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Internal control effectiveness and trade credit

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Abstract

In this study, we investigate whether trade credit is associated with internal control effectiveness. Using a sample of U.S. publicly listed firms over the period 2006–2018, we find strong and robust evidence that internal control effectiveness firms have a lower level of trade credit. Our additional analyses show that the cost of equity capital moderates the relation between internal control effectiveness and trade credit. We also find evidence that internal control effectiveness firms make quicker payments for their trade credit contracts than other firms. In addition, we find that firms have a higher demand for trade credit when the firms have ineffective internal controls, disclose entity level internal control material weaknesses, and report internal control ineffectiveness related to trade credit accounts. Taken together, these findings suggest that internal control effectiveness plays an important role in trade credit-a special form of firms’ short-term financing source.

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Notes

  1. We update the observations of each firm i for each data-year.

  2. In the main analysis, we follow prior research (e.g., Xu et al. 2020a, b) and use Compustat’s two-digit Standard Industrial Classification (SIC) codes to classify industry groups. We also conducted a robustness test using Fama French (FF) 48 industry classification. Our Pearson correlation results (untabulated) show that FF 48 industry classification is closely related to Compustat’s four-digit SIC classification. The FF 48 industry classification starts from Compustat’s four-digit SIC codes and links these codes to 48 industry groups (Fama and French 1997). Based on the FF 48 industry classification, we recalculate market shares for the 48 industries and rerun Eq. (1). The untabulated results are relatively similar to our main results in Table 4.

  3. To further check the robustness of the results reported in Table 4, we replicate Table 4 using industry-adjusted values for all continuous variables. An industry-adjusted variable refers to the raw measure of the variable adjusted by the median value of the same variable of all firms in Compustat in a given two-digit SIC industry and year. The untabulated results of the model using industry-adjusted values for all continuous variables are consistent with the primary results.

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Authors and Affiliations

  1. The Department of Accounting, The University of Toledo, Toledo, USA

    Mai Dao

  2. Department of Accounting, Economics, and Finance, University of Illinois Springfield, Springfield, USA

    Trung Pham

  3. Accounting and Finance Department, University of Massachusetts Dartmouth, Dartmouth, USA

    Hongkang Xu

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  1. Mai Dao
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  2. Trung Pham
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Correspondence to Mai Dao.

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Appendix: Variable definitions

Appendix: Variable definitions

Variable

 

Definition

Main variables

  

TRADECREDIT

=

The ratio of accounts payable (ap) to the book value of total assets (at) (Data source: Compustat)

IC_EFFECTIVE

=

An indicator variable equal to 1 if the auditor found the firm maintained, in all material respects, effective internal control over financial reporting and 0 if the auditor found at least a material weakness in internal control (ICMW) and the client firm received an adverse opinion on the effectiveness of internal control over financial reporting. A material weakness is a deficiency, or a combination of deficiencies, in internal control over financial reporting, such as there is a reasonable possibility that a material misstatement of the firm’s annual or interim financial statements will not be prevented or detected on a timely basis. A material weakness can be at the account/transaction level (e.g., internal control deficiency in approach, theory or calculation associated with the expensing of assets or understatement of liabilities, the recording of gains or losses from the sales of assets, etc.) and/or at the firm level (e.g., potentially improper or negligent conduct of the current or former senior management of the company) (Data source: Audit Analytics)

AP/LT

=

The ratio of accounts payable (ap) to the total liabilities (lt) (Data source: Compustat)

COGS_AP

=

The ratio of cost of goods sold (cogs) to accounts payable (ap) (Data source: Compustat)

AP_TURNOVER

=

The sum of inventory change (invch) and cost of goods sold (cogs) divided by average accounts payable (Data source: Compustat)

DAYS_PAYABLE

=

Days payable outstanding, measured as the product of accounts payable (ap) and 365 days divided by cost of goods sold (cogs) (Data source: Compustat)

COUNT_WEAK

=

The number of material weaknesses (count_weak) (Data source: Audit Analytics)

MW_ENTITY

=

An indicator variable equal to 1 if the firm disclosed at least one entity level material weakness over financial reporting as reported in Audit Analytics and 0 otherwise. Entity level material weaknesses are those that the Audit Analytics database (codes in parentheses) identifies as (1) nonroutine transaction control issues (code 77); (2) journal entry control issues (code 76); (3) foreign, related‐party, affiliated, or subsidiary issues (code 38); (4) an ineffective, nonexistent, or understaffed audit committee (code 11); (5) senior management competency, tone, or reliability issues (code 13); (6) an insufficient or nonexistent internal audit function (code 18); (7) ethical or compliance issues with personnel (code 21); or (8) accounting personnel resources, competency, or training issues (code 44) (Data source: Audit Analytics)

PAYABLE_ICW

=

An indicator variable equal to 1 if the internal control weakness is related to accounts payable and/or cost of goods sale, and 0 otherwise (Data source: Audit Analytics)

Control variables

  

AQ

=

Abnormal accruals computed using the Jones (1991) model modified by Dechow et al. (1995). This measure is then multiplied by -1 (Data source: Compustat)

BIG4

=

A dummy variable that equals 1 if the firm is audited by a Big 4 auditor, and 0 otherwise (Data source: Audit Analytics)

CA

=

The ratio of noncash current assets to the book value of total assets (Data source: Compustat)

CASHHOLD

=

The ratio of cash and marketable securities (che) to total assets (at) (Data source: Compustat)

COST_OF_DEBT

=

The ratio of total interest and related expense (xint) to total debts (Data source: Compustat)

COST_OF_EQUITY

=

The cost of equity capital estimated from the PEG model (Easton 2004) (Data source: IBES and CRSP)

CL_XTRADE

=

The ratio of current liabilities (lct) excluding accounts payable (ap) to total assets (at) (Data source: Compustat)

LEV

=

The ratio of long-term debt and debt (dltt) in current liabilities (dlc) to the book value of assets (at) (Data source: Compustat)

LIQUID_COST

=

liquidation costs calculated as the ratio of raw materials (invrm) to total assets (at) and multiplied by -1 (Data source: Compustat)

FIRM_AGE

=

The natural logarithm of firm age plus 1 (Data source: Compustat)

SIZE

=

The natural logarithm of the book value of total assets (at) (Data source: Compustat)

MKTSHARE

=

A firm's market share calculated as the firm's sales divided by total industry sales, where the classification of industry groups is based on Compustat’s two-digit Standard Industrial Classification (SIC) codes (Xu et al. 2020a, b) (Data source: Compustat)

MTB

=

The ratio of the market value of equity (prcc_f*csho) to the book value of net assets (ceq) (Data source: Compustat)

NEG_CHGSALE

=

Negative changes in sales scaled by the book value of total assets (at) (Data source: Compustat)

OPERATING_CYCLE

=

The natural logarithm of days of accounts receivable plus days of inventories (Data source: Compustat)

POS_CHGSALE

=

Positive changes in sales scaled by the book value of total assets (Data source: Compustat)

PRED_RATING

=

S&P letter credit ratings available (spcsrc) in the Compustat database converted into numerical ratings. Numerical credit ratings are obtained through a conversion process in which a rating of AAA (i.e., the highest credit rating) is assigned a value of 1 and a group of lowest credit ratings (including, CCC+, CCC, CC, C, CCC-, D, and SD) receives a value of 17. If the S&P rating is not available for a firm-year, we estimate a credit rating following Beatty et al. (2008). The larger the value of the predicted rating, the lower the credit quality (Data source: Compustat)

ROA

=

The ratio of net income over total assets (Data source: Compustat)

TANGIBILITY

=

The ratio of net property, plant, and equipment (ppent) to assets (at) (Data source: Compustat)

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Dao, M., Pham, T. & Xu, H. Internal control effectiveness and trade credit. Rev Quant Finan Acc 59, 1423–1452 (2022). https://doi.org/10.1007/s11156-022-01079-3

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