nhaliday + white-paper + evidence-based   5

A Rejection of 'Broken Windows Policing' Over Race Actually Hurts Minority Neighborhoods | Manhattan Institute
https://twitter.com/BookOfTamara/status/778838226983268352
https://archive.is/ETLXf
Late-night slightly controversial criminal justice thread:

Proactive policing and crime control: https://www.nature.com/articles/s41562-017-0227-x
Evidence that curtailing proactive policing can reduce major crime: https://www.nature.com/articles/s41562-017-0211-5

Proactive Policing: Effects on Crime and Communities: http://sites.nationalacademies.org/dbasse/claj/proactive-policing/index.htm
This report from the Committee on Law and Justice finds evidence that a number of proactive policing practices are successful in reducing crime and disorder, at least in the short term, and that most of these strategies do not harm communities’ attitudes towards police.

Is Racial Profiling a Legitimate Strategy in the Fight against Violent Crime?: https://link.springer.com/epdf/10.1007/s11406-018-9945-1?author_access_token=nDM1xCesybebx7yUX2BxZ_e4RwlQNchNByi7wbcMAY6py69jTlOiEGDIgqW0Vv2HrAor6wlMLH695I2ykTiKUxf1RBnu1u_6gjXU-6vgh2gIy6CX2npHD9GR350T20x_TbCcq4MmJUPrxAqsJSe1QA%3D%3D
- Neven Sesardić

Are U.S. Cities Underpoliced?: http://marginalrevolution.com/marginalrevolution/2017/08/u-s-cities-underpoliced.html
Chalfin and McCrary acknowledge the endogeneity problem but they suggest that a more important reason why ordinary regression gives you poor results is that the number of police is poorly measured. Suppose the number of police jumps up and down in the data even when the true number stays constant. Fake variation obviously can’t influence real crime so when your regression “sees” a lot of (fake) variation in police which is not associated with variation in crime it’s naturally going to conclude that the effect of police on crime is small, i.e. attenuation bias.

By comparing two different measures of the number of police, Chalfin and McCrary show that a surprising amount of the ups and downs in the number of police is measurement error. Using their two measures, however, Chalfin and McCrary produce a third measure which is better than either alone. Using this cleaned-up estimate, they find that ordinary regression (with controls) gives you estimates of the effect of police on crime which are plausible and similar to those found using other techniques like natural experiments. Chalfin and McCrary’s estimates, however, are more precise since they use much more of the variation in the data.

Using these new estimates of the effect of police and crime along with estimates of the social cost of crime they conclude (as I have argued before) that U.S. cities are substantially under-policed.

Crime Imprisons and Kills: http://marginalrevolution.com/marginalrevolution/2018/01/crime-imprisons-kills.html
…The everyday lived experience of urban poverty has also been transformed. Analyzing rates of violent victimization over time, I found that the poorest Americans today are victimized at about the same rate as the richest Americans were at the start of the 1990s. That means that a poor, unemployed city resident walking the streets of an average city today has about the same chance of being robbed, beaten up, stabbed or shot as a well-off urbanite in 1993. Living in poverty used to mean living with the constant threat of violence. In most of the country, that is no longer true.

http://marginalrevolution.com/marginalrevolution/2015/09/what-was-gary-beckers-biggest-mistake.html
http://www.sentencingproject.org/wp-content/uploads/2016/01/Deterrence-in-Criminal-Justice.pdf
Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?: http://link.springer.com.sci-hub.tw/article/10.1007/s00181-017-1332-4

Death penalty: https://offsettingbehaviour.blogspot.com/2011/09/death-penalty.html
And so I revise: the death penalty is wrong, and it also likely has little measurable deterrent effect. There may still be a deterrent effect; we just can't show one given available data.

The effects of DNA databases on the deterrence and detection of offenders: http://jenniferdoleac.com/wp-content/uploads/2015/03/DNA_Denmark.pdf
We exploit a large expansion of Denmark’s DNA database in 2005 to measure the effect of DNA registration on criminal behavior. Using a regression discontinuity strategy, we find that DNA registration reduces recidivism by 43%. Using rich data on the timing of subsequent charges to separate the deterrence and detection effects of DNA databases, we also find that DNA registration increases the probability that repeat offenders get caught, by 4%. We estimate an elasticity of criminal behavior with respect to the probability of detection to be -1.7. We also find suggestive evidence that DNA profiling changes non-criminal behavior: offenders added to the DNA database are more likely to get married, remain in a stable relationship, and live with their children.

Short- and long-term effects of imprisonment on future felony convictions and prison admissions: http://www.pnas.org/content/early/2017/09/26/1701544114.short
https://twitter.com/bswud/status/917354893907779585
Prison isn't criminogenic—offenders have higher rates of re-incarceration because of technical parole violations
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january 2017 by nhaliday
Democracy does not cause growth | Brookings Institution
64-page paper
Democracy & Growth: http://www.nber.org/papers/w4909
The favorable effects on growth include maintenance of the rule of law, free markets, small government consumption, and high human capital. Once these kinds of variables and the initial level of real per-capita GDP are held constant, the overall effect of democracy on growth is weakly negative. There is a suggestion of a nonlinear relationship in which democracy enhances growth at low levels of political freedom but depresses growth when a moderate level of freedom has already been attained.

The growth effect of democracy: Is it heterogenous and how can it be estimated∗: http://perseus.iies.su.se/~tpers/papers/cifar_paper_may16_07.pdf
In particular, we find an average negative effect on growth of leaving democracy on the order of −2 percentage points implying effects on income per capita as large as 45 percent over the 1960-2000 panel. Heterogenous characteristics of reforming and non-reforming countries appear to play an important role in driving these results.

Does democracy cause innovation? An empirical test of the popper hypothesis: http://www.sciencedirect.com.sci-hub.cc/science/article/pii/S0048733317300975
The results from the difference-in-differences method show that democracy itself has no direct positive effect on innovation measured with patent counts, patent citations and patent originality.

Benevolent Autocrats: https://williameasterly.files.wordpress.com/2011/09/benevolent-autocrats-easterly-draft.pdf
A large literature attributes this to the higher variance of growth rates under autocracy than under democracy. The literature offers alternative explanations for this stylized fact: (1) leaders don’t matter under democracy, but good and bad leaders under autocracy cause high and low growth, (2) leaders don’t matter under autocracy either, but good and bad autocratic systems cause greater extremes of high and low growth, or (3) democracy does better than autocracy at reducing variance from shocks from outside the political system. This paper details further the stylized facts to test these distinctions. Inconsistent with (1), the variance of growth within the terms of leaders swamps the variance across leaders, and more so under autocracy than under democracy. Country effects under autocracy are also overwhelmed by within-country variance, inconsistent with (2). Explanation (3) fits the stylized facts the best of the three alternatives.

Political Institutions, Size of Government and Redistribution: An empirical investigation: http://www.lse.ac.uk/internationalDevelopment/pdf/WP/WP89.pdf
Results show that the stronger democratic institutions are, the lower is government size and the higher the redistributional capacity of the state. Political competition exercises the strongest and most robust effect on the two variables.

https://twitter.com/GarettJones/status/899466295170801664
https://archive.is/sPFII
Fits the high-variance theory of autocracies:
More miracles, more disasters. And there's a lot of demand for miracles.

Measuring the ups and downs of governance: https://www.brookings.edu/blog/future-development/2017/09/22/measuring-the-ups-and-downs-of-governance/
Figure 2: Voice and Accountability and Government Effectiveness, 2016
https://twitter.com/whyvert/status/917444456386666497
https://archive.is/EBQlD
Georgia, Japan, Rwanda, and Serbia ↑ Gov Effectiveness; Indonesia, Tunisia, Liberia, Serbia, and Nigeria ↑ Voice and Accountability.

The logic of hereditary rule: theory and evidence: http://eprints.lse.ac.uk/69615/
Hereditary leadership has been an important feature of the political landscape throughout history. This paper argues that hereditary leadership is like a relational contract which improves policy incentives. We assemble a unique dataset on leaders between 1874 and 2004 in which we classify them as hereditary leaders based on their family history. The core empirical finding is that economic growth is higher in polities with hereditary leaders but only if executive constraints are weak. Moreover, this holds across of a range of specifications. The finding is also mirrored in policy outcomes which affect growth. In addition, we find that hereditary leadership is more likely to come to an end when the growth performance under the incumbent leader is poor.

I noted this when the paper was a working paper, but non-hereditary polities with strong contraints have higher growth rates.
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september 2016 by nhaliday

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