Sampling for Sales and Use Tax Audits

by Will Yancey, PhD, CPA

 

Winning Essay, Literary Award Competition,

Institute for Professionals in Taxation,

Awarded in Toronto, June 15, 1999

Published in IPT Sales Tax Report, July-August 1999, pp. 1-2.





 

Introduction

Why Sample?

Sampling Risk, Nonsampling Risk and Sampling Cost

Nonstatistical Versus Statistical Sampling

Financial Statement Versus Transaction Tax Audits

Summary and Call for Education



  Introduction

                       Sampling is growing as an important issue in sales and use tax audits. Auditors from some state tax departments are implementing
                       more advanced sampling methods than block sampling that has been used so heavily in the past. Taxpayers are more carefully
                       analyzing audit sampling plans to verify the accuracy and efficiency of those plans.

                       The purpose of this essay is to describe some fundamental concepts of sampling in sales and use tax audits. First, the essay
                       answers the question, "Why sample instead of detail examination of each transaction?" Answering this question leads to the second
                       topic, the definitions of sampling risk, nonsampling risk, and sampling cost. Third, nonstatistical and statistical sampling methods are
                       compared. Fourth, differences between financial statement audits and transaction tax audits are explained. The final section provides a
                       summary and call for more education on sampling for sales and use tax professionals.
 

 Why Sample?

                       Sampling is necessary when the taxpayer has so many records that a detailed examination of each record is not possible. Virtually all
                       state sales and use tax auditors use some form of sampling on large corporate taxpayers. Without sampling the auditors would be
                       unable to complete audits in a reasonable amount of time.

                       Sales and use tax audit samples consist of a subset of records drawn from a large population of transaction records. These sample
                       transactions are examined for errors, including tax underpayments and overpayments. Projections are made from the errors observed
                       in the sample to an estimate of the errors in the population. Usually positive and negative errors from the sample transactions are
                       netted against each other to yield a total net error. Some audits consist of detail examination of all transactions above some dollar
                       threshold, and sampling for transactions below that threshold.

                       Taxpayers benefit from efficient and effective sampling in sales and use tax audits. Proper sampling improves efficiency by testing a
                       much smaller number of records than a complete detail examination of the population. The sampling plan is effective when it provides
                       an accurate estimate of the true amount of error in the population. Effectiveness is not directly measurable, since the true amount of
                       error would be known only if every record were examined in detail.
 

 Sampling Risk, Nonsampling Risk, and Sampling Cost

                       Researchers in many scientific disciplines have evolved sophisticated sampling methods over the past century. Some concepts
                       relevant to sales and use tax audits are sampling risk, nonsampling risk, and sampling costs.

                       Sampling risk is the chance that the estimate projected from the sample is significantly different from the amount that would be
                       determined if every item in the population were tested. Sampling risk is inevitable whenever a sample is tested rather than the complete
                       population. Good sampling procedures are designed to reduce sampling risk, but this risk cannot be eliminated without testing every
                       item in the population. Unless we test every item in the population, we do not know the difference between the amount projected from
                       the sample and the true amount in the population.

                       Sampling risk is increased when small samples are taken. For example, suppose we know that in a population of 1,000,000 records
                       approximately two percent of those records contain tax errors. Taking a sample of only 50 records from this population has a high
                       sampling risk, because there is a high chance that this sample will show zero errors. It is remotely possible that a sample of 50 will
                       include exactly one error and that the projection from that one error will be close to the true amount of underpaid or overpaid tax in the
                       population. Taking a sample of 500 items increases the chances of accurately estimating the error rate (10 errors in a sample of 500
                       gives a two percent error rate).

                       Sampling risk should not be confused with sampling bias. Sampling risk is the probability that the sample projection differs from the
                       population without specifying a direction. Sampling bias is the probable direction of the difference between the estimate and the
                       population. The government will probably collect more revenue than it should when the sample is biased towards over assessment. The
                       taxpayer probably pays less than it should when the sample bias is towards under assessment. People experienced with sampling in
                       the sales and use tax environment can evaluate an audit sampling plan for both risk and bias.

                       Nonsampling risk is the risk that an incorrect determination of total error would be made even if the testing procedures were applied to
                       every item in the population. An example of nonsampling risk is where the auditor incorrectly applies the law to determine the taxability
                       of items in the sample. Another example of nonsampling risk is when reversing entries are omitted from the sample, but the projection
                       is made over a population that includes reversing entries.

                       Sampling cost in a sales and use tax audit is the total cost of planning, selecting, testing, and reviewing the sample. The most obvious
                       costs are the time for clerical staff to find and copy documents, and for the auditor to examine those documents. Sampling costs also
                       include the time and expense for the taxpayer and its representatives to review the auditor’s work and to resolve difficult items in the
                       sample.

                       Proper sample planning must consider the trade-offs between sampling risk, nonsampling risk, and sampling cost. Decreasing
                       sampling risk often requires increasing sample size and sampling cost. Decreasing nonsampling risk may require more extensive
                       training and review that increases sampling cost. However, sampling risk and nonsampling risk are also costly in the sense that
                       incorrect assessments or refunds. The taxpayer and the auditor should become aware of the risks and costs, and reach some
                       agreement on how to trade-off those risks and costs.
 

 Nonstatistical Versus Statistical Sampling

                       In nonstatistical sampling, the auditors estimate sampling risk by relying on professional judgment. The severe limitation of
                       nonstatistical sampling is that it does not allow the auditor to make a quantitative estimate of sampling risk. An example of
                       nonstatistical sampling is block sampling where auditors select a few days, weeks, or months from the population. The auditor
                       assumes the sample time periods are representative of the entire population. By not taking sample transactions over the entire audit
                       period, block samples increase sampling risk. If the tax error rate in the sample time periods differs significantly from the time periods
                       not sampled, the block sampling method will produce results that are not valid.

                       Statistical sampling methods do provide quantitative estimates of sampling risk. Statistical sampling requires that the person selecting
                       the sample relies on a random sample selection process rather than his or her judgment about the extent to which the sample
                       represents the population. The projected error from a statistical sample may differ significantly from the true error in the population, but
                       this sampling risk can be quantified using statistical formulas derived from the theory of probability. Sampling risk is usually expressed
                       as a confidence interval, such as a 95 percent chance that the total error is between $400,000 and $480,000.

                       A statistical sampling plan begins with (1) a goal for accuracy, such as a 95 percent confidence interval, (2) a tolerable error, such as
                       $25,000, and (3) an estimate of the error rate in the population, such as one percent. Statistical formulas are used to compute the
                       sample size that is likely to achieve these goals. The population is divided into two or more strata, and a specified number of items are
                       randomly selected from each stratum. After the sample results are collected, the sample is evaluated to determine if the sampling
                       goals are achieved. If those goals are not achieved, the sample could be expanded or the goals could be modified.

                       One nonstatistical method of sample evaluation used by some auditors is to compare the distribution of invoice dollars in the sample to
                       the distribution of invoice dollars in the population from which the sample is drawn. If the sample’s mean dollars per transaction is close
                       to the population’s mean, the auditor concludes the sample is representative of the population. The auditor assumes that if the invoice
                       dollars are representative, then the projected error from the sample will also be representative of the population. This method relies on
                       the auditor’s judgment rather than a quantified estimate of sampling risk.
 

 Financial Statement Versus Transaction Tax Audits

                       The primary purpose of a financial statement audit is to determine whether the financial statements taken as whole are materially
                       correct. Financial auditors explicitly consider materiality. For example, the materiality threshold for a corporation with $10 billion in
                       assets might be $50 million. The financial auditors’ null hypothesis is that the financial statements are materially correct. Sample data
                       is gathered to determine whether there is sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis that the
                       financial statements are materially incorrect. Similarly, financial auditors also test a corporation’s system of internal controls to
                       determine whether they are or are not functioning properly. Thus, the primary purpose of financial statement auditors is reach a
                       conclusion about whether to accept or reject a null hypothesis. A secondary purpose of financial audits is to estimate the amount of
                       adjustment that would materially correct the financial statements.

                       In contrast, the primary purpose of a tax audit is to estimate the amount of overpaid or underpaid tax. The tax auditor may have no
                       specific policy on the materiality threshold for a sales and use tax audit. If the threshold is zero, then any adjustment including one
                       single dollar is material. When a materiality threshold is specified for tax audits, it is far less than the level chosen for the audit of
                       taxpayer’s consolidated financial statements. A possible secondary purpose of a tax audit is to accept or reject the hypothesis that
                       the taxpayer’s tax accrual system is functioning with an acceptably low error rate.

                       Financial statement auditors have the advantage of well-developed set of professional standards on audit sampling. The best-known
                       financial statement audit standard is the American Institute of Certified Public Accountants’ Statement on Auditing Standards Number
                       39 ("SAS 39") that describes both statistical and nonstatistical sampling. SAS 39 provides general guidance for auditors to consider in
                       planning an financial statement audit. Professional standards for sales and use tax audits do not exist at this time.
 

 Summary And Call For Education

                       The preceding sections of this essay describe some general concepts for sampling in sales and use tax audits. Sampling is needed
                       when the taxpayer’s records are too voluminous to examine in detail. Sample planning requires trade-offs between sampling risk,
                       nonsampling risk, and sampling cost. Statistical sampling methods provide a quantified estimate of sampling risk, and nonstatistical
                       methods do not. Financial statement audits have a higher materiality threshold and more emphasis on hypothesis testing than sales
                       and use tax audits.

                       The reluctance of auditors, taxpayers, and consultants to discuss sampling issues is due to a lack of understanding of the fundamental
                       concepts. Better education and training guides specifically applying sampling to practical problems in sales and use tax audits will
                       improve understanding. Cooperation between government agencies and professional associations will improve the implementation and
                       training for sales and use tax audit sampling. As all parties become better educated, they will become more confident in the use of
                       sampling. Better cooperation might decrease sampling costs and audit dispute resolution time.