COVID-19 Pandemic, Internal Audit Function and Audit Report Lag: Evidence from Emerging economy

Figures & data

Table 1. Variable definition

Variable	Description	Source
ARL	Number of days between year-end date to auditor report date	(Baatwah et al., 2022; Al-Ebel et al., 2020)
COVID-19	Dummy variable, 1 if the fiscal year ended on or after 31/12/2019; 0 otherwise.	(Al-Qadasi et al., 2022)
LnIAFC	Natural log of investment (cost) in the internal audit function	(Wan-Hussin & Bamahros, 2013)
ACSIZE	Total number of audit committee members	(Ghaleb et al., 2021)
ACMEET	Frequent audit committee meetings	(Ghaleb et al., 2021)
BDSIZE	Number of members of board of directors	(Mohamad-Nor et al., 2010); (Qaderi et al., 2022)
BDMEET	Frequent meetings of board of directors	(Hashim & Abdul-Rahman, 2010)
IAFSOUR	1 if IAF in-house; 0 otherwise	(Wan-Hussin & Bamahros, 2013)
BIG4	1 if auditor is PricewaterhouseCoopers, Ernst and Young, KPMG, or Deloitte, 0 otherwise	(Mohamad-Nor et al., 2010)
AFEE	Natural log of audit fees	(Al-Qadasi et al., 2022)
LnNAFEE	Natural log of non-audit fees	(Baatwah & Al-Qadasi, 2019)
LnCSIZE	Natural log of total assets	(Mohamad-Nor et al., 2010)
LOSS	1 if the firm reported negative income, 0 otherwise	(Baatwah & Al-Qadasi, 2019)
LEV	Leverage is total debt to total assets	(AL-Qadasi et al., 2019)
YEAR	Years 2017–2020	(AL-Qadasi et al., 2019)
INDUS	Industry dummies	(Altarawneh et al., 2022; AL-Qadasi et al., 2019)

Table 2. Descriptive statistics

Variable	Mean	SD	Median	Min	Max
ARL	99.811	25.601	100	11	181
COVID-19	.398	.49	0	0	1
LnIAFC	4.946	1.691	4.468	0	9.863
ACSIZE	3.344	.611	3	3	7
ACMEET	5.118	1.239	5	3	18
BDSIZE	7.584	1.901	7	4	15
BDMEET	5.656	2.285	5	3	25
IAFSOUR	.441	.497	0	0	1
BIG4	.47	.499	0	0	1
LnAFEE	5.720	1.012	5.521	2.425	9.976
LnNAFEE	3.487	1.849	3.519	0	9.685
LnCSIZE	13.585	1.533	13.390	6.073	19.016
LOSS	.175	.38	0	0	1
LEV	.195	.161	.1693	0	.894

Table 3. Matrix of Pearson correlations

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)
(1) ARL	1.000
(2) COVID-19	0.348***	1.000
(3) LnIAFC	−0.302***	0.040	1.000
(4) ACSIZE	−0.152***	0.059**	0.278***	1.000
(5) ACMEET	0.004	−0.026	0.329***	0.142***	1.000
(6) BDSIZE	−0.119***	0.018	0.372***	0.372***	0.208***	1.000
(7) BDMEET	−0.026	0.057**	0.404***	0.140***	0.565***	0.222***	1.000
(8) IAFSOUR	−0.214***	0.033	0.716***	0.190***	0.201***	0.225***	0.239***	1.000
(9) BIG4	−0.170***	0.024	0.491***	0.139***	0.134***	0.177***	0.218***	0.426***	1.000
(10) LnAFEE	−0.169***	0.052*	0.765***	0.150***	0.337***	0.267***	0.417***	0.489***	0.483***	1.000
(11) LnNAFEE	−0.140***	0.002	0.554***	0.151***	0.272***	0.197***	0.334**	0.336***	0.440***	0.622***	1.000
(12) LnCSIZE	−0.198***	0.032	0.578****	0.143***	0.244***	0.276***	0.288***	0.382***	0.326***	0.590***	0.403***	1.000
(13) LOSS	0.097***	−0.144***	−0.027	−0.059**	0.065**	−0.101***	0.035	0.022	−0.002	0.014	−0.015	−0.118***	1.000
(14) LEV	0.015	0.059**	0.228***	0.012	0.114***	0.089***	0.148***	0.162***	0.159***	0.302***	0.161***	0.412***	0.084***	1.000

***p < 0.01, **p < 0.05, *p < 0.1

Table 4. FGLS regression analysis of ARL

Variables	Model 1	Model 2
ARL	Coef.	Coef
COVID-19	35.042***	40.778***
LnIAFC		−4.275***
COVID-19*LnIAFC		−1.241***
ACSIZE	−2.872***	−2.093***
ACMEET	0.419	0.664
BDSIZE	−0.222	0.226
BDMEET	1.1***	1.231***
IAFSOUR	−6.527***	−1.106
BIG4	−0.515	0.339
LnAFEE	−2.886***	0.506
LnNAFEE	0.301	0.502**
LnCSIZE	−.887***	−0.518**
LOSS	−0.305	−0.118
LEV	7.343***	7.521***
Constant	125.89	110.906
Year Effect	Include	Include
Industry Effect	Include	Include
Wald chi^2	2493.47	2726.17
Prob > chi^2	0.0000	0.0000

Note(s): ***p < .01, **p < .05, *p < .1.

Table 5. FGLS regression analysis of TRL

Variables	Model 1	Model 2
TRL	Coef.	Coef.
COVID-19	37.644***	45.072***
LnIAFC		−1.203***
COVID-19*LnIAFC		−1.405***
ACSIZE	−1.98***	−1.865***
ACMEET	0.67**	0.736**
BDSIZE	0.126	0.302*
BDMEET	0.42**	0.556***
IAFSOUR	−2.778***	−0.588
BIG4	−0.896	−0.613
LnAFEE	−0.695	0.159
LnNAFEE	−0.073	0.004
LnCSIZE	−0.831***	−0.578**
LOSS	0.785	1.092*
LEV	5.55***	4.607***
Constant	133.126***	126.56***
Year Effect	Include	Include
Industry Effect	Include	Include
Wald chi^2	3134.99	3450.84
Prob > chi^2	0.0000	0.0000

Note(s): ***p < .01, **p < .05, *p < .1.

Table 6. Regression results of study model using DV lagged value

Variables	Model 1	Model 2
ARL	Coef.	Coef.
ARLt-1	0.572***	0.558***
COVID-19	31.665***	41.298***
LnIAFC		−1.894**
COVID-19*LnIAFC		−1.895***
ACSIZE	−2.514**	−2.146**
ACMEET	1.597**	1.595**
BDSIZE	0.453	0.608*
BDMEET	0.516	0.792*
IAFSOUR	−3.079**	0.561
BIG4	−2.012	−1.752
LnAFEE	0.955	2.209**
LnNAFEE	0.419	0.512
LnCSIZE	−3.299***	−2.352***
LOSS	2.962	2.864
LEV	10.765***	9.991**
Constant	71.3***	56.182***
Year Effect	Include	Include
Industry Effect	Include	Include
R-squared	0.544	0.554
Prob > F	0.000	0.000

Note(s): ***p < .01, **p < .05, *p < .1.

Table 7. Two-way fixed-effect regression

	Model 1	Model 2
ARL	Coef.	Coef
COVID-19	32.33***	39.782***
LnIAFC		0.783
COVID-19*LnIAFC		−1.503***
ACSIZE	0.225	−0.008
ACMEET	−0.335	−0.437
BDSIZE	1.351***	1.348***
BDMEET	1.965***	2.039***
IAFSOUR	2.778	2.468
BIG4	7.482**	7.881***
LnAFEE	−1.475	−1.528
LnNAFEE	0.807	0.803
LnCSIZE	−0.613	−0.279
LOSS	−1.185	−1.069
LEV	5.71	6.306
Constant	79.457***	72.118***
Year Effect	Include	Include
Industry Effect	Include	Include
R-squared	0.509	0.514
Prob > F	0.000	0.000

Note(s): ***p < .01, **p < .05, *p < .1.

Baatwah, S. R., Almoataz, E. S., Omer, W. K., & Aljaaidi, K. S. (2022). Does KAM disclosure make a difference in emerging markets? An investigation into audit fees and report lag. International Journal of Emerging Markets, 17(9), 1–24. https://doi.org/10.1108/IJOEM-10-2021-1606

 Google Scholar

Al-Ebel, A., Baatwah, S., Al-Musali, M., & Ntim, C. G. (2020). Religiosity, accounting expertise, and audit report lag: Empirical evidence from the individual level. Cogent Business and Management, 7(1), 1–29. https://doi.org/10.1080/23311975.2020.1823587

 Google Scholar

Al-Qadasi, A., Baatwah, S. R., & Omer, W. K. (2022). Audit fees under the COVID-19 pandemic: Evidence from Oman. Journal of Accounting in Emerging Economies, 12(3), 1–19. https://doi.org/10.1108/JAEE-08-2021-0269

 Google Scholar

Wan-Hussin, W. N., & Bamahros, H. M. (2013). Do Investment in and the sourcing arrangement of the internal audit function affect audit delay? Journal of Contemporary Accounting and Economics, 9(1), 19–32. https://doi.org/10.1016/j.jcae.2012.08.001

 Google Scholar

Ghaleb, B. A. A., Kamardin, H., & Hashed, A. A. (2021). Investment in outside governance monitoring and real earnings management: Evidence from an emerging market. Journal of Accounting in Emerging Economies, 12(1), 52–76. https://doi.org/10.1108/JAEE-08-2020-0203

 Google Scholar

Mohamad-Nor, M. N., Shafie, R., & Wan-hussin, W. N. (2010). Corporate governance and audit report lag in Malaysia. Asian Academy of Management Journal of Accounting and Finance, 6(2), 57–84. https://ideas.repec.org/a/usm/journl/aamjaf00602_57-84.html

 Google Scholar

Qaderi, S. A., Ghaleb, B. A. A., Hashed, A. A., Chandren, S., & Abdullah, Z. (2022). Board characteristics and integrated reporting strategy: Does sustainability committee matter? Sustainability, 14(10), 1–24. https://doi.org/10.3390/su14106092

 Google Scholar

Hashim, U. J. B., & Abdul-Rahman, R. B. (2010). Board Independence, board diligence, board expertise and impact on audit report lag in Malaysian market. Finance and Corporate Governance Conference, 1–22.

 Google Scholar

Baatwah, S. R., & Al-Qadasi, A. A. (2019). Determinants of outsourced internal audit function: A further analysis. Eurasian Business Review, 10(4), 629–659. https://doi.org/10.1007/s40821-019-00142-9

 Google Scholar

AL-Qadasi, A. A., Abidin, S., & Al-Jaifi, H. A. (2019). The puzzle of internal audit function budget toward specialist auditor choice and audit fees: does family ownership matter? Malaysian evidence. Managerial Auditing Journal, 34(2), 208–243. https://doi.org/10.1108/MAJ-09-2017-1655

 Google Scholar

Altarawneh, M., Shafie, R., Ishak, R., & Ghaleb, B. A. A. (2022). Chief Executive Officer Characteristics and Discretionary Accruals in an Emerging Economy. Cogent Business & Management, 9(1), 1–20. https://doi.org/10.1080/23311975.2021.2024117

 Google Scholar