, research has obtained data from government-centralized share registers available in some countries (Grinblatt and Keloharju 2000, 2001; Calvet et al. 2007). While these data sources are highly accurate, they do not sample from the entire population, do not cover all relevant financial assets, or are only available in a few countries. These limitations prevent us from using these data in this study.

  7. ESA2010 replaced the former reporting framework, ESA95, in September 2014. As of the time of our study, not all European countries have transitioned to the ESA2010 reporting standards. However, because the impact of the change in standards on the financial accounts of interest in our study is minimal, we use ESA95 data for countries where the full ESA2010 data is not available. Furthermore, we are unaware of any aspects of MAD, MiFID, or other Lamfalussy Directives that would have affected the calculation of the values of the financial instruments used in our study.

  8. We separately examine changes in equity ownership within investment funds in Section IA2 of the internet appendix.

  9. Austria, Bulgaria, Cyprus, Iceland, Ireland, Liechtenstein, Netherlands, and Romania have missing or incomplete national accounts data. Croatia joined the European Union in the final year of our sample period (in July 2013). Of the 22 countries in our main sample, eight joined the Union over our sample period. In untabulated analysis, we confirm that our inferences are consistent if we exclude these countries.

  10. In the internet appendix (Section IA4), we provide evidence that the levels of household equity ownership and stock-market participation, although conceptually different, are positively correlated (Pearson correlation of 0.63). However, the correlation in levels does not necessarily imply a similar correlation in changes, which is the focus of our study.

  11. An important assumption is that the control group is not also affected by the treatment (i.e., the stable unit treatment value assumption, “SUTVA”). This assumption is unlikely to hold in our settingbecause we expect that foreign households are also affected by the adoption of the directives in other countries (e.g., through a reduction in home bias). This effect biases against finding an impact of the directives. We assess the magnitude of this bias in Table 4 by explicitly controlling for the effect of domestic adoption on foreign households.

  12. In Section IA5 of the internet appendix, we report results controlling for liquidity. While our sample size is slightly smaller for this analysis because some countries lack liquidity data, controlling for liquidity has little effect on the estimated treatment effect of the directives.

  13. In additional (untabulated) analyses, we find no evidence of significant (positive) abnormal returns in either a short-window (i.e., three days) around the directives’ entry-into-force dates or over the quarters subsequent to the entry-into-force dates, which mitigates the concern that the increase in household equity ownership we document is driven by an increase in the value of households’ existing equity portfolios.

  14. Household Equity Returns are calculated using a household-portfolio specific measure from the national accounts. Because the exact timing of portfolio changes is unknown, this adjustment is measured with some error. Thus we replace extreme (more than three standard deviations from the mean) or missing values of Household Equity Return with country-specific stock-market returns. As an alternative to including Household Equity Returns as a control variable, in Internet Appendix Section IA6, we report results where we directly adjust Equity Ownership for changes in equity values using the national-accounts-based adjustment factor. Results are very similar in this alternative specification. Results are also very similar if we use changes in a country’s stock-market index to control for share-price appreciation (untabulated).

  15. The household finance literature finds that the following factors significantly affect household stock-market participation: wealth, momentum, tax rates, education, financial sophistication, and marital status (Cohn et al. 1975; Campbell 2006; Barber and Odean 2013). We directly control for proxies for wealth, momentum, and tax rates. We do not include controls for education, financial sophistication, and marital status, which are likely slow-moving and therefore are unlikely to be correlated with entry-into-force dates. Additionally, they would (in part) be captured by including country fixed effects.

  16. In a sensitivity test, to address voluntary IFRS adoption as a potential correlated omitted variable, we exclude Germany, where voluntary IFRS adoption was common prior to mandatory adoption. Results are slightly stronger when Germany is excluded from the sample.

  17. We do not cluster standard errors by country, because, given that there are only 22 countries in our sample, this approach is likely to overstate or bias the standard errors. Specifically, there are only 22 countries included in the analysis, and clustering by country-year could understate the standard errors. Therefore, to assess the reasonableness of clustering by country-year, we also calculate standard errors using a Monte Carlo approach where we randomly select adoption dates for each country and assess significance by calculating the fraction of counterfactual treatment effects that exceed our actual estimated treatment effect. Using this method, the statistical significance of our results is higher than reported in the paper (untabulated).

  18. This estimate is based on an average participation rate of 0.15 for our sample countries from the 2005 Eurobarometer Survey.

  19. This finding is consistent with the results of Christensen et al. (2016), who, for one test, rely on variation in MiFID adoption dates and find that MiFID has a positive but insignificant effect on stock-market liquidity. Alternatively, Cumming et al. (2011) find a significant effect of MiFID on liquidity, using a control sample of firms from non-MiFID adopting countries (rather than using variation in the adoption dates among MiFID adopting countries).

  20. Calculated by multiplying the maximum MAD Foreign for Latvia (United Kingdom) of 8.28 (0.13) with the coefficient on MAD Foreign of 0.006.

  21. While there is some overlap between the Low Trust and High Trust Differential countries, the set is not the same. In Finland, Luxembourg, and Sweden, High Trust = 1 and High Trust Differential = 0. In Hungary, Italy, and Poland, High Trust = 0 and High Trust Differential = 1.

  22. The mutual fund data do have two important disadvantages that make it unsuitable for our primary analyses of household equity ownership. First, changes in mutual fund holdings are unlikely to be driven solely by the preferences of households (e.g., because other sectors, besides households, invest in mutual funds and mutual fund managers have some discretion over the allocation of invested funds). Second, we cannot measure households’ other liquid assets and cannot assess the proportion of their total liquid assets that households invest in the stock market (i.e., the focus of our main analysis).

  23. Croatia, Romania, and Lichtenstein are excluded from the analysis because of missing MAD or MiFID dates.

  24. Guiso et al. (2009) also consider several other proxies for bilateral trust, including genetic and somatic similarity and the extent of historical military conflict between countries. However, these proxies are not available for several EU countries, so we do not consider them in our analysis.

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Appendices

Appendix 1: Public Awareness of the Directives

In this appendix, we discuss the results of two additional analyses designed to assess the likelihood  that households are aware of the implementation of MAD and MiFID.

In Table 7, we report results from a Factiva search for the number of media (electronic and print) articles discussing MAD and MiFID. Specifically, we search for the terms “Market Abuse Directive” and “MiFID” in English one year prior (subsequent) to the earliest (latest) member-state implementation date for each directive and report both the total number of articles and the number of articles from the 20 most widely circulated newspapers in the European Union mentioning these terms. This analysis indicates that the directives were covered extensively by the European financial press and suggests that (at least) some households were likely aware of their implementation. MAD was mentioned over 1200 times across all news sources covered by Factiva (and in nearly 100 articles in the top 20 European newspapers by circulation). MiFID was mentioned over 15,000 times across all news sources (and in 1600 articles in the top 20 European newspapers).

An important caveat is that this approach likely understates the extent of media coverage because newspapers can report on the provisions of the directives without specifically mentioning the “Market Abuse Directive” or “MiFID” and because articles might mention only the non-English names of the directives. These issues are particularly pronounced for MAD, where, for obvious reasons, we cannot search using the directive’s acronym.

In Fig. 3, we report the results from a Google Trends plot of the relative search frequency for the terms “Market Abuse Directive” and “MiFID.” Also consistent with a broad awareness of the directives and the timing of their implementation, there is a visible spike in Google searches for the directives around their respective implementation dates.

Table 7 Media Coverage of MiFID and MAD around the Entry-into-Force Dates
Fig. 3
figure 3

MAD and MiFID Google Search Activity. Notes: This figure presents the global search interest for the terms “Market Abuse Directive” and “MiFID,” relative to the highest point on the chart over the period 2004–2010. A value of 100 is the peak popularity for the search term. Data are downloaded from the Google Trends website

Appendix 2: Variable Definitions

Equity Ownership

The ratio of the value of total household investment in listed shares (i.e., direct ownership in publicly traded equity) to the value of total household liquid assets for a particular country-quarter. Liquid assets include currency, transferable deposits, short-term debt securities, listed shares, and holdings in investment funds.

Listed Shares

Listed shares are equity securities listed on an exchange. An exchange may be a recognized stock exchange or any other secondary market. Listed shares are also referred to as quoted shares. The existence of quoted prices of shares listed on an exchange means that current market prices are usually readily available. (Definition ESA2010)

Investment fund shares or units

Investment fund shares are shares of an investment fund if the fund has a corporate structure. They are considered units if the fund is a trust. Investment funds are collective undertakings by which investors pool funds for investment in financial and/or non-financial assets. Investment funds are also called mutual funds, unit trusts, investment trusts, and undertakings for collective investments in transferable securities (UCITS); they may be open-ended, semi-open, or closed-end funds. (Definition ESA2010)

Currency

Currency is notes and coins that are issued or approved by monetary authorities. (ESA2010)

Transferable deposits

Transferable deposits are exchangeable for currency on demand, at par, and are directly usable for making payments by check, draft, giro order, direct debit/credit, or other direct payment facilities, without penalty or restriction. (ESA2010)

Short-term debt securities

Debt securities with an original maturity of one year or less and debt securities repayable on the demand of the creditor. (ESA2010)

Fund Equity Ownership

The ratio of the value of equity in equity-based investment funds to the total asset value of the investment fund for a particular country-quarter.

Ln(Investments/GDP)

The natural log of the ratio of aggregate mutual fund investment from investor country i (in billions of USD) in investee country j in quarter t scaled by the GDP (in billions of USD) of the investor country in quarter t. Mutual fund ownership data is from the Factset Ownership database.

MAD Domestic

An indicator variable that switches from zero to one for a country in the quarter of MAD adoption.

MAD Foreign

An index variable indicating, for each country-quarter, the number of foreign countries that have adopted MAD scaled by the adopting country’s relative market capitalization, divided by 100.

\( MAD\; Foreig{n}_{it}=\left(\sum \limits_{\begin{array}{l}j=1\\ {}i\ne j\end{array}}^{n=28}\left[ MAD\; Domesti{c}_{jt}\times \frac{\ln \left( Market\; Cap{.}_j\right)}{\ln \left( Market\; Cap{.}_i\right)}\right]\right)/100, \)

where i indexes household country, j indexes the MAD adopting country, and t indexes the year-quarter. We include all 31 EU countries, except Croatia, which did not join the EU until 2013 (after our sample period), and Liechtenstein, where CESR disputes proper MAD adoption and thus there is no clear adoption date.

MiFID Domestic

An indicator variable that switches from zero to one for a country in the quarter of MiFID adoption.

MiFID Foreign

An index variable indicating, for each country-quarter, the number of foreign countries that have adopted MiFID scaled by the adopting country’s relative market capitalization. Calculated analogously to MAD Foreign.

SecReg Domestic

The sum of MAD Domestic and MiFID Domestic.

SecReg Foreign

The sum of MAD Foreign and MiFID Foreign.

SecReg Investee Country

A variable that switches from zero to one beginning in the quarter in which MAD becomes effective in an investee country and from one to two beginning in the quarter in which MiFID also becomes effective.

GDP

The seasonal- and calendar-adjusted GDP based on chain linked volumes (2010), in millions of euro. Data are downloaded from Eurostat. Due to missing data, we use the unadjusted GDP (in millions of euro) based on chain linked volumes (2010) for Slovakia.

GDP Growth

The quarterly percentage change in GDP, defined as above.

Household Equity Return

The quarterly change in valuation of the households’ equity holdings in a country calculated as

\( Household\kern0.34em Equity\kern0.34em Retur{n}_{i,t}=\frac{revaluatio{n}_{i,t}}{\frac{1}{2}\left[ listed\kern0.34em share{s}_{i,t-1}+ revaluatio{n}_{i,t}+ listed\kern0.34em share{s}_{i,t}\right]} \)

where i indexes household country and t indexes the year-quarter. Revaluation is the value adjustment of the household equity holdings at the end of each quarter due to fluctuations in the individual stock prices. Listed shares are revalued at the end of the quarter to incorporate stock price fluctuations. Transactions of listed shares throughout the quarter are recorded at market price at the time of sale. Listed shares are the total value of a country’s household investment in listed shares at the end of the quarter. In the calculation above, the numerator is the revaluation amount for country i’s listed shares in period t. The denominator approximates the value of listed shares at the end of quarter t, before adjusting for market price fluctuations, and is calculated as the midpoint between the total amount of listed shares for country i in period t and the total amount of listed shares for country i in the previous period, t-1, adjusted for the revaluation for country i in the current period. Financial sector accounts data are downloaded from the ECB’s Statistical Data Warehouse. We replace missing and extreme values (more than three standard deviations from the mean) with Stock Market Returns, as defined below. In addition, we replace Household Equity Returns with Stock Market Returns for Slovakia, because the revaluation data has numerous zero values for that country.

Stock Market Return

The quarterly percentage change in a country’s stock-market index from the Global Financial Data database. The market indices used for each country are:

Austria

Austria Wiener Boersekammer Share Index (WBKI)

Belgium

Brussels All-Share Price Index (BSPTD)

Bulgaria

Bulgaria SE SOFIX Index (SOFIXD)

Cyprus

FTSE/Cyprus SE-20 (CYFTD)

Czech Republic

Prague SE PX Index (PXD)

Denmark

OMX Copenhagen All-Share Price Index (OMXCPID)

Estonia

OMX Tallin (OMXT)

Finland

OMX Helsinki All-Share Price Index (OMXHPID)

France

Paris CAC-40 Index (FCHID)

Germany

Germany DAX Price Index (GDAXIPD)

Greece

Athens SE General Index (ATGD)

Hungary

Vienna OETEB Hungary Traded Index (HTLD)

Iceland

OMX Iceland All-Share Price Index (OMXIPID)

Ireland

Ireland ISEQ Overall Price Index (ISEQD)

Italy

Banca Commerciale Italiane Index (BCIID)

Latvia

OMX Riga (OMXR)

Lithuania

OMX Vilnius (OMXV)

Luxembourg

Luxembourg SE LUXX Index (LUXXD)

Malta

Malta SE Index (MLTSED)

Netherlands

Netherlands All-Share Price Index (AAXD)

Norway

Oslo SE All-Share Index (OSEAXD)

Poland

Vienna OETEB Poland Traded Index (PTLD)

Portugal

Oporto PSI-20 Index (PSI20D)

Slovakia

Bratislava SE SAX Index (SAXD)

Slovenia

Slovenia SE SBITOP Blue Chip Index (SBITOPD)

Spain

Madrid SE IBEX-35 (IBEXD)

Sweden

OMX Stockholm All-Share Price Index (OMXSPID)

United Kingdom

UK FTSE All-Share Index (FTASD).

Momentum

The one-period lag of the Stock Market Return, defined as above.

Change in Unemployment

The quarterly percentage change in the seasonally adjusted unemployment rates (as a percentage of the active population), from the Eurostat Unemployment–EU Labor Force Survey (EU–LFS) adjusted series, including harmonized long-term unemployment.

Tax Rate

The net top statutory rate to be paid on dividend income at the shareholder level, taking into account all types of reliefs and gross-up provisions at the shareholder level. Data are collected from the OECD, except for Malta, Cyprus, and Bulgaria, which are not included in the OECD database. For Malta, Cyprus, and Bulgaria, we use the more general tax category of taxes on income, profits, capital gains levied on the actual or presumptive net income of individuals, profits of corporations and enterprises, and on capital gains (whether realized or not) on land, securities, and other assets. These data are downloaded from Eurostat.

Market Cap.

The market capitalization of each country in the year 2003 (prior to the first MAD entry-into-force date) in billions of US dollars, downloaded from the World Federation of Exchanges database.

Trust EVS

The percentage of households in a country that agreed with the statement “Most people can be trusted” from the European Values Survey conducted between 2008 and 2010 as per Guiso et al. (2008).

Trust Score

The average country response score of the European Values Survey (conducted between 2008 and 2010) on the question: “Do you think most people try to take advantage of you?” (10 point scale: 1 = people take advantage of me, 10 = most people try to be fair).

Trust Differential

The difference between the average country response score of the European Values Survey (conducted from 2008 to 2010) on the question: “Confidence: The Government?” (1 = A great deal, 2 = Quite a lot, 3 = Not very much, 4 = None at all) and the average country response score of the European Values Survey (conducted from 2008 to 2010) on the question: “Do you think most people try to take advantage of you?” (10 point scale: 1 = people take advantage of me, 10 = most people try to be fair), rescaled to a four-point scale (where a score of 1 translates to a new score of 4, a score of 2, 3, or 4 translates to a new score of 3, a score of 5, 6, or 7 translates to a new score of 2, and a score of 8, 9, or 10 translates to a new score of 1).

High Trust

An indicator variable based on a country’s Trust Score that equals one for countries with a Trust Score above the sample median and zero for countries below the sample median.

High Trust Differential

An indicator variable based on a country’s Trust Differential Score that equals one for countries with a Trust Differential Score above the sample median and zero for countries below the sample median.

Religious Similarity

A bilateral measure of the empirical probability that two randomly chosen individuals from two different countries will share the same religion, calculated (following Guiso et al. 2009) as the sum, across religion categories, of the fraction of respondents that report adherence to a particular religion in country A multiplied by the same fraction in country B. Survey data on religion are from the European Values Survey conducted between 2008 and 2010, which reports whether someone considers themselves religious and, if so, whether they identify as Buddhist, Hindu, Jewish, Muslim, Orthodox, Protestant, Roman Catholic, nonreligious, or Other. Other, Free Church/Nondenominational Church, and respondents who claimed to be religious but listed no denomination were counted as “Other.”

High Religious Similarity

An indicator variable based on a country-pair’s Religious Similarity that equals one for country-pairs with a Religious Similarity above the sample median and zero for country-pairs below the sample median.

Distance

The distance in 1000 km between the most populous cities for a given country pair. Distance data are from the Center for Prospective Studies and International Information (CEPII).

Close Proximity

An indicator variable based on a country-pair’s Distance that equals one for country-pairs above the sample median and zero for country-pairs below the sample median.

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Christensen, H.B., Maffett, M. & Vollon, L. Securities regulation, household equity ownership, and trust in the stock market. Rev Account Stud 24, 824–859 (2019). https://doi.org/10.1007/s11142-019-09499-8

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