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The Chinese pension system is highly fragmented and decentralized, with governance standards, pension fund management practices, their regulation and supervision varying considerably both across the funded components of the Chinese pension system and across provinces. This paper describes the key components of the system, highlights the progress made to date and identifies remaining weaknesses, in regard to information disclosure, the governance framework and pension fund management standards.

Using a unique data set, we document two secular trends in the shift from centralized to decentralized pension fund management over the past few decades. First, across asset classes, sponsors replace generalist balanced managers with better-performing specialists. Second, within asset classes, funds replace single managers with multiple competing managers following diverse strategies to reduce scale diseconomies as funds grow larger relative to capital markets. Consistent with a model of decentralized management, sponsors implement risk controls that trade off higher anticipated alphas of multiple specialists against the increased difficulty in coordinating their risk-taking and the greater uncertainty concerning their true skills.

With the emergence of a variety of pension service institutions, how to choose a suitable institution has become a strategic decision-making problem faced by pension service demanders. To solve this problem, this study identifies key evaluation criteria of pension service institutions through the analysis of the relevant literature. Then, this study proposes a mixed aggregation by comprehensive normalization technique (MACONT) with a personalized quantifier to select pension service institutions, where the personalized qualifier with cubic spline interpolation is used to derive the position weights of criteria, and the MACONT is improved to determine the ranking of alternatives. A case study about the selection of pension service institutions is provided to verify the feasibility of the proposed model. It is found that the proposed method is effective in dealing with heterogeneous evaluation information, and the personalized quantifiers can be combined with MACONT methods to obtain an optimal solution associated with the attitude of pension service demanders. The identified key evaluation criteria are not only significant for pension service demanders, but also conducive to the further improvement of property management related to pension services.

I exploit sharply nonlinear funding rules for defined benefit pension plans in order to identify the dependence of corporate investment on internal financial resources in a large sample. Capital expenditures decline with mandatory contributions to DB pension plans, even when controlling for correlations between the pension funding status itself and the firm's unobserved investment opportunities. The effect is particularly evident among firms that face financing constraints based on observable variables such as credit ratings. Investment also displays strong negative correlations with the part of mandatory contributions resulting solely from unexpected asset market movements.

We apply a dynamic stochastic control (DSC) approach based on an open-loop linear feedback policy to a classical asset-liability management problem as the one faced by a defined-benefit pension fund (PF) manager. We assume a PF manager seeking an optimal investment policy under random market returns and liability costs as well as stochastic PF members’ survival rates. The objective function is formulated as a risk-reward trade-off function resulting in a quadratic programming problem. The proposed methodology combines a stochastic control approach, due to Primbs and Sung (IEEE Trans Autom Control 54(2):221–230, 2009), with a chance constraint on the PF funding ratio (FR) and it is applied for the first time to this class of long-term financial planning problems characterized by stochastic asset and liabilities. Thanks to the DSC formulation, we preserve the underlying risk factors continuous distributions and avoid any state space discretization as is typically the case in multistage stochastic programs (MSP). By distinguishing between a long-term PF liability projection horizon and a shorter investment horizon for the FR control, we avoid the curse-of-dimensionality, in-sample instability and approximation errors that typically characterize MSP formulations. Through an extended computational study, we present in- and out-of-sample results which allows us to validate the proposed methodology. The collected evidences confirm the potential of this approach when applied to a stylized but sufficiently realistic long-term PF problem.

As a sovereign wealth fund, the $1 trillion Norwegian Government Pension Fund-Global ('the Oil Fund'), which is managed by Norges Bank Investment Management on behalf of the welfare of Norway's citizens, is supposed to be a flagship for socially responsible investments through its Council of Ethics. However, its investment in Delta Topco, the holding company of Formula 1 world championship that, through Formula One Group, brokered a deal with Russia to host a Formula 1 Grand Prix in 2014, raises the question of whether the Oil Fund should enhance its due diligence processes. Although no evidence of corruption related to the race is introduced, the complex relation between financial logic and the world of sports still raises questions about the ethical solidity of the Oil Fund's investment. Drawing upon reports of the relationship between political economy and sporting events, this paper therefore analyses, in light of the Oil Fund's ethical guidelines, the complexities of its investment in Delta Topco. As a result, it is argued that a new set of examination methods by the Council of Ethics may be warranted.

Pension funds provide income in retirement years. To accomplish this, they collect monthly contribution throughout the working life of beneficiaries and engage in investment activities. Rising inflation rates, higher life expectancy, increment to payments make it difficult for contributions alone to suffice the payment of benefits sustainably. Thus, for pension funds to fulfill their organisational objective of providing income for beneficiaries in their retirement years, investment has to be managed well. In addition to achieving the purpose of social insurance, the investment of pension funds boosts economic growth, resource mobilisation and operation of stock markets. Understanding the importance of pension fund management, this research attempts to assess the pension fund management practice of Public Servant Social Security Administration (PSSSA) and Private Organisation Employees Social Security Administration (POESSA). It attempts to assess the investment identification procedure, measure of performance, opportunities and challenges faced. It is descriptive research, where interview of respondents was analysed qualitatively to assess the aforementioned objectives. The researcher found that both PSSSA and POESSA used to engage in investment activities per directives of MOFED (previously MoF), but since 2022, they are in the process of drafting their own investment guideline and policy. The measurement and accounting standard used to measure performance were found to be inappropriate. The primary opportunity for the pension funds was participating in the capital market soon to emerge. Threats to the pension funds were lack of skilled manpower, rising contribution payments, inflation and behaviour of certain beneficiaries. The researchers recommends the critical evaluation of guidelines, proper measurement and disclosure of performance, account for the pension fund using IPSAS, train and outsources to contest the lack of skilled manpower.

Managers appear to manipulate firm earnings through their characterizations of pension assets to capital markets and alter investment decisions to justify, and capitalize on, these manipulations. Managers are more aggressive with assumed long-term rates of return when their assumptions have a greater impact on reported earnings. Firms use higher assumed rates of return when they prepare to acquire other firms, when they are near critical earnings thresholds, and when their managers exercise stock options. Changes in assumed returns, in turn, influence pension plan asset allocations. Instrumental variables analysis indicates that 25 basis point increases in assumed rates are associated with 5 percent increases in equity allocations.

This paper studies optimal defined-contribution (DC) pension management under stochastic interest rates and expected inflation. In addition to financial risk, we consider the risk of pre-retirement death and introduce life insurance to the pension account as an option to manage this risk. We formulate this pension management problem as a random horizon utility maximization problem and derive its explicit solution under the assumption of constant relative risk aversion utility. We calibrate our model to the U.S. data and demonstrate that the pension member’s demand for life insurance has a hump-shaped pattern with age and a U-shaped pattern with the real interest rate and expected inflation. The optimal pension account balance in our model resembles a variable annuity, wherein the death benefits are endogenously determined and depend on various factors including age, mortality, account balance, future contributions, preferences, and market conditions. Our study suggests that offering variable annuities with more flexible death benefits within the DC account could better cater to the bequest demands of its members.