does enterprise risk management spur corporate...

Xu and Xie Does ERM Spur Corporate Innovation?

Does Enterprise Risk Management Spur

Corporate Innovation?

Jianren XuUniversity of North Texas

Xiaoying XieCalifornia State University, Fullerton

Presentation at Modern Risk Society

February 24, 2019


Agenda

1. Introduction

2. Conceptual Background

3. Data and Methodology

4. Results

5. Conclusions


1. Introduction


Enterprise Risk Management

➢ Enterprise Risk Management (ERM) is a process that manages all risks in an integrated, holistic fashion by controlling and coordinating any offsetting risks across the enterprise to maximize firm value.

➢ The risks include

❑Hazard risk

▪ Liability torts, Property damage, Natural catastrophe

❑Financial risk

▪ Pricing risk, Asset risk, Currency risk, Liquidity risk

❑Operational risk

▪ Customer satisfaction, Product failure, Integrity, Reputational risk

❑Strategic risk

▪ Competition, Social trend, Capital availability


Motivation

➢ Previous ERM research focuses on the financial sector, while

limited research that includes industrial firms only examines

the financial or accounting implications of ERM.

➢ Gordon et al. (2009), Hoyt and Liebenberg (2011), Baxter et al.

(2013), Eastman and Xu (2015), Farrell and Gallagher (2015),

Lundqvist (2015), Bailey, Collins, and Abbott (2017)

➢ One question remains unanswered:

➢How does ERM affect the real economy?

➢ Address this question by investigating whether ERM

encourages or impedes corporate innovation


Motivation

➢ ERM calls for risk consideration both in the strategy-setting

process and in performance driving in order to ensure the

achievement of a firm’s objectives (COSO 2017). ➢ The Committee of Sponsoring Organizations of the Treadway Commission (COSO) is a joint

initiative of the five organizations, including the American Accounting Association (AAA), the

American Institute of Certified Public Accountants (AICPA), Financial Executives International

(FEI), the Institute of Management Accountants (IMA), and the Institute of Internal Auditors (IIA).

➢ Innovative activities are risky due to their long-term, nonroutine, and subtle

nature, with unpredictable outcomes and high probability of failure

(Aghion and Tirole 1994; Hall et al. 2005).

➢ If ERM can truly exploit the upside of risks and drive firm performance

from a strategic perspective, it should encourage firms to seize

opportunities and take risks that may help firms maximize value.


Motivation

➢ Previous literature provides evidence that ERM reduces

various types of risk➢ Eckles, Hoyt, and Miller (2014)

➢ Wade, Hoyt, and Liebenberg (2015)

➢ Berry-Stölzle and Xu (2018)

➢ Lundqvist and Vilhelmsson (2016)

➢ Gao and Hsu (2017)

➢ Bailey, Collins, and Abbott (2017)

➢ Test whether ERM encourages firms to actively increase risk

as a strategic plan to gain in the long-run


Motivation

➢ Differentiate ERM from internal control over financial

reporting (ICFR)

➢ Risk assessment activities of clients is one of the five components in

the ICFR process (COSO 2013).

➢ Audit committee members, external auditors, and top executives (the

governance triad) are responsible for financial reporting risks and for

monitoring and controlling the underlying activities generating these

risks (Cohen et al. 2017).

➢ According to COSO guidelines, the strategic focus is the major

difference between ERM and ICFR.

➢ We provide first direct empirical evidence on this unique feature of

ERM that differentiates it from ICFR.


2. Conceptual Background


ERM and Innovation – Information Asymmetry

➢ Facilitate firm risk disclosure and enhance the transparency of a firm’s

risk profile and risk management process

➢ S&P (2013); Wade, Hoyt, and Liebenberg (2015); Gao and Hsu (2017)

➢ Innovation– a great deal of uncertainty and high likelihood of failure

➢ With reduced information asymmetries, firm stock price would move

more closely to its fundamental value (efficient stock price).

➢ More precisely reflecting the manager’s effort to enhance long-term risky

investment decisions

➢ Efficient stock prices can be used as a signal by outside investors to

determine whether informed traders agree or disagree with the corporate

resource allocation.

➢ Investors can use this information to make more appropriate evaluations of

management ability, despite their negative reputation brought by previous failed

innovation investment attempts.


ERM and Innovation – Corporate Governance

➢ Establish the risk oversight from the board level and coordinates

the incentives from different divisions and hierarchies, improving

corporate governance (COSO 2009, 2010)➢ ERM is associated with greater internal control effectiveness, more stable audit

relationships, boards with longer tenure (Baxter at el. 2013), greater board

independence (Beasley et al. 2005), and the presence of Big Four auditors (Kleffner

et al. 2003).

➢ corporate governance motives are an important driver for ERM adoption

(Lundqvist, 2015)

➢ Better corporate governance with an enhanced monitoring and disciplining structure

helps mitigate the agency problem and managerial short-termism (Stein 1988;

Graham, Harvey, and Rajgopal 2005; He and Tian 2013).

➢ Increased monitoring resulting from the strong corporate governance protects

managers from the reputation loss due to innovation failures (Aghion, Van Reenen,

and Zingales 2013).


ERM and Innovation

➢ Stakeholder Orientation ➢ Firms adopt ERM to invest in the long-term relationship with their stakeholders

(RIMS 2015; Xu and Berry-Stölzle 2018, COSO 2018).

➢ Promote firm innovation by fostering a work environment of long-term commitment

to employees and high tolerance for failure, which encourages engagement in

experimentation and trial and error (Tian and Wang 2014; Flammer and Kacperczyk

2016).

➢ Increase the employee’s job satisfaction, and hence commitment and retention,

which in turn helps workers adopt long-term horizons and create novel, potentially

valuable ideas (Amabile et al. 1996; Turban and Greening 1997).

➢ Improve Innovation Efficiency ➢ Enable managers to make more informed decisions on adopting or abandoning

innovation projects

➢ Expedite the turnover of innovative ideas through enhanced communication (COSO

2012)


Hypotheses

➢ Hypothesis 1: Firms with an ERM program are more likely to

incur greater R&D expenditures.

➢ Hypothesis 2: Firms with an ERM program tend to generate

greater innovation outputs than firms without ERM.


3. Data and Methodology


Data Sample

➢ 1055 firms that were at least once included in the S&P 500 index during

the 1990 to 2015 period

➢ Collect ERM status and merge with

➢ firm characteristics from Compustat industry annual and quarterly files

➢ daily stock returns from CRSP

➢ institutional ownership data from firms’ 13-F filings

➢ innovation data provided by Kogan et al. (2017)

➢ Exclude

➢ firms that are in regulated industries such as financial firms (SIC codes between

6000 and 6999) and utility firms (SIC codes between 4900 and 4949).

➢ firms with missing total assets

➢ firm-year observations for which the preceding year of data is not available

➢ Final sample consists of 4,477 firm-year observations over the 1996

through 2010 period.


Numbers of Sample S&P 500 ERM Adopters by Year

1 1 2 2

75 6

13

17 18

30

47

57

67

83

0

10

20

30

40

50

60

70

80

90

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010


Measure of ERM Adoption

➢Following previous literature, perform a detailed search for

evidence of ERM activity for each publicly traded insurer in ❑ Newswires and other media including Factiva, LexisNexis, Google search, etc.

❑ Insurers’ financial reports and data libraries including Thomson One, Mergent

Online, and Edgar databases

➢ Search strings included the following phrases, their acronyms,

and the individual company names❑ “enterprise risk management,” “chief risk officer,” risk committee,” “strategic risk

management,” “consolidated risk management,” “holistic risk management,” and

“integrated risk management”

➢ Each search “hit” manually reviewed within its context

➢ Repeat search process to verify whether ERM firms terminated

their ERM program or not in any of the years


ERM Indicator

ERM = 0

ERM non-users

ERM = 0 ERM = 1

ERM users

ERM adoption

➢ ERM is an indicator variable that takes the value of 1 for firm-years starting

from the first year of firms’ ERM adoption, and 0 otherwise.


Measures of Innovation

➢ One innovation input➢ natural logarithm of one plus R&D expenditures

➢ Three innovation outputs➢ Google Patents assembled by Kogan et al. (2017)

➢ Inno1 – ln (1+patent count), where patent count is the total number of

patents applied by a firm in a given year that are eventually granted

➢ Inno2 – ln (1+ citation-weighted patent count/book assets of firm), where

citation-weighted patents is the total number of forward citations received

by these patents adjusted by the average number of citations received by

patents that were granted in the same year

➢ Inno3 – ln (1+patent value/book assets of firm), where the value of each

patent is estimated by referring to the stock price reaction during the

three-day window (t, t+2) around the grant announcement date (t) of that

patent


Variable Definitions (I)Variable Name Definition Source

ERM = 1 for a firm-year in which ERM is adopted, 0 otherwiseFactiva, SEC filings, Google search and

other media

R&D Ln (1 + R&D expenditures) Compustat: XRD

Inno1 Ln (1 + Patent count) Google Patents

Inno2 Ln (1 + Citation-weighted patent count / book assets of firm) Google Patents, CRSP

Inno3 Ln (1 + Market-based patent value / book assets of firm) Google Patents, CRSP

Inno_eff1 Ln (1 + (Patents count / R&D in year t-1)) Google Patents, Compustat: XRD

Inno_eff2 Ln (1 + (Citation-weighted patent count/ R&D in year t-1)) Google Patents, Compustat: XRD, CRSP

Inno_eff3 Ln (1 + (Market-based patent value /R&D in year t-1)) Google Patents, Compustat: XRD, CRSP

Size Ln (Sales) Compustat: SALE

Leverage Book value of liabilities / market value of equity Compustat: (AT- CEQ)/ (PRCC × CSHO)

Capex Capital expenditures / book value of assets Compustat: CAPX/AT

SalesGrowth

Average percentage change in sales over the prior three years. When

three years of data are unavailable, we use two years, and when two

years are unavailable, we just use the one-year growth rate.

Compustat: SALE

FirmAge Difference between current year and founding year Compustat

CashRatio Cash and short-term investments / book value of assets Compustat: CHE / AT

PPE Gross property, plant and equipment / book value of assets Compustat: PPEG / AT

Ln(SDRET) Ln (standard deviation of the firm's daily returns over the year) CRSP

PensionExp Pension and retirement expenses / sales Compustat: XPR/SALE

ValueChange (Firm value in year t – firm value in year t−1) / firm value in year t−1Compustat: PRCCt× CSHOt – PRCCt−1

× CSHOt−1


Variable Definitions (II)Opacity Intangible assets / book value of assets Compustat: INTAN / AT

Ln(SDCF)

Natural log of the standard deviation of the error term from a

regression of the firm’s quarterly operating cash flow (Compustat:

OANCFY) on the prior quarter’s operating cash flow, scaled by total

assets. This regression is run for eight quarters.

Compustat Quarterly: OANCFY

Ln(MB)Ln ((Market value of equity + book value of debt)/ book value of

assets)

Compustat: ((PRCC × CSHO) +

(AT - CEQ)) / AT

TaxSave

TaxSave represents the convexity of the firm’s tax structure. It is

calculated using Equation (1) of Graham and Smith (1999). TaxSave is

calculated as the fitted values of the following model. TaxSave = 4.88

+ 7.15 * TI (NEG) + 1.60 * TI (POS) + 0.019 * VOL− 5.50 * RHO −

1.28 * ITC + NOL * (3.29 − 4.77 * TI (NEG) − 1.93 * TI(POS)),

where TI (NEG) is a dummy variable for pretax income between

−$500,000 and 0 and TI (POS) is a dummy variable for pretax income

between 0 and $500,000. NOL is a dummy variable that takes the value

of 1 if the firm reports an unused net operating loss carryforward

(Compustat: TLCF). VOL is the absolute coefficient of variation of

taxable income computed as the absolute value of the ratio of the mean

of taxable income (Compustat: PI) to the standard deviation of taxable

income. RHO is the first-order serial correlation of taxable income.

VOL and RHO are computed using up to the past 10 years of data for

the firm. ITC is a dummy for the presence of investment tax credits

(Compustat: ITCB).

Compustat: PI, TLCF, ITCB

Numsegs Number of operating segments Compustat Historical Segments

PINSTPercentage of the firm’s stock held by institutional investors Thomson Reuters Institutional (13-

F) Holdings


4. Results


Univariate Differences across ERM Status (1) ERM = 1 (2) ERM = 0 Difference (1) - (2)

Variable Obs. Mean Median Obs. Mean Median Mean Median

R&D 527 3.161 3.477 3950 2.508 2.758 0.653*** 0.719***

Inno1 527 2.472 2.303 3950 1.838 1.099 0.634*** 1.204***

Inno2 527 2.863 2.615 3950 2.204 1.599 0.659*** 1.016***

Inno3 527 4.330 5.413 3950 3.290 3.284 1.040*** 2.129***

Inno_eff1 527 0.224 0.064 3950 0.203 0.003 0.021 0.061**

Inno_eff2 527 4.718 6.175 3950 3.737 2.206 0.982*** 3.969***

Inno_eff3 527 5.928 7.854 3950 4.655 3.084 1.273*** 4.770**

Size 527 8.370 8.301 3950 7.708 7.676 0.662*** 0.625***

Leverage 527 2.702 0.549 3950 0.896 0.464 1.806*** 0.085***

Capex 527 0.044 0.034 3950 0.059 0.045 -0.015*** -0.011***

SalesGrowth 527 0.072 0.063 3950 0.118 0.084 -0.046*** -0.021***

FirmAge 527 49.245 55.000 3950 46.606 50.000 2.639*** 5.000***

CashRatio 527 0.126 0.091 3950 0.121 0.062 0.006 0.030***

PPE 527 0.540 0.455 3950 0.589 0.518 -0.049*** -0.063*

Ln(SDRET) 527 -3.808 -3.824 3950 -3.805 -3.842 -0.004 0.018

PensionExp 527 0.010 0.008 3950 0.007 0.005 0.003*** 0.003***

ValueChange 527 0.191 0.079 3950 0.190 0.096 0.000 -0.018

Opacity 527 0.197 0.151 3950 0.157 0.108 0.040*** 0.043***

Ln(SDCF) 527 -3.194 -3.176 3950 -3.166 -3.147 -0.028 -0.029

Ln(MB) 527 0.567 0.491 3950 0.653 0.578 -0.086*** -0.087***

TaxSave 527 4.531 4.343 3950 4.377 4.067 0.154 0.276

Numsegs 527 2.338 2.000 3950 2.065 2.000 0.273*** 0.000***

PINST 527 0.768 0.802 3950 0.719 0.748 0.049*** 0.054***


Differences in

the Innovation

between ERM

Adopters and

Non-adopters


OLS

Regressions of

Innovation on

the ERM

Indicator and

Year FE and

Industry FE


Treatment Effects Model

➢ Two-step treatment effects model with a

consistent estimator to control for self-selection

and endogeneity

➢ Dependent variable: Innovation


Baseline Treatment Effects Model


Treatment Effects Model with Forward Innovation Variables


Logistic Regression of the ERM Indicator on Lagged Innovation Levels


Dynamic Binary Choice Model on

Survival Dataset

ERM = 0

ERM non-users

ERM = 0 observations dropped

ERM users

ERM = 1

observations kept

➢ The estimation of a logit or probit model assumes that all the observations of a firm are independent.

➢ Dynamic binary choice models based on survival datasets have a focus on the determinants of one-time events.

➢ Ensure the results are not confounded by firm-specific changes in the business environment of ERM adopters over time.


Treatment Effects Model with Survival Dataset


Treatment Effects Model on Innovation Efficiency


Treatment Effects Model on Innovation Efficiency with

Survival Dataset


Effect of ERM on Innovation - Propensity Score Matching


Treatment Effects of ERM on Innovation Based on Firm

or Industry Characteristics I


Treatment Effects of ERM on Innovation Based on Firm

or Industry Characteristics II


5. Conclusions


Conclusions

➢ ERM affects the real economy by enhancing innovation.

➢ ERM encourages firms to strategically increase risk to take opportunities

for possible gains in the long-run.

➢ We find that companies with ERM tend to make greater R&D

expenditures, and are able to generate greater innovation outputs as

measured by patent count, citation-weighted patent count, and market-

based patent value than those without ERM.

➢ Firms that have practiced ERM also embrace greater innovation efficiency.

➢ The positive impact of ERM on innovation lasts when forward-looking for

several years.

➢ Suggest that managerial short-termism alleviation and information

asymmetry reduction are the possible mechanisms through which ERM

enhances innovation.

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