2010 to RMB 37.9 billion in 2015 if the retirement age of female workers is increased gradually from 55 to 60 during that period (Figure 12). The pension fund annual balance increases further from RMB 47.8 billion in 2020 to RMB 133.1 billion in 2025 if the retirement age for all workers is increased gradually from 60 to 65 during that period.

Simulation results also show that increasing the retirement age will promote growth in GDP, investment, and private consumption (Figure 13). The effect on the GINI coefficient, however, is not significant after expanding coverage to rural areas and adjusting the retirement age gradually. This could be attributable to rural-to-urban income transfer in the initial years since the urban population is aging faster than the rural population. This might worsen income distribution since the rural population is much poorer than the urban population. Thus to maintain an equitable income distribution, it may not be advisable to expand pension coverage to rural enterprises too soon.

If a new social security tax is levied, the old fragmented system will become unified across the country, and the reformed pillar 1 will remain financially sustainable, even if the tax rate is lower than specified in State Council Document 26 (Figure 14). Here, raising the retirement age will improve the funding situation further, allowing some accumulation of reserve funds in pillar 1. Simulation results also show that increasing the retirement age will promote growth in GDP, investment, and private consumption (Figure 15).

# **Conclusions**

Ihis paper examines the impacts of various design options for pension system reform on the sustainability of the system and on overall economy growth. We are able to combine the CGE model and population growth model into a recursive dynamic framework, which provides a new flexible tool to simulate various pension reform plans in a general equilibrium setting. We differentiate production and employment by ownership type and organize the demographic data in a matrix with four dimensions. We then conduct three sets of simulations with 18 experiments, (1) limited changes within the current system (no structure reform), (2) a structural reform (phasing out notional individual account) and financing the transition cost by taxes, (3) various options after the proposed structural reform including levying a new social security tax. Results from simulations are promising and summarized in the executive summary.

Our simulation results provide useful insights for the design of Chinese pension system reform and illustrate how CGE models can be valuable tools for evaluating different pension policies. However, several important limitations need to be mentioned. First, few CGE models have been able to incorporate rational expectations into the behavior of agents (though there are perfect foresight models). In our recursive dynamic model, agents adjust their behavior according to information received in the last period. Thus, the existence of a future pension benefit will not affect agents' saving behavior today. Second, the model does not specify explicitly the different behavior rules of the various types of firms in China, but assumes that all operate to maximize profit. A third limitation is that the model may overestimate the impact of various pension reform policies on macroeconomic variables because it does not include an explicitly specified financial market. Gross national savings, including pension reserves, are assumed to become gross investment, implying a perfect capital market, which is far from the reality in China. It is assumed that pension funds can earn interest that is equal to the average return on capital, except that in experiment 4 and 5 interest rates are assumed as zero. To our knowledge, only one paper had attempted to incorporate financial market into a 33