TaxProf Blog

John Sabelhaus (University of Maryland) & Jae Song (U.S. Social Security Administration) have published Earnings Volatility Across Groups and Time, 62 Nat'l Tax J. 347 (2009).  Here is the abstract:

Inferences about earnings volatility across groups and time depend on the underlying models of earnings dynamics, data sources, earnings concepts, and sampling strategies. In this paper we evaluate a model of earnings dynamics in which the permanence of shocks varies by age and education. This specification is consistent with observed earnings changes in administrative panel data, and also with the variance of earnings levels in multiple cross–section (synthetic panel) data. However, expanding the earnings concept to include self–employment and changing sampling strategy to include observations with minimal labor force attachment has first–order effects, and may help explain why some studies conclude that earnings volatility is rising.

Molly Dahl (Congressional Budget Office), Thomas DeLeire (University of Wisconsin, Robert M. LaFollette School of Public Affairs) & Jonathan Schwabish (Congressional Budget Office) have published Stepping Stone or Dead End? The Effect of the EITC on Earnings Growth, 62 Nat'l Tax J. 329 (2009).  Here is the abstract:

While many studies have found that the EITC increases the employment rates of single mothers, no study to date has examined whether the jobs taken by single mothers as a result of the EITC incentives are “dead–end” jobs or jobs that have the potential for earnings growth. Using a panel of administrative earnings data linked to nationally representative survey data, we find no evidence that the EITC expansions between 1994 and 1996 induced single mothers to take “dead–end” jobs. If anything, the increase in earnings growth during the mid–to–late 1990s for single mothers who were particularly affected by the EITC expansion was higher than it was for other similar women. The EITC encourages work among single mothers, and that work continues to pay off through future increases in earnings.

David M. Hasen (Penn State) has posted Financial Options in the Real World — An Economic and Tax Analysis on SSRN.  Here is the abstract:

Many of the consequences of issuing and purchasing options on publicly traded property have been well understood since Black and Scholes developed a model for option pricing. No model of options, however, provides an accurate economic analysis of the actual transactions that issuers and purchasers engage in when options are bought and sold. One consequence of this gap in understanding is that the rules for taxing options remain poorly developed.

This article provides a transactional analysis of option sales for the first time. It demonstrates that while all options have as one component a swap of variable risks or returns on the underlying property for a fixed payment, “in-the-money” options contain, in addition, a simple forward transfer of the benefits and correlative burdens of a part of the underlying property that is equivalent to a forward sale of that part. Commentators have not identified this embedded forward sale because the payment arrangement between the parties to the option transaction masks it; however, a comparison of option prices derived under the Black-Scholes model and the theoretical prices of such forwards demonstrates that the transactions are identical. The analysis also illuminates the relationships between options and other common financial transactions, and it permits a cogent assessment of the advantages and disadvantages of possible tax rules for financial options.

Luisa R. Blanco (Pepperdine University, School of Public Policy) & Cynthia L. Rogers have posted Are Tax Havens Good Neighbors? An LDC Perspective on SSRN. Here is the abstract:

Tax competition and spillover models offer ambiguous predictions concerning tax haven consequences for non-tax haven countries. This paper investigates the impact of tax havens on foreign direct investment (FDI) in nearby non-tax havens that are less developed countries (LDCs). In particular, we investigate the potential for positive spillovers by creating a variable capturing two essential factors of an LDC’s nearest tax haven neighbor: its proximity and its level of FDI inflows. Employing cross sectional data of 115 LDCs from 1990 to 2006, we find positive spillovers from tax havens to nearby LDCs. This result is robust to several model specifications, including one with spatially correlated error terms. In addition, we use a non-linear specification to identify the relevant regions for which spillovers are most evident and to shed light on the nature of the spillover-distance relationship. Our results suggest that tax havens are good regional neighbors, but not good immediate neighbors from the non-tax haven LDC perspective.

Gerald Auten & Geoffrey Gee (both of the Office of Tax Analysis, U.S. Treasury Department) have published Income Mobility in the United States: New Evidence from Income Tax Data, 62 Nat'l Tax J. 301 (2009).  Here is the abstract:

While many studies have documented the long–term trend of increasing income inequality in the U.S. economy, there has been less focus on income mobility and the potential opportunity for upward mobility. Data from panels of individual income tax returns suggest that there was considerable income mobility in the U.S. economy over the 1987–1996 and 1996–2005 periods. Consistent with prior mobility studies, the data show that over half of taxpayers moved to a different income quintile and that roughly half of taxpayers who began in the bottom income quintile moved up to a higher income group by the end of each period. By contrast, those with the very highest incomes in the base year were more likely to drop to a lower income group and the median real income of these taxpayers declined in each period. Economic growth resulted in rising incomes for most taxpayers over both time periods. Initial position in the income distribution and changes in marital status were found to be associated with the largest upward or downward movements through the income distribution.