Institutionalization Rate

An economist at a financial firm emails Greg Mankiw an analysis, one paragraph I want to focus on:

Finally, critics like to make remarks that the US has artificially reduced its unemployment rate by putting people in jail, claiming that those people would otherwise be unemployed. First, there is no evidence they would be otherwise unemployed. But more important, secondly, the total institutionalization has not changed. Mental hospitals have been emptied out. Sad to say, many of these mentally ill people are in jail. The point is that the sum of all institutionalization is probably stable. As for comparing the US to Europe, many European countries reduce their unemployment rates by putting the long-term unemployed on disability, so they drop out of the labor force.

This is true. I talked about this graph here:

That is Mental Hospital versus Prison rate from Bernard Harcourt, with the total added together rate (which is the highest rate, of course). There were as many people, as a percent, in mental hospitals during the 1940s than are in prison today. (See here for full discussion.)

It’s worth noting that even back then, African-Americans incarcerated within mental hospitals faced different requirements and expectations to be declared ‘mentally-fit and socially-productive’, as researched in a paper by Matthew Gambino, ‘These strangers within our gates’: race, psychiatry and mental illness among black Americans at St Elizabeths Hospital in Washington, DC, 1900—40.

I have no idea what to make of the above graph. We have more people now, of course, and it isn’t a straight transfer of populations – the mental hospital institutionalization population was older, more female, and more white than the current jail population.

This entry was posted in Uncategorized. Bookmark the permalink.

3 Responses to Institutionalization Rate

  1. Chris says:

    I’d like to see this as percentage of the population, but it sure looks like Reagan started a massive crime wave. (Or maybe just a massive incarceration wave disconnected from actual crime rates?) Poverty rates and Gini coefficient seem like the obvious explanation there. Trying to make your fortune on the black market is a risky and probably suboptimal plan — unless you come from the ghetto and have no economic prospects in the legal sectors of the economy. (That isn’t actually why it’s called the black market, but in the U.S., it might as well be.)

    But what should we make of the past’s high mental hospitalization rates? How many of those people were really intractably mentally unstable? Is some of the progress attributable to improvements in mental health treatment, and if so, how much?

    The time delay between the mental hospitalization drop and the incarceration rise suggests that the explanation is *not* simply that all those lunatics immediately knocked over the nearest 7-11. If they were really dangerous why would they have waited ten years to land in jail? The substitution hypothesis can’t account for the low mental hospitalization, low incarceration equilibrium of the 70s. Or, in short, the total institutionalization rate *did* change — radically — and when it changed back it was in a completely different way.

  2. At first glance these seem to be unrelated phenomena – the emergence of a better understanding, better treatment and more humane interpretation of mental illness appears to be entirely independent of a society-wide rise in the harshness of sentencing.

    However… there is a – slightly outlandish – speculation one can make. It is possible to argue that both kinds of institutionalisation are different manifestations of equilibrium forces in the economy. Perhaps an employment equilibrium was reached in the US through institutionalisation of many of the least productive members of the population.

    Here’s a graph of US unemployment over roughly the same period: http://bubblemeter.blogspot.com/2009/02/graph-united-states-unemployment-rate.html

    When institutionalisation was at its lowest point (1982) unemployment was at its highest. Indeed, if you exclude recessions, the pattern of unemployment broadly looks like the inverse of the MH + Prison rate in the graph above.

    Say there is a small but positive structural level of demand in the economy for unskilled, low-productivity workers (let’s say 10%). And imagine this is combined with a slightly-too-large supply of low-productivity workers (let’s say 20%), which are distributed across various different demographic and social groups.

    It is not infeasible to imagine that the “excess” 10% of workers would overflow into different situations. 5% might be long-term unemployed. And another 5% would be marginalised in different ways, depending on the social constraints of the time. In the 1950s, certain people were locked up in mental hospitals. In the 1990s, different people were locked up in prisons.

    The flaw in this theory is that the numbers don’t match too well. In 1982 unemployment was 9% (compared with a long term average around 5%) – a difference of 4% of the population. But the institutionalisation rate never gets above 0.8%, and the difference between peak and trough is 0.5%.

    This doesn’t destroy the idea completely but it does mean it can only explain a part of the data. Still, it’s interesting to think about.

  3. wiscoDude says:

    It would have been better had the economist omitted the following line “First, there is no evidence they would be otherwise unemployed.” As there is considerable data to show those incarcerated are not a random sample of the population, but are in fact more likely to be under employed when compared with the overall population.

    In any case, this line:

    “There were as many people, as a percent, in mental hospitals during the 1940s than are in prison today.”

    is mind blowing.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s