The Significance of Tax Law Asymmetries: An Empirical Investigation

This study uses tax return data for U.S. nonfinancial corporations for the period 1971-82 to estimate the importance of restrictions on the ability of firms to use tax credits and to obtain refunds for tax losses. Our results suggest that the incidence of such unused tax benefits increased substantially during the early 1980s, though we do not find these increases attributable to increased investment incentives during that period. Using estimates of a three-state (taxable, not taxable, partially taxable) transition probability model, we calculate the effective tax rates on various types of investments undertaken by firms differing with respect to tax status. We confirm previous findings about the marginal tax rate on interest payments, and that it is important to distinguish current tax payments from marginal tax rates in estimating the incentive to invest.

The Changing Environment of Urban Development Policy—Shared Power or Shared Impotence?

In this Article we highlight five recent trends that have profoundly transformed the shared power system of American urban government as it relates to that arena of urban development in which we have been active over the past half-dozen years: transportation

Understanding U.S. corporate tax losses

Recent data on corporate tax losses presents a puzzle this paper attempts to explain: the ratio of losses to positive income was much higher around the recession of 2001 than in earlier recessions, even those of greater severity. Using a comprehensive sample of U.S. corporation tax returns for the period 1982-2005, we explore a variety of potential explanations for this surge in tax losses, taking account of the significant use of executive compensation stock options beginning in the 1990s and recent temporary tax provisions that might have had important effects on taxable income. We find that losses rose because the average rate of return of C corporations fell, rather than because of an increase in the dispersion of returns or an increase in the gap between corporate profits subject to tax and corporate profits as measured by the national income accounts. Our analysis also suggests that the increasing importance of S corporations may help explain the recent experience within the C corporate sector, as S corporations have exhibited a different pattern of losses in recent years. However, we can identify no simple explanation for the differing experience of C and S corporations. Our investigation concludes with some new puzzles: why did rates of return of C corporations fall so much early in the decade and why has the incidence of losses among C and S corporations diverged

Understanding U.S. Corporate Tax Losses

Recent data present a puzzle: the ratio of corporate tax losses to positive income was much higher around 2001 than in earlier recessions. Using a comprehensive 1982-2005 sample of U.S. corporation tax returns, we explore a variety of potential explanations for this surge in tax losses, taking account of the significant use of executive compensation stock options beginning in the 1990s and recent temporary tax provisions that might have had important effects on taxable income. We find that losses rose because the average rate of return of C corporations fell, rather than because of an increase in the dispersion of returns or an increase in the gap between corporate profits subject to tax and NIPA corporate profits. Our analysis also suggests that the increasing importance of S corporations may help explain the recent experience within the C corporate sector, as S corporations have exhibited a different pattern of losses in recent years. However, we can identify no simple explanation for this differing experience. Our investigation concludes with some new puzzles: why did rates of return of C corporations fall so much early in the decade and why has the incidence of losses among C and S corporations diverged?

Common Variants in 40 Genes Assessed for Diabetes Incidence and Response to Metformin and Lifestyle Intervention in the Diabetes Prevention Program

OBJECTIVE: Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. RESEARCH DESIGN AND METHODS: We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. RESULTS: We replicated the association of variants in the metformin transporter gene $SLC47A1$ with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene $STK11$, the AMPK subunit genes $PRKAA1$ and $PRKAA2$, and a missense SNP in $SLC22A1$, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene $PRKAG2$ (hazard ratio 1.24, 95% CI 1.09–1.40, P = 7 × 10$^{−4}$). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest $P$ values were consistent with experiment-wide 33% false discovery rates. CONCLUSIONS: We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples

Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: The Diabetes Prevention Program

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, Pinteraction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; Pinteraction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, Pinteraction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; Pinteraction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss

Common Variants in 40 Genes Assessed for Diabetes Incidence and Response to Metformin and Lifestyle Intervention in the Diabetes Prevention Program

OBJECTIVE: Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. RESEARCH DESIGN AND METHODS: We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. RESULTS: We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09-1.40, P = 7 × 10(-4)). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates. CONCLUSIONS: We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples

Tax Loss Offset Restrictions - Last Resort for the Treasury? An Empirical Evaluation of Tax Loss Offset Restrictions Based on Micro Data

In Germany, the tax loss carry-forward of corporations significantly increased over the last decade. At the same time only a small percentage of losses have been effectively offset in the following periods. One potential reason for this puzzle is that stricter loss offset restrictions have been introduced in recent years. I use a newly developed micro simulation model for the corporate sector in Germany to evaluate the fiscal effects of these restrictions. Additionally, distributional breakdowns concerning the amounts of tax loss carry-forward and the effects of loss offset restrictions are provided. I find that the restrictions on the use of tax loss carryback are rather ineffective while the newly introduced minimum taxation considerably increases yearly tax revenue by 1.1 billion