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[ODP] Crime, income and employment among immigrant groups in Norway and Finland

#1
Author
Emil OW Kirkegaard

Abstract
I present new prediction analyses for immigrant crime, income, educational achievement and employment in Norway and Finland. Results are in line with previous studies. Typical correlation sizes are around .4-.6 indicating that immigrant performance at the group level is substantially predictable by their countries of origin.

Key words
National IQs, group differences, country of origin, Norway, Finland, immigration, crime, spatial transferability hypothesis, income, employment, educational achievement

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This is the first draft. I wanted to keep it short. It is a replication article with some new datasets. Nothing much of interest aside from the fact that the spatial transferability hypothesis successfully replicated in new high-quality datasets.

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I accidentally forgot to save my R file when moving stuff. I have recreated it from the history.


Attached Files
.pdf   article.pdf (Size: 279.03 KB / Downloads: 523)
.zip   New crime data for immigrant groups in Norway and Finland.zip (Size: 1.06 MB / Downloads: 295)
.r   R.R (Size: 5.44 KB / Downloads: 282)
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#2
Several little things, before I give you my approval. Table 1 is troublesome. The numbers are just too small compared to the size of the text. Especially the rows "n".

Quote:I took a closer look at Statistisk Sentralbyra's (SSB) 2 website for data that was useful for testing the spatial transferability hypothesis.

No one can understand what is ST hypothesis if you don't explain it (with few words) or at least refer to a paper/article, or something.

I have the feeling this sentence has a word or two that has gone missing somewhere :

Quote:The big sample only educational attainment variable had higher correlations.
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#3
Hi MH,

Thank you for reviewing my paper.

MH Wrote:Several little things, before I give you my approval. Table 1 is troublesome. The numbers are just too small compared to the size of the text. Especially the rows "n".


It is hard to fit the table on the page. The width is already at maximum. I made the sample sizes (n's) smaller so to reduce the vertical size of the table. The n's are currently in size 7. Which size would you like me to change them to?

The table is here: https://docs.google.com/spreadsheets/d/1...1029777982

MH Wrote:No one can understand what is ST hypothesis if you don't explain it (with few words) or at least refer to a paper/article, or something.


Would you be satisfied with the following two paragraphs added to the introduction?

Quote:The theoretic background for testing country-level predictors is the spatial transferability hypothesis.\cite{Fuerst2014Do} Briefly, the idea is that 1) countries' performance on a variety of variables is to some degree caused by the psychological attributes of the people living in the countries. 2) When people move to another country they retain their psychological attributes to some degree which will be reflected on psychological tests. 3) Moreover, in the receiving countries the psychological attributes of the people cause to some degree their relative performance on a variety of socioeconomic variables such as crime, educational attainment, income, and employment rate.

For instance, when people from a e.g. poor country move to another country, they will tend to be relatively poor in that country as well. This is because part of the reason the country is poor is that the people living there are low in general intelligence (and possibly other psychological attributes too). When they move to a new country, they will generally still be low in general intelligence, and this will cause them to be relatively poor in that country as well. This is of course still allowing for other causes (e.g. culture that people tend to bring with them) as well as improvements on an absolute scale. Somalians living in Denmark are far richer than those who stayed in Somalia, but Somalians in Denmark are relatively poor compared to Danes who live in Denmark just as Somalia is relatively poor compared to Denmark.

MH Wrote:I have the feeling this sentence has a word or two that has gone missing somewhere :


The sentence is correct. Think of it this way:

(The big sample only educational attainment variable) had higher correlations.

However, I rewrote it to:

Quote:Findings of note include: Violent crime was easier to predict than property crime, just as in the Danish dataset.\cite{kirkegaard2014DK} The bad performance of Altinok in some cases seems to be due to sampling error. The educational attainment variable which includes only large samples ("Tert. ed. NO big") had higher correlations than the one with smaller samples too. This is probably because the smaller ones introduced sampling error. Islam was a better predictor of female unemployment than of male, which perhaps has something to do with the role of women in Islam.

Let me know what you think.
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#4
I agree with all of your changes. For ST hypothesis, I didn't mean you should write that much, just only one sentence or two. For the table, I suggest you make the size of the "n" rows as large as the size of the rows "IQ" "Altinok" "Islam" "GDP".

These are only minor changes, and I don't disagree with your analyses or your interpretation. I give you my approval.
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#5
This one has:
- A new correlation matrix with larger text for n's. Everything is now size 9.
- Two more paragraphs in the introduction.


Attached Files
.pdf   article.pdf (Size: 301.93 KB / Downloads: 319)
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#6
1) The 'draft' watermark is REALLY irritating when trying to copy text. Don't use it.

2) Figures 1 and 2 are under copyright and probably cannot be used under fair use.

3) "These findings indicate that the same areas of origin tend to be criminal in both Norway and Finland."

Areas are not criminal, people from those areas are.

4) "population sizes were not sorted by age, so I had to use the entire age group. This introduces error if the age population structures are"

Poorly worded. Also, aside from age, there are also differences in sex ratios.

5) "Pew Research's Islam rate."

"Islam rate" is meaningless. Clarify.

6) "the sample of countries was not so large as to introduce significant sampling error in estimates."

Clarify why increasing N increases sampling error.

7) I assume you used crime rates from Table 2 in Skardhamar et al. These rates are unadjusted for sex and age, unlike their Figure 1. Because sex and age are important causes of crime, not adjusting for group differences in them leads to biased estimates. You can get adjusted values from their Table 4 by converting the M2 odds ratios to d values (or, more roughly, by using sex and age as reported in Table 1 as covariates). The unemployment, education, and income results should also be adjusted for age and/or sex but I would guess it's not easy to do.

8) When you have four predictor variables, each of which predicts about equally well, the study seems incomplete without multiple regression analyses where the effect of each predictor is examined when holding the others constant. The unemployment, education, and income data are confounded by age and sex differences between groups, so even the zero-order results regarding them are dubious, but MR could be used on the sex- and age-adjusted crime rates. (Then again, the crime data have small Ns. Perhaps just run an analysis where one variable is held constant, e.g., what's the correlation with IQ when the effect of Islam is removed, and vice versa.)

9) In the references list, capitalize country names and nationalities. Your Norwegian immigrant paper is marked as "submitted", but it was already published.
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#7
Hi Dalliard,

Thank you for reviewing my paper.

(2014-Aug-29, 17:02:43)Dalliard Wrote: 1) The 'draft' watermark is REALLY irritating when trying to copy text. Don't use it.


You can just copy the text from the source file (article.tex). The reason to use the draft watermark was discussed here: http://www.openpsych.net/forum/showthread.php?tid=119

Quote:2) Figures 1 and 2 are under copyright and probably cannot be used under fair use.

The journal is hosted in Denmark and from my reading of the Danish copyright law, it is clearly a legal case of quotation.

Quote:3) "These findings indicate that the same areas of origin tend to be criminal in both Norway and Finland."

Areas are not criminal, people from those areas are.

Rewrote to: "These findings indicate that people from the same areas of origin tend to be criminal in both Norway and Finland."

Quote:4) "population sizes were not sorted by age, so I had to use the entire age group. This introduces error if the age population structures are"

Poorly worded. Also, aside from age, there are also differences in sex ratios.

I have rewritten it to:

"The reason it is a pseudo per capita is that population sizes were not available by age groups, so I had to use the entire age group even though the educational attainment data concerned only people aged 16 and above. This introduces error if the age population age structures are different. The data are also not broken down by gender so there is possibly gender ratio bias as well."

Does this work for you?

Quote:5) "Pew Research's Islam rate."

"Islam rate" is meaningless. Clarify.

Doesn't seem meaningless to me. It is the per capita rate, i.e. percent of population who believes in Islam. https://en.wikipedia.org/wiki/Islam_by_country#Table

I changed the wording to "Pew Research's Islam prevalence in percent.".

Does this work for you?

Quote:6) "the sample of countries was not so large as to introduce significant sampling error in estimates."

Clarify why increasing N increases sampling error.

It is indirectly mentioned earlier: "The first variable includes all groups with a population $>=200$. The second only includes groups with $>=1000$ such as to reduce sampling error."

Including many countries means the samples must be smaller. This introduces sampling error.

Quote:7) I assume you used crime rates from Table 2 in Skardhamar et al. These rates are unadjusted for sex and age, unlike their Figure 1. Because sex and age are important causes of crime, not adjusting for group differences in them leads to biased estimates. You can get adjusted values from their Table 4 by converting the M2 odds ratios to d values (or, more roughly, by using sex and age as reported in Table 1 as covariates). The unemployment, education, and income results should also be adjusted for age and/or sex but I would guess it's not easy to do.

I used Table 2 data, yes.

Adjusting for sex and age statistically overdoes the adjustment. If you look at their Table 4, M2 (age+sex adjust in logistic regression) has a rate of .7 for Afghans in Norway, lower than natives (1.0). That's not right. Afghan men aged 20-29 do not have lower crime rates than Norwegian men aged 20-29. (Looking at women is uninteresting since they commit only 10% of crimes or something).

The Danish dataset allows one to examine the effects of statistically controlling for age and sex while also doing it manually (by limiting the sample to men in some age group).

What one want to do is compare similar age groups as I did in the Danish study. I have asked SSB (Norway Statistics) for these data: men, age 15-19, 20-29, per capita crime rates by country of origin. It may take some time for them to give it to me. It may cost a lot of money. Basically, SSB is given a government monopoly on access to the data, so they can set the prices any way they want.

Perhaps they will give me the data soon, then we can compare the statistically adjusted values with the real ones.

Quote:8) When you have four predictor variables, each of which predicts about equally well, the study seems incomplete without multiple regression analyses where the effect of each predictor is examined when holding the others constant. The unemployment, education, and income data are confounded by age and sex differences between groups, so even the zero-order results regarding them are dubious, but MR could be used on the sex- and age-adjusted crime rates. (Then again, the crime data have small Ns. Perhaps just run an analysis where one variable is held constant, e.g., what's the correlation with IQ when the effect of Islam is removed, and vice versa.)

I did some MR analyses, but it didn't seem very interesting, so I left it out.

I used automatic modelling in R, using AIC and BIC. AIC results always included Islam and some at least one of the others. BIC always resulted in the model of Islam+GDP. This was also the result in my previous Danish study when I compared adjusted R^2 values.

Quote:9) In the references list, capitalize country names and nationalities. Your Norwegian immigrant paper is marked as "submitted", but it was already published.

Fixed.
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#8
1. "Islam was a better predictor of female unemployment than of male, which perhaps has something to do with the role of women in Islam."

That sounds a bit coy. Why not write: "which may be related to the role of women in Islam"

2. "I changed the wording to "Pew Research's Islam prevalence in percent."

It would be better to write "prevalence of Muslim adherents (as estimated by the Pew Research Center)". The Pew Research Center classifies people as Muslim even if they are only nominal Muslims and do not follow the precepts of Muslim law.

3. Does "area of origin" mean last country of residence, country of birth, or country of ancestral origin? I've been told that many "British" immigrants to Norway are actually of Pakistani origin. How would they be classified in your analysis?
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#9
It is probably last country of residence. I don't know exactly. Pakistani who went to UK and then to Norway would probably be classified as UK.
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#10
This version has the fixes that Dalliard and Peter Frost suggested.

The lack of capitalization in the references list is a LATEX feature (it strips it as a feature). However, we found a way to get around it. http://tex.stackexchange.com/questions/1...g-bbl-file


Attached Files
.pdf   article.pdf (Size: 302.12 KB / Downloads: 356)
.tex   article.tex (Size: 9.72 KB / Downloads: 283)
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