Table 1 presents means, median, 25th percentile, and 75th percentile of all kinds of assets. These assets are defined and classified based on the definitions of Friend and Blume’s paper (1975).
From Table 2, the mean value of pure risk of RRAI in 2007 is 0.5149, the mean value of pure risk of RRAI in 2009 is 0.7464, the mean value of pure and mixed risk of RRAI in 2007 is 0.5045, and the mean value of pure and mixed risk of RRAI in 2009 is 0.7318. All of them are between 0 and 1. The value of RRAI in 2009 are greater than in 2007, so on average investors in 2009 are more risk aversion than those in 2007.
From Table 3, in average, the median value for income in 2007 is $50,000, and the median value for income in 2009 is $49,000. The median value for financial assets in 2007 is $30,000, and the median value for financial assets in 2009 is $29,500.
These values of them are similar with the paper of Bricker, Bucks, Kennickell, Mach, and Moore (2011). The percentage of households who suffered capital loss is 3.8% in 2007, but it is 14.5% in 2009. The percentage of households who suffered capital gain is 19.6% in 2007, but it decreases to 11.76% in 2009. Similarly, in 2007 the percentage of the other behavioral variables is 0%, and all of the percentage increases in 2009.
The regression results of snake-bit effect and house money effect are given in Table 4 panel A. In model (1), we focused on snake-bit effect and change in RRAI of pure risk assets, the signs for the capital loss, bad investment, bad health, and bankruptcy variables are positive. The t-statistic for capital loss variable is significant at the 0.01 level, the t-statistic for bad investment variable is significant at the 0.05
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level, and the t-statistic for bad health variable is significant at the 0.1 level. They all mean when you had any bad experience in the period from 2007 to 2009, bad investment results in the period of financial crisis, and your health got worse off than you are before, made the change in RRAI greater what means householders became more risk aversion. The results match with our hypothesis. The sign for age variable is positive and significant at the 0.01 level. It indicated that the more in age, the more risk aversion. In this financial crisis period, most people are relative risk aversion. The signs for the college and high school variables are negative, and high school variable is significant at the 0.01 level. It indicates that the higher level of education, the more risk seeking. The sign for change in net worth from 2007 to 2009 variable is positive and significant at the 0.01 level. It indicates that if you increased in net worth, you are a risk aversion investor. In other words, in the period of financial crisis maybe if you are a risk aversive investor, you will be able to increase your net worth. The sign for Dwealth variable is positive and significant at the 0.01 level. People with wealth reached the 90th percentile, are more risk aversion. Based on 2008 and 2010 world wealth report information, it showed that the high net worth individuals’ allocation of financial assets in fixed income changed from 27% to 31%, and in equities changed from 33% to 29%. That both represented the high net worth individuals are more risk aversion. In model (2), we run the regression once more with change in RRAI of pure and mixed risk assets instead of change in RRAI of pure risk assets. The results are consistent with the results we mentioned. In model (3) and (4), we focus on testing house money effect. First, we use change in RRAI of pure risk assets to run. The signs for the wage and investment variables are negative, and the t-statistics of wage variable is significant at the 0.05 level. If the households got more money in wage against the others, they are more risk seeking. The result is matched with our
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hypothesis 1.2. We use change in RRAI of pure and mixed risk assets instead of change in RRAI of pure risk assets running the regression once more. The results are consistent with the results mentioned. Especially, the sign for the investment variable is negative and its t-statistics is significant at the 0.05 level. If the households got a good experience in investment, they are more risk seeking. However, the sign for the capital gain is positive and its t-statistics is significant at the 0.05 level. The result is beyond our imagination. According to Burman and Ricoy’s paper-Capital gains and the people who realize them (1997), they said “people who have higher incomes realize a large fraction of the taxable capital gains. In fact, most of the tax returns that report capital gains are filed by people whose incomes are under $50,000 a year. But their capital gains are very small compared with those of taxpayers who have high incomes.” So, the possible explanation is that realizing capital gain are the people who had higher incomes, and higher incomes people are more risk aversion in this period, based on world wealth report information. In the model (5) and (6), we pool all the variable mentioned, and run the regression. The results of the both regressions are consistent.
We separate households into three groups by net worth, and use the highest one-third group as my target group. To run the regression model (10) to (12) again, the results are showed in Table 4 panel B. The signs for the capital loss, bad investment, bad health, and no wage variables are positive. The t-statistic for capital loss variable is significant at the 0.01 level, the t-statistic for bad investment variable is significant at the 0.05 level, the t-statistic for bad health variable is significant at the 0.05 level, and the t-statistic for no wage variable is significant at the 0.01 level. They all mean when you had any bad experience in the period from 2007 to 2009, bad investment results in the period of financial crisis, and your health got worse off than
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you were before, made the change in RRAI greater what means householders became more risk aversion. The sign for the investment variable is negative, and the t-statistics of investment variable is significant at the 0.01 level. If the households got good experience in investing against the others, they are more risk seeking. These results in Table 4 panel B are consistence with the results in Table 4 panel A.
Table 5 displays the results of hypothesis 2. The model (1), fixed-effect model, is designed to test whether RRAI of regular account is bigger than RRAI of retirement account. It’s a cross-sectional data. The sign for retirement variable is negative and its t-statistics is significant at the 0.01 level. The RRAI of retirement account is less than the RRAI of regular account. That is, the retirement account (relative long-term account) is more risk seeking than the regular account (relative short-term account).
Risk aversion decreases with age and education increasing. The more income you got, and you are more risk seeking. If the households whose income is higher than property level or net worth is above 90th percentile are more risk seeking. RRAI of 2009 is bigger than RRAI of 2007. It indicated that, in general, people in 2009 are more risk aversion than in 2007.
From Table 5, the model (2) is designed to test whether the change in RRAI of retirement is less or not. The results match with our hypothesis 2. The sign of retirement variable is negative and its t-statistic is significant at the 0.01 level. The change in RRAI of retirement account is less than change in RRAI of regular account.
That is, the relative long-term account is more risk seeking than the relative short-term account. On the other hand, we find the change in RRAI increased with age, education, and change in income. But, the sign of Dincome variable is negative and its t-statistics is significant at the 0.01 level. Change in RRAI of the households whose income is higher than property level is less than the others. That is, those households whose income is higher are more risk seeking.
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