Leobardo Diosdado

Household composition in the United States is increasingly diverse; however, research into the diversity of the financial decision maker’s sexual orientation has yet to be explored. This analysis examines whether there are differences in financial risk tolerance between same-sex and different-sex couples using data from the Survey of Consumer Finances. The results from a propensity score matching technique, a Mann–Whitney U test, and interpretations of average treatment effects and average treatment effects of the treated suggest there is a statistical difference in risk tolerance between couples and that, on average, same-sex households are significantly more likely to report higher risk tolerance scores, at the 10% alpha level, when compared to their counterparts. Both treatment effect estimates suggest a high impact of the treatment at the 1% alpha level. This highlights the importance of not assuming homogeneous risk preferences across household types. These findings emphasize the importance of recognizing diversity in household composition. Thus, this study identifies the need for inclusiveness in all segments of financial planning.

This study examines the association between self-employment, otherwise known as entrepreneurship, and student loan debt. Based on data from the 2021 National Financial Capability Study, which were analyzed using a multinomial probit model, our results suggest that households that used student loans to finance the education of one household member are more likely to report that the other member of the household pursued self-employment, with everything else remaining equal. This association between student loans and household self-employment is both economically and statistically significant. Our results highlight the importance of alternative forms of financing for entrepreneurship and expand upon existing knowledge about the unintended effects of student loans. Policymakers should consider these results when analyzing the various intended and unintended benefits of policies affecting the availability of student loans.

Purpose: This paper investigates whether trading activity in the derivative markets, specifically options, can offer incremental information and insights into the underlying stock’s valuation beyond what is reflected in the company’s current stock price. By incorporating options market data into the analysis of an economic event, the proposed multivariate model aims to evaluate whether certain derivative investors may have capitalized on information not yet incorporated into the stock market price.Design/methodology/approach: The existing capital markets’ literature typically considers stock prices and (abnormal) returns in response to economic events; thus, this paper examines alternative measures. This analysis introduces a multivariate regression model incorporating the put-call ratio as an independent variable and examining its association with stock prices.Findings: This paper investigates whether trading activity in the derivative markets, specifically options, can offer incremental information and insights regarding the underlying stock’s valuation beyond what is reflected in the company’s current stock price. By incorporating options market data into the analysis of an economic event, the proposed multivariate model aims to evaluate whether certain derivative investors may have capitalized on information not yet incorporated into the stock market price.Research limitations/implications: Access to historical option market data is not readily available and is relatively expensive. Thus, the analysis was limited to the sole event of the 2010 BP Deepwater Horizon oil spill.Originality/value: The introduction of including deviate market movements could be especially beneficial for an industry like oil and gas, where the product is a commodity, and the firm’s value is largely driven by its identifiable assets and proven oil reserves. In addition, this may provide management insight into how the market perceives actions during an economic event. Based on the put-call ratio, management may be able to predict how their actions will impact future company share prices in the market.

This study examines the association between the location, relative to the coast, of an individual’s primary residence and the homeowners’ risk tolerance. Utilizing data from the 2021 National Financial Capability Study and employing a probit model, we analyzed how varying risk tolerance levels affect the likelihood of owning a home in a coastal ZIP code. The respondent’s risk tolerance was classified as high, medium, or low according to their self-reported willingness to take financial risks. Our results suggest that individuals with lower risk tolerances are less likely to own a home within a coastal ZIP code. Specifically, homeowners with medium-risk tolerance are 2.91% less likely, and those with low-risk tolerance are 3.17% less likely to own a primary residence in a coastal ZIP code when compared to those with high-risk tolerance. These results are statistically and economically similar when using a logit model. These findings are both statistically significant and align with economic theory. The analysis also included various demographic and socioeconomic factors, finding that age, income, and certain employment statuses influence coastal homeownership. This research contributes to the understanding of home ownership location choices and risk tolerance. Our results provide policymakers with insights into the risk characteristics of individuals who prefer coastal areas as their primary residences. This information can inform future policy decisions by highlighting the societal and economic implications of regulations related to residential coastal development.

A farming household’s decision to continue producing agricultural commodities within the United States is influenced by a multitude of factors. Thus, this study seeks to examine whether the outstanding student loan balance of any member within a farming household may explain why the total number of acres devoted to the production of agriculture in the United States continues to decline. Panel data from the 2007–2009 Survey of Consumer Finances are analyzed via a fixed effect model to estimate the effect of outstanding student loan balances on farmland acreage owned, controlling for other factors like farm income, debt, and land prices. The results suggest that for each additional dollar of outstanding student loan debt, there is an associated decrease of 0.0064 acres in total farmland ownership. This suggests that student loan debt may also be a factor in the decline in real estate devoted to agriculture production. The estimated effect is both economically and statistically significant. This study contributes to the literature on the risks and constraints associated with farming households that own or seek to procure additional acres of agricultural producing real estate.