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Benefits of Service-Learning on Students’ Achievement and Degree Attainment Outcomes: An Investigation of Potential Differential Effects for Low-Income and First-Generation Students
Get PDFPrevious researchers have demonstrated a positive association between enrolling in service-learning courses and achievement and graduation outcomes for college students. Less is known about whether results associated with service-learning hold for students from underrepresented backgrounds. Using propensity score matching, we explored whether enrollment in service-learning courses is related to 4-year retention and graduation outcomes of students who are low-income, first-generation college attendees, and who are both low-income and first-generation college attendees. We found positive relationships of service-learning course enrollment with higher achievement and higher odds of retention for students in the low-income category and the first-generation category. We also found a positive relationship between service-learning course enrollment and persistence for students who were both low-income and first-generation status. Implications of service-learning as a potential way of supporting the success of first-generation and low-income students are discussed
Households’ Decision on Capital Market Participation: What Are the Drivers? A Multi-Factor Contribution to the Participation Puzzle
No full textStock market investments are in the spotlight of the household finance literature, although real-world households make other financial decisions of higher relevance. We widen the scope and include decisions related to, e.g., voluntary pension plans, whole life insurance contracts, and housing and investments in other risky assets than stocks, e.g., bonds or mutual funds. Further, we provide a methodology that goes beyond regression analysis by employing a structural equation analysis (SEA) and apply it on data from a broad and representative survey of the German Central Bank. Our SEA allows us to investigate and quantitatively estimate complex relationships and to test several hypotheses simultaneously. Our structural equation model captures about 60% of the variation in the capital market participation decision. The results show that although households\u27 financial literacy and risk aversion are most strongly related to investments in risky assets, further factors such as wealth, voluntary pension plans and whole life insurance contracts, financial advice, and investment experience should also be considered. Financial literacy is negatively related to risk aversion, i.e., the higher the financial literacy, the lower is the risk aversion. Age and gender are directly related to capital market participation and indirectly via financial literacy and risk attitude
Profile to Portfolio: Where is the Missing Link?
No full textThis paper focuses on comparing reproducible methodologies to map an investor risk profile into portfolios, products, and solutions in a suitable manner. This study is premised on the assumption that financial advisors have access to valid measures of an individual’s tolerance to take investment risk or aggregate investor risk profile, and measures of the riskiness of products and portfolios of products. We compared three methodologies from the academic literature or regulators against investment alternatives we constructed. The alternatives were a range of 14 efficient portfolios using long-term indices in the United States, Canada, the United Kingdom, and Australia. Seven were based on an equal distribution of risk (i.e., the standard deviation increased equally between the seven portfolios), and seven portfolios where the percentage return of each portfolio increased by the same amount between each portfolio. The portfolios distributed by risk were discarded in favour of those distributed by return, and these were then mapped to determine the risk level of the investor they were considered suitable for based on the three methodologies. It was determined that (a) behavioural expectation and exposure to equities is a valid heuristic but insufficient to scale to the wide variety of portfolios and products, use of leverage, and other factors in the marketplace; (b) rolling standard deviation measures can lead to significantly understated assessments of risk in some periods; and (c) the VaR calculation is recognized in multiple sources as the preferred methodology to align investor concerns of drop in the value of their portfolio to the actual products, but like standard deviation, it is highly impacted by the period utilized. After altering two methodologies (i.e., MIFiD-II and RiskCAT) based on altered duration of data and scaling, respectively, we found that the four methodologies tested agreed with less than one risk band variance and an average correlation of 0.95 to 0.97
