Financial planners and educators comprised a panel of 156 experts in this Delphi study designed to identify and refine ratios and benchmarks for measuring financial well- being. Consensus between the two groups existed for benchmarks on 20 of 22 ratios in the areas of liquidity, savings, asset allocation, inflation prorection, tax burden, hous- ing expenses, and insolvency/credit. Consensus regarding the usefulness of specific ratios was observed for liquidity and tax burden but not for inflation protection and insolvency/credit. The preferred ratios were generally less complex and more easily measuredthanmanyoftheratiosusedinprevious work.From the findings, a profile of financial well-being for the typical family/individual was proposed.
Retirement planning guidelines were determined using a Delphi research design among 188 financial planners and educators. Consensus was found for using a 4% inflation rate, an 8.5% rate of return on investments, and a replacement ratio of 70 – 89% of current income when making retirement projections. Nine-tenths of the experts agreed that families should have achieved 50–60% of their retirement savings goal by age 50 and 85–90% by age 60. Regarding asset allocation, over 60% felt it was prudent to start moving toward more conservative investments about 3–5 years before retirement. Recommendations were developed on the proportion of growth-oriented equities to hold at various points prior to and after retiring. While the level of consensus was high, occupational and gender differences were noted. © 2001 Elsevier Science Inc. All rights reserved.
This study investigates funding trends in college/university home economics pro grams during 1975–80 based on survey data from 138 heads of home economics units. Home economics faculty salaries did not keep up with inflation and avail ability of resources to higher education during the period studied; however, this was true for faculty members in general from all disciplines. Although this study is largely descriptive, an exploratory stepwise multiple regression analysis iden tifies characteristics of programs which fared better in terms of budgetary expan sion in comparison to group norms. Home economics undergraduate degrees granted was the only variable significantly related (p < 0.01) to growth in faculty salary allocations. Although growth in overall university allocations was the only significant predictor (p < 0.01) for growth in the maintenance, operations, and equipment budget category, two other variables‐undergraduate degrees granted and percentage of faculty tenured‐were closely enough related to be considered in future research.
<p>This article provides a theoretical-based rationale and plan of action for educational programs to encourage and create opportunities for the integration of course study with professional exam preparation, while highlighting the complementary benefits for students, academic programs, and the financial services profession. Serving primarily as a model for faculty associated with university-based financial planning education, this article also provides a foundation for future research in this area. In addition, the article presents descriptive information on select designations and licenses currently available that finance and financial planning students could pursue concurrently with coursework.</p>
This research considers the impact of decision power (Blood & Wolfe, 1960) and demographic variables within a couples relationship on risk tolerance and portfolio risk levels. Married couples (N = 175) separately completed a survey consisting of the Blood and Wolfe Decision Power Index, the Survey of Consumer Finances risk tolerance question, demographic information, and selected financial variables. Unlike their husbands, the study found an effect of decision power for wives and portfolio risk level, suggesting that the wifes decision power affects portfolio risk levels. Decision power was found to be a significant factor in risk tolerance for both the husband and wife. Findings indicate that both portfolio risk levels and risk tolerance is determined by the education of the wife and not the husband. Further, a divergence in risk levels occurred when the husband owned a greater degree of assets than the wife.
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