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Abstract
This paper investigates the relation between characteristics of top management teams (TMTs) and corporate investment efficiency. After controlling for corporate governance and several firms characteristics, we find that firms with better and more reputable TMTs (measured by larger team size, higher percentage of members with an MBA, higher percentage of members with prior executive experience, and higher number of members serving on boards of other companies) are negatively related to investment inefficiency caused by over- and underinvestment. Furthermore, we find that TMT characteristics complement the positive effect of financial reporting quality on investment efficiency. Our findings suggest that better TMT characteristics can mitigate investment distortions caused by over- and underinvestment.
Notes
* Accepted by Hong Hwang upon recommendation by Philip Joos.
1. Managerial officers are defined in accordance with 2003.3.27 Taiwan Finance Securities Ruling Ref. 0920001301 issued by TSFI.
2. Boards provide two important services to other companies: monitoring and board resources (Hillman and Dalziel Citation2003).
3. Researchers often use Tobin’s Q as a proxy for growth opportunities (Biddle and Hilary Citation2006; McNichols and Stubben Citation2008; Biddle, Hilary, and Verdi Citation2009; Lai, Liu, and Wang Citation2014). The results are similar when we use sales growth or asset growth as proxies for growth in the investment model (McNichols and Stubben Citation2008; Biddle, Hilary, and Verdi Citation2009).When we consider internal financing capability (e.g. firm-level cash flows) in the investment model, the results are again similar.
4. Other measures such as the level of timely loss recognition (conservatism) can reduce managers’ ability and incentives to overstate earnings and net assets by requiring higher verification standards for gain recognition. However, this measure does not reflect understated earnings. To consider both over- and understated earnings in financial statements, we use the level of discretionary accruals to test our hypotheses.
5. Petersen (Citation2009) proposes this technique as the preferred method for estimating standard errors in corporate finance applications using panel data. Because our sample covers five years of data, we estimate Equation (Equation3(3) ) by adjusting the standard errors for heteroskedasticity, serial correlation, and cross-sectional correlation using a two-dimensional cluster at the firm and year level.
6. When we replace the individual TMT characteristic variables with the TRF and TSF scores, the untabulated results show that the TRF and TSF scores have a statistically significant and negative impact on inefficient investment.
7. We also use TRF and TSF scores instead of individual TMT characteristic proxies in the multinomial logistic regression. The untabulated results show that the TRF score has a statistically and significantly negative impact on a firm’s over- and underinvestment. However, the coefficients on the TSF score are negative but insignificant in both under- and overinvestment models.