Kate Litvak
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Transcript of Kate Litvak
Using a Randomized Experiment to Measure the Impact of Firm Governance
on Capital Raising and Investment
Kate Litvak
Map of This Talk
• Original Goal Here: Do Precisely Nothing– Not really
• Identification Idea• Theory• Unexpected Difficulties and Solutions• Results
Hierarchy of Identification
• Cross-Sectional Regs• Firm Fixed Effects• Exogenous Shock
– Legal Change– Natural Disaster
• Randomized Trial– Gold Standard
Randomized Trial Here• Conducted by the SEC in 2005-2007• Suspends Existing Restrictions on Short Selling• Up to July 2007:
– Rule 10a-1 from 1938– Ok to Sell Short if Price Is
• Above immediately preceding sale, or• At last sale price if it was higher than last diff price
– Goal: Prevent Downward Price Spirals• Restrictions Supported by Firm Managers
– Claim: Short Sellers Opportunistic, Drive Down Prices
Trial Details• True Randomized Experiment
– Not Just Natural Experiment • Based on Size etc.
• Take All Russell 3000 Firms (High Liquidity)– Rank by Trading Volume– Pick Every Third – “Pilot” Firms– Selection Period: June 2003-June 2004
• Suspends Uptick Rule for Pilot Firms• The Rest – Control Group• Trial Period
– May 2, 2005 to July 3, 2007
Prior/Concurrent Studies on Uptick Rule• SEC Office of Economic Analysis (2007)
– Effect of rule on volume of short sales, option trading, prices, liquidity, volatility
• Diether, Lee, Werner (2006)– Effect of rule on spread, volatility, short sale volume
• Alexander and Peterson (2006)– Volume, Volatility Around Announcement and Initiation Date of
Pilot Program• Bai (2007)
– Effect on Price, Volatility, Volume During Mkt Stress• Grullon et al. (2012)
– Increase in Short Selling Causes Prices to Fall– Small Firms Reduce Equity Issues
Prior Studies on Uptick Rule• No impact on
– Daily Return Volatility– Liquidity– Magnitude and Speed of Price Decline – When Stocks Subject to Downward Pressure
• Caused by Earnings Shocks– Options Trading
• Weak Evidence: Overpricing Caused by Selling Restrictions• So, SEC Concluded – Rule Useless
– Repealed it in June 2007• Now, Adopted Different, Narrower Rule
– No Trial There
Broad Research Question
• Interaction of Internal and External Governance
• Examples of Internal Governance– Boards, Procedures, S/h Voting Rules, Fiduciary
Duties Standards• Examples of External Governance
– Share Price– Mkt for Corporate Control– Product Mkt Competition
Research Design• Measures of Internal Governance + External
Governance Outcome• We Want:
– Exogenous Shock to Some Form of Governance • Then, See if Outcome Affected
– Maybe Conditional of Internal Gov’ce• Other Papers:
– Shocks to Internal Governance• Sarbanes-Oxley, Korean Corp Gov’ce Reform, DE Legal Rules
• This Paper: – Shock to External Governance
Identification
• Exogenous Shock to External Gov’ce – Through Randomized Trial
Hypothesis #1• Short Selling Permitted
– Negative Opinions Incorporated into Stock Prices – Prices More Accurate – Investors More Willing to Invest – Cost of Capital Down – Capital Raising Up
• Prediction:– Short Selling Permitted Capital Raising Up
• Theory:– Lintner (1969), Miller (1977), Scheinkman and Xiong
(2003), Gallmeyer and Hollifield (2006)
Hypothesis #2• Short Selling Permitted
– Manipulators Run Down Prices – Panics Up – Stock Prices Artificially Deflated – Capital Raising Down
• Note: – Gov’ce Value of Short Selling Lower than Damage
from Panics and Deflated Stock Prices• Prediction:
– Short Selling Permitted Capital Raising Down
Bottom Line on Hypotheses• Testing Governance Value of Short Selling
Research Design (1)• Classic Diffs in Diffs for Randomized Trials
– Developed for Drug Trials• Treated Firms
– Exempt from restriction on short-selling• Control Firms
– Short-Selling Restricted Under Old Rule• Compare:
– Outcomes of Treated Firms v. Outcomes of Control Firms
– During and Outside Test Period
Research Design (2)• If Randomized Trial Perfectly Executed No
Need for Regressions– Except if Want to Know Cross-Sectional Effects
• But Not Perfectly Executed Here– So, Need Some Extra Work
• Follow-Up– I Will Re-Do Prior Studies on Price, Volatility,
Volume etc
Summary of My Findings (1)
• Short Selling Causes:– Increase in Equity Raising– No Change in Debt Raising– Increase in Capital Investment– Increase in R&D Investment– Increase in Dividend Payments
Summary of My Findings (2)
• What Kinds of Firms Most Responsive to Short Selling Effects?– Worse Internal Governance– Higher Prior Cash Flows
Summary of My Findings (3)
• What Does Not Predict Response?– Prior Financial Constraint
• Relevant for Cash Flow – Investment Sensitivity Literature– Evidence Consistent with KZ, not FHP
• Capital Raising Made Cheaper for Random Firms– Treated Firms generally responded by raising more $
• And invested more– But more fin constrained firms not different from rest– Firs with higher pre-treatment cash flow investment
sensitivity not different from rest
Data: Intended Randomization Firm Characteristic Treated Group,
MeanIntended Control T-stat Treated v.
Intended ControlNumber of Firms 580 1168Asset Size 2958.95 3245.28 0.67Cash and Cash Equivalents 19.99 25.15 0.57
Capital Expenditures 152.80 141.14 0.59
Common Shares Issued 110.78 126.56 1.15
Long-Term Debt 694.13 769.53 0.74Total Liabilities 1772.77 2025.30 0.89Total Dividends Paid 41.18 40.27 0.12EBITDA 396.77 388.97 0.16Number of Employees 10.26 11.31 0.80
PPE Total 1829.85 1835.20 0.09Sales Growth 267.31 295.38 0.56R&D Expenditures 54.87 84.15 1.92Trading Volume, in $ 6.10e+09 6.17e+09 0.10
But There is Category B…
• Created by SEC, Listed on their Page– Not self-selection– Principles of selection not reported
• Prior Papers Assumed: Inconsequential• Rule for Them:
– Exempted From Uptick Rule from 4pm to 8pm– So, Partially Treated!
• Check: – Random?
Data: Actual Assignment (Compliers)Firm Characteristic Treated Group,
MeanTrue Control Group T-stat Treated v.
True ControlNumber of Firms 580 781Asset Size 2958.95 719.68 7.36Cash and Cash Equivalents 19.99 5.47 2.19
Capital Expenditures 152.80 37.30 7.19
Common Shares Issued 110.78 43.42 7.29
Long-Term Debt 694.13 204.83 6.25Total Liabilities 1772.77 445.25 6.82Total Dividends Paid 41.18 5.37 6.36EBITDA 396.77 79.80 8.38Number of Employees 10.26 3.90 6.47
PPE Total 1829.85 460.66 7.32Sales Growth 267.31 261.55 0.11R&D Expenditures 54.87 25.21 3.52Trading Volume, in $ 6.10e+09 1.67e+09 8.78
Data: Actual Assignment (Non-Compliers)Firm Characteristic Treated Group,
MeanNon-Compliers (Partially Treated)
T-stat Treated v. Partially Control
Number of Firms 580 387Asset Size 2958.95 8303.04 15.84Cash and Cash Equivalents 19.99 64.62 5.30
Capital Expenditures 152.80 349.37 14.99
Common Shares Issued 110.78 293.06 15.94
Long-Term Debt 694.13 1897.49 14.47Total Liabilities 1772.77 5185.41 14.39Total Dividends Paid 41.18 110.18 12.04EBITDA 396.77 1009.73 17.64Number of Employees 10.26 26.07 14.90
PPE Total 1829.85 4646.14 14.82Sales Growth 267.31 362.32 1.56R&D Expenditures 54.87 214.59 9.74Trading Volume, in $ 6.10e+09 1.51e+10 18.49
Kernel Density of Firm Asset Size for Treated v. Combination of Control and Partially-Treated Firms
(Intended by Randomization)0
.000
2.0
004
.000
6.0
008
Den
sity
0 2000 4000 6000 8000 10000at, Winsorized fraction .01
size, treated, as of 2004
size, intended control, as of 2004
kernel = epanechnikov, bandwidth = 171.1019
Kernel density estimate
Kernel Density of Firm Asset Size for Partially-Treated v. Control Firms
(Compliers v. Noncompliers In Control Group)0
.000
5.0
01.0
015
Den
sity
0 2000 4000 6000 8000 10000at, Winsorized fraction .01
size, partially treated, as of 2004size, control, as of 2004
kernel = epanechnikov, bandwidth = 581.0507
Kernel density estimate
So, Problem
• Non-Randomized Non-Compliance• Cannot Compare Treated v. Intended Controls
– Third of controls are partially treated• Cannot Compare Treated v. Real Controls
– Real controls not randomly chosen among intended controls
Solutions• Developed by Statisticians for Randomized Trials
– How to deal with non-compliers• Inverse Propensity Weighting
– Alone or with trimming of ranges without common support– Unbiased with heterogenous treatment effects– But inefficient
• Inverse Propensity Tilting– Creates exact covariate balance– Biased with heterogenous treatment effects– Unbiased with homogenous treatment effects– Efficient
• Propensity score (ptreated) is “balancing score” (Rosenbaum &
Rubin, 1983)
– Same propensity same expected covariates• Unbiased estimate with inverse propensity weights (IPW):
: 1 : 0
: 1 : 0
1 1ˆ * *ˆ ˆ(1 )1 1
ˆ ˆ(1 )i i
j j
N Ni i
ATE N Ni w i wi i
j w j wj j
y yp p
p p
Inverse propensity score reweighting
• Short Version: Multiply [standard weights} * p * (1-p)
• Exact Covariate Balance• Biased Estimate if Heterogenous Treatment Effects
Inverse propensity tilt reweighting
Kernel Density of Propensity to be Treated for Treated v. Control Firms
0.5
11.
52
2.5
Den
sity
0 .2 .4 .6 .8 1Pr(onlyaandcontrolgroup)
p treatedp control
kernel = epanechnikov, bandwidth = 0.0408
Kernel density estimate
Kernel Density of Propensity to be Treated for Partially-Treated v. Control Firms
02
46
8D
ensi
ty
0 .2 .4 .6 .8 1Pr(onlybandcontrolgroup)
p partly treatedp control
kernel = epanechnikov, bandwidth = 0.0879
Kernel density estimate
Tests (1)
• Use Inverse Prop Tilting – Weighting to Produce Exact Covariate Balance
• Ask: – Do Treated Firms Raise More Capital During
Treatment?• Answer:
– Yes for equity– No for debt
Panel, Inverse Prop Tilting
Equity Issuance Debt IssuanceTreatment Period * Treated Firm 0.0285*** -0.0109
(3.33) (-1.229)Treatment Period -0.0911*** 0.013
(-5.232) (0.85)Ln Assets -0.0877*** 0.0200***
(-16.27) (3.80)Ln Cash Holdings 0.0250*** -0.00488***
(15.36) (-3.331)Ln Closing Price 0.0417*** -0.0126**
(7.28) (-2.233)Ln Trading Volume 0.0107*** 0.000555
(3.15) (0.16)Constant 0.252*** -0.00583
(4.68) (-0.122)Fixed Effects firm, year firm, yearClusters firm firm Observations 8,372 8,163R-sq 0.223 0.016Firms 948 948
Tests (2)
• Use Inverse Prop Tilting – Weighting to Produce Exact Covariate Balance
• Ask: – Do Treated Firms Invest More During Treatment?
• Answer:– Yes for CapX– Yes for R&D– Also Increase Dividends
Panel, Inverse Prop TiltingCapital Expenditur
R&D Expenditures
Dividend Payments
Treatment Period * Treated Firm 23.23*** 26.27*** 15.37***(3.79) (2.92) (3.69)
Treatment Period 9.247 -14.09** -18.90***(0.61) (-2.355) (-3.116)
Ln Assets 22.21*** 30.99*** -1.312(4.63) (3.89) (-0.604)
Ln Cash Holdings -0.427 0.255 0.654(-0.354) (0.58) (1.27)
Ln Closing Price -10.08** -13.68*** -0.192(-2.190) (-2.942) (-0.109)
Ln Trading Volume 9.523*** 1.689 1.566(3.56) (0.73) (1.59)
Constant -241.3*** -131.7*** 17.67(-5.306) (-3.307) (0.98)
Fixed Effects firm, year firm, year firm, yearClusters firm firm firm Observations 8,451 7,755 8,500R-sq 0.069 0.127 0.048Firms 948 939 947
Tests (3)
• Use Inverse Prop Matching with Trimming– Covariate Balance not Exact– But not Biased when Heterogenous Treatment
Effects– Censored, Uncensored, and No Weighting
• Ask: – Do Treated Firms Raise More Equity During
Treatment?• Answer:
– Yes for equity
Panel, Inverse Propensity MatchingEquity Issuance
With weights, Censored
With weights, Not Censored
No Weights, Not Censored
Treat Period * Treated Firm 0.0144** 0.0184*** 0.0288***(2.11) (3.05) (4.43)
Treatment Period -0.0266*** -0.0759*** -0.0367***(-3.523) (-5.977) (-4.854)
Ln Assets -0.0887*** -0.0800*** -0.0844***(-16.87) (-17.77) (-19.25)
Ln Cash Holdings 0.0208*** 0.0186*** 0.0209***(15.78) (16.47) (18.10)
Ln Closing Price 0.0400*** 0.0317*** 0.0347***(7.36) (6.97) (8.11)
Ln Trading Volume 0.0112*** 0.0150*** 0.0155***(3.64) (5.59) (6.08)
Constant 0.211*** 0.163*** 0.115**(3.83) (3.90) (2.48)
Fixed Effects firm, year firm, year firm, yearClusters firm firm firmObservations 9,563 11,346 12,316R-squared 0.24 0.207 0.21Number of Firms 1,231 1,255 1,395
Tests (4)
• Use Inverse Prop Matching with Trimming– Covariate Balance not Exact– But not Biased when Heterogenous Treatment
Effects– Censored, Uncensored, and No Weighting
• Ask: – Do Treated Firms Raise More Debt During
Treatment?• Answer:
– No for debt
Panel, Inverse Propensity MatchingDebt Issuance
With weights, Censored
With weights, Not Censored
No Weights, Not Censored
Treat Period * Treated Firm -0.0042 -0.00688 -0.0102(-0.450) (-0.797) (-1.294)
Treatment Period -0.0285* 0.00459 -0.00042(-1.876) (0.33) (-0.0414)
Ln Assets 0.0317*** 0.0217*** 0.0213***(5.78) (4.69) (5.10)
Ln Cash Holdings -0.00438*** -0.00418*** -0.00401***(-3.045) (-3.093) (-3.306)
Ln Closing Price -0.00584 -0.00369 -0.00453(-1.084) (-0.719) (-1.006)
Ln Trading Volume -0.00483 -0.00266 -0.00272(-1.400) (-0.842) (-0.986)
Constant 0.0448 0.0325 0.0371(0.95) (0.74) (0.83)
Fixed Effects firm, year firm, year firm, yearClusters firm firm firmObservations 9,185 11,008 12,041R-squared 0.017 0.014 0.013Number of Firms 1,231 1,255 1,396
Tests (4a)
• Cross-Sectional Results• Ask:
– What Predicts Whether Treated Firm Will Raise Capital During Treatment?
• Possible Candidates:– Pre-Treatment Financial Constraint
• Use Inverse Prop Matching with Trimming
Tests (4b)• Intuition:
– Firm Is Financially Constrained Pre-Treatment – Randomly Given Chance to Raise More Capital – It should take it!
• Ask:– Do Pre-Treatment Financial Constraints Cause Capital Raising During
Treatment?• Fin Constraint = Dividends/Net Income• Use Inverse Prop Matching with Trimming• Answer:
– No– Very Robust– In All Specifications
• Panel, x-section• Linear and Categorical Measures of Fin Constraint• With different weighting, matching, etc.
Impact of Prior Fin Constraint on Equity RaisingX-Section, Before-After Tests
ΔEquityRaised/PPENT
ΔEquityRaised/PPENT
ΔEquityRaised/PPENT
Inverse prop match weighted and trimmed yes yes yesFin Constraint A in 2004 * Treated Firm 0.0121
(0.37)Fin Constraint A in 2004 -0.00956
(-0.562)Treated Firm -0.0167 -0.0196 0.00974
(-1.097) (-1.334) (1.05)Fin Constraint B in 2004 * Treated Firm 0.00909
(0.25)Fin Constraint B in 2004 -0.00856
(-0.336)Fin Constraint C in 2004 * Treated Firm -0.0419
(-0.853)Fin Constraint C in 2004 0.0256
(0.63)Assets, Cash Holdings, Closing Price, Trading Volume Yes Yes Yes Constant 0.0125 0.0421 0.0211
(0.12) (0.43) (0.27)Observations 537 529 32R-squared 0.059 0.062 0.37
Impact of Prior Fin Constraint on Equity RaisingPanel, Inverse Propensity Matching and Trimming
ΔEquityRaised/PPENT
ΔDebtRaised/PPENT
Financial Constraint A * Treatment Group
(0.00) 0.00 (-0.127) (0.22)
Financial Constraint A 0.00 (0.00)(0.08) (-0.202)
Treatment Group (0.02) (0.02) 0.01 (0.00) (0.00) 0.01 (-1.019) (-1.019) (1.05) (-0.472) (-0.472) (0.52)
Financial Constraint B * Treatment Group
(0.00) 0.00 (-0.127) (0.22)
Financial Constraint B 0.00 (0.00)(0.08) (-0.202)
Financial Constraint C * Treatment Group (0.04) (0.05)
(-0.853) (-0.633)Financial Constraint C 0.03 0.03
(0.63) (0.52)Constant 0.01 0.01 0.02 0.01 0.01 0.01
(0.10) (0.10) (0.27) (1.05) (1.05) (0.09)Assets, Cash Holdings, Closing Price, Trading Volume yes yes yes yes yes yesObservations 537.00 537.00 32.00 490.00 490.00 27.00 R-squared 0.06 0.06 0.37 0.01 0.01 0.11
More Robustness
• Same results with categorical measures of constraints
Tests (5a)
• Use Cash Flow – Investment Sensitivity as Proxy for Financial Constraint
• Theory: – Firm Cannot Raise Outside Capital – Has to Rely on Internal Cash Flows – Investment Correlated with Cash Flows
Tests (5b)• Replicate Prior Results in FHP• Ask:
– Does Pre-Treatment Investment-Cash Flow Sensitivity Predict Pre-Treatment Financial Constraint?
• Fin Constraint = Dividends/Net Income
• No Treatment, Just Check• Panel• Use Inverse Prop Matching with Trimming• Answer:
– Yes – Higher Fin Constraint More Cash Flow – Investment
Sensitivity
Correlation: Fin Constraint versus Cash Flow Investment Sensitivity (No Treatment)
Panel, Inverse Prop Score Weighted and TrimmedCash Flow
Investment Sensitivity
Cash Flow Investment Sensitivity
Cash Flow Investment Sensitivity
Financial Constraint Group 1 0.102***(9.63)
Financial Constraint Group 2 -0.0362*(-1.872)
Financial Constraint Group 3 -0.109***(-9.312)
Constant 0.213*** 0.288*** 0.309***(23.96) (54.28) (56.02)
Inverse prop match weighted and trimmed yes yes yes
Obs 863 863 863R-Squared 0.097 0.004 0.091
Tests (5c)
• Ask:– Does Pre-Treatment Investment-Cash Flow
Sensitivity Cause Capital Raising During Treatment?– Firms Randomly Offered Easy Ways to Raise Capital Do High-Sensitivity Firms Raise More?
• Use Inverse Prop Matching with Trimming• Answer:
– No
Impact of Prior Investment Cash Flow Sensitivity on Equity Raising; X-Section, Before-After Tests
Equity Raising
Debt Raising
Equity Raising
Debt Raising
Cash Flow Investment Sensitivity Pre-Tr * Treated Firm
-0.106 -0.0204* -0.109 -0.0204*(-1.180) (-1.649) (-1.208) (-1.651)
Fin Constraint Group 1 0.00517 -0.00099(0.29) (-0.412)
Fin Constraint Group 2 0.0215 0.00127(0.77) (0.35)
Cash Flow Investment Sensitivity Pre-Treatment
-0.0362 -0.00192 -0.0383 -0.00146(-0.532) (-0.216) (-0.558) (-0.162)
Treated Firm0.0159 0.00486 0.0154 0.00472(0.54) (1.23) (0.53) (1.19)
Assets, Cash Holdings, Closing Price, Trading Volume yes yes yes yesConstant -0.0525 0.00618 -0.0581 0.00599
(-0.556) (0.49) (-0.612) (0.47)Inverse prop match weighted and trimmed yes yes yes yesObservations 486 443 486 443R-squared 0.052 0.015 0.053 0.016
Tests (6)• Ask:
– Doe Pre-Treatment Cash Flows Cause Capital Raising During Treatment?
• Use Inverse Prop Matching with Trimming• Answer:
– Yes– More Pre-Treatment Cash Flows More Capital
Raising During Treatment• All Adjusted for PPENT
– Opposite of Theories Using Cash Flow Investment Sensitivity as Proxy for Fin Constraint
Impact of Prior Cash Flows on Equity RaisingX-Section, Before-After Tests
ΔEquityRaised/PPENT
ΔDebtRaised/PPENT
Cash Flows in 2004 * Treated Firm 0.0258*** 0.0009***(9.80) (2.61)
Treated Firm -0.021 -0.00096(-1.560) (-0.530)
Assets, Cash Holdings, Closing Price, Trading Volume Yes Yes
Constant 0.0618 0.0149(0.66) (1.18)
Inverse prop match weighted and trimmed yes yesObservations 537 490R-squared 0.203 0.02
Tests (7)
• Ask:– What Are Firms Doing with Extra Capital They Raise
During Treatment Because of Treatment?• Use Inverse Prop Matching with Trimming• Answer:
– Invest It
Impact of Equity Raising During Treatment on InvestmentX-Section, Before-After Tests
ΔCapx/PPENT
ΔCapx/PPENT
ΔEquityRaised * Treated Firm 0.641**(2.52)
ΔEquityRaised 0.221(1.09)
ΔDebtRaised * Treated Firm 6.637***(2.99)
ΔDebtRaised 0.0589(0.04)
Treated Firm 0.0299 0.00582(0.69) (0.13)
Assets, Cash Holdings, Closing Price, Trading Volume
Yes Yes
Constant 0.264 -0.00873(0.88) (-0.0283)
Inverse prop match weighted and trimmed yes yesObservations 537 490R-squared 0.146 0.107
Tests (8)• Ask:
– Does Pre-Treatment Internal Gov’ce Affect Capital Raising During Treatment?
• Interaction of Internal and External Gov’ce
• Use Inverse Prop Matching with Trimming• Answer:
– Low-Gov’ce Firms More Equity Raising• Substitute External Gov’ce for Internal
– Firms with Higher Risk for Min S/hs More Equity Raising
Internal Governance Predicts Reaction to Changes in External Gov’ce, Panel, Inverse Prop Score Weighted and Trimmed
Equity Issuance Debt Issuance Equity Issuance Debt Issuance
Yes Blockhold No Blockhold Yes Blockholders
No Blockholders
E-Index Bad Gov
E-Index Good Gov
E-Index Bad Gov
E-Index Good Gov
Test Period * Control Group 0.0277*** -0.00881 -0.00957 -0.0176 0.0415*** 0.00908 -0.0272** -0.0023
(2.78) (-0.642) (-0.955) (-0.830) (2.78) (0.89) (-2.060) (-0.190)
Test Period -0.0477*** -0.00552 -0.00584 0.0531* -0.117*** -0.0311*** -0.00272 -0.0227
(-4.290) (-0.357) (-0.412) (1.88) (-3.643) (-2.650) (-0.160) (-1.070)
Assets, Cash Holdings, Closing Price, Trading Volume yes yes yes yes yes yes yes
Constant 0.214*** 0.127 0.0399 -0.183 0.196** 0.278*** -0.0973 0.0655
(3.11) (0.93) (0.69) (-1.511) (2.10) (3.65) (-1.237) (0.88)
Observations 6,743 1,780 6,516 1,773 3,568 4,955 3,483 4,806
R-squared 0.252 0.152 0.016 0.046 0.239 0.227 0.028 0.02
Number of gvkey 780 168 780 168 526 578 523 577
Other Internal Gov’ce Predictors of Responses to Changes in External Gov’ce
• Shareholder Votes to Amend Charter – Worse Gov’ce More Equity Raised
• Cumulative Voting– No Cumulative Voting More Equity Raised
• But Some RiskMetrics Measures Opposite• So, Not Conclusive
Bottom Line• Use Randomized Experiment
• Test Impact of Short Selling in Capital Raising and Investment
• Short Selling Permitted More Capital Raising More Investment
• No Evidence that Fin Constraints Affect Capital Raising and Affect Investment
• Some Evidence that External Gov’ce Is Substitute for Internal Gov’ce
Correlation: Fin Constraint versus Cash Flow Investment Sensitivity (No Treatment)
Panel, Inverse Prop Score Weighted and TrimmedCash Flow
Investment Sensitivity
Cash Flow Investment Sensitivity
Cash Flow Investment Sensitivity
Financial Constraint Group 1 0.102***(9.63)
Financial Constraint Group 2 -0.0362*(-1.872)
Financial Constraint Group 3 -0.109***(-9.312)
Constant 0.213*** 0.288*** 0.309***(23.96) (54.28) (56.02)
Inverse prop match weighted and trimmed yes yes yes
Obs 863 863 863R-Squared 0.097 0.004 0.091