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Abstract
This paper investigates the impact of CEO overconfidence on the probability of corporate bankruptcy. Using a large dataset of UK firms, we find that firms with overconfident CEOs face a greater risk of failure. The presence of overconfident CEOs leads to a higher risk of bankruptcy in innovative environments, while the impact is insignificant in non-innovative environments. Moreover, overconfident CEOs can increase the bankruptcy risk of firms with less conservative accounting. We find that banks, as major creditors, seem to play an important role in constraining CEO overconfidence, and hence in reducing the likelihood of bankruptcy. Finally, the impact of overconfidence on the probability of bankruptcy is stronger in firms with generalist CEOs than specialist CEOs.
Acknowledgements
We thank Chris Florackis, Phil Holmes, Robert Hudson, Andrew Stark, Abhijit Sharma, Bin Xu, audiences at 1st Financial Management and Accounting Research Conference (Limassol, Cyprus), 3rd International Corporate Governance Society Conference (Rome, Italy), and Corporate Governance and Corporate Finance Workshop held at the University of Sheffield for comments and suggestions. Any errors are entirely our own.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 In this paper, we use interchangeably the terms bankruptcy, insolvency, and failure to mean the same thing.
2 The principle of lender liability holds that banks may face a penalty if it is judged to have taken actions that improve their position at the expense of other owners (for e.g. shareholders). This principle discourages US creditors from active monitoring when a firm faces financial distress.
3 FAME, Financial Analysis Made Easy, is a database of public and private companies, administered by Bureau Van Dijk.
4 We use Thomson Reuters Datastream item: BDATE to mark the start of the duration.
5 Following Charitou, Neophytou, and Charalambous (Citation2004) and Ozkan, Poletti-Hughes, and Trzeciakiewicz (Citation2017), we define corporate failure by observing any one of the following events in the data: administration, liquidation, receivership and dissolution. Administration is a formal rescue procedure, involving to appoint an insolvency practitioner as administrator to salvage the company in financial distress. During the period of administration, the debt repayments are suspended and creditors’ rights freeze. Liquidation is a procedure whereby a liquidator is appointed to sell the assets of the firms and distribute the proceeds to debtholders. The liquidation procedure can be initiated either by the company through a ‘voluntary liquidation’ or by the creditors through a ‘compulsory liquidation’. Receivership takes place only when one or more of a firm’s creditors (lenders) have a particular right to the firm’s assets. The creditor has a right to appoint an administrative receiver, who then ‘receives’ any of the assets of the company that it can liquidate in order to pay back the lender. Dissolution involves voluntarily striking the company off the register at Companies House and thereby terminating its existence. For details on the legal qualities of the insolvency procedures and dissolution see Insolvency Act of 1986 and Companies Act 2006.
6 Our overconfidence measures are based on insider dealings which regulated by the Companies Act 2006, and Model Code on directors’ dealings, set out in Chapter 9 of the Listing Rules (LR9 Annex 1). For a discussion on the UK regulatory framework of the insider trading activity see Ozkan, Poletti-Hughes, and Trzeciakiewicz (Citation2017).
7 The construction of buy-and-hold abnormal returns is described in detail in Ozkan and Trzeciakiewicz (Citation2014).
8 Following Campbell et al. (Citation2011) and Kim, Wang, and Zhang (Citation2016) we additionally construct the overconfidence measure requiring that the CEO does not exercise (at least twice) his options that are more than 100 percent in the money. We further test the stricter measure in the hazard model (as in Table ) and find that the association between CEO overconfidence and the probability of corporate failure remains positive and significant.
9 For a number of option packages BoardEX does not provide the stock price, but the elements from which the stock price can be derived. Specifically the items that can be used are Exintval, which is the intrinsic value of exercisable options, that is defined as a gap between stock price and the exercise price multiplied by the volume of exercisable shares, and is reported in ‘000s, and Exvol, which is the volume of exercisable shares. Hence we calculate the missing stock prices as exintval*1000/exvol + exercise price.
10 We have also tested an alternative methodology and matched the names of individual directors with the Thomson Reuters EIKON database that contains the information on insider dealings. Out of all types of transactions we considered only the ones that are labelled as ‘exercise of options’. We have not been able to identify a sufficient number of trades to perform the classification.
11 Malmendier and Tate (Citation2005) suggest that to guarantee that every CEO in the sample had an opportunity to be classified as Holder67, one should restrict the sample to CEOs who a least twice held options, which were valued above the threshold during the year of vesting, and hence limit the degree of unobserved bias in the control group. Due to a limited number of observations we also include in our control group those CEOs who who a least once held options, which were valued above the threshold during the year of vesting.
12 We are grateful to the anonymous referee for suggesting this extension to the analysis.
13 In this process, we limit our search to English language and drop identical duplicates.
14 In untabulated results, for robustness purposes, we also include the firm/year observations where Factiva reports zero articles on the CEO and generally obtain similar results.
15 We observe that there are firms which stop producing financial statements well ahead of recording failure. In our sample 71% of failed firms produce financial statement until the year of filing, 27% produce the statements between three to one year prior to the year of filing and 2% stop earlier than 3 years. The main results of our study are not sensitive to the exclusion of the firms with the gap longer than 1 year.
16 In untabulated results we further the analysis by including the year dummies to our hazard models. The inclusion of the main results does not affect our main results.
17 The innovative industries include all those which have 100% innovative years, i.e. petroleum and natural gas (sic 13); household and office furniture (sic 25); commercial machinery and computer hardware (sic 35); electric equipment and electronic equipment (sic 36); measuring & control equipment, medical equipment (sic 38); consumer goods (sic 39); communications (sic 48); business services (sic 73, 87). The non-innovative industries include all those which have less than 30 % of innovative years, i.e. agricultural services (sic 7); coal mining & coal mining services (sic 12), heavy construction – not building contractors (sic 16); food and drink products (sic 20); tobacco products (sic 21);transit and passenger transportation (sic 41); retail (sic 52, 54, 55, 58); metal mining and metal mining services (sic 10), apparel and other finished products (sic 23); wholesale (sic 50); construction (sic 17); primary metal (sic 33); water transportation (sic 44); transportation services (sic 47); services (sic 82); build construction (sic 15); textiles (sic 22). The full classification is provided in Table IA.II of online appendix to Hirshleifer, Low, and Teoh (Citation2012).
18 We calculate z-score using the following formula and Datastream items, z-score=1.2*(WorkingCapital/Total Assets)+1.4*(Retained Earnings/Total Assets)+3.3*(EBIT/Total Assets)+0.6*(Market Capitalization/ Total Liabilities)+0.999*(Net Sales or Revenue/Total Assets).
19 In unatbulated results we also consider the financial crisis as a period during which banks behaved more vigilantly and raised monitoring of the corporations. We define the period of the financial crisis from 2008 to 2013, as the time when economic conditions are adverse (Salachas, Laopodis, and Kouretas Citation2017). We find that the association between CEO overconfidence and the probability of corporate failure is more pronounced in the period outside financial crisis, when the monitoring of corporations by banks was weaker.
20 This could be the effect of a rapidly changing business environment, which creates a risk for the specialist's skills to get quickly outdated and therefore a risk for specialist CEOs to be less demanded on the job market. Changes in the business environment are driven by, among others, advancements in technology (Garicano and Rossi-Hansberg Citation2006), product market changes due to industry deregulation (Cunat and Guadalupe Citation2009a), or foreign competition (Cunat and Guadalupe Citation2009b).
21 We source our data on conglomerates from Datastream. Following Custódio, Ferreira, and Matos (Citation2013) we a firm as a conglomerate if operates across at least two different segments and use dummy variable to flag if a firms is a conglomerate. To verify operations across two sectors we consider if a firm reports total sales (Datastream items: WC19501, WC19511, WC19521, WC19531, WC19541, WC19551, WC19561, WC19571, WC19581, WC19591) as well as total assets (Datastream items: WC19503, WC19513, WC19523, WC19533, WC19543, WC19553, WC19563, WC19573, WC19583, WC19593) for least two different product segments.