Adult entertainment establishments and sex crime

Is adult entertainment (e.g. strip clubs) a substitute for sex crime? It's an unpalatable question for many people, but this 2020 working paper by Riccardo Ciacci (Universidad Pontificia Comillas) and Maria Sviatschi (Princeton University) suggests they may be. They take high-frequency (hourly) observations from the NYPD Stop, Question and Frisk dataset, which is based on records by police officers of every person they stop while on patrol. Most stops did not result in a crime being recorded, and there were some serious problems with who was being stopped. The stop-and-frisk approach wound down after a 2013 lawsuit resulted in it being declared unconstitutional (see here).

Ciacci and Sviatschi use the police data covering the period from 2004 to 2012 (limiting their main analysis to records of "sexual abuse, sexual misconduct and rape"). They link that data to the number of adult entertainment establishments (strip clubs, gentlemen's clubs and escort girl services) at the police precinct level (for 77 precincts across all five boroughs of New York City). They use business records (like the Yellow Pages) and state administrative records to identify the opening dates of each establishment. Then, using a fairly straightforward regression model, they find that:

...the presence of an adult entertainment establishment in a given precinct leads to a 13% reduction in sex crime in the precinct one week after the opening.

Much of the rest of the paper is given over to demonstrating the robustness of their main result, which survives various tests (including the use of lower-frequency reported crime data, rather than the Stop, Question and Frisk data), and exploring the mechanisms that might explain the result. Showing that the results hold when avoiding the problematic Stop, Question and Frisk data is important, although it is worth noting that the effect they find is roughly half the size (although still statistically significant), when using the Citywide Historical NYPD data instead.

In terms of the mechanisms though, Ciacci and Sviatschi identify three possible channels (police channel, potential victims channel, and potential criminals channel). As they explain:

First, it could be the case that adult entertainment establishments reinforce security in the precinct if more police officers are assigned to the area. In this case, a decline in sex crimes could reflect a general decline in crime due to the higher number of officers present in the area after an establishment opens (police channel)... Second, women may be avoiding precincts where adult entertainment businesses have opened and are moving to bordering precincts where there are no establishments. Thus, the decline in crime could be explained by a reduction in potential victims. It could also be the case that adult entertainment establishments are employing potential street sex workers who, in absence of opportunities for indoor prostitution, would work on the streets. If most sex crimes are committed against street sex workers, adult entertainment establishments might reduce sex crimes by merely providing protection to street workers (potential victims channel). Finally, potential offenders might prefer to use adult entertainment establishments services instead of committing sex crimes... To put it another way, they provide consensual sexual activities that could substitute forced sexual activities (potential criminals channel).

Ciacci and Sviatschi demonstrate that there is no statistically significant relationship between adult entertainment establishments and other types of crime (burglary, drug offences, arson, weapon offences, criminal mischief, murder, forgery, obscenity, graffiti, or trespass, each considered individually). That seems to rule out the police channel, since you would expect higher numbers of these other crimes to be recorded if more police officers were in the area. They then look at the impact on street prostitution stops and find:

...no statistically significant effect... This result suggests that there has not been a reallocation of street sex workers to adult entertainment businesses, and it rules out the possibility that the decline in crime is driven by a reduction of street sex workers who could be the main potential victims of sex crimes in the street...

That leaves the potential criminals channel, which they find support for by showing that the impact on reducing sex crime is larger in the evenings (6 p.m. to midnight), when adult entertainment establishments are open, and that there is no significant effect in the afternoon (midday to 6 p.m.) when they are not. I don't find those results to be particularly compelling, (mainly because there is no effect at night (from midnight to 6 a.m., when many establishments would still be open), but they are at least consistent with the potential criminals channel.

There were a couple of things that I found interesting in the paper. First, the number of adult entertainment establishments grew rapidly in New York City over that eight-year period, from 76 in 2004 to 280 in 2012. Ciacci and Sviatschi note that there was only one closure of an establishment in that time, which I found to be extraordinary. They don't provide any real explanation for why there had been such a rapid increase in establishments over that period, nor why the increase was heavily concentrated in Manhattan (which had 75% of the openings). I don't know if it threatens the validity of the results, but we really need to know in order to interpret them. Second, this bit gave me a slight chuckle:

The New York State Department of State classifies adult entertainment establishments as businesses that regularly feature movies, photographs, or live performances that emphasize ”specified anatomical areas” or ”specified sexual activities” and excludes minors by reason of age.

"Specified anatomical areas" may be a candidate for euphemism of the year.

Overall, Ciacci and Sviatschi conclude that:

...the results show that providing substitute services may have positive externalities not only for sex workers but also for all women in the areas where these businesses opened.

In other words, providing adult entertainment establishments offers a substitute that might reduce sex crimes in the neighbourhood.

[HT: Marginal Revolution]

Read more:

• Legalised prostitution and crime

Cricket coin tosses, auctions, and the winner's curse

The cricket season starts soon, so I was interested to read this article on ESPN Cricinfo, arguing to change the way that the toss is decided at the start of each match:

In cricket, the fairness of the pre-match coin toss is the subject of perennial debate. And rightly so.

The toss is random but its impact is not. Over a long series of games, the impact of the toss is neutral, but if it is meant to offer both sides an equal shot at winning any one game, it fails. Our analysis of more than 40,000 professional matches suggests as much: the team that wins the toss wins the game 2.8 percentage points more often. And if that were not sobering enough, in day-night one-day matches, the advantage of winning the toss is a whopping 5.9%...

Auctioning off the ability to choose whether to bat or bowl first is a better idea. Instead of awarding the decision to the captain who correctly calls the face of the coin left staring at the sky after landing on the ground, we should ask teams to use their knowledge and experience to price the value of getting to pick whether to bowl or bat first.

After giving the teams time to inspect the playing surface, each team should simultaneously bid the number of runs that should be added to the other team's score. The team that puts in the higher bid - proposes more runs be added to the other team's score - wins the right to choose whether to bowl or bat. (If the bids are tied, which suggests that teams price the ability to choose the same, an actual coin toss can be used to decide which team chooses and the runs would be added to the other team's score.)

It's an interesting suggestion. If both team captains are equally skilled (which is a heroic assumption), then the coin toss as currently practiced confers a random advantage to one team. Auctioning that advantage to the highest bidder would cost the team winning the toss some runs (because they would have to score additional runs in order to win), reducing the size of the random coin toss advantage. If both teams are equally adept at bowling first (or batting first), both captains are equally skilled, and both captains have complete information about the state of the pitch, then both would be willing to bid the same number of runs.

However, I see three problems here. First, as highlighted in the article:

Cricket teams already heavily use data to help guide decisions on who they draft, what to pay for each player, what tactics to use against each bowler and batter. And the decision on what to do when a team wins a toss is probably already guided by the analytics companies. So yes, teams with more money and better analytics obviously have a leg up.

So, it isn't fair to assume that both captains are equally skilled, because analytics matters. And that leads to the second problem, which is the winner's curse. Consider the two team captains. If both are rational then they will each bid the number of runs that they think fairly represents the advantage they would get from winning the 'coin toss auction'. They won't bid less than that number of runs, because that reduces their chance of winning the auction. They won't bid more than that number of runs, because that reduces their chance of winning the game, if they win the auction. This rational bidding behaviour is what would make this auction format attractive to many economists. However, the captain's estimates of the advantage they get from winning the auction is subject to some random error. They might overestimate the advantage, or they might underestimate the advantage. Since both captains are bidding at the same time, the one that overestimates the advantage by the most will win the auction. And they will likely have bid too many runs for the true value of winning the coin toss. That is the winner's curse. The auction format is good in theory, but it might simply change winning the coin toss from a likely advantage to a likely disadvantage. [*]

A third problem arises when the two teams are mismatched. How many runs should Afghanistan or Kenya bid when playing Australia or India? Could they bid negative runs? And, knowing that, would Australia or India be willing to bid many runs at all? It seems to me that this proposal would ensure that top teams always win the toss when playing against teams that are far below them.

As an economist, it would be interesting to me to see how this would all play out. However, as a cricket fan, the status quo is much preferable because at least the randomness gives the underdogs a chance. For that reason alone, I hope that we never get to see this in practice.

[HT: Marginal Revolution]

*****

[*] The winner's curse is a problem in an auction with many bidders. In an auction with only two bidders (such as this), it is possible that both might underestimate the size of the advantage, and whichever captain underestimates by the least will win. In that case, the winning captain does bank an advantage for their team, but the advantage is smaller than it would be based on a pure coin toss.

Drug use and life satisfaction

One of the late Gary Becker's many contributions to economics is a theory of rational addiction (RA; which he developed along with Kevin Murphy (see here, or here for an ungated version). That theory suggests that drug users (and other addicts) are rational utility maximisers, and that drug use today contributes to higher utility from future drug use. For drug users to be rational though, they need to be able to accurate predict their future utility from drug consumption. In contrast with the rational addiction model, the utility misprediction (UM) theory in psychology suggests that people make errors in predicting their utility from consumption. In the context of drug use, they may overestimate the short-term benefits and/or underestimate the long-term costs of their drug use.

In the context of these competing theories, this 2018 article by Julie Moschion (University of Melbourne) and Nattavudh Powdthavee (Warwick Business School), published in the Journal of Economic Behavior and Organization (ungated earlier version here), attempts to determine which theory is more consistent with empirical data. They first note that:

The key distinction between the RA and the UM models is the prediction on the effect of current substance use on life satisfaction. If current use is associated with lower life satisfaction, then the coefficient on Uit [current use] should be negative – and even more negative than the coefficient on Uit+1 [future use]. This would be consistent with the psychology model of UM, which predicts that consuming addictive substances that have harmful properties should lead to a significant deterioration of life satisfaction. However, if the coefficient on Uit is positive – or significantly less negative than the coefficient Uit+1 - then we have evidence that current consumption may have improved users’ life satisfaction compared to the previous period, which would be consistent with the prediction made by the RA model.

Moschion and Powdthavee use data from 1174 respondents who answered all six waves of the Journeys Home survey in Australia over the period from September 2011 to May 2014. The survey included in each wave measures of respondents':

...usage and the frequency of usage in the past 6 months of: tobacco, alcohol, cannabis, and any other type of illegal/street drugs (which might include amphetamines, such as speed and ice, heroin, cocaine, ecstasy, and so on). We focus on the following substance use variables: smoking tobacco daily (versus not smoking or smoking less than daily), drinking 21 or more standard drinks a week (versus not drinking or drinking less than 21 drinks a week)... using cannabis daily (versus not using or less than daily), using illegal/street drugs weekly (versus not using or less than weekly).

The dataset also includes a measure of life satisfaction (measured on a 0-10 scale). Essentially, Moschion and Powdthavee explore the relationship between respondents' current life satisfaction and their past, current, and future drug use. They find that:

• Average life satisfaction drops significantly prior to the consumption of illegal/street drugs, but not prior to the consumption of other types of substances. The evidence on illegal/street drugs is consistent with the idea that less satisfied individuals are more likely to consume addictive substances because of the expectation that by doing so, their experienced utility could improve.
• An excessive consumption of alcohol, the use of cannabis daily and illegal/street drugs weekly is observed together with a significant drop in life satisfaction. This finding is more consistent with the UM framework in which experienced utility is predicted to decrease in periods following individuals’ consumption of addictive substances.
• We find evidence that the consumption of illegal/street drugs 6 months to a year prior to the interview is associated with lower current life satisfaction, independently of current consumption. This suggests that of the substances studied, only illegal/street drugs may have an effect on life satisfaction for more than 6 months.
• Our results thus suggest a vicious circle of illegal/street drug use by which lower life satisfaction increases the propensity to consume illegal/street drugs that in turn further lowers life satisfaction in the future.

They also find that:

...the estimated effects of past, present, and future consumption of illegal/street drugs on current life satisfaction to be noticeably more negative and statistically more pronounced for women and those from a lower educational background.

These results seem more consistent with the UM model than the RA model. On that point, Moschion and Powdthavee note that:

Our estimates could therefore suggest that respondents’ substance use patterns don’t follow a pattern consistent with the RA model although in reality they do if mental health issues explain non-rational patterns of substance use. To test the implications of controlling for mental health issues, we add 5 dummy variables to capture whether the respondent was diagnosed with any of the following mental health conditions between interviews: bipolar affective disorder, schizophrenia, depression, post-traumatic stress disorder and anxiety disorder. Our results are largely unchanged.

However, in spite of those results Moschion and Powdthavee are still unwilling to declare the rational addiction model dead:

Indeed, this drop in average life satisfaction of substance users over the six months following the use of substances is less consistent with the RA model, but does not rule it out completely, provided that the use of substances increases individual’s life satisfaction in the very short term and that individuals have an extremely high discount rate.

So, I guess until we have a dataset that can not only include past, current, and future drug use, along with a measure of utility (like life satisfaction, and probably measured at high frequency in order to pick up short-term effects) and a measure of discount rate, we're not going to be able to definitively satisfy ourselves that the rational addiction model cannot adequately capture drug users' behaviour. In the meantime, the utility misprediction model has the edge.

Bullshitting as a signal of intelligence

Yesterday's post was a book review of Carl Bergstrom and Jevin West's excellent book Calling Bullshit. One question that probably didn't receive enough coverage in the book is the question of why people bullshit. I guess Bergstrom and West felt that it was self-evident. However, this recent article by Martin Turpin (University of Waterloo) and co-authors, published in the journal Evolutionary Psychology (open access) may provide an answer. They argue that:

The ability to produce satisfying bullshit, with its emphasis on impressing others without regard for truth or meaning... may represent an energetically inexpensive strategy for both signaling one’s intelligence, and deceiving others to one’s advantage.

How does that work? First, it's worth considering what a signal is, and why we provide signals. Signalling is a way of overcoming problems of adverse selection, which is a problem of asymmetric information. Each person knows how intelligent they are, but we don't know. This is asymmetric information. Since we don't know who is intelligent and who is not, it makes sense for us to assume that everyone has low intelligence. This is what we call a pooling equilibrium, and that pooling equilibrium would create problems. If you believe that everyone has low intelligence, it's hard to believe anything you are told (which will make bullshitting as a solution to this problem pretty ironic).

How can someone reveal that they are intelligent? They could just tell you, "Hey, I'm smart". But, anyone can do that. Telling people you are intelligent is not an effective signal. To be effective, a signal needs to meet two conditions:

1. It must be costly; and
2. It must be costly in such a way that those with low quality attributes (in this case, those who are less intelligent) would not be willing to attempt the signal.

Bullshitting is costly - there is a chance that you are caught out in your bullshitting, and people then think less of you (the cost is mostly social in nature). If more intelligent people are better at bullshitting, then it is less likely that they get caught out. That would make bullshitting less attractive of a strategy for less intelligent people. In that case, bullshitting would be an effective signal of intelligence.

Are more intelligent people better at bullshitting? That is the question that Turpin et al. answer in their article. Their research was split into two studies. In the first study, 483 undergraduate students were recruited and given two tests of intelligence (the 'Wordsum' test of verbal intelligence; and Raven's Progressive Matrices (RPM), which is a test of abstract reasoning and general intelligence:

...we presented participants with ten concepts (e.g., cognitive dissonance) four of which were fake (i.e., subjunctive scaling, declarative fraction, genetic autonomy, neural acceptance). Participants’ first task (bullshit willingness task) was to rate their knowledge of each concept on a 5-point scale ranging from “never heard of it” to “know it well, understand the concept.” Responses given to fake concepts were summed to create an index of participants’ bullshit willingness, with higher scores indicating a greater tendency to bullshit (i.e., feign knowledge of fake concepts). Next, a subset of participants (Bullshit Producers) were presented with each of the ten concepts individually and... were instructed to “produce the most convincing and satisfying explanation” they could for each concept. For concepts they were unfamiliar with, participants were instructed to “be creative and make up an explanation that you think others will find convincing and satisfying.”

Turpin et al. then had another subset of participants (Bullshit Raters) rate how accurate and satisfying each of the bullshit explanations was. They found that there was:

...significant positive correlations between participants’ bullshit ability and Wordsum scores... as well as between bullshit ability and RPM scores... Therefore, we find initial evidence of bullshit ability sharing a modest positive association with measures of intelligence.

The second study reported in the article expanded on the first with a new sample of 534 undergraduates, by asking the Bullshit Raters about the perceived intelligence of the Bullshit Producers. In addition to similar correlations with measured intelligence as Turpin et al. found in the first study, they found that:

...the perceived intelligence of Bullshit Producers was positively correlated with assessments of their bullshit ability... This association is consistent with the hypothesis that producing satisfying and seemingly accurate explanations of completely fictional concepts is perceived by individuals as a signal of intelligence.

In other words, bullshit ability does appear to be a signal of intelligence. However, there is one inconsistency. From the first study:

...participants’ willingness to bullshit was negatively associated with scores on the Wordsum... and RPM... suggesting that those scoring higher on our measures of cognitive ability were less willing to bullshit.

If bullshitting really is a signal of intelligence, then we would expect more intelligent people to be more willing to bullshit. However, perhaps more intelligent people have a better theory of mind, and so they are more accurate in assessing other people's receptiveness to bullshit. That would mean that less intelligent people are more willing to bullshit because they incorrectly believe that they can mislead others. Alternatively, perhaps the measure of bullshit willingness (which is made up of the number of made up concepts that research participants claimed to know) is at fault. Perhaps less intelligent people, in an experimental or survey setting, are more likely to claim to know things that they don't? Either way, before we can say for certain that bullshitting is an effective signal of intelligence, we'd want to establish that, ceteris paribus, more intelligent people are more likely to bullshit. That is a task for future research.

[HT: Marginal Revolution]