Local Gambling Preferences and

Corporate Innovative Success

Yangyang Chen, Monash UniversityEdward J. Podolski , La Trobe University

S. Ghon Rhee, University of Hawai’iMadhu Veeraraghavan , TA PAI Management Institute

This paper is about….

St. Peter’s Basilica

Steve Jobs Apple Inc.

Factors Affecting Innovations (I) Underlying

Factor Impact on Innovation

Authors

CEO Overconfidence Positive

Hirshleifer, Low, and Teoh (2012)

Galasso and Simcoe (2013)

Institutional Ownership

Positive Aghion, Van Reenan, and Zingales (2013)

Product Market Competition

Positive (Competitive Firms)

Negative (Laggard Firms

Aghion, Bloom, Blundell, Griffith, and

Howitt (2005)

No. of Financial Analysts

Negative He and Tian (2013)

Non-Executive

Employee Stock Options

Positive

Chang, Fu, Low, and

Zhang (2013)

Accounting Conservatism

Negative Chang, Hilary, Kang,

and Zhang (2013)

Stock Liquidity

Negative Fang, Tian, and Tice

(2013)

Banking Deregulation

Negative (Intrastate Deregulation)

Positive (Interstate Deregulation)

Chava, Oettl,

Subramanian, and Subramanian (2013)

Factors Affecting Innovations (II) Underlying

Factor Impact on Innovation

Authors

Individualism Positive Gorodnichenko and

Roland (2011)

Religion (CP Ratio) Positive Adhikari and

Agrawal (2013)

Corporate Income Taxes

Tax Decrease: Positive

Tax Increase: Negative

Atanassove and Liu (2014)

Economic Policy Uncertainty

High Uncertainty: Negative

Bhattacharya, Hsu, Tian, and Xu (2014); Mukherjee, Singh,

and Zaldokas (2013)

Corporate Governance

Positive Becker-Blease

(2011)

CEO Connections Positive Faleye, Kovacs, and

Venkateswaran (2012)

Board Friendliness

Positive

Kang, Liu, Low, and

Zhang (2012)

Hostile Take-Overs Negative

Antanassove (2013); Sapra, Subramanian,

and Subramanian (2013)

Corporate Diversification

Not Necessarily Negative

Cardinal and Opler (1995)

Corporate Ownership

Concentrated Ownership: Positive Diffuse Ownership:

Negative

Francis and Smith (1995)

Characteristics of Corporate Innovations

–Large Payoff–High Probability of Failure

Geographical Variation of Corporate R&D

Top and Bottom Five States

for R&D ExpenditureTop Five

New Mexico

Massachusetts

Maryland

Washington

Connecticut

Bottom Five

Wyoming

Louisiana

Nevada

Arkansas

Oklahoma

R&D Spending and State Lotteries

NM MA MD WA CT WY OK NV LA AK0

200

400

600

Lot

tery

Sal

es p

er C

apita

Most R&D Intensive States Least R&D Intensive States

Characteristics of Gambling Attitude

– Overstating Small Probability of Success

– Understating High Probability of Failure

In Contrast,

Characteristics of Corporate Innovation

– Large Payoff– High Probability of Failure

Our Intuition is….

Corporations • Not detached from local

environment• Take risk on innovation if

local residents are prone to gambling

Are Catholics more risk-taking than Protestants?

“The Higher the Catholics-to-Protestants (CP) Ratio, the Higher Gambling Attitude”1. Kumar, Page, and Spalt (2011, JFE)

• Stocks with lottery features• IPO underpricing

2. Shu, Sulaeman, and Yeung (2012, MS)

• MFs: Higher return volatilities & Higher Turnover

CP Ratio Across the United States

Source: Kumar, Page, and Spalt (JFE, 2011)

Religion and R&D

0

0.05

0.1

0.15

0.2

0.25

0.3

Catholic ratio Protestant ratio CP ratio

Religion and Patents

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Catholic ratio Protestant ratio CP ratio

Religion and Citations

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Catholic ratio Protestant ratio CP ratio

Major Findings 1. Firms in high CP ratio region spend

more on innovation and attain higher innovative output

2. Social gambling and/or Religion: More important drivers of innovative activities than CEO overconfidence

3. Impact of CEO overconfidence on Innovative industries …..Conditioned on Gambling Preferences or Religion

Data and Study Period DATA Sources• NBER Patent Database: 2006 Patent and Citation Data• American Religious Data Archives:

Religious adherence at county level• Compustat: Firm-Level Accounting information• CRSP: Stocks returns• S&P Execucomp Database: CEOs and compensation • I/B/E/S (Institutional Brokers’ Estimate System):

Analysts coverage• Forbes: State economic and regulatory variables• US Census Bureau: County Demographic DataStudy Period: January 1980-December 2006Final Sample: 34,097 firm-year observations

US Corporate Innovation Summary Statistics

Whole Sample

Innovative Industry

Non-Innovative Industry

R&D/Assets 0.05 0.07 0.05

Patent Count

7.81 8.13 7.60

Citation per Patent

1.75 2.50 1.34

Tobin’s Q 1.81 1.83 1.78

Ln (R&D Capital)

0.64 0.67 0.59

Ln (Sales) 5.62 5.62 5.60

Ln (PPE/EMP)

3.62 3.62 3.63

Lerner Index

0.09 0.04 0.12

Ln(Analysts) 1.63 1.64 1.62

County-Level Variables

Whole Sample Std Dev

CP Ratio 2.02 1.78

Religiosity 0.53 0.12

Ln (Popula-tion)

13.54 1.18

Ln (Age) 3.54 0.07

Social Gambling Preferences and Corporate Risk-Taking (I)

Firms located in areas where gambling is more socially accepted undertake more risky projects

Corporate Risk = f(CP Ratio and Controls)Where,

Corporate Risk measured by • Return Volatility = Std Dev of Daily Returns over the

fiscal year• Profit Volatility = Std Dev of firm profitability over

subsequent 20 quarters

Social Gambling Preferences and Corporate Risk Taking (II)

Dependent

Variable Return Volatility

Dependent Variable

Profit Volatility

Ln(CP Ratio) 0.05

(9.63**) 0.01

(3.87**) 0.02

(9.66**) 0.008

(3.60**)

Firm Level Controls

No Yes No Yes

Year Fixed Effects

Yes Yes Yes Yes

Firm Fixed Effects

Yes Yes Yes Yes

No. of Observations

90,762 25,604 138,740 29,158

Adjusted R2 0.09 0.25 0.07 0.30

Gambling Preferences and Corporate Innovation Input

Dependent Variable:

R&D/Assets (1) (2) (3)

Ln(CP Ratio) 0.02

(6.28***) 0.02

(3.95***) 0.01

(4.44***) Controls (Firm

Characteristics) Yes Yes Yes

Controls (Firm Characteristics)

Lerner Index No -0.001

(-2.17**) -0.0003 (-2.04**)

Total IO No 0.002 (1.26)

0.002 (1.32)

Ln(Analysts) No 0.01

(4.91***) 0.008

(4.45***) Controls (County

Demographic Characteristics) No No Yes

Year Fixed Effects Yes Yes Yes Firm Fixed Effects Yes Yes Yes

No. of Observations 103,598 31,757 31,757 Adjusted R2 0.15 0.23 0.25

Gambling Preferences and Corporate Innovation Output

Dependent Variable: Ln(1+Patent Count)

Dependent Variable: Ln(1+Citations-per-

Patent)

Ln(CP Ratio) 0.05

(2.54**) 0.07

(2.79**) 0.04

(3.14***) 0.07

(4.54***)

R&D/Assets 0.29

(29.01***) 0.28

(28.50***) 0.13

(31.60***) 0.13

(30.15***)

Firm Characteristics

Yes Yes Yes Yes

County Characteristics

No Yes No Yes

Year Fixed Effects

Yes Yes Yes Yes

Firm Fixed Effects

Yes Yes Yes Yes

No. of Observations

31,757 31,757 31,757 31,757

Adjusted R2 0.41 0.42 0.25 0.27

Robustness Tests (I) R&D

Expenditure/ Assets

Ln(1+patent count)

Ln (1+citations-per-patent)

Coeff. t-stat Coeff. t-stat Coeff. t-stat

Base Line Model 0.01 4.44 0.07 2.79 0.07 4.54

(1) CP ratio 0.003 3.72 0.02 2.45 0.02 3.66

(2) Control for firm age

0.009 3.57 0.07 2.75 0.09 5.01

(3) Survey year only

0.008 3.12 0.14 2.34 0.05 2.01

(4) Excluding 2005 and 2006

0.01 3.56 0.06 2.57 0.08 4.35

(5) Excluding firm-years with zero patent count

0.01 2.14 0.12 2.87 0.09 2.53

(6) Fama-Macbeth regression

0.009 1.74 0.16 3.25 0.11 2.45

(7) Include industry cluster control

0.009 3.53 0.07 2.64 0.12 4.23

(8) Double-cluster control for firm and county

0.01 3.97 0.09 2.18 0.11 4.12

Robustness Tests (II) R&D

Expenditure/ Assets

Ln(1+patent count)

Ln (1+citations-per-patent)

Coeff. t-stat Coeff. t-stat Coeff. t-stat

Base Line Model 0.01 4.44 0.07 2.79 0.07 4.54

(9) Control for State level business environment

0.006 2.11 0.06 2.55 0.05 2.57

(10) Control for corporate governance

0.009 3.50 0.15 3.30 0.07 2.59

(11) Control for CEO incentives

0.006 5.09 0.03 2.14 0.03 2.94

(12) Including county fixed effects

0.005 2.04 0.03 1.85 0.06 1.69

(13) 2SLS with lagged CP ratio

0.009 3.74 0.11 2.19 0.13 6.59

(14) Including firm fixed effects

0.004 2.54 0.08 1.88 0.10 2.23

(15) Exclude 5 most and least CP ratio counties

0.009 3.58 0.10 3.14 0.13 6.32

(16) Exclude 10 largest counties

0.007 2.43 0.06 2.69 0.05 3.28

(17) Exclude Silicon Valley firms

0.005 2.29 0.09 4.64 0.10 5.42

Religion and CEO Overconfidence

Innovation Input

(R&D/Assets)

Innovation Output

[Ln(1+Patent Count)]

Innovation Output

[Ln(1+Citation per Patent)]

LN(CP Ratio) 0.009 (3.49***) 0.17 (3.04***) 0.06 (2.17**)

Holder67 -0.004 (-1.19) -0.07 (-0.95) -0.04 (-1.01)

LN(CP Ratio)*Holder67

0.009 (2.40**) 0.14 (1.82*) 0.09 (2.38**)

All Controls Yes

Yes

Yes

CEO Characteristics (Delta; Vega;

Tenure)

Yes Yes Yes

Year Fixed Effects

Yes

Yes

Yes

Industry Fixed Effects

Yes

Yes

Yes

Observations 11,382 11,382 11,382

Adjusted R2 0.33 0.18 0.22

Effect of Religion, Industry and Overconfidence

Innovation

Input (R&D/Assets)

Innovation Output

[Ln(1+Patent Count)]

Innovation Output

[Ln(1+Citation per Patent)]

Innovative Industries

Non-Innovative Industries

Innovative Industries

Non-Innovative Industries

Innovative Industries

Non-Innovative Industries

Ln(CP Ratio) 0.009

(2.65***) 0.01

(2.60***) 0.02

(1.52) 0.08

(2.71***) 0.11

(2.45***) 0.23

(3.57***)

Holder67 -0.002 (-0.53)

0.004 (0.83)

-0.05 (-0.48)

0.04 (0.35)

-0.05 (-0.85)

0.03 (0.47)

Ln(CP Ratio)*Holder67

0.007 (1.75*)

-0.005 (-0.87)

0.08 (0.80)

0.06 (0.53)

0.09 (1.89*)

0.02 (0.30)

CEO Characteristics

(Delta; Vega; Tenure)

Yes Yes Yes Yes Yes Yes

All Controls Yes Yes Yes Yes Yes Yes

Observations 7,159 4,186 7,159 4,186 7,159 4,186

Adjusted R2 0.42 0.42 0.22 0.27 0.29 0.28

Thank You for Your Attention