Volume 15, Issue 1
possible conversions of deductible/non-deductible IRAs. This paper develops a multi-dimensional decision framework. The framework includes a metric to compare the expected marginal tax rate at the time of the withdrawal of funds, as well as, the minimum investment horizon needed to break even in terms of expected after-tax future values of the alternatives. The paper also analyzes the impact of random variability in the expected returns on these metrics. Roth conversion would benefit investors with long investment horizons and those who do not expect any significant reduction in their marginal tax rates. Possible tax law changes represent the greatest uncertainty for anyone considering conversion. Measuring the Financial Consequences of IRA to Roth IRA Conversions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 James S. Welch, Jr., Senior Application Developer for Dynaxys, LLC. The tax code permits the conversion of IRA funds to a Roth IRA provided that personal income taxes are paid on the IRA distributions. Common motivations for IRA to Roth IRA conversions are to increase retirement disposable income, insure against future tax increases, and allocate retirement savings to minimize combined taxes for retirees and their heirs. This paper quantitatively assesses the financial consequences of making conversions with respect to these motivations. Our laboratory was a linear programming retirement planning calculator that, given a set of assumptions and constraints, computes retirement cash flow that maximizes disposable income by minimizing taxes and maximizing compounded asset returns. Disposable income is our metric for evaluating different assumptions, such as doing or not doing conversions. Our results are that partial conversions early in the optimal plan increases disposable income by around 1% in most situations. Conversions reduce total income taxes paid by 19% as it shifts taxes from later in retirement to earlier in retirement. Pre-positioning savings for inheritance purposes can be accomplished with minor reductions in disposable income. Making Your Money Work: Tax Refunds to Debt Reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Norma B. Coe, Assistant Professor, University of Washington and NBER Timothy Clegg Financial education and literacy, especially among low-income households, have become popular policy and research topics. This qualitative study combined information from tax preparation services with credit counseling services at a Volunteer Income Tax Assistance (VITA) site, and documents the existence of low-income, high-debt, over-withholding households. A subgroup of these clients who also predicted stable tax situations for the upcoming year were selected to receive additional information and tools to change their withholding and pay down their debt to help achieve the broader goal of improving their financial security. This study suggests that this combining of tax preparation and credit counseling services may provide a promising avenue to help individuals change their financial security. Measuring Risk Tolerance: A Review of Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Michael S. Finke, Professor, Department of Personal Financial Planning, Texas Tech University Michael A. Guillemette, Assistant Professor, Department of Personal Financial Planning, University of Missouri This paper provides a review of literature on the theory and measurement of risk preferences. The manuscript begins with a discussion on the origin of risk aversion and the evolution of prospect theory. We explore how risk perceptions alter household financial decision making, the effect cognitive ability has on risk preferences and the extent to which risk preferences change over time. Next, we examine ways to measure investor risk preferences and provide insight into the construction of risk assessment questionnaires. We conclude with a discussion on advisor compensation models and how they may affect the risk level of client portfolios.
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