Abortion and crime: who should you believe?

Two very vocal critics, Steve Sailer and John Lott, have been exerting a lot of energy lately trying to convince the world that the abortion reduces crime hypothesis is not correct. A number of readers have asked me to respond to these criticisms. First, let’s start by reviewing the basic facts that support the Donohue-Levitt hypothesis that legalized abortion in the 1970s explains a substantial part of the crime decline in the 1990s:

1) Five states legalized abortion three years before Roe v. Wade. Crime started falling three years earlier in these states, with property crime (done by younger people) falling before violent crime.

2) After abortion was legalized, the availability of abortions differed dramatically across states. In some states like North Dakota and in parts of the deep South, it was virtually impossible to get an abortion even after Roe v. Wade. If one compares states that had high abortion rates in the mid 1970s to states that had low abortion rates in the mid 1970s, you see the following patterns with crime. For the period from 1973-1988, the two sets of states (high abortion states and low abortion states) have nearly identical crime patterns. Note, that this is a period before the generations exposed to legalized abortion are old enough to do much crime. So this is exactly what the Donohue-Levitt theory predicts. But from the period 1985-1997, when the post Roe cohort is reaching peak crime ages, the high abortion states see a decline in crime of 30% relative to the low abortion states. Our original data ended in 1997. If one updated the study, the results would be similar.)

3) All of the decline in crime from 1985-1997 experienced by high abortion states relative to low abortion states is concentrated among the age groups born after Roe v. Wade. For people born before abortion legalization, there is no difference in the crime patterns for high abortion and low abortion states, just as the Donohue-Levitt theory predicts.

4) When we compare arrest rates of people born in the same state, just before and just after abortion legalization, we once again see the identical pattern of lower arrest rates for those born after legalization than before.

5) The evidence from Canada, Australia, and Romania also support the hypothesis that abortion reduces crime.

6) Studies have shown a reduction in infanticide, teen age drug use, and teen age childbearing consistent with the theory that abortion will reduce other social ills similar to crime.

These six points all support the hypothesis. There is one fact that, without more careful analysis, argues against the Donohue-Levitt story:

7) The homicide rate of young males (especially young Black males) temporarily skyrocketed in the late 1980s, especially in urban centers like Los Angeles, New York City, and Washington, DC, before returning to regular levels soon thereafter. These young males who were hitting their peak crime years were born right around the time abortion was legalized.

If you look at the serious criticisms that have been leveled against the Donohue-Levitt hypothesis, virtually all of them revolve around this spike in homicide by young men in the late 1980s-early 1990s. (There are also some non-serious criticisms, which I will address below.) This is the point that Sailer is making, and also the point made far more rigorously by Ted Joyce in an article published in the Journal of Human Resources.

So, a reasonable thing to ask yourself is: Was there anything else going on in the late 1980s that might be causing young Black males to be killing each other at alarming rates that might be swamping the impact of legalized abortion over a short time period? The obvious culprit you might think about is crack cocaine. Crack cocaine was hitting the inner cities at exactly this time, disproportionately affecting minorities, and the violence was heavily concentrated among young Black males such as the gang members we write about in Freakonomics. So to figure out whether this spike in young Black male homicides is evidence against legalized abortion reducing crime, or even evidence legalized abortion causes crime, one needs to control for the crack epidemic to find the answer. This is the argument that I have been making for years. First in the Slate exchange with Steve Sailer back in 1999, then in the Donohue and Levitt response to Ted Joyce, and now in a recent paper by Roland Fryer, Paul Heaton, me, and Kevin Murphy.

The key points I mentioned in Slate five years ago in debating Sailer are reprinted below:

Your hypothesis that crack, not abortion, is the story, provides a testable alternative to our explanation of the facts. You argue:

The arrival of crack led to large increases in crime rates between 1985 and the early ’90s, particularly for inner-city African-American youths. The fall of the crack epidemic left many of the bad apples of this cohort dead, imprisoned, or scared straight. Consequently, not only did crime fall back to its original pre-crack level, but actually dropped even further in a “overshoot” effect.
States that had high abortion rates in the ’70s were hit harder by the crack epidemic, thus any link between falling crime in the ’90s and abortion rates in the ’70s is spurious.

If either assumption 1 or 2 is true, then the crack epidemic can explain some of the rise and fall in crime in the ’80s and ’90s. In order for your crack hypothesis to undermine the “abortion reduces crime” theory, however, all three assumptions must hold true.

So, let’s look at the assumptions one by one and see how they fare.

1)Did the arrival of crack lead to rising youth crime? Yes. No argument from me here.

2) Did the decline in crack lead to a “boomerang” effect in which crime actually fell by more than it had risen with the arrival of crack? Unfortunately for your story, the empirical evidence overwhelmingly rejects this claim. Using specifications similar to those in our paper, we find that the states with the biggest increases in murder over the rising crack years (1985-91) did see murder rates fall faster between 1991 and 1997. But for every 10 percent that murder rose between 1985 and 1991, it fell by only 2.6 percent between 1991 and 1997. For your story to explain the decline in crime that we attribute to legalized abortion, this estimate would have to be about five times bigger. Moreover, for violent crime and property crime, increases in these crimes over the period 1985-91 are actually associated with increases in the period 1991-97 as well. In other words, for crimes other than murder, the impact of crack is not even in the right direction for your story.

3) Were high-abortion-rate states in the ’70s hit harder by the crack epidemic in the ’90s? Given the preceding paragraph, this is a moot point, because all three assumptions must be true to undermine the abortion story, but let’s look anyway. A reasonable proxy for how hard the crack epidemic hit a state is the rise in crime in that state over the period 1985-91. Your theory requires a large positive correlation between abortion rates in a state in the ’70s and the rise in crime in that state between 1985 and 1991. In fact the actual correlations, depending on the crime category, range between -.32 and +.09 Thus, the claim that high-abortion states are the same states that were hit hardest by crack is not true empirically. While some states with high abortion rates did have a lot of crack (e.g., New York and D.C.), Vermont, Kansas, Hawaii, Massachusetts, and Washington were among the 10 states with the highest abortion rates in the ’70s. These were not exactly the epicenters of the crack epidemic.

So, what is the final tally? Two of the key assumptions underlying your alternative hypothesis appear to be false: The retreat of crack has not led to an “overshoot” in crime, causing it to be lower than 1985, and even if it had, the states with high abortion rates in the ’70s do not appear to be affected particularly strongly by the crack epidemic. Moreover, when we re-run our analysis controlling for both changes in crime rates from 1985 to 1991 and the level of crime in 1991, the abortion variable comes in just as strongly as in our original analysis.

Re-reading this response five years later, it still sounds pretty good to me. Interestingly, at the time, Sailer refused to respond directly to my arguments. His response in Slate completely side-stepped the fact that I had destroyed his core argument. He wrote, for instance, “…rather than mud wrestle in numbers here, I’ll privately send you my technical suggestions. In this essay I’ll step back and explain why this straightforward insight [that abortion reduces crime] might not work in practice.” I should note that I am still waiting for those technical suggestions he promised to arrive!! And if you compare his Slate arguments to his “new” article in the American Conservative, you will see that his thinking has not progressed very far on the issue. In contrast, I spent two years working on that paper on crack cocaine, which provides hard, quantitative evidence in favor of those earlier conjectures I had made.

Now let’s talk about John Lott for a minute. Along with John Whitley, he wrote a paper on abortion and crime. It is so loaded with inaccurate claims, errors and statistical mistakes that I hate to even provide a link to it, but for the sake of completeness you can find it here. Virtually nothing in this paper is correct, and it is no coincidence that four years later it remains unpublished. In a letter to the editor at Wall Street Journal, Lott claims that our results are driven by the particular measure of abortions that we used in the first paper. I guess he never bothered to read our response to Joyce in which we show in Table 1 that the results are nearly identical when we use his preferred data source. It is understandable that he could make this argument five years ago, but why would he persist in making it in 2005 when it has been definitively shown to be false? (I’ll let you put on your Freakonomics-thinking-hat and figure out the answer to that last question.) As Lott and Whitley are by now well aware, the statistical results they get in that paper are an artifact of some bizarre choices they made and any reasonable treatment of the data returns our initial results. (Even Ted Joyce, our critic, acknowledges that the basic patterns in the data we report are there, which Lott and Whitley were trying to challenge.)

To anyone who actually made it this far, I applaud you for your patience. Let me simply end with an analogy. Let’s say that we are living in a world in which global warming is taking place, but also a world in which El Nino occasionally leads to radical, short run disruptions in normal weather patterns. You wouldn’t argue that global warming is false because for a year or two we had cold winters. You’d want to figure out what effect El Nino has on winter weather and then see whether controlling for El Nino it looks like global warming is taking place. The impact of legalized abortion on crime is a lot like global warming — it is slow and steady and grows a little year by year. Crack is like El Nino, it comes in with a fury and then largely disappears. That is why I have invested so much time and effort in understanding both abortion and crack, and why the criticisms made against the abortion-reduces-crime hypothesis to date have not been very compelling.

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  1. Shauna says:

    “let the OB/GYNs do their jobs.” Bryan says above. What a pity our culture has gotten to the point where we feel that the job of the doctor is to end life. How about promoting the responsible use of birth control? How about promoting parents actually spending some time with their kids and raising them instead of whatever else they’re doing? How about telling people that we actually value people from the time that they are young until the time they are old, and that criminal acts against people of any age are horrible travesties, not something to be glorified in movies, video games, tv, etc.

    You know, I really don’t give a hoot about whether your freakonomic theory suggests that the crime rate has been lowered by abortion or not. I remember my stat teacher relating a yarn about the woman who won horse races depending on her basal body temperature for the day too. Next you will tell us that there will be less crime against seniors if there is legal euthanasia because there will be less seniors to commit crimes against.

    Abortion IS a crime, except in the most limited of circumstances. Yes, probably some criminals were not born, but if you look at the fact that a lot of boomers are now going to reach retirement on the shoulders of far fewer busters and gen Xers etc. because of abortion, and also that some very brilliant people may not have been born as well, abortion is playing God. And we are not smart enough to be God.

    The fact that we have made it okay to get rid of the very weakest members of society for our convenience tells people that people in general are not very valuable and crime really isn’t very important at all.

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  2. Jonathan Schwartz says:

    Prostitute versus architect salary:

    I just got to the point in your book where you claim that prostitutes make more than architects because of the compensating differentials and the demand for their services. The passage came right after you debunked the misconception that crack-dealers make so much money. I do not have data on the average salary of a prostittute or the average salary of an architect but I would guess that the architect makes more. I think that prostitutes are probably subject to the same plight as the foot soldier crack dealer and the McDonald’s employee whereby they do the ‘grunt’ work but someone else is making all the money.

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  3. deadman says:

    I am writing back because I was curious to see if you had any interest in the idea I touted earlier, Mr. Levitt. That despite random variation shifts by minor variables such as in your El nino analogy:.. I am discussing the same analogy, except the Idea that one impacting variable of minor, therefore, extractable from the equation,… Is an example of what I am asking::: IS IT possible to extract all the noise??? And point out that it is indeed noise. You point to how the crack problem is extractable as noise and find data as to why. Fine…What I am suggesting is how is it possible to suggest that such an issue of the Crack problem that should Damage the sturdy model but fits as extractable noise. While I contend there is so much more noise to extract!!… Arno Penzias When working at Bell labs was trying to extract noise from a freqency of Microwaves with a new antenna Described by George Gamow years before in a paper He stated : Such an antenna will easily detect microwave background radiation from the birth of the universe.. The big bang. Although penzias and his collegue (whose name I can’t recall) won the Nobel prize in Physics.. At the time they didn’t know what it was or even what they’ed found. Why is this so hard to say? People can look at data and say oh this is a real factor “check it out”!! Others may have not a clue. Working out all these variables (even knowing they exist) is difficult in hard Science. I just don’t see how with so many other variables why it even matters if we disover that Crack was not a factor…The line is long. Besides there is still the argument that you cannot prove what you prevent. If you stop something from happening, Yet the trail to its absence is fraught with multitudes of other behaviors and incidents, conditions, Changes in Mores over 30 years. The only point that is worth considering is how closely will every value properly weighted for these upteen other factors; follows state implementation and adoption as policy….. How closely the changes in crime rate follow the trend in every state individually as more abortions were done in percapita stats as the changes were implemented more slowly in some areas and quicker in others. How well does this multiweighted variable mesh with the thesis: Abortion lowered the crime rate on a continuous descent over the 1992 to approx.2002 period. If you have the time I just want to know what you think. Can you contradict my economic pressures and other factors of law change? Well, we can look at one issue in crime by the complexion of its commiters. About 90% Male around 50-55% black. This could give us a clue as who would be best aborted….Allow easier and incentive for women considering abortions for males, and discourage female fetus abortion (Even put quota and rationing “one girl per girl”) (have more forms to be completed and have a “keep your baby girl counceling session) . Males could be allowed to be aborted later term and state could give the “young lady in trouble” a 40$ travel voucher for males. Black Males would be even more encouraged. In fact tuition for the first semester in the institution of choise paid by the state if you abort your black male fetus.

    IT’s late I am being obscene and Stupid forgive me.

    Whadduya think??/////////////////////////////////////////////////////////////////The Variable Jungle?/////cutting away the useless brush and vine in 7 easy lessons??

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  4. Jake says:

    I just wanted to say that you are the man.

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  5. Anonymous says:

    The person who wrote that concealed weapons laws reduced crime was John Lott. To see a paper challenging Lott’s position, see Duggan (JPE) or a more recent working paper by Phillips (NBER, 2005)
    As for abortion. Has anyone done this study for England?

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  6. Anonymous says:

    I have 3 statistical questions regarding the Abortion Regression.

    (1) You say in the book that preganancies rose 30% post Roe v. Wade, but births declined 6%. Implying that Abortion is replacing other forms of Birth Control to a large extent. So states with High v. Low abortion rates may not be relevant. A state with a 36% abortion rate could be roughly equivalent to a state with a 6% abortion rate if they did not see the +30% increase. Should you look at (normalized) birth rates not abortions?

    (2) How are you measuring Crack in the regression? You say in the book that it isn’t users it is dealers who commit the crimes. Therfore the relevant measure should not be useage but marginal gain for marginal turf gain. The crash in price is relevant not the level of use.

    (3) The logic of your paper argues that unwantedness leads to crime. The proxy for this in the bast is children in poverty and single-parent households. I would suggest using a variable for births into poverty and births to unmarried mothers as variables in your regression, so that you can isolate the degree of unwantedness attributeable to abortions. One of Sailer’s key criticisms is that post roe v wade abortions possibly led to higher rates of “illegitimacy”. So why not include that as a variable?

    Thanks,
    Jeff

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  7. Anonymous says:

    Sorry for some of the misspellings above. “bast” was supposed to be “past”. The other misspellings get the meaning accross.

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  8. deadman says:

    Anonymous #12 named Jeff makes my point exactly he has noticed more varibles I didn’t mention. There are people on here, who, if they thought on it, could come up with 10 more challenging variables that have to be accounted for as well. So, What do you think Mr. Levitt?? How reasonable is it to do microanalysis on macro-range issues in Economics? Me again.

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