Internal control and internal capital allocation: evidence from internal capital markets of multi-segment firms

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We investigate the impact of internal control over financial reporting on management decisions in directing corporate resources to alternative investment projects in multi-segment firms. Results from cross-sectional and inter-temporal analyses indicate that internal control weaknesses (ICWs) are associated with distortionary internal capital allocations. The adverse impact on internal capital markets is more pronounced for firms with company-level ICWs. Our analyses also show that firms with weak existing governance mechanisms benefit more from maintaining effective internal control. We further document that the negative impact of ICWs on firms’ internal capital transfers manifests in a lower excess value of diversification.

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  1. 1.

    See “Testimony: Concerning the Impact of the Sarbanes-Oxley Act. House Committee on Financial Services.” Washington, D.C.: Goverment Printing Office.

  2. 2.

    Using a larger sample spanning from 2004 to 2009, we also document that multi-segment firms have a higher probability of reporting ICWs, especially company-level ICWs.

  3. 3.

    The sample distribution for each year (2004–2009) is as follows: 348 (50 firms, or 14.37 %, reporting ICWs) in 2004, 327 (34, or 10.40 %) in 2005, 336 (32, or 9.52 %) in 2006, 319 (27, or 8.46 %) in 2007, 303 (22, or 7.26 %) in 2008, and 284 (14, or 4.93 %) in 2009.

  4. 4.

    We subtract a segment’s interest and tax expenses from earnings before interest and taxes to obtain its after-tax cash flow. There are three ways to calculate a segment’s interest and tax expenses. The first is to impute interest expense and tax rate using same-industry single-segment firms; the second is to prorate a firm’s interest and tax expenses based on each segment’s asset size; and the third is to prorate expenses based on each segment’s sales. Our measure (ICM_ROA) uses the third approach. We obtain similar results if the other two approaches are used.

  5. 5.

    Billett and Mauer (2003) report a lower mean value of ICM_ROA. The difference is probably a result of the different sample periods of the two studies. Their sample period spans from 1990 to 1998, which is before the new segment reporting standard [Statement of Financial Accounting Standards (SFAS) 131] took effect. As noted by Hoechle et al. (2012), Compustat segment files changed substantially under the new reporting framework and segment data before and after 1997 might not be directly comparable.

  6. 6.

    Industry is defined at the firm level based on the Fama and French (1997) 48-industry classification. However, our results remain largely unchanged if we define industry at the segment level, which means more than one industry indicator can equal one if the segments in a firm are from different industries.

  7. 7.

    The internal capital market measures used in the current literature capture underinvestment by good segments and overinvestment by bad segments without considering that firms may invest more than is optimal in high Q segments. To account for potential overinvestment in good segments, we modify the measure of Rajan et al. (2000) by treating overinvestment in high Q segments as inefficient transfers. Overinvesting in a high Q segment is assumed to occur if the segment has above average Q and has capital expenditure more than one standard deviation of capital expenditure of same-industry single-segment firms. The mean (median) value of this alternative measure is −0.0012 (−0.0002). The coefficient on ICW is −0.0013 (p-value =0.066) when this measure is used as dependent variable to estimate Eq. (1). A drawback with this alternative measure is that overinvesting in a high Q segment is deemed worse than overinvestment in another good but lower Q segment. The reason is this measure is weighted by the difference between a segment’s Q and the average of segment Q in the firm. As such, this alternative measure only serves to suggest that overinvestment in high Q segments does not drive our main inferences.

  8. 8.

    The regression result is as follows: ICW = −0.966 (0.017) – 0.186 (0.007) * Size + 0.269 (0.203) * Restructure + 0.589 (0.003) * Loss + 0.351 (0.059) * Foreign + 0.328 (0.296) * M&A + 0.528 (0.013) * ExtrSales - 0.009 (0.151) * Age – 0.522 (0.024) * Big4. Variable definitions are in the Appendix and P-values in parenthesis.

  9. 9.

    To test the effectiveness of the matching, we conduct a covariate balance test and find that the differences in the determinants of ICWs between ICW firms and non-ICW matching firms are not statistically significant except for Loss and Big4, which are marginally significant.

  10. 10.

    CompanyICW is set to one if a firm reports internal control problems related to a lack of segregation of duties, inadequate disclosure controls, an ineffective or understaffed audit committee, a lack of senior management competency and tone, ineffective internal audit functions, and ineffective personnel, and 0 otherwise. AccountICW equals one for firms reporting any weaknesses other than CompanyICW, and 0 otherwise.

  11. 11.

    The E-Index is composed of six of the provisions of the G-Index that Bebchuk et al. (2009) find to drive corporate governance. E-Index is available every other year; for years when the index is not available, we follow previous studies and use the index of the most recent years. Our measure (EIndex) is a linear transformation of E-Index and is defined as 6 – E-Index. Therefore, a higher (lower) value of EIndex indicates a greater (smaller) takeover exposure and better (worse) governance.

  12. 12.

    In this regression, firm-years without status change in ICFR serve as benchmark. For robustness check, we also conduct a change analysis for firm-years with ICFR status change. This analysis directly contrasts the impact of deterioration in ICFR with improvement. When we use ICW_NICW (improvement) as default, the coefficient on NICW_ICW (deterioration) is −0.0035 (t = −3.25) for ΔICM_Invst and −0.0267 (t = −1.81) for ΔICM_ROA, confirming our original conclusions. We thank the referee for this suggestion.

  13. 13.

    We do not impose the sample restriction that firms to be included in diversification discount tests have to be present in the sample for internal capital market analyses because this restriction requires firms to have two consecutive years’ data to compute ICM_Invst and ICM_ROA at year t and ExValA, ExValS, and ExValM at year t + 1. This restriction excludes a large number of valid observations and reduces the sample size substantially.

  14. 14.

    Berger and Ofek (1995) find that, on average, diversified firms are valued less than matching portfolios of specialized firms by 13 to 15 %. Ammann et al. (2012) report a significant diversification discount of between 5 and 21 % for US nonfinancial firms between 1998 and 2005.

  15. 15.

    As Hoechle et al. (2012) document that a substantial portion of the diversification discount can be explained away by governance variables, we control for the effects of outside directors, institutional shareholders, analysts, the takeover market, and executive equity incentives. The results (untabulated) indicate that the coefficient on ICW remains significant for ExValA and ExValM but with a smaller magnitude, and negative but insignificant for ExValS.

  16. 16.

    In this regression, firm-years without status change in ICFR serve as benchmark. For robustness check, we also conduct a change analysis for firm-years with ICFR status change. This analysis directly contrasts the impact of deterioration in ICFR with improvement. When we use ICW_NICW (improvement) as default, the coefficient on NICW_ICW (deterioration) is −0.1820 (t = −3.55) for ΔExValA, −0.1742 (t = −2.83) for ΔExValS, and −0.1832 (t = −2.85) for ΔExValM.

  17. 17.

    As with multi-segment firms, excess value for single-segment firms is the natural logarithm of the ratio of a firm’s actual value to its imputed value estimated as its assets (sales) multiplied by the median multiple of firm value to assets (sales) across all single-segment firms in the same industry. In essence, this measure reflects industry-adjusted firm value.


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We would like to thank an anonymous referee, Lakshmanan Shivakumar (the editor), Srini Krishnamurthy, Santanu Mitra, Tim Trombley and participants at the 2013 AAA, FMA and 2014 MFA conferences for valuable comments and suggestions. All errors remain our own.

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Correspondence to Yonghong Jia.



Table 9 Variable definitions

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D’Mello, R., Gao, X. & Jia, Y. Internal control and internal capital allocation: evidence from internal capital markets of multi-segment firms. Rev Account Stud 22, 251–287 (2017) doi:10.1007/s11142-016-9377-8

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  • Internal control over financial reporting
  • Internal capital allocation
  • Internal capital market
  • Diversification

JEL Classifications

  • M41
  • M48
  • G32