The minimum wage is a widely used but controversial policy tool. A minimum wage can increase low-skilled workers’ wages at the expense of other factors of production such as higher skilled workers or capital and hence can be potentially useful for redistribution. However, it may also lead to involuntary unemployment, thereby worsening the welfare of workers who lose their jobs. A large empirical literature has studied the extent to which the minimum wage affects the wages and employment of low-skilled workers (see e.g., Card and Krueger (1995), Brown (1999), or Neumark and Wascher (2006) for extensive surveys). The normative literature on the minimum wage, however, is much less extensive.
This paper provides a normative analysis of optimal minimum wage policy in a conventional competitive labor market model, using the standard social welfare framework adopted in the optimal tax theory literature. Our goal is to use this framework to illuminate the trade-offs involved when a government sets a minimum wage, and to shed light on the appropriateness of a minimum wage in the presence of optimal taxes and transfers.
We investigate bank holding companies’ (BHCs) window dressing of quarter-end financial leverage through short-term borrowings and the stock market reaction around the public release of this information. We define window dressing as a short-term deviation around quarter-end reporting dates of a financial variable from its quarterly average level. The recent financial crisis brought into focus financial institutions’ risk-taking behavior and raised concerns about whether their end-of-quarter balance sheets are fair depictions of the risk levels during the quarter. Even though the spotlight has been on the financial industry, similar incentives to mask true risk levels and the tools to achieve such objectives can exist in other industries as well.
Does financial wealth drive the share of risky assets in the portfolios of individual investors? Is the financial wealth elasticity of the risky share homogenous across investors or does it vary with their demographic, financial and portfolio characteristics? How does the aggregate demand for risky assets respond to changes in the wealth distribution? In portfolio choice theory, mechanisms such as habit formation, borrowing constraints, decreasing relative risk aversion, portfolio insurance, or a “capitalist” taste for wealth, all imply that richer households allocate a higher fraction of their financial wealth to risky investments. These theories also predict that the financial wealth elasticity of the risky share should vary with household characteristics, including financial wealth itself. Furthermore, a growing literature investigates how at the aggregate level, the demand for risky assets relates to the distribution of household preferences and characteristics.
The empirical household finance literature provides only partial evidence on these mechanisms. In cross-sections, richer and more educated investors are known to allocate a higher proportion of their financial wealth to risky assets than less sophisticated households (e.g. Campbell 2006; Calvet Campbell and Sodini, “CCS” 2007, 2009a, 2009b). In addition, the risky share has a negative cross-sectional relation to real estate holdings (Cocco 2005, Flavin and Yamashita 2002), leverage (Guiso Jappelli and Terlizzese 1996), and internal consumption habit (Lupton 2002). It is unclear, however, whether these variables directly impact portfolio choice, or simply proxy for latent traits such as ability, genes, risk aversion, or upbringing. Several recent papers suggest that panel data offer a possible solution to this identification problem when the characteristic of interest exhibits sufficient time variations (e.g. Brunnermeier and Nagel 2008, CCS 2009a, Chiappori and Paiella 2008). One difficulty with the dynamic panel approach is that the researcher needs to control for household inertia by using instruments, and the results are sensitive to the validity of the instruments.
