nep-age New Economics Papers
on Economics of Ageing
Issue of 2023‒07‒31
five papers chosen by
Claudia Villosio
LABORatorio R. Revelli

  1. CBO’s 2023 Long-Term Projections for Social Security By Congressional Budget Office
  2. How Do Firms Respond to State Retirement Plan Mandates? By Adam Bloomfield; Kyung Min Lee; Jay Philbrick; Sita Slavov
  3. The Welfare Economics of Reference Dependence By Daniel Reck; Arthur Seibold
  4. Machine Learning and Hamilton-Jacobi-Bellman Equation for Optimal Decumulation: a Comparison Study By Marc Chen; Mohammad Shirazi; Peter A. Forsyth; Yuying Li
  5. Demography and migration processes in Russia in 2022 By Makarentseva M.; Mkrtchyan Nikita; Florinskaya Yulia; Khasanova Ramilya

  1. By: Congressional Budget Office
    Abstract: In CBO’s projections, spending for Social Security increases rapidly in relation to gross domestic product over the next decade as the large baby-boom generation continues to reach retirement ages. Growth then slows as members of that generation die and people from later generations become eligible for Social Security, but spending continues to rise throughout the 75-year projection period because life expectancy increases. Unlike outlays, revenues for Social Security are projected to remain stable in relation to the size of the economy.
    JEL: H50 H55 H60 H68 J26
    Date: 2023–06–29
  2. By: Adam Bloomfield; Kyung Min Lee; Jay Philbrick; Sita Slavov
    Abstract: This paper investigates the effect of state retirement plan mandates on the supply of employer-sponsored retirement plans (ESRPs) by firms. These policies require employers to either (1) offer ESRPs to workers or (2) facilitate automatic payroll deductions that are deposited into individual retirement accounts (IRAs) established for workers by the state. In this paper, we utilize individual-level data from the Current Population Survey (CPS) and firm-level data from Form 5500 filings to examine the effect of these automatic-enrollment IRA (“auto-IRA”) policies on employer decisions to offer, and worker inclusion in, ESRPs. We exploit variation in the timing of implementation across states and firm size categories and estimate that auto-IRA policies increase the probability that an individual works for a firm with an ESRP by roughly 3 percent, and the probability that the individual participates in that ESRP by 33 percent. These policies also increase the number of ESRP participants at the average firm in our sample by 3-5 percent.
    JEL: D14 H75 J26
    Date: 2023–06
  3. By: Daniel Reck; Arthur Seibold
    Abstract: Empirical evidence suggests that individuals often evaluate options relative to a reference point, especially seeking to avoid losses. We undertake the first welfare analysis under reference-dependent preferences. We characterize the welfare impact of changes in reference points and prices, decomposing these into direct and behavioral effects. The sign of direct and behavioral effects depends on the form of reference-dependent payoffs; which of these effects matter for welfare depends on whether reference dependence reflects a bias or a normative preference. We derive sufficient statistics formulas quantifying the social welfare effects of changes in reference points and prices in terms of estimable reduced-form parameters and normative judgments. We illustrate these findings with an empirical application to reference dependence exhibited in German workers' retirement decisions. We find positive social welfare effects of increasing the Normal Retirement Age, but ambiguous effects of financial incentives to postpone retirement.
    JEL: D60 D90 H55
    Date: 2023–06
  4. By: Marc Chen; Mohammad Shirazi; Peter A. Forsyth; Yuying Li
    Abstract: We propose a novel data-driven neural network (NN) optimization framework for solving an optimal stochastic control problem under stochastic constraints. Customized activation functions for the output layers of the NN are applied, which permits training via standard unconstrained optimization. The optimal solution yields a multi-period asset allocation and decumulation strategy for a holder of a defined contribution (DC) pension plan. The objective function of the optimal control problem is based on expected wealth withdrawn (EW) and expected shortfall (ES) that directly targets left-tail risk. The stochastic bound constraints enforce a guaranteed minimum withdrawal each year. We demonstrate that the data-driven approach is capable of learning a near-optimal solution by benchmarking it against the numerical results from a Hamilton-Jacobi-Bellman (HJB) Partial Differential Equation (PDE) computational framework.
    Date: 2023–06
  5. By: Makarentseva M. (RANEPA); Mkrtchyan Nikita (RANEPA); Florinskaya Yulia (RANEPA); Khasanova Ramilya (RANEPA)
    Abstract: In 2022, natural population decline was equal to nearly 600, 000 persons (599, 600) or 4.1‰ (per mille) which is much below the level of a natural decline in the population in 2021 (1, 042, 700, 7.2‰) (Fig. 13). Such a decrease was feasible owing to the return of the mortality rate to the normal (non-pandemic) level. Experts approached the beginning of 2022 with negative expectations regarding the birth rate dynamics and the demographic situation as a whole. First, Russia is approaching the “bottom” as regards the number of women of the most active reproductive age (Fig. 14). With each year, a large generation of the late 1980s makes a smaller and smaller contribution to the current birth rate. All subsequent cohorts of women are substantially smaller in number. Second, as of the beginning of 2022 an upcoming decrease in the intensity of childbirth was mainly driven by the COVID-19 pandemic in 2021 and the accompanying economic stagnation. Now we can say that the effect of the coronavirus pandemic on the birth rate has become inseparable in Russia from the effects of subsequent developments (the beginning of the special military operation, the sanctions regime and the economic crisis) since Autumn 2022.
    Keywords: Russian economy, population decline, demographic trends, childbirth, migration, internal migration, temporary migration, long-term migration
    JEL: J11 J13 J61 J62
    Date: 2023

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