Are Stand Your Ground Laws in Florida Racist?: Some regression evidence
Did the victim initiate the confrontation?
Was the victim armed?
Was the victim committing a crime that led to the confrontation?
Did the defendant pursue the victim?
Could the defendant have retreated to avoid the conflict?
Was the defendant on his or her property?
Did someone witness the attack?
Was there physical evidence?
Case type
Alleged Home Invasion
Alleged sexual assault
Argument over love interest
Argument turned violent
Attempted car theft
Attempted home invasion
Attempted robbery
Burglary
Citizen enforcing the law
Dispute over money/property
Domestic argument
Domestic dispute
Drug deal gone bad
Fight at bar/party
Home invasion
Neighborhood dispute
Retaliation
Road Rage
Robbery
Roommate Dispute
Teenage bullying
Trespassing
Unknown
Unprovoked attack
Case yearBefore I lose people by reporting the regressions below, let me provide a brief verbal discussion. There is a simple problem with comparing the mean conviction rates as I have done earlier. Just because two people are charged with murder doesn't mean the two cases are identical. Using the Tribune data, blacks killed in these confrontations were 13 percentage points more likely to be armed than the whites who were killed, thus making it more plausible that their killers reasonably believed that they had little choice but to kill their attacker. By a 43 to 16 percent margin, the blacks killed were also more often committing a crime. Further, there were also more cases with a witness around when a black was killed (69 to 62 percent).
Everything else equal, in cases with only one person killed, killing a black rather than a white increases the defendant's odds of being convicted doubles, though the result is not statistically significant. If you also include multiple murder cases, killing a black increases the chances of conviction even more.
Regression looking at the odds of someone being convicted of murder for those who have killed one person.
xi: logit convicted VictimHispanic VictimWhite VictimBlack VictimMale DefendantHispanic DefendantWhite DefendantBlack DefendantMale DidVictimInitiateConfrontation WastheVictimArmed WasVictimCommittingCrime DidDefendantPursueVictim CouldDefendantRetreat WasDefendantonHisProperty DidSomeoneWitnessAttack WasTherePhysicalEvidence othermurdered casetype_2-casetype_25 year_2006-year_2012 if pending=="Decided" & MurderVictim2sRace =="NA", or robust
. test VictimWhite=VictimBlack
( 1) VictimWhite - VictimBlack = 0
chi2( 1) = 0.04
Prob > chi2 = 0.8386
. test VictimHispanic=VictimBlack
( 1) VictimHispanic - VictimBlack = 0
chi2( 1) = 2.55
Prob > chi2 = 0.1100
. test VictimHispanic=VictimWhite
( 1) VictimHispanic - VictimWhite = 0
chi2( 1) = 4.91
Prob > chi2 = 0.0267
. test DefendantWhite=DefendantBlack
( 1) DefendantWhite - DefendantBlack = 0
chi2( 1) = 0.23
Prob > chi2 = 0.6316
I have tried other specifications, but there is no evidence that black and white defendants or black and white victims are treated differently. For example, here is the simplest specification with just the victim's race and gender and defendant's race and gender as well as the number of people murdered.
. xi: logit convicted VictimHispanic VictimWhite VictimBlack VictimMale DefendantHispanic DefendantWhite DefendantBlack DefendantMale othermurdered if pending=="Decided", or robust
Iteration 0: log pseudolikelihood = -71.958988
Iteration 1: log pseudolikelihood = -65.974128
Iteration 2: log pseudolikelihood = -65.940597
Iteration 3: log pseudolikelihood = -65.940546
Iteration 4: log pseudolikelihood = -65.940546
Logistic regression Number of obs = 111
Wald chi2(9) = 8.59
Prob > chi2 = 0.4762
Log pseudolikelihood = -65.940546 Pseudo R2 = 0.0836
----------------------------------------------------
| Robust
convicted | Odds Ratio Std. Err. z P>|z|
-------------+----------------------------------------
VictimHisp~c | .3791321 .580078 -0.63 0.526
VictimWhite | 1.009958 1.446379 0.01 0.994
VictimBlack | .4897925 .7041905 -0.50 0.620
VictimMale | .1134137 .1374925 -1.80 0.073
DefendantH~c | 1.415624 2.026775 0.24 0.808
DefendantW~e | 1.587212 1.956111 0.37 0.708
DefendantB~k | 2.120857 2.711162 0.59 0.556
DefendantM~e | .7934841 .4977044 -0.37 0.712
othermurde~d | 6.797993 7.429584 1.75 0.079
-----------------------------------------------------
. test VictimWhite=VictimBlack
( 1) VictimWhite - VictimBlack = 0
chi2( 1) = 1.93
Prob > chi2 = 0.1650
. test VictimHispanic=VictimBlack
( 1) VictimHispanic - VictimBlack = 0
chi2( 1) = 0.10
Prob > chi2 = 0.7566
. test VictimHispanic=VictimWhite
( 1) VictimHispanic - VictimWhite = 0
chi2( 1) = 1.41
Prob > chi2 = 0.2353
. test DefendantWhite=DefendantBlack
( 1) DefendantWhite - DefendantBlack = 0
chi2( 1) = 0.28
Prob > chi2 = 0.5939
. test DefendantWhite=DefendantHispanic
( 1) - DefendantHispanic + DefendantWhite = 0
chi2( 1) = 0.02
Prob > chi2 = 0.8918
. test DefendantBlack=DefendantHispanic
( 1) - DefendantHispanic + DefendantBlack = 0
chi2( 1) = 0.23
Prob > chi2 = 0.6324
I suspect that there are real biases in how this data is collected. An obvious example is how the Tampa Bay Tribune classified the Zimmerman case.
For example, many would strongly disagree with the newspaper's contention that Martin did not initiate the confrontation, that Zimmerman was pursuing Martin at the time of their confrontation, and that Zimmerman could have retreated to avoid the conflict. The point here is that even using the data with the obvious liberal bias in terms of how this data was entered, the results do not support the claims of bias against blacks.
Labels: CastleLaw, george zimmerman