There’s a chart circulating amongst South Carolina family law attorneys that lists most of the published alimony opinions and has columns for the amount of alimony ordered, length of marriage, the spouses’ respective incomes and expenses, grounds for divorce, and other factors described in the alimony statute. My understanding is that family law attorneys look to this chart in an attempt to divine how a family court judge might set alimony in their individual cases. Their Holy Grail is to develop a mathematical formula that predicts alimony–much as we have the child support guidelines to determine child support. It’s a fools quest.
If there’s a method for gaining insight into alimony awards by reviewing this chart–outside of simply noting that obvious factors like length of marriage, the parties’ incomes and reasonable expense, and fault are correlated with alimony awards–I’ve yet to discover it. Given the myriad alimony factors and the relative dearth of published alimony opinions, it’s likely impossible to determine how and how much each alimony factor correlates with the likely range of alimony awards. Further many of these opinions fail to note factors, such as the parties’ income and expenses, the length of marriage, or the grounds for divorce, that tend to be the most meaningful–further reducing their predictive value.
Even if one had perfect information from the appellate court opinions about all twelve alimony factors listed in S.C. Code § 20-3-130(C) (not even considering a catch-all thirteenth factor of “such other factors the court considers relevant”), it would be impossible to run a meaningful regression analysis to determine how and how much each factor impacts the ultimate result.
A significant problem would simply be designing the formula for the regression. While income and years of marriage are easy to code, how would one turn marital fault into a number? Further the design of the regression would involve choices that would affect the outcome. One would likely assume that the relationship between income and alimony is linear but that is clearly not the case. A supporting spouse making $1,000 a month is not likely to pay 1/10th the alimony of a supporting spouse making $10,000 a month. However a supporting spouse making $1,000,000 a month is unlikely to pay ten times more than a supporting spouse making only $100,000 a month. One assumes the relationship between income and alimony has both a floor and a ceiling–that is there are certain income levels so low that little or no alimony will be awarded and income levels so high that the relationship between income and alimony is no longer linear. How does one model this relationship?
A similar problem occurs in length of marriage. One would suspect it is not linear–the difference between a marriage lasting five years and a marriage lasting ten is probably more significant than the difference between a marriage lasting thirty years and one lasting thirty-five. But is isn’t geometric either–the difference between a marriage of one and two years is probably less significant than the difference between a marriage lasting ten and twenty years. How would one model this?
Moreover, while there are a number of data points (each reported alimony case), there are way too few data points to run a regression that wouldn’t have substantial standard deviations for the more meaningful factors. In layman’s terms, this means that a regression might show that income is highly correlated with alimony but that there is tremendous variability in the data between income and alimony.
Finally, how would one code the “catch all” provision?
As I suggested above, the desire to find some mathematical formula to predict alimony is understandable but a fool’s quest. Frankly, I understand the impulse behind the alimony chart but have never found it useful. In prosecuting or defending alimony claims, I’ve never even found basic case law useful, as there are myriad ways each individual case can be distinguished from previously reported decisions.
Of the four alimony factors I’ve found most significant, only one–length of marriage–is rarely subject to dispute. The fault factor–especially South Carolina’s unique adultery bar to alimony–has kept myriad private investigators employed. I’ve spent years thinking about how to develop evidence of substance abuse or how to pursue or refute allegations of domestic violence.
However, the backbone of any alimony case is establishing the parties’ respective income/earning capacity and reasonable expenses. This makes the parties’ initial financial declarations so important–as deliberate inaccuracies in these documents create credibility problems that cannot be overcome at trial. Much of my litigation strategy will be to review the parties’ initial financial declarations and develop evidence that bolsters the accuracy of my client’s financial declaration and undermines the other side’s credibility. If I represent the spouse pursuing alimony, my goal will be to demonstrate my client has a need for alimony (and the amount of that need) and the other party has the ability to pay. If I represent the supporting spouse, my goals will be to show the other party has no need for alimony (or limited need) and that my client cannot pay alimony without having a lesser lifestyle compared to his or her spouse. These tasks initially involve collection of the parties’ incomes and expense histories. How to employ this information is only limited by the attorney’s creativity.
The simple answer to “how will the family court decide this alimony case?” is that there is no simple answer. Because one cannot rely on caselaw or a mathematical formula to determine it, alimony is an area of family law in which the skill and experience of the attorney is most meaningful to the ultimate outcome.
