The Arizona Supreme Court Weighs In

A.R.S. §12-2203 did not have any teeth, however, until September 7, 2011, when the Arizona Supreme Court approved the Petition to Amend Rules of Evidence and Rule 17.4 (f), Arizona Rules of Criminal Procedure (“the Petition”).  This is because the Arizona Supreme Court, not the state legislature, is responsible for deciding the procedural rules that Arizona courts must follow.

What the Arizona Supreme Court did was to amend several of Arizona’s Rules of Evidence with the Petition.  The Petition’s Prefatory Comment to 2012 Amendments summarizes three kinds of changes:

“(1) the Arizona rules have generally been restyled so that they correspond to the Federal Rules of Evidence as restyled.  These  ‘restyling’ changes are not meant to change the admissibility of evidence; (2) in several instances, the Arizona rules have also been amended to ‘conform’ to the federal rules, and these changes may alter the way in which evidence is admitted (see, e.g., Rule 702); and (3) in some instances, the Arizona rules either retain language that is distinct from the federal rules (see, e.g., Rule 404), or deliberately depart from the language of the federal rules (see, e.g., Rule 412).”

The Prefatory Comment concludes with: “Where the language of an Arizona rule parallels that of a federal rule, federal court decisions interpreting the federal rule are persuasive but not binding with respect to interpreting the Arizona rule.”

Don Bays, CPA/ABV/CFF, CVA

Senate Bill 1189 to ARS §12-2203

In 2010, Senate Bill 1189 was enacted into law by the Arizona Legislature as Arizona Revised Statute, Section 12-2203, which states the following:

12-2203. Admissibility of expert opinion testimony
A.  In a civil or criminal action, only a qualified witness may offer expert opinion testimony regarding scientific, technical or other specialized knowledge and the testimony is admissible if the court determines that all of the following apply:
1. The witness is qualified to offer an opinion as an expert on the subject matter based on knowledge, skill, experience, training or education.
2. The opinion will assist the trier of fact in understanding the evidence or determining a fact in issue.
3. The opinion is based on sufficient facts and data.
4. The opinion is the product of reliable principles and methods.
5. The witness reliably applies the principles and methods to the facts of the case.

B. The court shall consider the following factors, if applicable, in determining whether the expert testimony is admissible pursuant to subsection A:
1. Whether the expert opinion and its basis have been or can be tested.
2. Whether the expert opinion and its basis have been subjected to peer reviewed publications.
3. The known or potential rate of error of the expert opinion and its basis.
4. The degree to which the expert opinion and its basis are generally accepted in the scientific community.

Don Bays, CPA/ABV/CFF, CVA

For this particular project we created three different tables within Access to handle all of the line items and linked them together as relational databases.   We linked all three tables together with a common ID tag that is seen in each table.  This allows us to ensure the data with the same ID tag will still be related to each other while stored in different databases.  Linking also helps to show the data in a meaningful way that is easily interpreted and reference specific columns to place the data. 

Since the client was more familiar with Excel, we created a template that they could use in Excel to input the data.  Access has a feature that allows the importation of data from many programs, including Excel.  This allows a user with limited Access experience to enter data into Excel that can easily be put into Access.  This is also useful if not all of the clients data entry personnel have Access installed on their computer.  By creating this template it also helped us create the database because the data import feature will import column headings and formatting.

Being able to track the data was very important for the client.  Using Excel by itself would require having to link numerous excel worksheets together to track data and create sophisticated functions to sort it.  This creates a time consuming process to link each spreadsheet together and could cause Excel to crash or run very slowly if the spreadsheet has too many links to other sheets.  It helps the client keep track of which data points are comparable to create averages with great ease of use.  In addition, the reports and queries that Access has to offer produce a wonderful presentation of the data.

This is an important lesson of flexibility and being responsive to client needs.  In the ever growing age of technology, it is important to be able to adapt to any project put in your path. 

Mark Hughes, CPA, ABV, CFF

This payment data does not exhibit the normal distribution pattern which is not uncommon, as discussed above.  Of particular importance is the small number of payment observations in which the company took significantly longer than usual to pay the invoice.  This dataset produces a median of 33 due to the large cluster of payments around 30 days and an average of 64 due to the influence of the invoices which were paid after a long number of days.  The median absolute deviation for the payments is 4 days due to the tight grouping of payments around the median.  However, the standard deviation for the payments is 76 days due to the influence of the long dated payments.

From a visual standpoint, it is apparent that the historical payments fell overwhelmingly between 30 and 35 days with a small number of payments falling outside of that period.  Utilizing a range of one median absolute deviation on each side of the median would yield an ordinary course range between 29 and 37 days and would indicate that approximately 65 percent of the historical payments can be said to represent an ordinary range.  It is important to note that this percentage is comparable to the 68 percent of the population captured by a one standard deviation range for the normal distribution presented in Figure 1.

However, utilizing one standard deviation on each side of the mean to determine the ordinary course of historical payments would yield a range between 0 and 140 days.  This methodology would indicate that approximately 92 percent of the historical payments represent an ordinary range.

Now that the ordinary course ranges defined by the median absolute deviation and standard deviation methodologies have been examined, let us consider the effect of the results of each methodology when applied to the following hypothetical dataset consisting of 50 payments in the 90 day preference period preceding a bankruptcy filing.

A visual analysis of this data once again reveals that there are several payments clustered around 33 days, as was the case in the historical period.  However, there is no large spike in the frequency of payments around this point as there was in Figure 3 and the remaining payments show that only 1 payment was made between 40 and 60 days with the remaining payments falling relatively evenly from 60 to 110 days.

Utilizing the standard deviation method discussed above, all of the payments in the preference would meet the definition of ordinary course since they fall within the range of zero to 140 days.  If the median absolute deviation methodology is employed, all payments over 37 days would be considered outside of the ordinary course of business based on the payment history between the parties. 

To understand how the magnitude of the difference between the ordinary course indications under the two different methods, it is often useful to express the standard deviation range in terms of median absolute deviations.  In this case, payments of 60 days would represent a variance of 6.75 median absolute deviations from the historical median observation of 33.  A payment of 100 days would represent a variance of 16.75 median absolute deviations and a payment of 140 days would represent a variance of 26.75 median absolute deviations.  Therefore, the influence of outliers in the standard deviation methodology becomes apparent when expressed in terms of median absolute deviations.

Conclusion

While many sophisticated statistical analyses have been developed by financial experts to support their opinions of the ordinary course of dealings between parties to a preference dispute, the standard deviation methodology has often been utilized due to its simplicity and familiarity when presented in a legal proceeding.  However, due to the sensitivity of the standard deviation calculation to outliers, the financial expert is often forced to subjectively remove these outliers, which can create the appearance of bias.  If the outliers are not removed, as demonstrated above, the ordinary course indication produced by the standard deviation methodology can appear at odds with the data analyzed.

If a dataset is normally distributed as presented in Figure 1, the mean and median will be very similar to one another and the median absolute deviation will typically also produce similar results.  However, due to several factors specific to common payment practices, payment data does not typically exhibit a normal distribution pattern.  Therefore, the median absolute deviation methodology can be employed by financial experts to present an easily understandable approach to triers of fact that does not require the subjective removal of outliers.

The Pillowtex decision once again thrusts the subjective issue of the ordinary course of payments between the parties in the historical period into the spotlight.  As is the case with all financial analyses, the most appropriate methodology will depend on the facts and circumstances of each project.  By utilizing the median absolute deviation, a financial expert can eliminate the need to eliminate outlier data from a population of payment data and can also test the number of implied median absolute deviations represented in the ordinary course range indicated by standard deviation or other methodology.

Mark Hughes, CPA, ABV, CFF

One of the key concepts in determining fair value is the transaction price between market participants which requires the valuation analyst to consider the market that would be most advantageous for the asset.  The three valuation approaches utilized are the same as in determining fair market value:  1) market approach; 2) income approach; and 3) the asset approach.  However, in determining fair value there are three levels of a hierarchy of inputs:

• Level 1 – quoted prices in active markets for identical assets that are available as of the date of valuation;
• Level 2 – observable market data other than quoted market prices; and
• Level 3 – unobservable inputs for the asset which include the reporting entity’s own assumptions about the assumptions market participants would use in pricing the asset.

EXAMPLE:

Help Others Foundation, a non-profit entity, owns a 10% noncontrolling, nonmarketable membership interest in ABC, LLC.  For financial statement reporting purposes in accordance with Generally Accepted Accounting Principles, the foundation is required to report the fair value of the interest as of its fiscal year-end, which is December 31, 2011.  ABC, LLC’s sole asset is vacant land located in Yuma, Arizona and there are no liabilities.  Susan Wright, ASA, has been hired to determine the fair value of the 10% interest.   John Smith, MAI prepared the property appraisal, valuing the vacant land at $10,000,000 as of December 31, 2011.  In this example, Level 1 inputs cannot be utilized as there are no quoted market prices for a fractional interest in ABC, LLC.  However, Level 2 inputs can be utilized as there is observable market data in the sale of comparable fractional interests in publicly registered real estate limited partnerships that own vacant land.  Twenty-three comparable transactions were found between 1994 and 2010 resulting in a median discount/net asset value ratio of 39%.   Applying the 39% discount to 10% of the net asset value of ABC, LLC results in a fair value of $610,000 ($10,000,000 x 10% x (1-39%)) as of December 31, 2011 for the 10% membership interest in ABC, LLC held by Help Others Foundation.

Cindy Andresen

Metro Phoenix Class A Office absorption experienced its tenth consecutive quarter of growth.  A total of 476,225 square feet of positive absorption Valleywide occurred in the third quarter of 2011 and year to date cumulated absorption was 1,340,078.  Other good news in the third quarter for Class A space was a decline in vacancy rates from 24.3 percent at the end of the first quarter to 21.7 percent.

Unfortunately, Metro Phoenix Class B Office absorption experienced net negative absorption of 85,251 square feet in the third quarter and a vacancy rate of 27.1 percent with Class C Office buildings reporting an even higher vacancy rate at 28.8 percent.

The office market vacancy rate will not be impacted by the addition of new product, as there continues to be no speculative buildings under construction.  In fact, the only reported office construction in the third quarter was a 225,000-square-foot building in the Deer Valley submarket that will be leased and occupied by the FBI.

The third quarter full service average asking lease rate for existing product in metropolitan Phoenix was $20.98 per square foot, compared to $22.25 per square foot one year ago.  At quarter-end, the average Class A, Class B and Class C asking lease rates were $25.90, $20.48 and $15.37 per square foot respectively.  It is expected that property owners will cautiously maintain low asking rental rates in order to remain competitive with the abundant supply of office space on the market.  This trend is expected to continue well into 2012.

Forecast
• Net absorption is expected to post gains in 2011 and 2012.
• Asking rents are expected to reach bottom during 2011.
• Smaller tenants, which comprise the majority of Metro Phoenix tenants, will absorb previously vacated Class B space.
• Areas located within the Central Business District, Camelback Corridor, Scottsdale and Tempe submarkets will fare better will respect to rent stabilization.

Gary Ringel, CGREA

According to CBRE MarketView, The metropolitan Phoenix industrial market posted overall absorption of nearly 3.4 million square feet in the third quarter and nearly 6.4 million for the first three quarters.  This trend is expected to continue due to the availability of inexpensive but educated labor, cheap utilities and an excellent transportation network which attract companies looking to relocate into Phoenix from California, Texas and the eastern United States.

Construction activity in 2011 totals 3.5 million square feet through the first three quarters compared to 619,800 square feet a year ago. Build-to-suit projects, which include Intel, First Solar, Crescent Crown Distributing and FedEx, represent 87.5 percent of all current construction activity.

The metropolitan Phoenix industrial vacancy rate decreased 210 basis points in the third quarter to 12.6 percent, from 14.7 percent at the end of 2010.  In comparison, the vacancy rate one year ago was 15.3 percent. This represents a decline of 17.7 percent in vacant space year-over-year. Continuing to have a significant impact on the overall vacancy rate is the distribution market, which ended the third quarter at 12.2 percent vacant, compared to 18.4 percent vacant one year ago.  Vacant distribution space totals 9.7 million square feet or 27.9 percent of all vacant space Valley-wide.  One year ago, there was 14.6 million square feet of vacant distribution space, which accounted for 34.9 percent of all the vacant industrial space in metro Phoenix.

While the net direct average asking lease rate in metropolitan Phoenix varies considerably based on submarket and product type, the third quarter average asking lease rate for existing product remained relatively unchanged from the previous quarter, at $0.55 per square foot.  One year ago the rate was $0.54 per square foot.  By product type, the current net direct average asking lease rates for existing product are as follows: $0.63 per square foot for multi-tenant buildings, $0.34 per square foot for distribution buildings, $0.56 per square foot for general industrial buildings and $0.96 per square foot for back office buildings.

Gary Ringel, CGREA

Phoenix Retail Vacancy and Lease Rates Stabilize in Third Quarter of 2011

The retail market experienced positive absorption in the third quarter with 98,775 square feet after two consecutive quarters of negative absorption. 

Retail centers currently under construction in metropolitan Phoenix total 218,000 square feet.

At the end of the third quarter the metropolitan Phoenix retail vacancy rate was 12.4 percent, compared to 12.3 percent one year ago. In the third quarter, the vacancy rate had increased by 490 basis points to 12.4 percent from year-end 2008 when the vacancy rate was 7.5 percent. New construction delivered in the third quarter was 182,000 square feet. There currently is 218,000 square feet of retail space under construction in metropolitan Phoenix, compared to 407,590 square feet one year ago.

The average net asking lease rate for existing retail centers in metropolitan Phoenix at the end of the third quarter was $15.95 per square foot, compared to $15.53 per square foot at year-end 2010. The average asking rate is up 1.5 percent from one year ago when the rate was $15.71 per square foot. At the end of the third quarter, the average net asking lease rate for existing space in power centers was $8.92 per square foot, with neighborhood centers asking $15.29 per square foot, community centers $16.27 per square foot and strip centers $3.47 per square foot.

Thinking of Purchasing a Retail Property?

We believe the retail market, with the exception certain submarkets, has reached bottom.  If you agree, are contemplating purchasing a retail shopping center, contact a real estate appraiser.

Gary Ringel, CGREA

Mr. Jones’ eyes became fixed on a pitcher of ice water setting in the middle of the conference room’s table.  He no longer was focusing on the examining attorney.  Then it happened.  Mr. Kruft stood up, walked around the table next to the attorney, reached across the table for the pitcher of ice water, and promptly deposited its contents squarely on the lap of his now stunned antagonist.

This is a true story – one related to me a few years ago by a court reporter who was present at this particular deposition.  Typically, court reporters do word processing of pretty much the spoken word in a deposition.  But, on the other hand, they will also make careful typed note of really unusual actions while the deposition is in process.  Purposefully dropping a load of ice water on one’s lap in the deposition room is stuff that is sure to make it to the deposition transcript.

Can you imagine how the description of this scenario would read to a judge or jury?  You can almost bet it would bring out a few giggles.  Would it make Mr. Kruft’s testimony appear less truthful?  Probably not.  However, with the deposing attorney now knowing that Mr. Kruft has some hot buttons that are easy to push, what better place to push them than in the courtroom?

What about you?  What will you do if ever you are deposed?   A good common sense approach to consider is this:  At a deposition, you need to keep your cool – period.  The old saying that “Composure is power” is true here.  If you are deposed you must try as best you can to remain unflappable.  Don’t allow yourself to be so intimidated that you start volunteering information about which you were not asked;  or, arguing with the deposing attorney.  Be comfortable with answering only what you were asked- nothing more.

Opposing attorneys will judge how you respond to their questioning.  They will consider this as they envision how you will come across in the courtroom to a judge, or a jury.  They will like to know if you will be a calm and persuasive witness.  Or, one that gets easily flustered when asked to state the truth.  Or, one that likes to argue with the cross-examining attorney.

By the way, if you are deposed by an ornery, bad-mannered attorney, don’t take it personal.  Most of the attorneys who have ever deposed me that I thought were of this ilk turned out to be pretty decent folks outside of the deposition room.  They are merely doing their job, even if it requires a bit of “tough-guy” theatrics.

Don Bays, CPA, ABV, CVA, CFF

The standard deviation is most applicable in situations in which the data is similar to a normal distribution.  As shown below, a normal distribution exhibits a “bell curve” shape and a range of one standard deviation will capture the central most two thirds of the data.

Vendor payment data does not typically exhibit a normal distribution pattern for the following common reasons:

• Payments are typically bounded at the lower end of the range by zero, as payment typically occurs after an invoice has been remitted, and often require up to five days for processing and remittance
• Companies can have payment cycles that lump the payment of multiple invoices from different dates into one payment which leads to longer tails on the right side of the distribution
• Disputes and administrative errors can often lead to outlier payments with a high reported days to pay on the right side of the distribution
• Payments will tend to cluster around stated terms, discount terms, or industry terms which leads to a spike in the distribution around these number of days

The graph below shows a typical non-normal payment distribution with a long right-sided tail.

While much lesser known than standard deviation, median absolute deviation is a more robust estimator of scale than standard deviation for data sets that are not normally distributed.  The median absolute deviation is said to be a robust statistic because it is more resilient to outliers in data than the standard deviation.  This is because in computing the standard deviation, the distances from the mean are squared, so that on average, large outliers are weighted more heavily and can potentially skew the results.  In computing the median absolute deviation, the magnitude of a relatively small number of outliers is irrelevant and will not skew the results.  Therefore, utilizing a median absolute deviation methodology can eliminate the need to subjectively eliminate outliers from the data set.

The median absolute deviation is computed by first determining a median for a given population.  Second, the absolute value of the distance between each separate observation and the median is computed.  The median absolute deviation is then determined by computing the median of the values computed in the second step.  An example of this calculation is presented below.

Mark Hughes, CPA, ABV, CFF