Clouds, Clocks and Sitting at Tables

Last Tuesday in POLI 1140, the students completed an class oil-market exercise in which pairs of students engaged in a strategic situation that required them to sell oil at specific prices. Many students were able to understand relatively quickly that the “Oil Game” was an example of the classic prisoner’s dilemma (PD). As Mingst and Arreguin-Toft note on page 78, the crucial point about the prisoner’s dilemma:

Neither prisoner knows how the other will respond; the cost of not confessing if the other confesses is extraordinarily high. So both will confess, leading to a less-than-optimal outcome for both.

From a theoretical perspective (and empirical tests have generally confirmed this) there will likely be very little cooperation in one-shot prisoner’s dilemma-type situations. Over repeated interaction, however, learning can contribute to higher levels of cooperation. With respect to IR theories, specifically, it is argued that realists are more likely to defect in PD situations as they are concerned with relative gains. Liberals, on the other hand, who value absolute gains more highly, are more likely to cooperate and create socially more optimal outcomes. What were the results in our class?

The graph above plots the level of cooperation across all six years (stages) of the exercise. There were seven groups and what the probabilities demonstrate is that in each year there was only one group for which the interaction was cooperative. In year 2, there was not a single instance of cooperation. Moreover, it was the same group that cooperated. Therefore, one of the groups cooperated 5 out of 6 years, while none of the other six groups cooperated a single time over the course of the sex years!! What a bunch of realists!!

If you were involved in this exercise, please let me know your reactions to what happened.

We talked a little bit in class today about the link between ethnic (cultural) diversity and public spending. The empirical record seems to find that the more ethnic diversity in a polity, the less public spending–health, education, etc.–there is. A recent article in the American Political Science Review (Habyarimana et al. 2007) addresses the theoretical mechanisms that may underlie this empirical association:

A large and growing literature links high levels of ethnic diversity to low levels of public goods provision. Yet although the empirical connection between ethnic heterogeneity and the underprovision of public goods is widely accepted, there is little consensus on the specific mechanisms through which this relationship operates. We identify three families of mechanisms that link diversity to public goods provision—what we term “preferences,” “technology,” and “strategy selection” mechanisms—and run a series of experimental games that permit us to compare the explanatory power of distinct mechanisms within each of these three families. Results from games conducted with a random sample of 300 subjects from a slum neighborhood of Kampala, Uganda, suggest that successful public goods provision in homogenous ethnic communities can be attributed to a strategy selection mechanism: in similar settings, co-ethnics play cooperative equilibria, whereas non-co-ethnics do not. In addition, we find evidence for a technology mechanism: co-ethnics are more closely linked on social networks and thus plausibly better able to support cooperation through the threat of social sanction. We find no evidence for prominent preference mechanisms that emphasize the commonality of tastes within ethnic groups or a greater degree of altruism toward co-ethnics, and only weak evidence for technology mechanisms that focus on the impact of shared ethnicity on the productivity of teams. (my emphasis)

Thus, what the experimenters found was that (at least in their experiment) co-ethnics were more likely to co-operate in a strategic setting than non-co-ethnics. An additional important factor is the ability of the threat of social sanction to be stronger within a homogenous social group, presumably due to more closely linked social networks. (“I’ll tell your mother on you!” as a threat has more of a potential enforcement effect if you think the person making the threat may actually know your mother. And the likelihood of that person knowing your mother increases, other things being equal, if s/he shares the same ethnicity as your mother.

In the wake of the revolutionary changes that have (hopefully) taken place in Tunisia and Egypt, much has been made about the role of social media–particularly Facebook–in facilitating the participatory aspect of the revolutionary end-game. (A Google search of `Facebook AND Egypt revolution’ turns up over 22 million hits.) The Globe and Mail’s  Chrystia Freeland is the latest journalist to address the phenomenon, quoting economists Daron Acemoglu and Matthew Jackson.

Freeland notes that social network media have helped resolve what social scientists refer to as the collective action problem.

“It is a question of co-ordinating people’s beliefs,” said Daron Acemoglu, a professor of economics at the Massachusetts Institute of Technology, who, with Matthew Jackson of Stanford University in California, is working on a paper about the effect of social networks on collective action problems.

Protesting against an authoritarian regime is a prime example of this issue, Mr. Acemoglu said, because opponents of a dictator need to know that their views are widely shared and that a sufficient number of their fellow citizens are willing to join them to make opposition worthwhile.

“I need to know if other people agree with me and are willing to act,” he said. “What really stops people who are oppressed by a regime from protesting is the fear that they will be part of an unsuccessful protest. When you are living in these regimes, you have to be extremely afraid of what happens if you participate and the regime doesn’t change.”

That makes publicly protesting an oppressive regime a classic collective action problem: If everyone who wants regime change takes to the streets, the group will achieve its shared goal. But if too few protest, they will fail and be punished. Even if an overwhelming majority wants change, it is smart for individuals to speak out only if enough compatriots do, too.

To Freeland’s characterisation of the collective action problem I would add that the reason it is “smart for individuals to speak out only if enough compatriots do, too” is because each individual reasons in the following manner:

• I am only one person; my individual marginal contribution to the probability of having a successful revolution is infinitesimally small.
• Thus, my taking part or not will not be determinative. That is, the revolution will succeed or fail regardless with or without my participation.
• Given the above, and given potential costs of participating, it is rational for me to not participate.

Social media, however, can help to change the calculus of participation by assuring the would-be participant that millions of others will also participate, thereby decreasing the potential costs of participation to any one individual. I do have an issue, however, with Freeland’s use of the Groupon analogy, which is based on the difference between the types of private goods Groupon specialises in and the truly public good that is a revolution.

Following closely in the aftermath of the dramatic changes that have taken place in Tunisia recently, the political unrest seems to have swept its way across northern Africa, with the situation in Egypt now drawing most of the attention. Alan Cowell of the New York Times writes:

After days of protests that have toppled one president and shaken many others, governments across the Middle East braced on Friday for http://www.guardian.co.uk/global/blog/http://www.guardian.co.uk/global/blog/2011/jan/25/middleeast-tunisia://www.guardian.co.uk/global/blog/2011/jan/25/middleeast-tunisia/jan/25/middleeast-tunisia outbursts of rage and discontent directed at entrenched regimes confronting an exceptional clamor for democracy.

The immediate epicenter of the protests was Egypt, where Internet and cellphone connections were closed or restricted in Cairo, Alexandria and other places. Riot police took to the streets of Cairo before the Friday noon prayers that in http://www.guardian.co.uk/global/blog/2011/jan/25/middleeast-tunisia parts of the Islamic world have been a prelude to unrest as worshippers pour onto the streets.

The protests have underscored the blistering pace of events that have transformed the visage of the Arab world, particularly among regimes that have traditionally enjoyed the support of successive administrations in Washington.

Note the words that I have changed to red in the quote above. Is this author using these words as synonyms? If so, is he using them as precisely as he could be? Is he using them incorrectly?

For more information, here’s a useful set of reports, with myriad links to video and audio, from the UK Guardian’s Jack Shenker reporting in Cairo. In addition, the CBC website has an interesting flash-type graphic showing how the geographical extent of the spread of the protests.

In IS 309 this evening, we assessed the strengths and weaknesses of three competing theories of ethnic identity (and ethnic violence)–constructivism, primordialism, and instrumentalism. We read the following:

We then viewed a video on the breakdown of political life in the Ivory Coast and the descent of that once relatively prosperous west African state into civil war. The civil war was characterised as a battle between the “Muslim-populated north and the Christian-dominated south.” How accurate is this characterisation of the ethnic character of Cote D’Ivoire’s civil war?

http://www.youtube.com/watch?v=UOjgiPMs7nc

For information about the current political situation, in the wake of the refusal of former(?) President Laurent Gbagbo to acknowledge having lost power in elections held several weeks ago, watch these.

Next week–January 21st–we’ll be looking at the debate between cultural and rationalist approaches to the analysis of political phenomena. As Whitefield and Evans note in the abstract of their 1999 article in the British Journal of Political Science:

There has been considerable disagreement among political scientists over the relative merits of political culture versus rational choice explanations of democratic and liberal norms and commitments. However, empirical tests of their relative explanatory power using quantitative evidence have been in short supply.

Their analysis of the political attitudes of Czech and Slovak residents is relatively rare in that the research is explicitly designed to assess the relative explanatory purchase of cultural and rationalist approaches to the study of political phenomena. Whitefield and Evans compile evidence (observational data) by means of a survey questionnaire given to random samples of Czech and Slovak residents. In order to assess the strengths of rationalist versus cultural accounts, Whitefield and Evans use statistical regression analysis. Some of you may be unfamiliar with statistical regression analysis, This blog post will explain what you need to know to understand the regression analysis results summarised in Tables 7 through 9 in the text.

Let’s take a look at Table 7. Here the authors are trying to “explain” the level of “democratic commitment”–that is, the level of commitment to democratic principles–of Czech and Slovak residents. Thus, democratic commitment is the dependent variable. The independent, or explanatory, variables can be found in the left-most column. These are factors that the authors hypothesize to have causal influence on the level of democratic commitment of the survey respondents. Some of these are nationality–Slovaks, Hungarians, political experience and evaluations–past and future–of the country’s and family’s well-being.

Each of the three remaining columns–Models 1 through 3–represents the results of a single statistical regression analysis (or model). Let’s take a closer look at the first model–ethnic and country dummy variables. In this model, the only independent variables analysed are one’s country and/or ethnic origin. The contrast category is Czechs, which means that the results are interpreted relative to how those of Czech residence/ethnicity answered. We see that the sign for the result of each of the two explanatory variables–Slovaks and Hungarians–is negative. What this means is that relative to Czechs, Slovaks and Hungarians demonstrated less democratic commitment. The two ** to the right of the numerical results (-0.18 and -0.07, respectively) indicate that this result is unlikely to be due to chance and is considered to be statistically significant. This would suggest that deep-seated cultural traditions–ethnicity/country or residence–have a strong causal (or correlational, at least) effect on the commitment of newly democratic citizens to democracy. Does this interpretation of the data still stand when we add other potential causal variables, as in Models 2 and 3? What do you think?

In IS 302 today, we viewed the first 2/3 of the PBS documentary, Worse than War, based on the work of genocide (note: not genocidal) scholar Daniel Goldhagen , who is probably known best for his book Hitler’s Willing Executioners. Many of the issues raised by Goldhagen in the documentary were relevant to the readings of this week by Kaldor, et al.

According to rational choice theorists, how do individuals make decisions?  Put simply, they act so as to maximize their expected utility, given their a priori preferences and some general idea of the nature of the world (by this, they mean that individuals have some idea of the probability of certain actions leading to specific outcomes).  While rational choice theory was first developed in academic disciplines such as economics, political scientists have adopted the technique and it’s use has proliferated in that discipline.  One of the criticisms of using rational choice theory to explain political phenomena is that often individuals have difficulty ordering preferences adequately.  This is because there is no single “currency” of utility in political science.  The same, however, can not be said for economics as it is much easier to order preferences when there are dollar values attached.  But what happens when time, leisure, etc., have to be taken into account.  Well, it turns out that individuals make many “mistakes” that diverge from that expected of instrumentally rational decision-makers.

Jonah Lehrer informs his readers of a fascinating series of studies done by Ap Dijksterhuis, a psychologist at Radboud University in the Netherlands.  One of these studies looks at decisions related to real estate purchases.  The studies:

look at how people shop for “complex products,” like cars, apartments, homes, etc. and how they often fall victim to what he calls a “weighting mistake”. Consider two housing options: a three bedroom apartment that is located in the middle of a city, with a ten minute commute time, or a five bedroom McMansion in the suburbs, with a forty-five minute commute. “People will think about this trade-off for a long time,” Dijksterhuis writes. “And most them will eventually choose the large house. After all, a third bathroom or extra bedroom is very important for when grandma and grandpa come over for Christmas, whereas driving two hours each day is really not that bad.” What’s interesting is that the more time people spend deliberating, the more important that extra space becomes. They’ll imagine all sorts of scenarios (a big birthday party, Thanksgiving dinner, another child) that will turn the suburban house into an absolute necessity. The lengthy commute, meanwhile, will seem less and less significant, at least when compared to the allure of an extra bathroom.

But, as Dijksterhuis points out, that reasoning process is exactly backwards: “The additional bathroom is a completely superfluous asset for at least 362 or 363 days each year, whereas a long commute does become a burden after a while.” For instance, a recent study found that, when a person travels more than one hour in each direction, they have to make forty per cent more money in order to be as “satisfied with life” as someone with a short commute. Another study, led by Daniel Kahneman and the economist Alan Krueger, surveyed nine hundred working women in Texas and found that commuting was, by far, the least pleasurable part of their day. And yet, despite these gloomy statistics, nearly 20 percent of American workers commute more than forty-five minutes each way. (More than 3.5 million Americans spend more than three hours each day traveling to and from work: they’re currently the fastest growing category of commuter. For more on commuter culture, check out this awesome New Yorker article.) According to Dijksterhuis, these people are making themselves miserable because they failed to properly “weigh” the relevant variables when they were choosing where to live. Because these deliberative homeowners tended to fixate on details like square footage or the number of bathrooms, they assumed that a bigger house in the suburbs would make them happy, even if it meant spending an extra hour in the car everyday. But they were wrong.:

Canadian academic Thomas Homer-Dixon (we will read one of his papers this semester in Intro to IR) has written a piece for Canada’s “paper of record”–the Globe and Mail, which is titled “From Risk to Uncertainty.”  Those of you in my intro to comparative politics class will surely recognize immediately the difference between the tho concepts.

Remember when we read the first two chapter of Shepsle and Bonchek on instrumental rationality, the authors used the example of then-Massachusetts Governor Weld.  Weld had to decide whether to run for Governor again, or to commit to challenging Democratic Senator Ted Kennedy’s Senate seat.  A win there would have given him a nice platform for an eventual presidential run.  Weld, as we know, was operating in a world or risk rather than uncertainty when making his decision, given that there were public opinion polls published that estimated his chances of winning in either election.

What is the difference between risk and uncertainty and how does it apply to the contemporary global financial system (which, by the way, for those of you not paying attention is precariously teetering on the edge of meltdown–you heard it here first!)?

So the rules of the game have now fundamentally changed. Our global financial system has become so staggeringly complex and opaque that we’ve moved from a world of risk to a world of uncertainty. In a world of risk, we can judge dangers and opportunities by using the best evidence at hand [what Shepsle and Bonchek call beliefs] to estimate the probability of a particular outcome. But in a world of uncertainty, we can’t estimate probabilities, because we don’t have any clear basis for making such a judgment. In fact, we might not even know what the possible outcomes are. Surprises keep coming out of the blue, because we’re fundamentally ignorant of our own ignorance. We’re surrounded by unknown unknowns.

Jensen and Wantchekon (2000) have created an index of resource dependence and determined the level of the same for the states of sub-Sarahan Africa.  The scores range from 1 (no resource dependence) to 4 (extreme resource dependence).  They use this as an important independent variable in determining democratic transition, consolidation, and government effectiveness.  How much of an effect does resource dependence have on each of these dependent variables?  You’ll have to read the paper to find out, or attend my class in intro to comparative tomorrow.