Chapter one makes two novel contributions related to the two workhorse models in the human capital literature: Learning by Doing (LBD) and Ben-Porath (BP).
First, I show that BP is much more consistent with empirical life-cycle patterns related to individual earnings growth rates relative to LBD.
Second, I show that the same model features that generate different life-cycle predictions between models also generate different policy implications. In particular, increasing the top marginal labor tax rate, relative to the current US level, generates much larger reductions in lifetime human capital accumulation in the BP model versus the LBD model.
Chapter two examines reforms to the Social Security taxable earnings cap in the context of a human capital model. Old age Social Security benefits in the US are funded by a 10.6% payroll tax up to a cap of $118,500. There has been little work examining the likely outcomes of such a policy change. I use a life-cycle BP human capital model with heterogeneous individuals to investigate the aggregate and distributional steady state impacts of several policy changes the earnings cap. I find that when I eliminate the cap: (1) aggregate output and consumption fall substantially; (2) the role of endogenous human capital is first order; (3) total federal tax revenues are lower or roughly unchanged; (4) about 1/3 of workers are made worse off.
The final chapter studies the existence and optimality of equilibria in the presence of asymmetric information. I develop an equilibrium concept which corresponds to the presence of mutual insurance organizations for a class of adverse selection economies which includes the Spence (1973) signaling and Rothschild-Stiglitz (1976) insurance environments. The defining features of a mutual insurance organization are that policy holders are also the owners of the organization, and that the organization can write policies for which the terms depend on the experience of the mutual members. In general the equilibrium exists and is weakly Pareto optimal. Further, all equilibria have the same individual type utility vector.
The majority of trust research has focused on the benefits trust can have for individual actors, institutions, and organizations. This “optimistic bias” is particularly evident in work focused on institutional trust, where concepts such as procedural justice, shared values, and moral responsibility have gained prominence. But trust in institutions may not be exclusively good. We reveal implications for the “dark side” of institutional trust by reviewing relevant theories and empirical research that can contribute to a more holistic understanding. We frame our discussion by suggesting there may be a “Goldilocks principle” of institutional trust, where trust that is too low (typically the focus) or too high (not usually considered by trust researchers) may be problematic. The chapter focuses on the issue of too-high trust and processes through which such too-high trust might emerge. Specifically, excessive trust might result from external, internal, and intersecting external-internal processes. External processes refer to the actions institutions take that affect public trust, while internal processes refer to intrapersonal factors affecting a trustor’s level of trust. We describe how the beneficial psychological and behavioral outcomes of trust can be mitigated or circumvented through these processes and highlight the implications of a “darkest” side of trust when they intersect. We draw upon research on organizations and legal, governmental, and political systems to demonstrate the dark side of trust in different contexts. The conclusion outlines directions for future research and encourages researchers to consider the ethical nuances of studying how to increase institutional trust.