YANG Jisheng;ZOU Jianwen
With the spread of the COVID-19 epidemic, the external uncertainty of the Chinese economy has increased. As China’s rapid economic growth has always been accompanied by high investment and low consumption, the expansion of domestic demand can no longer rely so heavily on investment for infrastructure construction. Therefore, promoting household consumption has become a more important means for increasing domestic demand in response to external shocks. For many years, the Chinese economy has faced two major problems: deficient household consumption and unbalanced household consumption. Therefore, identifying the behavioral characteristics and structural heterogeneity of household consumption is crucial to any plan for stimulating Chinese household consumption and expanding domestic demand. Concerning the low level of household consumption and the high rate of saving, many previous studies argue that precautionary saving is the key factor in explaining China’s high rate of saving. Studies that investigate Chinese precautionary saving take two main approaches. One approach is, on the basis of a reduced-form regression, to find proxy variables to measure income risk as a means to study the effects of such risk on consumption. The other approach is to derive an equation for measuring the level of precautionary saving based on the Euler equation. However, the abovementioned studies mainly focus on empirically examining the motives for household precautionary saving instead of seeking to identify the mechanism for smoothing of household consumption over the life cycle. On the basis of a life cycle model of income risk, and with reference to data from the 2010, 2012, 2014, and 2016 China Family Panel Studies launched by Peking University, this paper investigated the structural heterogeneity of consumption smoothing over different stages in the life cycles of rural and urban households. First, we estimated the structural parameters by using the simulated moment method for matching actual and simulated life cycle consumption profiles. Then we performed several counterfactual simulations based on the estimated life cycle model. We studied how to improve willingness for increased household consumption by analyzing the influence of precautionary savings. We also investigated how to improve the household capacity for consumption by analyzing the effects of borrowing constraints and income shocks. In addition, we examined the effects of housing costs on the smoothing of household consumption, considering that housing expenses affect motives for household precautionary saving. Last, we analyzed the patterns of household consumption smoothing in relation to consumption insurance. Our findings can be summarized as follows. (1) The consumption smoothing behavior of Chinese households changes when the members are around 45 years old. The motive for precautionary saving increases in young adulthood and weakens after middle age. Borrowing constraints restrict consumption by young households, but these constraints stimulate consumption by middle-aged households. (2) The ability of urban households to smooth their life cycle consumption is much stronger than that of rural households. Rural households also have stronger risk aversion, and they pay more attention to current consumption. Furthermore, rural households have stronger motives for precautionary saving and greater reactions to both borrowing constraints and permanent income shocks. (3) Urban households with low levels of housing wealth face higher income risks, have stronger motives for precautionary saving, and are more susceptible to borrowing constraints than urban households with high levels of housing wealth. (4) The results regarding consumption insurance validate the robustness of the counterfactual simulation results. These results show that the level of consumption insurance against income shock in urban households is significantly higher than that in rural households. Unlike previous studies that examine the Chinese consumption-saving problem on the basis of life cycle models, this paper systematically analyzed the dynamic effects of precautionary motives, borrowing constraints, and income shocks. These analyses indicate ways to improve households’ willingness and capability for consumption. The findings also provide means for perfecting the mechanism by which higher potential for consumption can be realized. In addition, we empirically examine the behavior patterns involved in household consumption smoothing, and we do so with consideration of consumption insurance.
consumption smoothing;life cycle model;consumption insurance;structural parameter
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