異常關係人銷貨偵測模型之建構

Constructing the Model of Detecting Abnormal Related-Party Sales

林昱成(Yu-Cheng Lin) ； 吳壽山(Sou-Shan Wu) ； 蕭子誼(Tzy-Yih Hsiao) ； 林金賢(Chin-Shien Lin)

《管理學報》 24卷5期 (2007/10) Pp. 585-601

https://doi.org/10.6504/JOM.2007.24.05.06

摘要

本研究之目的在於建構一個偵測異常關係人銷貨之模型－RPS模型(Related-party Sales Model)，且運用統計分析及測試RPS模型之顯著水準與檢定力。過去研究者多以Dechow et al.(1995)所發展之Modified-Jones模型作為偵測企業盈餘管理之實證模型。然而Modified-Jones模型係假設企業以應計項目作為盈餘管理方法，惟企業若以誘導（或強迫）銷貨予關係人，並於期末時將應收帳款收回、運用借款資金之流入以沖銷應收帳款或採用假賣斷應收帳款等方式以壓低裁決性應計項目，則此應計基礎模型之偵測能力十分低弱。因此，本研究認為若以應計基礎模型偵測盈餘管理時，在企業基於特定目的而刻意將關係人銷貨所產生的應收帳款收回的方式操縱盈餘時，必然出現模型檢定力低弱之情形，此為應計項目盈餘管理模型之嚴重限制。故本研究先藉由銷管費用以推估企業正常銷貨數，乘上前期關係人銷貨比率，以計得正常關係人銷貨數，其後以當期實際關係人銷貨數，推估出異常關係人銷貨數。因此，本研究所推估出之異常關係人銷貨數，其中已包括異常應計與非應計基礎下關係人銷貨數，此舉將可改善Modified-Jones模型偵測企業在以非應計基礎之方法進行盈餘管理時，檢定力低弱之情形。研究結果顯示，RPS模型在樣本公司以隨機抽樣時，推估異常關係人銷貨模型呈現良好的顯著水準。此外，研究結果也證實，以橫斷面方式推估異常關係人銷貨的RPS模型在盈餘管理數操縱數達前期總資產約百分之四時，模型檢定力即趨近於百分之百。

關鍵字

操縱損益 ； 盈餘管理 ； 關係人銷貨 ； RPS模型

並列摘要

Earnings management is the choice by a manager of accounting policy to achieve some specific objectives; such choices divide into two categories. One is choice of accounting policies, such as straight-line versus declining-balance amortization, or policies for revenue recognition. The other is discretionary accrual, such as provision for credit losses, warranty costs, inventory values, and timing and amounts of non-recurring and extraordinary items like write-offs and provision for recognization (Scott, 2003). An establishment wanting to manage earnings has many tricks to choose, such as adjusting operational discretionary accruals or arranging dealings with its conglomerates. Many scholars study this field, using discretionary and non-discretionary accruals to detect earnings management. Yet few studies confer on related party transactions as a way of earnings management. Actually, there are many instances of controlling stockholders pillaging their own firms through related party transactions. To transfer assets and earnings out of firm for the benefit of those who control them, such as transactions between Enron, Worldcom and its special-purpose entities, firms conduct related party transactions for two reasons. One is to minimize transaction costs, as normal related party transactions. The other is to use related party transactions to manage earnings, as abnormal related party transactions and related party sales as a key related party transaction item for earnings management. Firms could dissimulate opportunistic behavior by manipulating related party sales, since such sales figures are disclosed only in footnotes, not in the income statement (Jian and Wong, 2004). Hence it is not easy to distinguish between normal and abnormal related party sales.
The major purpose of the study is that we are a pioneer in detecting abnormal related party sales (RPS) model, considering recent financial frauds in Taiwan. In the case of manipulating company financial reports, it was revealed that an entity could operate well and attain fiscal solvency. It did much trade with its conglomerates and cashed accounts receivable at the end of the fiscal year, such that the firm could raise funds from investors successfully. Related party transactions are in want of operating for a business once in a while. If an entity makes bargains with its conglomerate persistently, motives of the transactions are dubious, and it is so perplexing to distinguish between normal or abnormal related party transactions. Although specific disclosure requirements are set forth in Statement on Auditing Standards (SAS) Number 6, which provides guidance to auditors in identifying related party transactions, the abnormal related party transactions on financial statement in fact could not be presented in the integrity. So it is a common manner of managing earnings by making bargains with conglomerates in Taiwan. For this reason, we develop the RPS Model to detect abnormal related-party transactions to atone for sad fact that financial reporting is imperfect. And we evaluate performance of the RPS Model by contrasting specification and power, using test statistics. The RPS Model reveals specific items well when applied to a random sample of firm-years, and it also proves that the fine power of RPS Model, measured by cross-sectional method.
Managerial discretion hypotheses are presented from existing literature, and an accrual-based model is used for
detecting earnings management, such as Jones Model (Jones, 1991) and Modified Jones Model (Dechow et al., 1995).They estimate the discretionary components of reported income. Those models appear highly specific and good for detecting manipulated earnings. The accuracy of the Modified Jones Model (Dechow et al., 1995) rises to a hundred percent when earnings manipulation amount come to 10 % of prior assets. But an industry may do extensive trade with conglomerates and cash accounts receivable at the end of the fiscal year for the sake of diminishing the discretionary accruals. Actually such a business manipulates related party transactions for its own interests; it is a pity that those accrual-based models could not detect the management level effectively. Low accuracy of accrual-based models means the model is invalid. It is our belief that there is no use detecting earnings management which administrative department diminishing discretionary accruals items with accrual-based models. It is the restrictions on accrual-based models whereby discretionary accruals are diminished. In this research the RPS Model uses selling expenses and administrative expenses to project the abnormal sales amount from abnormal related party transactions. Management manipulates earnings without respect to accrual or non-accruals; the RPS Model could detect earnings management amount more effectively than accrual-based models.
To an extent, our assumptions are that selling expenses and administrative expenses project the normal sales amount and multiply by the ratio of related party sales is normal related party sales amount. Subtract this from actual relatedparty sales amount and we have abnormal amount of related-party sales. Thus, abnormal accruals and amount of nonaccrual-basis related-party sales are all included in our estimated abnormal amount of related-party sales. Results show RPS Model as an accurate specification via random sample. Besides, it also proves the accuracy of the RPS Model, measured by cross-sectional way, almost reaches one hundred percent, while the amount of related party transactions rises to nearly four percent of prior total assets. So the RPS Model could detect abnormal related-party sales effectively and usefully.

並列關鍵字

Manipulate Income ； Earnings Management ； Related-Party Sales ； and RPS Model

參考文獻

working paper

Dechow, P. M.,R. G. Sloan,A. P. Sweeney(1995).Detecting Earnings Management.Accounting Review.70(2),193-225.

Jian, Ming,T. J. Wong(2004).Earnings Management and Tunneling through Related Party Transactions: Evidence from Chinese Corporate Groups.American Accounting Association 2004 Annual Conference.(American Accounting Association 2004 Annual Conference).

Jones, J. J.(1991).Earnings Management during Import Relief Investigations.Journal of Accounting Research.29(2),193-229.

Peasnell, K. V.,P. F. Pope,S. Young(2000).Detecting Earnings Management Using Cross-Sectional Abnormal Accruals Models.Accounting and Business Research.30(4),313-326.