Peter Freund

November 11, 2014
Posted by Jay Livingston

Last weekend we honored our colleague Peter Freund, who died in June. Peter and George Martin were the co-founders, in the 1970s, of our New York Walk – an unofficial, informal, and very loosely planned event for faculty, students, friends, anyone who wanted to join us.  It started as a one-off in the 1970s but became a semi-annual event. Our route usually took us to places like Grand Central Station (Peter loved showing students the whispering gallery there) and downtown sites (Lower East Side, Chinatown). But for Saturday’s reunion, we walked the High Line.  George Martin and Laura Kramer, both retired, were there.

Faye Allard, our colleague till last year, came in from Philadelphia. Here she is with Sangeeta Parashar.

On Sunday, there was a memorial service.  More former Montclair colleagues came – Gil Klajman, Barbara Chasin – and spoke. 

Anecdotes, admiration, and appreciation were offered also by Peter’s wife Miriam, his sisters and nephews, and several friends and colleagues who collaborated with him on his research and activism, all with the goal of reducing the dominance of automobiles, especially in our cities.  (Peter was a founding member of Auto-Free New York, and he never learned to drive a car – a decision that was both ideological and prudent.)

Food and beer, travel and cities, generosity and humor – these were the recurrent themes in people’s reminiscences. That plus a deliberate unconventionality, often as a gambit to get others to question their usually unquestioned assumptions. Like tearing up a dollar bill or two on the first day of class, and when students got upset, asking them why. Peter had a wonderful golden retriever. He had named her Igor. He said it was in tribute to Dr. Frankenstein’s assistant, but I think it was also so he could delight in the reactions of those who insisted that this male name was just wrong for a female pup or, better yet, that the dog would wind up with a confused gender-identity.  In a way I cannot quite articulate, this fits with something else Peter loved – British entertainments like The Goon Show, Monty Python, and Gilbert and Sullivan.  A female dog named Igor – Peter’s own Python sketch.

Peter Freund
November 14, 1940 - June 12, 2014

The ASA Footnotes obituary for Peter is here.

As Others See Us – Maybe Not

November 9, 2014
Posted by Jay Livingston

National character has been sliding out of fashion for a long time.  Here is the Google nGrams chart for the appearance of that phrase in books since 1800.

(Click on an image for a larger view.)

Except for a brief comeback after World War II (there’s something about the Germans), the direction has been downhill,  perhaps because it sounds so much like ethnic or cultural stereotyping. Or maybe it was because valid research on it was difficult and unrewarding. Whatever. Ordinary people, though, have no difficulty in attributing personal characteristics to entire nations. But as is often true among individuals, people do not always see themselves as other see them. And in some cases, they view themselves and others with ambivalence.

Pew recently asked Europeans what they thought of the EU countries. (The report is here.) Things are not going well economically in the EU, and the three traits Pew asked about have little to do with economic policy; instead they tap into people’s feelings about other nations and nationalities. 

Germany is doing best economically, so it’ s not surprising that the five countries doing worst see Germany as the most arrogant. (The Germans themselves modestly ranked their country as the least arrogant.)  Greece too suffers from discrepant perceptions and self-perception, especially in trustworthiness. All other countries rate Germany as the most trustworthy, but Greeks see Germany as least trustworthy.

Presumably, Europeans have concluded that the profligate public policies of Greece and Italy were, if not a prime cause of the collapse, then at least a drag on recovery. These countries could not be trusted to run their economies with honesty and prudence. The Italians seem willing to concede the point. But Greeks rank themselves as the most trustworthy, though on what basis one can only guess.

In two countries, the survey turned up bi-polar reactions. Poles ranked Germany as both most and least trustworthy. The Economist suspects a generational divide between “older Poles with memories of war and younger ones who admire its reputation for prudence.”  Even more puzzling are the French, who give themselves both the highest and lowest ranking on arrogance.  Two other countries agree on the former; but nobody else thinks the French are least arrogant.

Finally, while six of the eight countries identified Germany as least compassionate, every country saw itself as the most compassionate.  Why Germany?  People may see compassion as the opposite of self-interest, with non-Germans thinking that Germany should be willing to do more for other EU countries even at the expense of its own prosperity. At the same time, people in each country, including Germany, are thinking, “We’re being as generous as we can.”

So there is a remarkable similarity of responses here. Ask “Who is the most trustworthy, most arrogant, and least compassionate?” “Germany.”

Ask “Who is the most compassionate?” “We are.”

Data in the Streets

November 2, 2014
Posted by Jay Livingston

I confess, I have little memory for books or articles on methods. I may have learned their content, but the specific documents and authors faded rapidly to gray.  And then there’s Unobtrusive Measures. It must have been Robert Rosenthal who assigned it. He was, after all, the man who forced social scientists to realize that they were unwittingly affecting the responses of their subjects and respondents, whether those subjects were people or lab rats.  The beauty of unobtrusive measures is that they eliminate that possibility. 

Now that states have started to legalize marijuana, one of the questions they must deal with is how to tax it. Untaxed, weed would be incredibly cheap. “A legal joint would cost (before tax) about what a tea-bag costs” (Mark Kleiman, here). Presumably, states want to tax weed so that the price is high enough to discourage abuse and raise money but not so high that it creates a black market in untaxed weed.

The same problem already occurs with cigarettes.

The above graph, from a study commissioned by the Tax Foundation, shows that as taxes increase, so does smuggling. (The Tax Foundation does not show the correlation coefficient, but it looks like it might be as high as 0.6, though without that dot in the upper right, surely New York, it might be more like 0.5.)

In a high-tax area like New York City, many of the cigarettes sold are smuggled in from other states. But how much is “many cigarettes,” and how can you find out? Most studies of smuggled and counterfeit cigarettes get their estimates by comparing sales figures with smoking rates. The trouble with that method is that rates of smoking come from surveys, and people may not accurately report how much they smoke.

That’s why I liked this study by Klaus von Lampe and colleagues.* They selected a sample of South Bronx census tracts and walked around, eyes down, scanning the sidewalks for discarded cigarette packs to see whether the pack had the proper tax stamps.

 All in all, they picked up 497; of those, 329 still had the cellophane wrapper that the stamp would be on.  If there was a tax stamp, they sent it the state to determine if it was counterfeit.

In the end, they estimate that only 20% of the cigarettes were fully legit with state and city taxes paid. About two-fifths had no tax stamp, another 15% had counterfeit stamps, and 18% had out-of-state stamps.

Unobtrusive measures solve one methodological problem, but they are not perfect. The trouble  here, and in many other cases, is the limited range.  Extending this research to the entire city let alone the fifty states would be a huge and costly undertaking.

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* Hat tip to Peter Moskos, who mentioned it on his Cop in the Hood blog.

Whose Bad Guess is More Bad? Difficult Comparisons

October 29, 2014
Jay Livingston

How to compare percentages that are very different? 

A recent Guardian/Ipsos poll asked people in fourteen wealthy nations to estimate certain demographics. What percent of the population of your country are immigrants? Muslim? Christian?

People overestimated the number of immigrants and Muslims, and underestimated the number of Christians. But the size of the error varied.  Here is the chart on immigration that the Guardian published (here).

Italy, the US, Belgium, and France are way off. The average guess was 18-23 percentage points higher than the true percentage.  People in Japan, South Korea, Sweden, and Australia were off by only 7-8 percentage points.

But is that a fair comparison? The underlying question is this: which country is better at estimating these demographics? Japan and South Korea have only 2% immigrants. People estimated that it was 10%, a difference of eight percentage points. But looked at another way, their estimate was five times the actual number. The US estimate was only 2½ times higher than the true number.

The Guardian ranks Hungary, Poland, and Canada together since they all have errors of 14 points. But I would say that Canada’s 35% vs. 21% is a better estimate than Hungary’s 16% vs. 2%.  Yet I do not know a statistic or statistical technique that factors in this difference and allows us to compare countries with very few immigrants and those with far more immigrants.* 

My brother suggested that the Guardian’s readers could get a better picture of the differences if the chart ordered the countries by the immigrant percentage rather than by the percentage-point gap.

This makes clearer that the 7-point overestimate in Sweden and Australia is a much different sort of error than the 8-point overestimate in South Korea and Japan. But I’m still uncertain as to the best way to make these comparisons.

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* Saying that I know of no such statistic is not saying much. Perhaps others who are more familiar with statistics will know how to solve this problem.