Financial Literacy and Risky Asset Holdings: Evidence from China

Accounting & Finance 57 (2017) 1383–1415

Financial literacy and risky asset holdings: evidence from China

Li Liaoa, Jing Jian Xiaob, Weiqiang Zhanga, Congyi Zhoua

aPBC School of Finance, Tsinghua University, Beijing, China bDepartment of Human Development and Family Studies, Transition Center, University of Rhode Island, Kingston, RI, USA

Abstract

Although financial literacy is important for participating in financial markets, the level of financial literacy of Chinese consumers is low compared with those in developed countries. Using data from the 2014 China Survey of Consumer Finances, we examine the relation between financial literacy and the risky asset holding behaviour of Chinese households, in the context of an emerging financial market with a distinct institutional background. The findings reveal that consumers with higher levels of financial literacy are more likely to hold risky financial assets than those with lower levels. The potential impacts are derived mainly from advanced financial literacy.

Key words: Chinese households; Financial literacy; Risky asset holdings

JEL classiﬁcation: D12, D14, E21 doi: 10.1111/acﬁ.12329

1. Introduction

In contemporary China, the financial industry is playing an essential role in boosting economic growth. The Chinese stock market has risen to one of the largest stock markets in the world. The market capitalisation of the Shanghai Stock Exchange and the Shenzhen Stock Exchange reached US $6.27 trillion at the end of January 2015, ranking second only to that of the U.S.A. (World Federation of Exchange, 2015). Over the past decade, the growing complexity of financial products spurred by financial innovations

The authors acknowledge funding support from the National Natural Science Foundation of China (71232003 and 71573147) and China Postdoctoral Science Foundation (2016T90073, 2015M570066).

© 2018 AFAANZ 1384 L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 has transferred increasing financial risks to households and has imposed enormous pressures on consumers who are expected to absorb these risks. Risky financial assets, such as stocks, mutual funds, corporate bonds and commodity futures, as well as risk-free bank deposits, are available for household portfolio selection. The goal of portfolio allocation is to maximise the optimal level of growth in the wealth of a household. The classical portfolio theory implies that risky assets should be included in the household portfolio (Markowitz, 1952), yet research shows that many households do not establish their portfolio allocation in accordance with financial theory. Campbell (2006) observes that American households with less wealth prefer to allocate their assets to vehicles and cash rather than to risky assets such as stocks. Although households tend to hold stocks more than other risky assets when they accumulate wealth, many wealthy households nevertheless do not participate in the stock market. Previous studies have explored factors associated with risky asset holdings. An empirical study in Europe indicates several determinants of risky asset holdings, including labour income uncertainty and health risk (Atella et al., 2012). Moreover, Cardak and Wilkins (2009) find that financial awareness and knowledge play an important role in determining risky asset holdings among Australian households. It is worth noting that despite increasing access to financial markets, risky financial assets constitute a small percentage of Chinese households’ portfolios, possibly because of the lack of financial literacy. This study examines the potential effect of financial literacy on the risky asset holdings of Chinese households. In recent decades, financial literacy has attracted more attention regarding its great economic significance. Lusardi and Mitchell (2014) propose the theoretical and empirical importance of financial literacy. They argue that the gap between reality and theoretical models may originate in the hypothesis, which states that individuals have the capacity to undertake complex economic tasks and possess expertise in engaging with financial markets, a hypothesis contradicted by findings of prevailing financial illiteracy across countries. Financial illiteracy has been empirically linked to undesirable financial decisions (Agarwal et al., 2009). Consumers with low levels of financial literacy tend to save less and accumulate less wealth (Lusardi and Mitchell, 2007; Jappelli and Padula, 2013). To provide a solution to financial illiteracy, as much as 59 economies in the world are implementing or actively designing national strategies to improve financial education (OECD, 2015). Effective financial education programmes will contribute to higher financial literacy, more desirable financial behaviours, and better financial ability (Bernheim and Garrett, 2003; Collins, 2010; Carlin and Robinson, 2012; Luhrmann€ et al., 2015; Xiao and O’Neill, 2016). Based on previous research, we predict that financial literacy is an important factor for explaining the risky asset holding behaviour of Chinese households, given that China has experienced the transition of economic system, and

© 2018 AFAANZ L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1385 therefore, many households remain unfamiliar with the emerging financial market and risky financial assets. Consequently, consumers with low levels of financial literacy may face high costs of participation in risky financial markets because financial literacy could be viewed as costly in terms of human capital. Although research on financial literacy in many countries, particularly developed countries, is growing, the financial literacy research in China is limited. To address this research gap, we use data from the 2014 China Survey of Consumer Finance to examine the role of financial literacy in determining the risky asset holdings of Chinese households. Based on descriptive statistics, we find that financial illiteracy in Chinese households is both prevailing and severe at the national level. We then employ regression models to examine the potential effect of financial literacy on risky asset holdings. After controlling for the potential endogeneity of financial literacy and risky asset holdings, the results and robustness checks show that financial literacy is associated with risky financial asset holdings among Chinese households. Moreover, advanced financial literacy is strongly associated with risky asset holdings. Our study contributes to existing literature by adding new evidence from the emerging market. Although there has been increasing research on financial literacy and household portfolio, most studies are rooted in the context of mature markets, both theoretically and empirically (Lusardi and Mitchell, 2007; Cardak and Wilkins, 2009; Jappelli and Padula, 2013). However, consumers in emerging markets face more constraints than those in mature markets. Take the pension system as an example. The Chinese social pension account is managed as a mutual fund by a specialised government institution. Individual account holders are not in charge of the portfolio allocation of their own accounts. From the individuals’ perspective, the pension account works as a long-term saving account with a risk-free return. The opportunity for individual investors to allocate risky financial assets is largely narrowed by this systematic arrangement. These constraints and special institutional arrange- ments make the asset allocation pattern of Chinese households generally different from that of Western countries. Therefore, it is necessary to examine the impact of financial literacy on Chinese household behaviour to enrich the literature of financial literacy, even though there are rich existing studies using data from developed economies. To our knowledge, our study is the first to characterise Chinese financial literacy using international comparable data. Moreover, previous research has studied the potential effects of financial literacy on stock market participation (Van Rooij et al., 2011), but little attention has been given to the entire set of risky financial assets in household portfolios. This study attempts to fill this gap too. The paper is organised as follows. Section 2 presents a literature review on financial literacy and risky asset holdings, in which research hypotheses are proposed. Section 3 introduces the survey data, and section 4 describes the financial literacy situation of Chinese households. Section 5 reports the

© 2018 AFAANZ 1386 L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 empirical results regarding the association between the ﬁnancial literacy and risky asset holdings of Chinese households. Section 6 concludes and discusses policy implications on national ﬁnancial education.

2. Literature review and hypotheses

2.1. Research on ﬁnancial literacy

During the past decade, research on financial literacy has increased. Definitions of financial literacy vary in the literature (Hung et al.,2009). Lusardi and Mitchell (2014) define financial literacy as the ability to ‘process economic information and make informed decisions about financial planning, wealth accumulation, debt and pensions (p6)’. To measure financial literacy, they have designed three questions to examine people’s numeracy capability and their understanding of concepts such as inflation, interest and risk diversification. This set of questions is broadly adopted for conducting financial literacy surveys in different countries (Lusardi and Mitchell, 2011). Apart from Lusardi’s measurement, the International Network of Financial Education (INFE) has decomposed financial literacy into financial knowledge, financial attitude and financial behaviour and developed questions for each part (Atkinson and Messy, 2012). To evaluate the level of financial literacy in OECD countries, INFE conducted a massive pilot survey across 14 countries to collect micro household data. The results show that low levels of financial literacy generally exist in nearly all OECD or OECD-partner countries. Similar to the findings of Atkinson and Messy (2012), low levels of financial literacy are repeatedly discovered in many countries and areas, including Germany, Italy, Russia, Japan and the U.S.A., which means it exists in developed countries and emerging markets alike (Bucher-Koenen and Lusardi, 2011; Fornero and Monticone, 2011; Klapper and Panos, 2011; Sekita, 2011; Bumcrot et al., 2013). To our knowledge, no study has examined financial literacy in China. In this paper, we describe the financial literacy situation of Chinese households with data from the 2014 China Survey of Consumer Finances. Many previous studies have focused on the consequences of financial illiteracy. Financial literacy has been shown to exert a positive effect on household financial management and to improve financial well-being. House- holds with higher levels of financial literacy tend to make sound financial decisions. Bernheim and Garrett (2003) find that people would save more if they have received financial education in the workplace. Lusardi and Mitchell (2007) show that people with lower levels of financial literacy have accumulated less wealth because of their failure to adequately consider retirement planning. Agarwal et al. (2009) find that financial decision mistakes are more common among young and older people, and that they usually perform worse on measures assessing financial literacy than middle-aged people. Jappelli and

Padula (2013) integrate financial literacy into the consumption model and provide evidence of a strong correlation between financial literacy and wealth accumulation. They argue that financial literacy and wealth are endogenous and affected by common factors over a life cycle so that they use instrument variable estimates to address the endogeneity bias in empirical analyses. Evidence from emerging markets also confirms financial literacy as a predictor of financial behaviour. Cole et al. (2011) use survey data from Indonesia and India to demonstrate that financial literacy is positively correlated with the demand for financial services and financial products.

2.2. Financial literacy and risky asset holdings

Previous studies have explored the determinants of household holdings of risky financial assets. Demographic characteristics, such as age, gender and marital status of the household head, are considered possible determinants (Poterba and Samwick, 2001; Bertocchi et al., 2011; Halko et al., 2012). These studies reveal that women generally are more risk averse and less likely to invest in risky assets. Family changes, including changes in marital status and the number of children, would fundamentally affect household portfolio decisions (Love, 2010). Atella et al. (2012) analyse data from ten European countries to study the influence of health status on household portfolio choices. They find that in countries with less protective healthcare systems, the current and expected health statuses affect the household’s portfolio allocation of risky assets. Until recently, financial literacy was not valued as an important determi- nant in the decision making of households in regard to risky asset holdings. Apart from the background risk factors posed by labour income uncertainty, health risk and home ownership, financial awareness and knowledge may play an important role in the risky asset holdings of Australian households (Cardak and Wilkins, 2009). Jappelli and Padula (2015) have developed an intertemporal portfolio choice model suggesting that acquiring human capital in the form of financial literacy may help investors reduce entry and transactional costs associated with financialmarkets.Theirmodelpredicts that increased financial literacy would increase stock market participation and commit a larger share of risky assets to a portfolio. This prediction is supported by cross-country data in Europe. Additional evidences from several countries show that both financial literacy and cognitive abilities are closely linked to decisions regarding stock investments (Christelis et al., 2010; Van Rooij et al., 2011). Based on these theoretical and empirical studies, we infer that a positive correlation may exist between financial literacy and risky asset holdings of Chinese households. In households lacking formal financial education, where risky assets are relatively new, higher levels of financial literacy would lower the costs of understanding risky financial assets. Furthermore, it would eliminate

H1: Keeping other variables constant, ﬁnancial literacy is positively correlated with risky asset holdings.

2.3. Advanced ﬁnancial literacy and risky asset holdings

To further scrutinise the influence of financial literacy, we distinguish advanced financial literacy from basic financial literacy following Van Rooij et al. (2011). Based on Van Rooij et al. (2011), most households are informed of basic financial concepts and ideas, but experience difficulty grasping advanced professional knowledge. They have distinguished the professional knowledge (referred to as ‘advanced financial literacy’) from the basic economic concept (‘basic financial literacy’) and believe that understanding advanced financial knowledge will help predict the household’s investment behaviour. Households with less advanced financial literacy are more reluctant to participate in the stock market. By including the same advanced financial literacy questions and some additional items on investment markets and products, Balloch et al. (2015) have developed an index of ‘stock market literacy’. They relate this measurement of sophisticated financial literacy to stock ownership decisions and find that stock market literacy helps explain not only the probability of participation but also the share of investments in stocks. Advanced financial literacy focuses on specific financial products, while basic financial literacy covers only fundamental economic concepts, which represent different levels of financial literacy. For example, the computation of compound interest represents basic financial knowledge, but is not restricted to the field of finance. This point can be well illustrated through comparisons between National Standards for Financial Literacy (Bosshardt and Walstad, 2014) and National Content Standards in Economics (Walstad et al., 2013), which are both published by the U.S. Council for Economic Education. Some economic concepts such as interest rate and inflation are required for financial literacy as well, while the standards for economics include few items about financial investment products. Hence, it is important to distinguish between advanced and basic financial literacy. Regarding the household asset holding behaviour, advanced financial literacy provides core financial concepts more closely linked with risky assets. We infer that advanced financial literacy, which requires a deeper understanding of financial assets, would exert a greater effect on the household with respect to choosing appropriate risky assets than would the fundamental economic and numeracy capability provided by basic financial literacy. Hence, we propose the second hypothesis:

H2: Keeping the basic ﬁnancial literacy constant, advanced ﬁnancial literacy is positively correlated with risky asset holdings.

3. Data

Data for this study are from the 2014 China Survey of Consumer Finances (CSCF), a national survey on urban household finances. The sample is obtained by probability-proportional-to-size sampling (PPS) with implicit stratification. Administrative units and variables measuring the local economic development level are used for stratification. The nationally representative sample contains information on 3921 households from 25 provinces or municipalities. Populations in these provinces/municipalities constitute 95 percent of the national population. The survey collects household finance data by conducting a computer-assisted personal interview, generally lasting 30 min. In the 2014 wave of CSCF, a distinct module on financial literacy was added. Most questions in the questionnaire are similar to those in the financial literacy modules of the 2005–2006 De Nederlandsche Bank’s Household Survey (Van Rooij et al., 2011) and the 2010–2011 OECD/ International Network of Financial Education (INFE) Pilot Study (Atkinson and Messy, 2012). Thus, using the same scoring technique, we are able to compare the Chinese financial literacy situation with the situation in other countries. Because CSCF shared samples with the China Family Panel Studies (CFPS), we used additional information on household characteristics available from the CFPS. It should be noted that it is a household survey, and thus, the interviewee should be carefully selected to ensure that his/her responses represent the household and connected to the household’s financial behaviours. Instead of randomly assigning a household member within the household, we require that the respondent who answers questions in the financial literacy module be the one taking charge of the family financial affairs. Thus, we assume the respondent’s financial literacy applies to the household financial decisions. The financial literacy questions comprise two categories. The first category includes basic financial knowledge such as numeracy and common financial concepts, whereas the second category requires advanced financial knowledge. Terms corresponding to types of financial assets, such as stocks and mutual funds, are mentioned in the advanced category. Some questions are closely related to popular topics in the contemporary financial situation in China, such as the time deposit interest rate and commercial bank financial products. The wording of the questions is shown in Appendix I, and all questions can be answered with ‘I don’t know’ to discourage guessing, although the ‘I don’t know’ response is not among the alternatives shown to the interviewee.

4. Financial literacy in China

The responses from our national sample indicate a severe lack of financial literacy in China. A large number of people lack financial knowledge to support their daily financial activities. Responses to each question are reported in Table 1, which show that the accuracy rates of most questions are fairly low. We use household weights to ensure that all of the below statistics are nationally representative. Respondents are more knowledgeable about the financial matters that they are involved in. Few financial products were available before the emerging financial market launched, and therefore, most households select time deposits as their primary financial asset. It is plausible that the time deposit interest rate may be one of the financial concepts that Chinese households are most familiar with. However, only about half (51.32 percent) of the households are aware of the approximate range of the 1-year time deposit interest rate, whereas 38.38 percent of households do not know the rate. For the computing questions, nearly all participants can perform simple division, while 45.23 percent of them

Table 1 Responses to all ﬁnancial literacy questions (N = 3875)

Correct Wrong Don’t know

Basic financial literacy 1. Division* 100%* –– 2. Interest rate 51.32% 10.30% 38.38% 3. Calculation of simple interest & principal 45.23% 31.19% 23.58% 4. Compound interest 50.33% 24.47% 25.20% 5. Inflation 57.32% 19.17% 23.51% 6. Time-value of money 68.22% 13.21% 18.56% 7. Risk and return 85.13% 5.76% 9.11% Advanced financial literacy 1. Bank function 33.29% 34.45% 32.27% 2. Risky assets 67.74% 10.57% 21.68% 3. Diversification 35.43% 23.38% 41.19% 4. Knowledge of stock 16.34% 40.55% 43.10% 5. Knowledge of mutual fund 11.17% 31.09% 57.74% 6. Knowledge of commercial bank financial products 28.66% 33.06% 38.28% 7. Knowledge of stock market 28.60% 20.98% 50.42%

This table reports the weighted proportion of households in the survey giving correct/wrong/ do not know answer to each question. Accuracy rate is generally low and there is high proportion of ‘I don’t know’ reply, reflecting the fact of serious financial illiteracy. *This question was not asked in the field survey. According to the pilot survey with approximately 1000 responses, the correct rate is 97 percent. To make the results comparable, we retain the question here. Hence, the score will slightly overestimate the true level of basic financial literacy. Data source: 2014 China Survey of Consumer Finances.

© 2018 AFAANZ L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1391 can compute the simple interest, and 50.33 percent can calculate the compound interest. It is striking that more people know about compound interest than people who know about simple interest, which is a less complex calculation and concept. We are unsure, however, whether this gap in knowledge is caused by participants guessing rather than stating that they do not know the answer. Therefore, we consider participants who correctly answered questions on both simple interest and compound interest to be those who clearly understand compound interest, 25 percent of all participants understood both types of interest. More participants are familiar with the concepts of inflation and the time-value of money, 57.32 and 68.22 percent correctly answer the questions, respectively. Finally, most people (85.13 percent) understand that a high return is often accompanied by a high risk. Table 2 reports the distribution of numbers of correct, incorrect and ‘I don’t know’ responses. On average, respondents answered 4.35 of seven questions correctly in terms of basic financial knowledge but only 2.21 of seven questions correctly in the advanced financial literacy category. One-fifth (19.02 percent) of the respondents provided no correct answers to any advanced questions, and 12.09 percent reported ‘I don’t know’ to all of the advanced literacy questions. We compare the performance of the Chinese participants with that of people in OECD/OECD-partner countries in Table 3. The eight questions in the 2010/ 2011 OECD pilot study are included in CSCF, with seven of the questions corresponding to the basic financial literacy and one to the advanced category. The questions are modified slightly. We focus on the percentage of people receiving high scores on at least six correct answers of the eight-question total. Panel A shows the comparison. The Chinese performance is lower than that of most countries involved in the OECD survey approximately 5 years ago. Only one-third (37 percent) of Chinese respondents received a relatively high score.

Table 2 Distribution of correct/wrong/do not know responses (N = 3875)

01234567Mean

Basic ﬁnancial literacy Correct 0 6.53 11.83 14.06 18.94 19.35 14.60 14.70 4.35 Incorrect 36.51 22.74 24.44 11.29 4.27 0.7 0.04 0 1.26 Do not know 51.05 17.96 6.46 6.44 7.11 6.17 4.81 0 1.38 Advanced ﬁnancial literacy Correct 19.02 21.29 20.78 16.36 10.31 6.98 3.67 1.59 2.21 Incorrect 25.73 20.12 19.56 14.83 11.26 6.05 2.06 0.38 1.94 Do not know 27.60 12.76 10.55 9.90 8.31 9.49 9.31 12.09 2.85

This table reports the distribution of the number of correct/wrong/do not know items with respect to seven questions in basic ﬁnancial literacy module and seven questions in advanced ﬁnancial literacy module. Data source: 2014 China Survey of Consumer Finances.

Table 3 International comparison of ﬁnancial literacy (N = 3875).

Panel A: Basic ﬁnancial literacy

Score ≥6 (%)

China (2014) 37 Armenia (2010) 46 Czech Republic (2010) 57 Estonia (2010) 61 Germany (2010) 58 Ireland (2010) 60 Malaysia (2010) 51 Peru (2010–2011) 41 Poland (2010) 49 South Africa (2010) 33 UK (2010) 53

Panel B: Advanced ﬁnancial literacy

Correct (%) Incorrect (%) Do not know (%)

CSCF DHS CSCF DHS CSCF DHS

Risky assets 67.74 68.50 10.57 12.70 21.68 18.40 Diversiﬁcation 35.43 48.20 23.38 24.80 41.19 26.60 Knowledge of stock 16.34 62.20 40.55 25.60 43.10 11.00 Knowledge of mutual fund 11.17 66.70 31.09 11.20 57.74 21.70 Knowledge of stock market 28.60 67.00 20.98 12.90 50.42 19.70

This table compares the performance of Chinese households and residents in some other countries, based on the similar questionnaire and scoring mechanism presented in Appendix I. Data source: 2014 China Survey of Consumer Finances; Van Rooij et al. (2011); Atkinson and Messy (2012). N = 3875

The performance on advanced financial literacy questions is compared with results from the 2005 DHS, as reported in Panel B of Table 3. Of the seven advanced financial literacy questions, five are identical to questions adminis- tered by the DHS (see Appendix I). The comparison indicates that the Chinese participants lack specialised financial knowledge. For each question, they report fewer correct answers and more ‘I don’t know’ responses than people from the Netherlands. The disparity worsens when participants are asked about a specific financial product in detail. For example, only 11.17 percent of the Chinese households possess a clear understanding of mutual funds, and 57.74 percent admitted that they know nothing about mutual funds. These findings suggest that financial markets and products remain new to many consumers in China. The above comparisons suggest that Chinese consumers severely lack financial literacy. Many people experience difficulties determining deposit

© 2018 AFAANZ L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1393 interest, despite possessing good numerical ability. They believe financial concepts are ambiguous, and few understand the required knowledge needed for financial products. We also examine sociodemographic differences in financial literacy. Unlike most findings in other countries, namely that the relation between financial literacy performance and age can be described by a reverse U-shaped curve, a downward line suggests the monotonous decrease of financial literacy when ageing in China. There exists a large gender gap in financial literacy, with males generally scoring higher on sophisticated questions compared with females. Consumers with lower education and lower income levels also perform worse on financial literacy questions than do consumers with higher education and income levels.

5. Financial literacy and risky asset holdings

5.1. Descriptive statistics

In the survey, information about risky asset holdings is requested with the following question:

Do you have any of the following ﬁnancial products in your household portfolio? 1) Stock 2) Mutual Fund 3) Treasury Bond 4) Trust 5) Foreign Exchange 6) Other ﬁnancial assets (e.g. Futures/Derivatives) 7) None of the above

Households that possess at least one of the listed assets except treasury bonds are coded as currently holding risky financial assets. We define risky asset share as the ratio of risky financial assets to the total amount of financial assets in the household portfolio. Financial asset comprises risky financial assets mentioned above, as well as safe financial assets including cash, time deposit and treasury bond. Table 4 presents the distribution of household risky asset holdings. Only 12.67 percent of all households report holding risky financial assets. Particu- larly, stocks represent the most popular risky asset among Chinese households, 8.21 percent of them participate in the stock market directly. Only 2.76 percent of the households diversify their portfolio by holding two or more types of risky financial assets. Most households allocate a small proportion of their portfolio using risky assets, with almost 90 percent of households holding risky financial asset share lower than 20 percent. These findings suggest that risky assets have not been widely accepted by Chinese households. The direct stock market participation rate (8.21 percent) in China is approximately 40 percent lower than that in the U.S.A. (13.8 percent). Moreover, 48.8 percent of American households own publicly traded stocks, mainly through pension accounts. Data from the Eurozone show that direct and indirect stock

Table 4 Risky asset holdings of Chinese households

Panel A

Risky asset ownership Risky Stock Mutual Trust Foreign Other risky asset funds exchange assets Proportion (%) 12.67 8.21 5.7 0.72 0.27 0.88

Panel B

Number of risky assets 0 1 2 3 4 5 Proportion (%) 87.33 9.91 2.45 0.28 0.03 0

Panel C

Risky asset share 0 (0,0.2] (0.2,0.4] (0.4,0.6] (0.6,0.8] (0.8,1] Proportion (%)* 87.33 2.57 2.53 1.81 0.70 0.30

Panel D†

Proportion (%) U.S.A. Germany Ireland The Poland Finland Netherlands Stock 13.8 9.6 13.1 8.0 3.5 21.4 Mutual fund 8.2 13.1 3.3 13.3 4.2 27.0 Bond‡ 1.4 4.2 4.5 3.8 1.0 0.9 Voluntary Pension/ 49.2 46.3 10.0 35.3 51.3 23.6 Whole Life Insurance§

Data source: 2014 China Survey of Consumer Finances; Eurosystem’s Household Finance and Consumption Survey, the second wave; Bricker et al. (2017) (N = 3875). In this table, Panel A presents the statistical description on risky asset ownership. We define risky asset ownership as owning at least one category of the following risky financial assets: stock, mutual fund, trust, foreign exchange or other risky assets. Panel B indicates the extremely low level of risky portfolio diversification by reporting the distribution of the number of risky financial assets that households hold. Risky asset share is defined as the ratio of risky financial asset to total amount of financial asset in the household portfolio. Financial asset comprises risky financial asset mentioned above, as well as safe financial asset including cash, deposit and treasury bond. Panel C shows that most households allocate small proportion of portfolio on risky asset. Panel D compares risky asset ownership (Participation rate) across countries. *Do not sum to 100 due to missing values.†Data Source: Survey of Consumer Finance 2013; Household Finance and Consumption Survey 2013–2014.‡The U.S. term does not include savings bond. §The U.S. term does not include life insurance. ownerships differ much across European countries. We emphasise that in China, the opportunity for individual investors to allocate risky financial assets is largely limited by the national system. The Chinese social pension account is managed by specialised government institutions. Individual account holders are not in charge of the portfolio allocation of their own accounts. This

© 2018 AFAANZ L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1395 institutional arrangement makes the asset allocation pattern of Chinese households generally different from that of Western countries. Therefore, it is necessary to examine the impact of financial literacy on Chinese household behaviour to enrich the literature of financial literacy, even though there are rich existing studies using data from developed economies. To measure financial literacy, two methods were used. The first method is to sum the number of correct answers, as conducted in the OECD pilot study (Atkinson and Messy, 2012). Although the questions are ranked by a progressive degree of difficulty, it is challenging to determine the exact weight, as each question contains specific information. Therefore, it is reasonable to treat each question equally. The index of financial literacy constructed thus is denoted the financial literacy_addition. The second method is to conduct a factor analysis on these questions and extract the factor score as the index of financial literacy (Van Rooij et al., 2011). Thus, factor loadings are designated as the weights of the questions. This index is denoted the financial literacy_- factor, and the factor loading is reported in Appendix II. It is difficult to discern which index is superior; hence, both indexes are used in the analyses. The questions in both basic and the advanced categories are pooled to construct the index of financial literacy. For control variables, risk attitude is considered first. In the questionnaire, the respondents are asked: ‘How much risk can you tolerate in your household investment?’ The response choices are ‘1. High risk with high return’; ‘2. Medium risk with medium return’; ‘3. Low risk with low return’; and ‘4. No risk at all’. A dummy variable for subjective risk attitude is set to 1 if ‘3’ or ‘4’ is chosen, to indicate a household showing a strong risk-averse attitude. We also include a set of variables indicating sociodemographic characteristics of the household head. A set of dummy variables indicated the level of education using five response choices that ranged from ‘below primary school’ to ‘with a bachelor degree or above’. The annual disposable income and net wealth of all household members are included. To avoid the influence of outliers, we winsorise the reported family income and wealth at the top and bottom 1 percent. Housing asset plays an important role in household portfolio allocation. The status of owning a house may affect a household’s decision concerning risky asset holdings (Fratantoni, 1998). For a household operating a small business, the financial situation is unique and thus may affect financial decisions (Heaton and Lucas, 2000). Therefore, a dummy variable is used to indicate whether the household head is self-employed. The household size and structure are also included as control variables because the number of household members in the labour force and the dependency ratio are linked to the household’s financial constraints (Love, 2010). Then, variables are included to indicate the total number of family members and whether any senior older than 60 or child younger than 18 required support in a given household. Health status is also a control variable (Rosen and Wu, 2004). People may consider the potential shock from the family members’ health status when they face risky

© 2018 AFAANZ 1396 L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 asset holding decisions. In the current medical insurance system, medical expenses would be high and uncompensated by insurance in many cases. The variable of household medical expenditure in the last year is used to indicate the health risk. Moreover, financial service differs greatly among different cities in China. Household decisions on risky asset holdings may rely on the availability and convenience to hold financial assets (Yin et al., 2015). Financial development is highly correlated with the local economic conditions. Therefore, we include GDP per Capita to control the effect of financial availability. Finally, a group of dummies of provinces is used to control for the region effect. After removing missing values and outliers, 3875 observations are retained for further analysis. Table 5 presents descriptive statistics of the major variables. In the sample, 45 percent of household heads are male. The average age of the household head is 49, and 21 percent of household heads have

Table 5 Descriptive statistics of main variables (N = 3875)

Variables Mean Median SD P1 P99

Dummy: Risky Asset Ownership 0.13 0 0.35 0 1 Risky Asset Share 0.03 0 0.12 0 0.67 Financial Literacy_Addition 6.57 7 3.11 1 13 Financial Literacy_Factor 0 0.02 0.90 1.59 1.87 Dummy: Risk Attitude 0.62 1 0.49 0 1 Dummy: Male 0.45 0 0.50 0 1 Age 49.24 49 15.10 21 82 Education Dummy: Below Primary School 0.11 0 0.31 0 1 Education Dummy: Primary school 0.13 0 0.34 0 1 Education Dummy: Junior school 0.30 0 0.46 0 1 Education Dummy: High school 0.25 0 0.43 0 1 Education Dummy: College 0.12 0 0.33 0 1 Education Dummy: University or Above 0.09 0 0.29 0 1 Married 0.81 1 0.39 0 1 Household Income Last Year (Thousands, 64.64 50 51.09 5 300 Yuan) Household Net Asset (Thousands, Yuan) 529.78 277.35 705.66 4.08 3475.00 Number of Family Members 3.19 3 1.45 1 8 Dummy: Owning Estate 0.79 1 0.41 0 1 Dummy: Self-employed 0.13 0 0.33 0 1 Dummy: Senior Family Member 0.34 0 0.48 0 1 Dummy: Dependent Children 0.31 0 0.46 0 1 Household Medical Expense Last Year 4.70 1.50 13.05 0 50 (Thousands, Yuan) Local GDP per Capita (Thousands, Yuan) 65.28 37.68 69.57 5.52 285.16

This table reports the main statistics of variables involved in multivariate regressions. ‘Financial literacy_addition’ and ‘Financial literacy_factor’ are diﬀerent measurements for ﬁnancial literacy. Data source: 2014 China Survey of Consumer Finances; 2010, 2012 China Family Panel Studies.

© 2018 AFAANZ L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1397 completed higher education. 13 percent of the households include risky assets in their portfolio. On average, households allocate 3 percent of their total financial assets on risky assets. The low participation in risky assets and small share correspond to the undesirable performance on financial literacy and strong risk aversion. On average, 6.57 of the 14 financial literacy questions are correctly answered. 62 percent of households in the sample report that they tolerate little risk.

5.2 Risky asset ownership

To test the hypotheses, we first focus on the binary choice problem of risky asset ownership, and then examine the effect of financial literacy on risky asset share. In the first step, multivariate probit regression analyses are conducted. The empirical model can be expressed as:

Prðrisky asset ownership ¼ 1jXÞ¼UðX0 bÞ ¼ Uða financial literacy þ x0c þ eÞð1Þ where e ~ N(0, 1). In this model, the financial literacy of a Chinese household is linked to the portfolio decision on risky financial asset ownership, where x represents the set of control variables. Table 6 presents the results of the probit regression in which the marginal effect of each explanatory variable is shown. The first model examines the potential effects of financial literacy on household decisions concerning risky financial asset ownership, where financial literacy is measured by pooling responses of all questions to obtain the general financial literacy index. Financial literacy is positively correlated with the probability of household holding of risky financial assets. That is, households with higher levels of financial literacy are more likely to hold risky financial assets in their household portfolios. The effect size is large even after controlling for other factors. With one additional point of the financial literacy score, the probability that the household holds risky financial assets increases 2.40 percent on average. This statistically significant effect does not diminish as the measurement of financial literacy changes. Model 2 adopts the same specification, except that the financial literacy index is measured by factor scores. Therefore, our first hypothesis is supported. It is worth noting that the risky asset ownership decision is significantly affected by the local economic status (GDP per Capita), which indicates that financial service coverage is still one of the constraints related to household portfolio choice. While this constraint and other potential factors being controlled, financial literacy helps to explain the low participation rate in the risky financial market. Chinese consumers could be easily prevented from holding risk assets because of the unfamiliarity and ambiguity they feel in relation to the financial market.

Dependent: Risky Asset Ownership (1) (2) (3) (4) (5) (6)

Financial Literacy_Addition 0.0240*** (0.0022) Financial Literacy_Factor 0.0795*** (0.0076) tal. et Basic Financial Literacy_Addition 0.0138*** 0.0115*** (0.0040) (0.0041) Acutn iac 7(07 1383–1415 (2017) 57 Finance & /Accounting Advanced Financial Literacy_Addition 0.0331*** 0.0207*** (0.0037) (0.0045) Basic Financial Literacy_Factor 0.0259*** 0.0238*** (0.0076) (0.0076) Advanced Financial Literacy_Factor 0.0741*** (0.0079) Advanced Financial Literacy_Unknown 0.0189*** (0.0037) Advanced Financial Literacy_Factor2 0.0876*** (0.0083) Strong Risky Aversion 0.0550*** 0.0567*** 0.0530*** 0.0529*** 0.0484*** 0.0494*** (0.0120) (0.0120) (0.0120) (0.0120) (0.0119) (0.0119) Male 0.0302** 0.0283** 0.0330*** 0.0321*** 0.0340*** 0.0318*** (0.0119) (0.0119) (0.0119) (0.0119) (0.0119) (0.0119) Age 0.0176*** 0.0178*** 0.0175*** 0.0176*** 0.0172*** 0.0173*** (0.0031) (0.0031) (0.0031) (0.0031) (0.0031) (0.0031) Age Squared 0.0001*** 0.0001*** 0.0001*** 0.0001*** 0.0001*** 0.0001*** (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) Education Dummies (Base: Below Primary School) Primary school 0.0146 0.0157 0.0142 0.0159 0.0087 0.0072 (0.0276) (0.0272) (0.0271) (0.0265) (0.0301) (0.0307)

(continued) © Table 6 (continued) 08AFAANZ 2018 Dependent: Risky Asset Ownership (1) (2) (3) (4) (5) (6)

Junior school 0.0450* 0.0472** 0.0464* 0.0493** 0.0320 0.0294 (0.0241) (0.0237) (0.0238) (0.0233) (0.0264) (0.0269) High school 0.0576** 0.0610** 0.0571** 0.0599** 0.0409 0.0398 Liao L. (0.0250) (0.0246) (0.0246) (0.0242) (0.0271) (0.0276) College 0.0796*** 0.0845*** 0.0787*** 0.0820*** 0.0643** 0.0657**

(0.0292) (0.0289) (0.0289) (0.0285) (0.0306) (0.0309) al. et University or above 0.0746** 0.0809** 0.0697** 0.0725** 0.0571* 0.0600* (0.0318) (0.0317) (0.0313) (0.0309) (0.0329) (0.0333) 1399 1383–1415 (2017) 57 Finance & /Accounting Married 0.0111 0.0106 0.0094 0.0081 0.0065 0.0052 (0.0192) (0.0193) (0.0189) (0.0189) (0.0191) (0.0193) Ln (Household Income Last Year) 0.0543*** 0.0551*** 0.0548*** 0.0554*** 0.0529*** 0.0531*** (0.0116) (0.0117) (0.0114) (0.0114) (0.0113) (0.0114) Ln (Household Net Asset) 0.0309*** 0.0313*** 0.0306*** 0.0307*** 0.0307*** 0.0316*** (0.0063) (0.0063) (0.0062) (0.0062) (0.0062) (0.0062) Number of Family Members 0.0152*** 0.0155*** 0.0154*** 0.0157*** 0.0152*** 0.0157*** (0.0052) (0.0052) (0.0051) (0.0051) (0.0052) (0.0052) Owning Estate 0.0264 0.0261 0.0280* 0.0281* 0.0297* 0.0310* (0.0170) (0.0170) (0.0170) (0.0169) (0.0171) (0.0171) Self-employed 0.0299 0.0309 0.0286 0.0292 0.0293 0.0304 (0.0202) (0.0202) (0.0201) (0.0201) (0.0199) (0.0198) Senior Family Member 0.0140 0.0138 0.0132 0.0129 0.0114 0.0104 (0.0153) (0.0154) (0.0152) (0.0152) (0.0151) (0.0152) Dependent Children 0.0079 0.0083 0.0073 0.0079 0.0035 0.0028 (0.0150) (0.0150) (0.0149) (0.0149) (0.0148) (0.0148) Ln (Household Medical Expense) 0.0011 0.0011 0.0010 0.0010 0.0010 0.0010 (0.0018) (0.0018) (0.0018) (0.0018) (0.0018) (0.0018) Ln (Local GDP per Capita) 0.0353*** 0.0352*** 0.0367*** 0.0364*** 0.0353*** 0.0351*** (0.0089) (0.0090) (0.0088) (0.0088) (0.0089) (0.0090)

(continued) 40L Liao L. 1400 © Table 6 (continued) 08AFAANZ 2018 Dependent: Risky Asset Ownership (1) (2) (3) (4) (5) (6)

Dummies on Provinces Yes Yes Yes Yes Yes Yes

Obs. 3875 3875 3875 3875 3875 3875 Pseudo R-squared 0.296 0.293 0.299 0.300 0.310 0.311

Robust standard errors in parentheses. *p < 0.1; **p < 0.05; ***p < 0.01. This table reports the results of probit regression. For better al. et interpretation on the effect on dependent variable, marginal effect of each explanatory variable is reported instead of the estimated coefficient. Acutn iac 7(07 1383–1415 (2017) 57 Finance & /Accounting Models 1 and 2 show the estimated effect of financial literacy on household risky financial asset ownership. Financial literacy is decomposed into two parts: the basic and advanced component. Models 3 and 4 are employed to examine their effect on risky financial asset ownership simultaneously. Models 5 and 6 include the information of ‘do not know’ reply. Large proportion of the advanced module received ‘do not know’ response. The number of ‘do not know’ reply in the advanced financial literacy module is used as a negative indicator of advanced financial literacy. This information is also considered in the factor index ‘advanced financial literacy_factor2’. The financial literacy is positively correlated with the risky financial assets ownership. Beyond basic financial literacy, advanced financial literacy is further required and exerts larger effect on risky assets ownership. Data source: 2014 China Survey of Consumer Finances; 2010, 2012 China Family Panel Studies. L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 1401

Financial literacy could help reduce feelings of uncertainty and ambiguity, hence encouraging acceptance of risky financial assets. In Models 3 and 4, financial literacy is decomposed to examine potential effects of the basic and advanced components separately. Both estimates on basic and advanced financial literacy are significantly positive. One additional score point achieved in basic financial literacy would increase the chance of holding risky financial assets 1.38 percent on average when advanced financial literacy and other factors are controlled. The effect of advanced financial literacy is 3.31 percent. The difference in marginal effects of the two levels of financial literacy implies that their functions in promoting risky asset holdings differ. We thus infer that, in addition to basic financial concepts, advanced financial knowledge is needed to accept risky financial assets. Thus, the second hypothesis is also supported. Additional effort is made to refine the financial literacy measurement in the final two models (i.e. Models 5 and 6). A large percentage of ‘I don’t know’ responses were recorded for nearly every advanced financial literacy question. We believe that the ‘I don’t know’ response provides additional information aside from indicating the accuracy of an answer. Hence, we include the variable ‘Advanced Financial Literacy_Unknown’ to indicate the number of ‘I don’t know’ responses to advanced financial literacy questions. This variable is used to measure the feeling of ambiguity towards financial products. The factor index of advanced financial literacy is correspondingly revised to incorporate ‘I don’t know’ responses, denoted as ‘Advanced Financial Literacy_Factor2’. The factor loadings of ‘I don’t know’ responses are negative, as reported in Appendix II. Because only a small fraction of the sample responded ‘I don’t know’ to the basic financial literacy questions, the index of basic financial literacy remains unchanged. The results of Models 5 and 6 in Table 6 support the hypotheses by providing similar results. In Model 5, the effect of advanced financial literacy is again confirmed by the positive coefficient estimate of ‘Advanced Financial Literacy_Addition’ and the negative coefficient estimate of ‘Advanced Financial Literacy_Unknown’. With an additional ‘I don’t know’ response, the propensity to hold risky financial assets in household portfolios decreases 1.89 percent on average. In Model 6, the effect of advanced financial literacy is integrated into the coefficient of ‘Advanced Financial Literacy_Factor2’. The positive marginal effect on the factor index indicates that financial literacy remains positively correlated with the household holding of risky assets. The estimates of the control variables highlight several sociodemographic factors that may encourage households to hold risky assets. The risk attitude is shown to be a key variable for explaining a household’s probability of holding risky assets. As the regression coefficients indicate, households with strong risk-averse attitude are separated from their low risk–averse counterparts by approximately 5 percentage points. Households with female heads are more inclined to hold risky financial assets, which is different from most empirical studies in other countries (Barber and Odean, 2001; Halko et al.,

2012). This may be caused by the interactive effect of gender and marriage. As shown by Bertocchi et al. (2011), married women invested more in risky assets than single women. Most women in our sample are married, and the role of household head may make them less risk averse when taking responsibility of the household portfolio. The estimates also show that households with higher levels of income and wealth are more likely to hold risky financial assets. Households with heads with a higher educational level are more likely to hold risky financial assets because education cultivates cognitive abilities. The study by Christelis et al. (2010) has reported a positive correlation between cognitive abilities and stock holding. Large families with greater numbers of old family members and children to support are less inclined to hold risky financial assets. These findings are consistent with previous research concerning background risk factors that are commonly linked with risky asset holdings.

5.3. Risky asset share

As financial literacy contributes to holding of risky financial assets, will it have effects on the risky asset share in the total financial assets? In this step, the dependent variable is the risky asset share, and explanatory variables remain the same as those in the binary choice problem. We conduct Tobit regressions which are left-censored at zero. The model can be expressed as:

risky asset share ¼ X0 b ¼ a financial literacy þ x0c þ e; ð2Þ where e Nð0; 1Þ

The results are presented in Table 7. Similar to the results of the probit regression, the coefficient on financial literacy remain significantly positive, indicating a positive correlation between financial literacy and the risky asset share, which also supports our hypotheses. When other potential factors are controlled, one more score point on financial literacy questions would promote households to allocate 1.04 percent more of the financial asset on risky assets. Advanced financial literacy may exert a larger effect than basic financial literacy. Households who get one more correct answer on basic financial literacy intend to allocate 0.55 percent more on the risky financial asset, while the effect of advanced financial literacy is 1.48. Households with one more ‘I don’t know’ answer would decrease the risky asset share in their portfolio by 0.84 percentage point. Again, different indexes on financial literacy are employed to avoid bias caused by measurement, and control variables are included to isolate the effect of financial literacy. Table 7 adds to the evidence with data from Chinese urban households indicating that financial literacy is positively correlated with risky financial asset holdings.

Dependent: Risky Asset Share (1) (2) (3) (4) (5) (6)

*** Financial Literacy_Addition 0.0104 Liao L. (0.0011) Financial Literacy_Factor 0.0343*** (0.0039) tal. et Basic Financial Literacy_Addition 0.0055*** 0.0043** (0.0020) (0.0020) Acutn iac 7(07 3311 1403 1383–1415 (2017) 57 Finance & /Accounting Advanced Financial Literacy_Addition 0.0148*** 0.0093*** (0.0019) (0.0022) Basic Financial Literacy_Factor 0.0099*** 0.0086** (0.0038) (0.0037) Advanced Financial Literacy_Factor 0.0330*** (0.0040) Advanced Financial Literacy_Unknown 0.0084*** (0.0019) Advanced Financial Literacy_Factor2 0.0388*** (0.0043) Strong Risky Aversion 0.0219*** 0.0226*** 0.0212*** 0.0212*** 0.0188*** 0.0192*** (0.0061) (0.0061) (0.0061) (0.0061) (0.0060) (0.0060) Male 0.0072 0.0062 0.0087 0.0081 0.0087 0.0073 (0.0060) (0.0060) (0.0059) (0.0059) (0.0059) (0.0059) Age 0.0067*** 0.0068*** 0.0067*** 0.0068*** 0.0065*** 0.0065*** (0.0015) (0.0015) (0.0015) (0.0015) (0.0015) (0.0015) Age Squared 0.0001*** 0.0001*** 0.0001*** 0.0001*** 0.0001*** 0.0001*** (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) Education Dummies (Base: Below Primary School) Primary school 0.0002 0.0009 0.0001 0.0011 0.0026 0.0033 (0.0159) (0.0158) (0.0156) (0.0154) (0.0165) (0.0167)

(continued) 44L Liao L. 1404 © Table 7 (continued) 08AFAANZ 2018 Dependent: Risky Asset Share (1) (2) (3) (4) (5) (6)

Junior school 0.0041 0.0054 0.0052 0.0068 0.0020 0.0030 (0.0137) (0.0136) (0.0136) (0.0134) (0.0143) (0.0144) High school 0.0145 0.0163 0.0143 0.0158 0.0064 0.0060 (0.0138) (0.0137) (0.0137) (0.0134) (0.0144) (0.0145) College 0.0197 0.0221 0.0198 0.0217 0.0127 0.0132 (0.0156) (0.0155) (0.0155) (0.0153) (0.0159) (0.0159) al. et University or above 0.0158 0.0189 0.0140 0.0155 0.0081 0.0098 (0.0166) (0.0166) (0.0163) (0.0162) (0.0168) (0.0169) 1383–1415 (2017) 57 Finance & /Accounting Married 0.0057 0.0054 0.0050 0.0045 0.0036 0.0030 (0.0099) (0.0099) (0.0098) (0.0097) (0.0097) (0.0097) Ln (Household Income Last Year) 0.0298*** 0.0304*** 0.0298*** 0.0303*** 0.0285*** 0.0286*** (0.0062) (0.0062) (0.0060) (0.0060) (0.0059) (0.0060) Ln (Household Net Asset) 0.0109*** 0.0112*** 0.0107*** 0.0108*** 0.0104*** 0.0107*** (0.0031) (0.0031) (0.0031) (0.0030) (0.0031) (0.0031) Number of Family Members 0.0083*** 0.0086*** 0.0081*** 0.0082*** 0.0080*** 0.0083*** (0.0026) (0.0026) (0.0026) (0.0026) (0.0026) (0.0026) Owning Estate 0.0125 0.0124 0.0137* 0.0139* 0.0143* 0.0148* (0.0083) (0.0083) (0.0082) (0.0082) (0.0083) (0.0083) Self-employed 0.0081 0.0084 0.0081 0.0083 0.0079 0.0080 (0.0104) (0.0104) (0.0103) (0.0103) (0.0101) (0.0100) Senior Family Member 0.0032 0.0031 0.0032 0.0031 0.0023 0.0018 (0.0080) (0.0080) (0.0079) (0.0079) (0.0078) (0.0079) Dependent Children 0.0038 0.0040 0.0032 0.0033 0.0015 0.0012 (0.0076) (0.0076) (0.0076) (0.0076) (0.0074) (0.0074) Ln (Household Medical Expense) 0.0005 0.0004 0.0005 0.0005 0.0004 0.0004 (0.0009) (0.0009) (0.0009) (0.0009) (0.0009) (0.0009) Ln (Local GDP per Capita) 0.0171*** 0.0170*** 0.0180*** 0.0179*** 0.0173*** 0.0171*** (0.0046) (0.0046) (0.0045) (0.0045) (0.0046) (0.0046)

(continued) © Table 7 (continued) 08AFAANZ 2018 Dependent: Risky Asset Share (1) (2) (3) (4) (5) (6)

Dummies on Provinces Yes Yes Yes Yes Yes Yes Obs. 3678 3678 3678 3678 3678 3678 Pseudo R-squared 0.296 0.293 0.301 0.301 0.311 0.311 Liao L.

Robust standard errors in parentheses. *p < 0.1; **p < 0.05; ***p < 0.01. This table reports the results of Tobit regression. The list of explanatory variables is identical to that of the risky asset ownership problem in Table 6. Models 1 and 2 show the estimated effect of financial al. et literacy on risky financial asset share in the household portfolio. Models 3 and 4 examine the effect of basic and advanced financial literacy on Acutn iac 7(07 3311 1405 1383–1415 (2017) 57 Finance & /Accounting risky financial asset share. Models 5 and 6 modify the measurement of financial literacy by including the information of ‘do not know’ reply. The result demonstrates financial literacy is significantly positively related to the household risky asset share, which adds to the evidence from Chinese urban households that financial literacy is positively correlated with risky financial asset holdings. Data source: 2014 China Survey of Consumer Finances; 2010, 2012 China Family Panel Studies. 1406 L. Liao et al./Accounting & Finance 57 (2017) 1383–1415

5.4. The endogenous problem

We realise that the problem of endogeneity may apply to the above regression models because the coefficients cannot determine the causality between financial literacy and investing behaviour. It is also plausible that experience in financial markets could enhance participants’ financial literacy. Specifically, several questions on advanced financial literacy test specialised knowledge concerning risky financial products. Therefore, the potential endogeneity of advanced financial literacy must be treated with care. We employ the following instrument variable and conduct a two-stage regression to remedy this problem (Newey, 1987). The 2010 China Family Panel Study conducted a verbal test to measure familiarity with Chinese characters. We use the test score of the household head to proxy his/her financial literacy for the following consideration. Due to the fact that the test score reflects the basic language skill and implicitly, the learning ability, it is considerably easier to obtain a sound understanding of the field of finance and to achieve good financial literacy with a higher verbal test score. Moreover, it is unlikely that one’s investing decision would be affected by one’s language skill 5 years ago. We realise that verbal score is not completely exogenous and cannot rule out the endogenous problem perfectly. However, the testing result makes us believe that this instrument helps to alleviate endogeneity. We first perform a regression on the advanced financial literacy factor score on the verbal test score and the control variables. The first stage regression result is shown in Table 8. The expected positive correlation between language ability and financial literacy is indicated by the significant coefficient estimate, and the F statistic of the regression (69.66) is beyond the critical values, thus indicating that the verbal test score is not a weak instrument for advanced financial literacy. Additionally, the estimates confirm the relation between advanced financial literacy and one’s demographic background. The younger, more highly educated, males or those with higher household income are likely to possess greater financial literacy compared with their counterparts. Then, an IV-probit model and IV-Tobit model are run on the risky asset ownership and risky asset share, respectively. The estimate of coefficient on the instrument of advanced financial literacy is positive and statistically significant, with the signs of coefficients of other variables almost remaining unchanged. The result of the Wald test of exogeneity shows that an endogeneity problem indeed exists. IV estimations confirm that advanced financial literacy is a key predictor of household investing behaviour. Households with specialised financial knowledge are more likely to hold risky financial assets, as well as a larger risky asset share in their household portfolios.

Table 8 IV estimation to address the potential endogenous problem

Step 2: Probit/Tobit Step 1: OLS Advanced Financial Risky Asset Risky Asset Dependent Literacy_Factor2 Ownership Share

Advanced Financial Literacy_Instrumented 0.3025*** 0.2323** (0.0522) (0.1032) Verbal Test Score 0.0112*** (0.0024) Basic Financial Literacy_Factor 0.2939*** 0.0488* 0.0410 (0.0195) (0.0258) (0.0295) Strong Risky Aversion 0.2539*** 0.0168 0.0182 (0.0321) (0.0288) (0.0251) Male 0.1475*** 0.0597*** 0.0380** (0.0301) (0.0137) (0.0191) Age 0.0038 0.0134*** 0.0085*** (0.0071) (0.0043) (0.0027) Age Squared 0.0001* 0.0001** 0.0001** (0.0001) (0.0000) (0.0000) Education Dummies (Base: Below Primary School) Primary school 0.0831 0.0225 0.0345 (0.0595) (0.0381) (0.0396) Junior school 0.2833*** 0.0660 0.0858 (0.0589) (0.0410) (0.0528) High school 0.3806*** 0.0819* 0.0884 (0.0651) (0.0476) (0.0615) College 0.5096*** 0.0924 0.1032 (0.0755) (0.0583) (0.0723) University or above 0.5962*** 0.1191* 0.1271 (0.0793) (0.0624) (0.0805) Married 0.0772* 0.0210 0.0214 (0.0447) (0.0211) (0.0188) Ln (Household Income Last Year) 0.1017*** 0.0198 0.0175 (0.0248) (0.0195) (0.0118) Ln (Household Net Asset) 0.0390** 0.0211* 0.0115* (0.0167) (0.0113) (0.0061) Number of Family Members 0.0167 0.0095 0.0088* (0.0115) (0.0070) (0.0045) Owning Estate 0.0524 0.0370** 0.0319* (0.0402) (0.0183) (0.0166) Self-employed 0.0004 0.0284 0.0094 (0.0452) (0.0219) (0.0169) Senior Family Member 0.0188 0.0166 0.0138 (0.0414) (0.0171) (0.0149) Dependent Children 0.0525 0.0147 0.0125 (0.0370) (0.0162) (0.0145) Ln (Household Medical Expense) 0.0002 0.0003 0.0004

(continued)

Table 8 (continued)

Step 2: Probit/Tobit Step 1: OLS Advanced Financial Risky Asset Risky Asset Dependent Literacy_Factor2 Ownership Share

(0.0049) (0.0021) (0.0017) Ln (Local GDP per Capita) 0.0334 0.0268** 0.0216*** (0.0219) (0.0128) (0.0078) Dummies on Provinces Yes Yes Yes Obs. 3875 3875 3678 F valuep-value: Wald Test of Exogeneity 69.66 0.0067 0.0271

Robust standard errors in parentheses. *p < 0.1; **p < 0.05; ***p < 0.01. This table reports the result of instrument variable regressions. Two-step estimator is employed to tackle with the potential endogenous problem. Verbal test score is used as the instrument for advanced financial literacy. In the first step, the advanced financial literacy factor score is estimated by the verbal test score and the control variables in an OLS regression. In the second step, an IV- probit model and IV-Tobit model are run on risky asset ownership and risky asset share, respectively, where the explanatory variable ‘Advanced Financial Literacy’ is instrumented. Data source: 2014 China Survey of Consumer Finances; 2010, 2012 China Family Panel Studies

5.5. Robustness check

To examine the robustness of the estimates, we change the dependent variable to stock. As shown in the previous section, stock is a representative asset among all types of risky financial assets held by Chinese households, and many households holding risky assets also hold stocks exclusively. Hence, we substitute the dependent variable, risky asset holding, with its main component stock holding in the first specification. We also adjust the sample in the second specification. Several cities are oversampled in the sampling scheme of the survey, and we omit the oversampled observations and repeat the regression. Table 9 presents the results. The coefficients of advanced financial literacy remain significantly positive for all specifications. Based on the robust results shown in Table 9, we conclude that there is a robust relationship between the financial literacy and the risky financial asset holdings of Chinese households.

6. Conclusion

Our study provides empirical evidence suggesting that low levels of financial literacy pose an obstacle to Chinese households in terms of allocating risky financial assets to their portfolios. Based on descriptive statistics of the financial literacy of Chinese households, we find a nationwide phenomenon of financial

Table 9 Robustness check

(1) Stock Ownership (2) Subsample Panel A Probit IV-Probit Probit IV-Probit

Advanced Financial 0.0766*** 0.3035*** 0.0632*** 0.2176** Literacy_Factor2 (0.0078) (0.0501) (0.0084) (0.0896) Basic Financial Literacy_Factor 0.0186*** 0.0552** 0.0214*** 0.0211 (0.0069) (0.0240) (0.0080) (0.0298) Controlled Variables Yes Yes Yes Yes Obs. 3875 3875 2552 2552

(1) Stock Share (2) Subsample Panel B Tobit IV-Tobit Tobit IV-Tobit

Advanced Financial 0.0412*** 0.3888** 0.0407*** 0.2158** Literacy_Factor2 (0.0048) (0.1614) (0.0057) (0.1051) Basic Financial Literacy_Factor 0.0107*** 0.0803* 0.0135** 0.0296 (0.0041) (0.0474) (0.0054) (0.0292) Controlled Variables Yes Yes Yes Yes Obs. 3678 3678 2452 2452

Robust standard errors in parentheses. *p < 0.1; **p < 0.05; ***p < 0.01. This table combines the results of robustness check. Panel A shows the robustness check for risky asset ownership problem. In the first specification, the dependent variable ‘risky asset ownership’ is substituted by its main component ‘stock ownership’. In the second specification, we use a subsample. Panel B shows the robustness check for risky asset share problem. The first specification substitutes the dependent variable for its main component ‘stock share’. The second specification is run on a subsample. Data source: 2014 China Survey of Consumer Finances; 2010, 2012 China Family Panel Studies. illiteracy in China where a large percentage of urban households are equipped with little financial knowledge. The findings of our study suggest that higher levels of financial literacy would increase risky asset holdings in the household portfolio. The impacts may mainly derive from advanced financial literacy. When basic financial literacy and other variables are controlled, advanced financial literacy continues to be significantly positively correlated with the probability of the risky financial asset ownership as well as the risky asset share. Although the portfolio theories suggest that risky assets should be included in the portfolio, the welfare of financial-illiterate households holding risky assets yet remains to be seen. Based on the evidence that most households have not been equipped with adequate financial literacy that is essential to participate in the financial market, we believe that the need for consumer financial education in China

© 2018 AFAANZ 1410 L. Liao et al./Accounting & Finance 57 (2017) 1383–1415 is urgent. In the past decades, a growing number of countries have been engaged in promoting nationwide financial education to complement financial consumer protection and provide effective solutions to financial illiteracy. In recent years, as many as 34 economies with different income levels are implementing national strategies for financial education, while additional 25 economies including mainland China are actively designing the national strategy (OECD, 2015). It would be an enormous challenge to carry out financial education programmes across the whole population. Therefore, it would be much more efficient to start with the most vulnerable groups, which suggested by our findings, are females, seniors, the poor and the less educated. We recommend that financial knowledge be incorporated into the national compulsory education system to improve financial literacy among the young generation. Multiple channels exist that can be used to disseminate financial knowledge. The financial regulatory authorities and financial institutions should take efforts to provide financial education for individual investors. In this study, the sample is limited to urban households. Chinese rural areas differ substantially from urban areas. In addition, a large gap exists in urban and rural households’ access to financial products. It may thus be interesting and important to study the financial literacy and the risky asset holding behaviour of Chinese rural households in future research.

References

Agarwal, S., J. C. Driscoll, X. Gabaix, and D. Laibson, 2009, The age of reason: Financial decisions over the life-cycle with implications for regulation. (SSRN) Available at: http://ssrn.com/abstract=973790. Atella, V., M. Brunetti, and N. Maestas, 2012, Household portfolio choices, health status and health care systems: a cross-country analysis based on SHARE, Journal of Banking and Finance 36, 1320–1335. Atkinson, A., and F. Messy, 2012, Measuring Financial Literacy: Results of the OECD/ International Network on Financial Education (INFE) Pilot Study (OECD Publishing, Paris). Balloch, A., A. Nicolae, and D. Philip, 2015, Stock market literacy, trust, and participation, Review of Finance 19, 1925–1963. Barber, B. M., and T. Odean, 2001, Boys will be boys: gender, overconfidence, and common stock investment, The Quarterly Journal of Economics 116, 261–292. Bernheim, B. D., and D. M. Garrett, 2003, The effects of financial education in the workplace: evidence from a survey of households, Journal of Public Economics 87, 1487–1519. Bertocchi, G., M. Brunetti, and C. Torricelli, 2011, Marriage and other risky assets: a portfolio approach, Journal of Banking & Finance 35, 2902–2915. Bosshardt, W., and W. B. Walstad, 2014, National standards for financial literacy: rationale and content, The Journal of Economic Education 45, 63–70. Bricker, J., L. J. Dettling, A. Henriques, J. W. Hsu, L. Jacobs, K. B. Moore, S. Pack, J. Sabelhaus, J. Thompson and R. A. Windle, 2017, Changes in U.S. family finances from 2013 to 2016: evidence from the survey of consumer finances. Available at: https://www.federalreserve.gov/publications/files/scf17.pdf.

Bucher-Koenen, T., and A. Lusardi, 2011, Financial literacy and retirement planning in Germany, Journal of Pension Economics & Finance 10, 565–584. Bumcrot, C., J. Lin, and A. Lusardi, 2013, The geography of financial literacy, Numeracy 6, 1–16. Campbell, J. Y., 2006, Household finance, The Journal of Finance 61, 1553–1604. Cardak, B. A., and R. Wilkins, 2009, The determinants of household risky asset holdings: Australian evidence on background risk and other factors, Journal of Banking and Finance 33, 850–860. Carlin, B. I., and D. T. Robinson, 2012, What does financial literacy training teach us?, The Journal of Economic Education 43, 235–247. Christelis, D., T. Jappelli, and M. Padula, 2010, Cognitive abilities and portfolio choice, European Economic Review 54, 18–38. Cole, S., T. Sampson, and B. Zia, 2011, Prices or knowledge? What drives demand for financial services in emerging markets?, The Journal of Finance 66, 1933–1967. Collins, J. M., 2010, The impacts of mandatory financial education: evidence from a randomized field study, Journal of Economic Behavior and Organization 95, 146–158. Fornero, E., and C. Monticone, 2011, Financial literacy and pension plan participation in Italy, Journal of Pension Economics & Finance 10, 547–564. Fratantoni, M. C., 1998, Homeownership and investment in risky assets, Journal of Urban Economics 44, 27–42. Halko, M., M. Kaustia, and E. Alanko, 2012, The gender effect in risky asset holdings, Journal of Economic Behavior and Organization 83, 66–81. Heaton, J., and D. Lucas, 2000, Portfolio choice and asset prices: the importance of entrepreneurial risk, The Journal of Finance 55, 1163–1198. Hung, A., A. M. Parker, and J. Yoong, 2009, Defining and measuring financial literacy. RAND Working Paper Series WR-708. Available at SSRN: http://ssrn.com/abstrac t=1498674. Jappelli, T., and M. Padula, 2013, Investment in financial literacy and saving decisions, Journal of Banking and Finance 37, 2779–2792. Jappelli, T., and M. Padula, 2015, Investment in financial literacy, social security, and portfolio choice, Journal of Pension Economics & Finance 14, 369–411. Klapper, L., and G. A. Panos, 2011, Financial literacy and retirement planning: the Russian case, Journal of Pension Economics & Finance 10, 599–618. Love, D. A., 2010, The effects of marital status and children on savings and portfolio choice, Review of Financial Studies 23, 385–432. Luhrmann,€ M., M. Serra-Garcia, and J. Winter, 2015, Teaching teenagers in finance: does it work?, Journal of Banking and Finance 54, 160–174. Lusardi, A., and O. S. Mitchell, 2007, Baby boomer retirement security: the roles of planning, financial literacy, and housing wealth, Journal of Monetary Economics 54, 205–224. Lusardi, A., and O. S. Mitchell, 2011, Financial literacy around the world: an overview, Journal of Pension Economics & Finance 10, 497–508. Lusardi, A., and O. S. Mitchell, 2014, The economic importance of financial literacy: theory and evidence, Journal of Economic Literature 52, 5–44. Markowitz, H., 1952, Portfolio selection, The Journal of Finance 7, 77–91. Newey, W. K., 1987, Efficient estimation of limited dependent variable models with endogenous explanatory variables, Journal of Econometrics 36, 231–250. OECD, 2015, National Strategies for Financial Education: OECD/INFE Policy Handbook. Available at: http://www.oecd.org/daf/fin/financial-education/National- Strategies-Financial-Education-Policy-Handbook.pdf.

Poterba, J. M., and A. Samwick, 2001, Household portfolio allocation over the life cycle, in: S. Ogura, T. Tachibanaki, D. A. Wise, eds., Aging Issues in the United States and Japan (University of Chicago Press, Chicago), 65–104. Rosen, H. S., and S. Wu, 2004, Portfolio choice and health status, Journal of Financial Economics 72, 457–484. Sekita, S., 2011, Financial literacy and retirement planning in Japan, Journal of Pension Economics & Finance 10, 637–656. Van Rooij, M., A. Lusardi, and R. Alessie, 2011, Financial literacy and stock market participation, Journal of Financial Economics 101, 449–472. Walstad, W. B., K. Rebeck, and R. B. Butters, 2013, The test of economic literacy: development and results, The Journal of Economic Education 44, 298–309. World Federation of Exchange, 2015, Major stock exchanges. Available at: https://en. wikipedia.org/wiki/List_of_stock_exchanges#Major_stock_exchanges. Xiao, J. J., and B. O’Neill, 2016, Consumer financial education and financial capability, International Journal of Consumer Studies 40, 712–721. Yin, Z., Y. Wu, and L. Gan, 2015, Financial availability, financial market participation and household portfolio choice, Economic Research Journal 3, 87–99 (In Chinese).

Appendix I

Questionnaire for the ﬁnancial literacy

In OECD/ Questions DHS

Basic financial literacy Division Imagine that five brothers are given a gift of ￥10000. If the OECD brothers must share the money equally, how much does each brother receive? Time deposit What do you think the interest rate is of the 1 year time deposit? No interest rate i) <1% ii) 1–5% iii) 5–10% iv) >10% Calculation of Suppose you deposit ￥10000 into a savings account with a OECD/ simple interest guaranteed annual interest rate of 3%. You neither deposit DHS and principal additional payments into this account nor withdraw money. What would the account balance be at the end of the first year, after the interest payment? i) exactly ￥10300 ii) greater than ￥10300 iii) less than ￥10300 Compound and what would the account balance be at the end of the second OECD/ interest year? DHS i) exactly ￥10600 ii) greater than ￥10600 iii) less than ￥10600 Inflation Imagine that the annual interest rate of your savings account is OECD/ 3% and that annual inflation is 5%. After 1 year, how much DHS would you be able to buy with the money in this account? i) more than today ii) the same; iii) less than today Time-value of Suppose you can receive ￥100000 today, and your brother will OECD/ money receive ￥100000 3 years later. Who is richer because of the DHS income?

(continued)

Table (continued)

In OECD/ Questions DHS

i) you ii) your brother iii) both are equally rich Risk and return An investment with a high return is likely to be high risk. OECD i) true ii) false Advanced financial literacy Bank function Which of the following banks is responsible for monetary No policymaking and implementation? i) Bank of China ii) Industrial and Commercial Bank of China iii) People’s Bank of China iv) China Construction Bank Risky assets Normally, which asset displays the highest fluctuations over DHS time? i) Savings accounts ii) Bonds iii) Stocks iv) Mutual Funds Diversification It is usually possible to provide a safer return by investing in a OECD/ single stock instead of a stock mutual fund. DHS i) True ii) False Knowledge of What happens if you buy the stock of company X? DHS stocks i) You have loaned money to company X; ii) You become a shareholder of company X; iii) In the long term, you are a shareholder of company X, but in short term, you are a lender; iv) None of the above Knowledge of Which statement concerning mutual funds is correct? DHS mutual funds i) A fund with a low price is supposed to provide a high return; ii) Mutual funds can usually invest in several assets, for example, invest in both stocks and bonds; iii) Mutual funds usually pay a guaranteed rate of return that depends on their past performance; iv) None of the above Knowledge of Which statement concerning financial products sold in No commercial commercial banks is correct? bank i) Financial products may provide a negative return similar to financial other risky assets; ii) Financial products are as safe as savings products accounts are and will not lose the principal at minimum; iii) The expected and actual return of a financial product are equivalent; iv) None of the above Knowledge of Which of the following statements specifies the main function DHS stock market of the stock market? i) The stock market helps predict stock earnings; ii) The stock market increases the price of stocks; iii) The stock market brings people who want to buy stocks together with people who want to sell stocks; iv) None of the above

The last column indicates the sources of the questions. Questions with ‘No’ in the last column are created by the researchers of the Chinese survey.

Appendix II

Factor loadings of the Financial Literacy Index

Factor loading

Financial Literacy_Factor Interest Rate_Correct 0.1250 Calculation of Interest & Principal_Correct 0.1803 Compound Interest_Correct 0.1734 Inflation_Correct 0.1657 Time-Value of Money_Correct 0.1337 Risk and Return_Correct 0.0959 Bank Function_Correct 0.0943 Risky Assets_Correct 0.1373 Diversification_Correct 0.1063 Knowledge of Stock_Correct 0.0789 Knowledge of Mutual Fund_Correct 0.0942 Knowledge of Commercial Bank Financial Products_Correct 0.1349 Knowledge of Stock Market_Correct 0.1216 Basic Financial Literacy_Factor Interest Rate_Correct 0.1574 Calculation of Interest & Principal_Correct 0.3366 Compound Interest_Correct 0.2972 Inflation_Correct 0.1977 Time-Value of Money_Correct 0.1719 Risk and Return_Correct 0.1194 Advanced Financial Literacy_Factor Bank Function_Correct 0.1573 Risky Assets_Correct 0.2007 Diversification_Correct 0.1970 Knowledge of Stock_Correct 0.1551 Knowledge of Mutual Fund_Correct 0.1926 Knowledge of Commercial Bank Financial Products_Correct 0.2373 Knowledge of Stock Market_Correct 0.2269 Advanced Financial Literacy_Factor2 Bank Function_Correct 0.0533 Risky Assets_Correct 0.0956 Diversification_Correct 0.0840 Knowledge of Stock_Correct 0.0413 Knowledge of Mutual Fund_Correct 0.0554 Knowledge of Commercial Bank Financial Products_Correct 0.0674 Knowledge of Stock Market_Correct 0.0679 Bank Function_Unknown 0.0951

(continued)

Table (continued)

Factor loading

Risky Assets_Unknown 0.1553 Diversiﬁcation_Unknown 0.1000 Knowledge of Stock_Unknown 0.1399 Knowledge of Mutual Fund_Unknown 0.1256 Knowledge of Commercial Bank Financial Products_Unknown 0.1401 Knowledge of Stock Market_Unknown 0.1961