The past few weeks have been a bit overwhelming for me, and I wasn’t able to blog as much as I would like to. My class on the effects of taxes and transfers has come to an end (many thanks for Prof. Hotz and my classmates for the intellectual simulation!). In this post and the next two posts, I share my thoughts on the contributions and limitations of the life cycle labor supply models and potential areas for future research.
The main contribution of life cycle models is to expand the margins along which individuals can adjust their behaviors. The earliest models addressed the endogeneity of nonlabor incomes introduced by life time budget constraints while abstracting from endogenous human capital accumulation and uncertainty. Subsequent research has built on this framework and accounted for different sources of uncertainty that might affect individual behavior. Incorporating uncertainty in prices and interest rates into the life cycle model links microeconomics with macroeconomics literature on business cycles and intertemporal labor supply decisions. Models of human capital accumulation highlights the long lasting impact of current labor supply on life cycle earnings. Relaxing the nonseparability constraints on utility allows for habit formation and persistence in tastes for work. In particular, allowing for intertemporally nonseparable budget constraints enables us to jointly model nonlinear taxes on labor incomes and interest rates jointly. These advances allow us to estimate labor supply elasticities more accurately and evaluate the effects of taxes more realistically.
I. Effects of Taxes on Work Incentive
Life cycle labor supply models allow us to estimate intertemporal (Frisch) elasticity, Marshallian compensated elasticity, and Hicksian uncompensated labor supply elasticity more accurately, which has critical implications for optimal tax policies. In a static setting, taxes only changes the relative prices of labor supply to consumption in the current period. In the life cycle setting, however, current tax changes can have a long lasting effect on future periods depending on individual expectations about their future wage profiles and whether the changes in taxes are permanent. The tax changes also affect people on different segments on the tax schedule differently. Progressive taxation introduces disincentive for work because workers receive relative lower after-tax wage rates as they move up the income ladder.
II. Retirement Decisions
One of the key assumptions in the life cycle model is that individuals are forward-looking and have rational expectations. In the earlier models, the length of working periods is taken as exogenous, but retirement decisions are likely to be endogenous. This can affect life cycle human capital investment decisions as the horizon over which the returns will be realized are changing endogenously.
One of the earliest investigation on this issue is Rust (1989). He outlines a dynamic programming problem where individuals maximize expected utility in their remaining life by choosing consumption and the degree of labor force participation (part-time, full-time, non participation). This model highlights the sequential nature of the retirement decision problem and accounts for uncertainty in the state variables including health, marital status, employment, earnings, assets, etc. More recently, French (2005) estimates a life cycle model of retirement behavior where health, wealth, and wages are uncertain and individuals face borrowing constraints. He finds that the tax structures of the Social Security incomes and the pension incomes are key determinants of retirement behavior while Social Security benefit levels, health, and borrowing constraints are less important. Consistent with previous research, he finds little life-cycle variation for prime-age working men and large declines in labor force participation and hours worked among older men near retirement age.
III. Incentives to Invest in Human Capital
The literature has mainly explored two channels of human capital accumulation: schooling or on-the-job training (OJT), and learning-by-doing (LBD). In the former scenario, an individual’s time is allocated between human capital investment, work, and leisure. Learning is rivalrous with working but will increase future wages. In the latter scenario, skills are acquired as a byproduct of working. Without the nonlinearity in budget constraint (introduced by progressive taxes and welfare transfers), lower taxes discourages human capital investment in the OJT scenario but encourages human capital investment in the LBD scenario (as individuals will have a stronger incentive to work). When the budget constraint is nonlinear, however, the effects on human capital investment are more subtle. Heckman (2002) shows that changes in EITC rates will affect different individuals differently depending on the income segment they are located and the the magnitude of the increase in wages brought by human capital investment.
The life cycle perspective is useful for characterizing a broader set of forces that drive the human capital accumulation process. For instance, taxes that privilege certain types of incomes over others creates varying incentives to investment in skills among sub populations with different social-economic status. The fact that interest rates paid on educational loans are not tax deductible while mortgage interests are creates a privilege towards the skilled and the wealthy who are more likely to own homes and can finance their children’s education by taking mortgages. In the long term, this unbalanced treatment might aggravate the income inequality in the US (Heckman, 2000).
IV. Welfare Dependence
The life cycle framework suggests the possibility that welfare recipients might “bank” their benefits, i.e. participate in welfare programs in economic downturns to mitigate negative income shocks. Bitler et al (2014) find evidence that the EITC is stronger counter cyclical for married couples with children.
Participation in welfare programs also affects the future earnings ability and work incentive of welfare recipients. If the goal of the welfare system is to provide a safety net for those in need but to introduce them job-relevant skills, optimal design of the welfare system needs to account for the dynamic considerations in individual decisions of welfare participation. Keane and Wolpin (2002a, 2002b) investigate the long term effects of welfare benefits on economic and demographic behaviors including welfare participation, marriage and fertility, and work and schooling. Approximating decision rules from dynamic optimization, they find that welfare benefit as measured by the current realization of the benefit rule parameters and by their “permanent” means are jointly significant determinants of all the choices they consider.
Another branch of the literature investigates the effectiveness of different training programs on encouraging welfare recipients to work. For example, Hotz et al (2006) highlight the importance of the interactions between labor market conditions after the random treatment of welfare programs and the estimated effects of labor force attachment (LFA) versus human capital development (HCD) training components. They account for differences in the mix and assignment of LFA and HCD programs using non experimental regression adjustment, and find a bigger impact of HCD programs (relative to LFA) on labor force participation and hours worked in the long run.
References are available upon request.