Managing tax audits using sampling techniques.

AuthorAshtiani, Hamid

Both state and federal tax examiners regularly use sampling and estimation in their tax audits. While sampling in an audit can be a convenient time-saver for both taxpayers and examiners, it is important to know the pitfalls that can cause unduly overstated estimated adjustments when sampling is used in a tax audit. This article explores those potential pitfalls and offers practical advice and best practices.

Sampling is a tool that is generally used whenever there is a list of records, also known as the population, that requires an assessment in order for the taxpayer to categorize the costs in a correct manner. Taxpayers use sampling to estimate the total amount of taxable transactions, meals deductions, expenditures qualifying for the Sec. 41 research credit (R&D credit), and several other applications. (1) The IRS and state taxing authorities typically use sampling to audit taxpayer determinations and estimate adjustments to amounts reported on tax returns. Sampling can produce efficiencies by reducing the volume of work and time required to make the necessary determinations required for tax filings or audits of tax fillings.

The two types of sampling: Statistical and judgmental

The two types of sampling used across tax audits are statistical (random) sampling and judgmental (nonrandom) sampling.

A statistical sample gives each record in the population a known, nonzero chance of selection. This allows for an unbiased sample selection and an unbiased representation of the population. Moreover, the examiner can make mathematically defensible conclusions about the population and the accuracy of the estimates.

A judgmental (nonrandom) sample is based entirely on the examiner's judgment. For example, the examiner may pick the sample based on prior research and knowledge of problematic areas. While this can be efficient for finding issues, it causes gross bias when extrapolating sample results to make conclusions about the population. Even when the examiner attempts to select the sample haphazardly in an effort to judgmentally choose a random assortment, there is a human tendency to select a sample that is not representative of the population, and therefore judgmental samples risk a skewed calculation of adjustments, disallowed amounts, or even penalties and fines.

Both methods of sampling have advantages and disadvantages.

Pros and cons

A common fallacy is that statistical samples require larger sample sizes than judgmental ones. The apparent larger sample sizes are due to stricter specifications for confidence levels and accuracy of estimates, not because the sample is statistically selected.

For example, in an IRS field directive on the use of statistical and judgmental sampling in R&D credit examinations, (2) exam teams are instructed to first calculate the sample size required for an estimate of the disallowance to be accurate within plus or minus 10%. If that required sample size is too large, the directive recommends discussing a smaller sample size with the taxpayer --using judgmental sampling. However, often, that "judgment" sample is merely a randomly selected statistical sample --just a smaller sample size. While many taxpayers would find a smaller, less intrusive audit more appealing, it is important to consider the potential resulting accuracy of an adjustment from a sample that is too small; it could result in a wildly inaccurate estimate of the disallowance. True, a smaller effort could result in a wildly small or wildly large estimated adjustment. The point is that the small sample size is akin to playing high-stakes adjustment roulette.

As a side note, in this particular example, if the taxpayer agreed to the smaller size under a judgmental sample, they would give up more than just protection from a wildcard on the accuracy--whether it is randomly selected or not. IRS guidelines give taxpayers the benefit of the doubt on accuracy when the IRS draws a random sample in an audit. (3) For example, as a result of the sampling, if an unfavorable taxpayer adjustment is estimated to...

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