Household portfolio allocation, uncertainty, and risk

Brown, Sarah; Gray, Daniel; Harris, Mark N.; Spencer, Christopher

doi:10.1016/j.jempfin.2021.05.004

Cited by 14 publications

(9 citation statements)

References 35 publications

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“…Expected utility theory assumes that markets are efficient and investors are perfectly rational, and that investors allocate assets based on expected utility maximization (Neumann and Morgenstern, 2007). The uncertainty of economic and social development breaks the perfect market assumption, and the influence of individual psychological expectations on household financial asset allocation behavior cannot be ignored (Gollier and Pratt, 1996;Brown et al, 2021). As uncertainty about future household income increases substantially, residents' precautionary saving incentives increase (Leland, 1968;Deaton, 1989), increasing the likelihood that households will change their portfolios (Yue et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Impact of the COVID-19 pandemic on household financial asset allocation: A China population study

2022

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During the COVID-19 pandemic, the Chinese government implemented a “dynamic zero” epidemic prevention policy, which led to an increase in the likelihood of business shutdowns, increased uncertainty about people's income, and changes in people's psychological expectations, which in turn influenced their behavioral choices. This study aims to understand the impact of COVID-19 and other major public health emergencies on household financial asset allocation. To do so, we conducted an online survey of 712 people in China to measure household financial asset allocation behavior during three different time periods: pre-pandemic, mid-pandemic, and post-pandemic. At the same time, we analyzed the impact of sociodemographic characteristics on risk attitudes and the differences in household asset allocation decisions at different pre-pandemic time points among people with different risk attitudes. The results show that household financial asset allocation changed significantly before, during, and after the pandemic, and residents' precautionary savings increased. In addition, gender, education level, occupation, and annual income have significant effects on risk preferences. The pandemic leads to increased uncertainty in economic and social development, people's psychological expectations of economic development play an important role in household financial asset allocation.

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Section: Introductionmentioning

confidence: 99%

Impact of the COVID-19 pandemic on household financial asset allocation: A China population study

2022

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“…Most studies find that the increased healthcare expenditures as a result of household members experiencing health shocks inevitably affect various aspects of household life, including the time allocation between work and leisure ( 12 ), consumption-savings ratio ( 13 ), and preference for investment risks ( 14 ), forcing the household to adjust their behaviors in making economic-related decisions ( 15 ) and ultimately creating a significant crowding-out effect on other household expenditures, such as income, labor supply, and education ( 16 ). This effect is more evident in rural households and households with a medium-level income ( 17 , 18 ). Further, when an individual household member suffers health shock, the shock will spread within the entire household ( 19 ) and indirectly affect the economic life of other household members, thereby increasing the probability that the entire household will fall into relative poverty ( 20 ).…”

Section: Introductionmentioning

confidence: 93%

Health Shocks and Household Education Burden—A Study From the Perspective of Relative Poverty Alleviation in China

Wang

Chu

2022

Front. Public Health

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Health shocks and household education burden influence levels of expenditure on healthcare and education, which are two major non-discretionary expenditures for households. From the perspective of relative poverty alleviation in China and based on the peer effects theory, this study uses the dataset from the rural areas in CFPS database and employs the spatial Durbin model and spatial DID model to investigate—when a household suffers health shocks—the influence of such impact on the education burden of closely related households and to test the effect of single rescue policy in this circumstance. Further, this study employs a spatial mediating effect model to analyze the spatial transmission mechanism. The results indicate that when a household has health shocks, it can aggravate the education burden of closely related households through inter-household social networks. The findings substantiate that the targets of different rescue policies have cross effects and that single rescue policy does not have significant effect on the targets of other policies. To avoid the situation where rescue policies operate in silos and to reduce the internal coordination cost between different policies within a system, a coordinating mechanism should be established between different rescue policies to better alleviate relative poverty.

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“…By contrast, using Japanese data, Iwaisako et al [22] reveal that the quantity of risky assets held by a household increases with the age of the household head increases. Elderly households (as proxied by the age of the household head) tend to invest more in stocks and less in savings [3]. Based on this stream of research, we propose the hypothesis of the structural effects of aging on financial markets.…”

Section: Literature Review Andmentioning

confidence: 99%

“…Although virtually every country has been experiencing growth in the number and proportion of the elderly in their population [1], aging's effects on the financial market remains a complex question to be answered. Aging may influence the financial market by affecting the scale or structure of microagents' financial asset allocation [2][3][4]. erefore, two kinds of hypotheses could be proposed concerning the scale and structure of the impacts of demographic change on the financial market.…”

Section: Introductionmentioning

confidence: 99%

“…Existing studies on the effects of aging on the financial market have been conducted mainly from a macroperspective using theoretical methods [5]. Limited research on the relationship between aging and financial assets allocation has been conducted using microdatasets [3,6], based on which our scale hypothesis and structural hypothesis are proposed. However, existing microlevel studies mainly focus on the relationship between the age of individuals and their financial knowledge, cognitive ability, and risk preference [7,8], but not directly explore the influence of aging on financial asset allocation.…”

Section: Introductionmentioning

confidence: 99%

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Complexity between Aging and the Structure of Financial Market: Empirical Evidence from Microdata

Wang

Luo

et al. 2022

Complexity

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By empirically testing the scale and structure hypotheses of aging’s impacts on the financial market using Tobit, FRM, and Heckman selection models, this paper proves that the number and proportion of elderly family members change the structure of families’ financial assets, though without significant effects on their overall size. Specifically, aging increases the share of cash and deposits in families’ total financial assets and decreases both the quantity and percentage of investment in risky assets. One more family member aged sixty and over, the risky assets decline by 5, 500RMB and its share decreases by 8.8 percent. A Heckman two-step model verifies the robustness of our results. The heterogeneity analysis reveals that aging plays different roles in different types of financial assets.

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Household portfolio allocation, uncertainty, and risk

Cited by 14 publications

References 35 publications

Impact of the COVID-19 pandemic on household financial asset allocation: A China population study

Impact of the COVID-19 pandemic on household financial asset allocation: A China population study

Health Shocks and Household Education Burden—A Study From the Perspective of Relative Poverty Alleviation in China

Complexity between Aging and the Structure of Financial Market: Empirical Evidence from Microdata

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