Statistically Distinguishing Between Active and Passive Appreciation

It is important to recognize that business success in creating wealth is a direct reflection of the economic environment. Economic conditions outside the control of owners have significant impact on the growth, survival, and value of the business. The following three-step analysis is often used for a determination of the active and passive appreciation:

• Determine whether the property in question is either separate or marital property;
• Calculate the property's value at the commencement of the action, in relation to its value on the date(s) gifted or acquired; and
• Determine as to what extent the increase in the value of the non-marital property is active appreciation or passive appreciation.

Other Considerations

In case of a separate property, any increase in value in the separate property of either of the parties to a marriage resulting from either of the following factors becomes marital property subject to division as part of the marital estate:

• An expenditure of funds which are marital property, including an expenditure of such funds which reduces indebtedness against separate property, extinguishes liens, or otherwise increases the net value of separate property; or
• Work performed by either or both parties during the marriage.

While expenditure of marital funds may be a question of fact, it is difficult to measure the contribution of either party's work to the (active) change in value of the business. It is, however, possible to quantify the proportion of the change in value of the businesses started/acquired pre-marriage that is passive, if the following two questions can be answered:

• Which factors outside the control of the owner manager(s) of the business, if any, significantly impact the changes in value of the business?
• What proportion of the change in business value can be explained by these external factors outside the control of the managers?

Quantitative Analysis

Quantitative analysis using multi-variate ordinary least squares (OLS) regression provides a valuable tool for answering both of these questions. It can help to identify external economic factors that can explain the changes in value of the business interests. Further, it can also answer the second question by quantifying the proportion of change attributable to the impact of these factors. OLS has been used extensively for more than a century and is a well-established statistical tool for hypothesis testing. A careful analysis of the industry in which the business operates can identify the external variables that are likely to impact the value of the business. Measuring the impact of those variables that are outside the control of the managers can help to quantify the proportion of appreciation that can be claimed as passive. The key lies in identifying macro economic variables that are statistically significant and applying standard statistical techniques so that the analysis is replicable and meets Daubert standards.

Briefly, the OLS regression procedure consists of specifying a model equation with the dependent variable (e.g., changes in revenues/value of a business) as the factor to be explained and the independent variables being the factors providing an explanation. These independent factors may include the level of economic activity, interest rates, customer demographics, regulatory changes, and other similar data. The sum of regression squares (R-square) statistic for the specified regression equation (model) measures the percentage of change in value of the dependent variable that can be explained by these external factors and may be considered passive appreciation not subject to distribution. The results presented in the following section are illustrative in identifying the impact of external factors on revenues of two categories of businesses. Such analysis can be adapted for changes in income stream, cash flows, or value of the subject business being analyzed. This analysis uses publicly available macro economic factors and retail sales data from the monthly retail trade reports prepared by the U.S. Census Bureau. www.census.gov/prod/www/abs/br_month.html.

Illustration of the Impact of External Economic
Factors

OLS regression methodology is used to analyze monthly data covering the retail sales activity from the U.S. Census Bureau (www.census.gov/mrts/www/mrts.html) and the macroeconomic variables data from the Federal Reserve Economic data (www.research.stlouisfed.org/fred2).The regression results are used to identify macro economic variables significant in explaining the changes in the level of retail sales, and the percentage of passive changes in retail sales that can be explained by the changes in three external variables (inflation, unemployment, and the bank prime rate) over which the business management would have no control. The results are estimated over five, 10, and 15 years ending in December 2010. The three factors tend to differ in importance and significance for different industries.

The chart below illustrates the proportion of changes in national-level sales for automobile and food service industries explained by external economic factors such as the level of inflation, unemployment, and Bank Prime Rate of interest during 1996-2010. The results are statistically robust and indicate that the sales revenues for these industries are significantly impacted by external factors. These results indicate support for a significant passive appreciation component in appreciation of such businesses during the time period 1996-2010. These regression results are estimated over a 15-year time period, 1996-2010, and sub-periods of five and 10 years using the same aggregate national level data. Additional business-specific factors should be identified, and regression analysis performed using national, regional, and local data, as available, for the period of analysis, to get case-specific results. The range of explanatory power for the regression model changes over the periods of analysis.

Measuring the Outcome

A robust measure of the active and passive appreciation of a business interest in a divorce can make an enormous difference in the outcome of the case. For example, the data illustrate that in a long-term marriage, more than 90% of the change in revenues of a food service entity would be attributable to external factors, and therefore potentially indicate presence of substantial passive appreciation, not subject to division in a divorce.

Younger individuals are spending more time in early adulthood pursuing education and careers, creating wealth, and postponing marital relationships. Consider what Google co-founders Larry Page and Sergey Brin, and Facebook founder Mark Zuckerberg have in common, other than starting their ventures in 2004 and joining the ranks of the super rich by 2007. As it turns out, all of them were single at the time the foundations of their wealth were laid. Google stock went public at $108 in August 2004, was $470 in May 2007 when Larry Page got married, and trades currently at $540. An estimated $19.7 billion of Page's current Google stake was worth $17 billion at the time of his marriage, leaving “only” $2.7 billion of current total appreciation since his marriage. Excluding each 1% of the change in value of Page's Google stake (36.5 million shares) between the date of his marriage and today would reduce the distributable marital estate by $27 million.

Conclusion

Active and passive appreciation is an important issue in division of marital estates, irrespective of good or bad economic times. It is important to work with qualified business appraisers who are well versed in the statistical tools required for making robust estimates of active and passive appreciation.

[IMGCAP(1)]

Ashok Abbott, Ph.D, is a tenured Associate Professor of Finance at West Virginia University, specializing in issues of business value measurement. He has testified as an expert witness in U.S. Federal Court and in New Jersey and West Virginia, and has been deposed as an expert witness in Florida, New Jersey, and West Virginia.

When divorce occurs, how do matrimonial attorneys deal with division of wealth that exists at the time of filing? Depending on state laws, very contentiously.

The combination of delayed marriages, considerable wealth being created pre-marriage, and an almost 50% rate of divorce, (6.8 marriages/3.5 divorces per 1000 population) brings an urgency to the issue of apportioning the active and passive components of the growth in value of the business during the marriage. This issue has been extensively litigated and the rulings generally state that increased value of separate property resulting directly from spousal efforts (active appreciation) becomes the property of the marital partnership, and increased value attributable to other external sources (passive appreciation) remains separate property. While the theoretical existence of passive appreciation has been recognized in most venues, a clear approach to distinguishing between passive and active components is not well defined and remains the playground of dueling business appraisers. Having the right business expert on your side ' well-armed with robust statistical tools ' can make an enormous difference in the outcome of the case.

A Three-Step Analysis

It is important to recognize that business success in creating wealth is a direct reflection of the economic environment. Economic conditions outside the control of owners have significant impact on the growth, survival, and value of the business. The following three-step analysis is often used for a determination of the active and passive appreciation:

• Determine whether the property in question is either separate or marital property;
• Calculate the property's value at the commencement of the action, in relation to its value on the date(s) gifted or acquired; and
• Determine as to what extent the increase in the value of the non-marital property is active appreciation or passive appreciation.

Other Considerations

In case of a separate property, any increase in value in the separate property of either of the parties to a marriage resulting from either of the following factors becomes marital property subject to division as part of the marital estate:

• An expenditure of funds which are marital property, including an expenditure of such funds which reduces indebtedness against separate property, extinguishes liens, or otherwise increases the net value of separate property; or
• Work performed by either or both parties during the marriage.

While expenditure of marital funds may be a question of fact, it is difficult to measure the contribution of either party's work to the (active) change in value of the business. It is, however, possible to quantify the proportion of the change in value of the businesses started/acquired pre-marriage that is passive, if the following two questions can be answered:

• Which factors outside the control of the owner manager(s) of the business, if any, significantly impact the changes in value of the business?
• What proportion of the change in business value can be explained by these external factors outside the control of the managers?

Quantitative Analysis

Quantitative analysis using multi-variate ordinary least squares (OLS) regression provides a valuable tool for answering both of these questions. It can help to identify external economic factors that can explain the changes in value of the business interests. Further, it can also answer the second question by quantifying the proportion of change attributable to the impact of these factors. OLS has been used extensively for more than a century and is a well-established statistical tool for hypothesis testing. A careful analysis of the industry in which the business operates can identify the external variables that are likely to impact the value of the business. Measuring the impact of those variables that are outside the control of the managers can help to quantify the proportion of appreciation that can be claimed as passive. The key lies in identifying macro economic variables that are statistically significant and applying standard statistical techniques so that the analysis is replicable and meets Daubert standards.

Briefly, the OLS regression procedure consists of specifying a model equation with the dependent variable (e.g., changes in revenues/value of a business) as the factor to be explained and the independent variables being the factors providing an explanation. These independent factors may include the level of economic activity, interest rates, customer demographics, regulatory changes, and other similar data. The sum of regression squares (R-square) statistic for the specified regression equation (model) measures the percentage of change in value of the dependent variable that can be explained by these external factors and may be considered passive appreciation not subject to distribution. The results presented in the following section are illustrative in identifying the impact of external factors on revenues of two categories of businesses. Such analysis can be adapted for changes in income stream, cash flows, or value of the subject business being analyzed. This analysis uses publicly available macro economic factors and retail sales data from the monthly retail trade reports prepared by the U.S. Census Bureau. www.census.gov/prod/www/abs/br_month.html.

Illustration of the Impact of External Economic
Factors

OLS regression methodology is used to analyze monthly data covering the retail sales activity from the U.S. Census Bureau (www.census.gov/mrts/www/mrts.html) and the macroeconomic variables data from the Federal Reserve Economic data (www.research.stlouisfed.org/fred2).The regression results are used to identify macro economic variables significant in explaining the changes in the level of retail sales, and the percentage of passive changes in retail sales that can be explained by the changes in three external variables (inflation, unemployment, and the bank prime rate) over which the business management would have no control. The results are estimated over five, 10, and 15 years ending in December 2010. The three factors tend to differ in importance and significance for different industries.

The chart below illustrates the proportion of changes in national-level sales for automobile and food service industries explained by external economic factors such as the level of inflation, unemployment, and Bank Prime Rate of interest during 1996-2010. The results are statistically robust and indicate that the sales revenues for these industries are significantly impacted by external factors. These results indicate support for a significant passive appreciation component in appreciation of such businesses during the time period 1996-2010. These regression results are estimated over a 15-year time period, 1996-2010, and sub-periods of five and 10 years using the same aggregate national level data. Additional business-specific factors should be identified, and regression analysis performed using national, regional, and local data, as available, for the period of analysis, to get case-specific results. The range of explanatory power for the regression model changes over the periods of analysis.

Measuring the Outcome

A robust measure of the active and passive appreciation of a business interest in a divorce can make an enormous difference in the outcome of the case. For example, the data illustrate that in a long-term marriage, more than 90% of the change in revenues of a food service entity would be attributable to external factors, and therefore potentially indicate presence of substantial passive appreciation, not subject to division in a divorce.

Younger individuals are spending more time in early adulthood pursuing education and careers, creating wealth, and postponing marital relationships. Consider what Google co-founders Larry Page and Sergey Brin, and Facebook founder Mark Zuckerberg have in common, other than starting their ventures in 2004 and joining the ranks of the super rich by 2007. As it turns out, all of them were single at the time the foundations of their wealth were laid. Google stock went public at $108 in August 2004, was $470 in May 2007 when Larry Page got married, and trades currently at $540. An estimated $19.7 billion of Page's current Google stake was worth $17 billion at the time of his marriage, leaving “only” $2.7 billion of current total appreciation since his marriage. Excluding each 1% of the change in value of Page's Google stake (36.5 million shares) between the date of his marriage and today would reduce the distributable marital estate by $27 million.

Conclusion

Active and passive appreciation is an important issue in division of marital estates, irrespective of good or bad economic times. It is important to work with qualified business appraisers who are well versed in the statistical tools required for making robust estimates of active and passive appreciation.

[IMGCAP(1)]

Ashok Abbott, Ph.D, is a tenured Associate Professor of Finance at West Virginia University, specializing in issues of business value measurement. He has testified as an expert witness in U.S. Federal Court and in New Jersey and West Virginia, and has been deposed as an expert witness in Florida, New Jersey, and West Virginia.