Modeling Social Processes–Abortion in Cross-national Comparison

Thanks to a post by Zoe and Geoff, I decided to use the social fact of variation in abortion rates from country to country as the inspiration for class discussion today on the modeling process in social sciences. First, the data* (listing only the top and bottom 10–the US is 30th (out of 90 countries with data available) with a rate of 23.9% in 2003):

Country

Year

%

Russia

2005

52.5

Greenland

2004

50.2

Bosnia and Herzegovina

1988

48.9

Estonia

2004

47.4

Romania

2004

46.9

Belarus

2004

44.6

Hungary

2004

42.0

Guadeloupe

2005

41.4

Ukraine

2004

40.4

Bulgaria

2004

40.3

Suriname

1994

3.0

Puerto Rico

2001

2.2

Malta

2004

1.7

Qatar

2004

1.3

Portugal

2005

0.8

Venezuela

1968

0.8

Mexico

2003

0.2

Poland

2004

0.06

Panama

2000

0.02

Chile

1991

0.02

Now, according to Lave and March, the next step in the model-building process is to consider a social process that would lead to this outcome. There were three potential answers given in class, which correspond to three categories of explanation that we will address throughout the course:

1) Cultural–it would seem that religion is very important to individuals in the countries with the lowest rates. Most of these countries are strongly Catholic and the Church’s official policies are strongly anti-abortion (pro-life). Thus, individuals in these societies are inculcated with a strong view of what to do in the case of an unwanted pregnancy.

2) Rational Choice–one of the groups argued that the decision to abort (or not) a fetus was made on the basis of strategic calculations of self-interest. The countries at the bottom, these students argued, were agricultural and poorer, and children are needed as a source of labor for the household, as a future hedge against retirement for parents who live in societies with a poorly developed social welfare state, with little hope of receiving retirement funds from the government.

3) Institutional–rules, laws, regulations. Some students argued that some countries (like Chile) have laws making abortion illegal, thus either lowering the number overall, or decreasing the incentive for those having illegal abortions to report them to the official authorities.

That was great work; give yourselves a pat on the back or a round of applause.

The third step in the modeling process is, then, to tease out further implications of your preferred hypothesis above. Let’s go back to the cultural explanation. If it’s true that the Catholic Church has a tremendous impact on people’s views of what is right and wrong then, as one student asked, “wouldn’t it also be the case that divorce levels in these countries should be lower than divorce levels in the countries at the top of the list (since the Catholic Church also frowns upon divorce) ?

Continue reading “Modeling Social Processes–Abortion in Cross-national Comparison”

Kenya, ethnic diversity, and fractionalization scores

Had you taken my Introduction to Comparative Politics class in the fall of 2007, you would have been faced with writing a paper in response to this:

There is much debate regarding the determinants of, and obstacles to, democratization. Are states that rely on natural resources for a large share of their GDP less likely to become and remain democratic? Does ethnic diversity present an obstacle to the democratization and democratic consolidation of a regime? Your term paper will answer one of these two questions either in the affirmative or the negative.

In addition to making the theoretical argument, students were asked to use Iraq and one other state to illustrate and support their argument(s). A few students chose to write on Kenya. I hope they go back and read their papers in light of the current situation in that multi-ethnic state.

Is Kenya ethnically diverse? How can we measure ethnic (or religious, or linguistic) diversity? There is a formula called the fractionalization index, which essentially gives us an idea of how diverse a state is. You can find a table–in Appendix A (which I have excerpted here) of over 100 states around the world with their corresponding fractionalization scores (in three categories), in this National Bureau of Economic Research (NBER) paper by Alesina et al. here The higher the value the higher the level of diversity. Notice the relatively low diversity of states like Poland and Norway and the high amount of diversity of almost all African states. Which is the best way to measure “diversity”? Ethnically? Linguistically? By religion?


Country
Date (Ethnicity Data)
Ethnic
Language
Religion
Afghanistan
1995
0.7693
0.6141
0.2717
Canada
1991
0.7124
0.5772
0.6958
China
1990
0.1538
0.1327
0.6643
Croatia
1991
0.3690
0.0763
0.4447
Kenya
2001
0.8588
0.8860
0.7765
Malawi
1998
0.6744
0.6023
0.8192
Mozambique
1983
0.6932
0.8125
0.6759
Nigeria
1983
0.8505
0.8503
0.7421
Norway
1998
0.0586
0.0673
0.2048
Portugal
1998
0.0468
0.0198
0.1438
USA
2000
0.4901
0.2514
0.8241

Informal Institutions and Democracy in Africa

Using results from the Afrobarometer surveys, Michael Bratton has written an article in a recent issue of Journal of Democracy (you must have access to JoD articles to read this) on the relationship between formal and informal institutions and democracy in a sample of African countries.

This is a blurb from the article about Afrobarometer: “[Bratton] is also founder and director of the Afrobarometer, a collaborative international survey-research project that measures public opinion regarding democracy, markets, and civil society in eighteen African countries.”

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