18
May

Morality and Political Science

Often I get into a debate with people (mostly students) about the role of morality in politics. The argument usually begins after I after I have articulated some theory of politics which invokes incentive based explanations for some phenomena where the outcome is normatively distasteful. The view that political actors should act in some way preferable to one’s subjective morals is ubiquitous. Moreover, the argument also follows discussions of formal models making the rationality assumption (or as my mentor likes to say models where “actors have preferences that won’t cycle”).

As a student of politics I am trying to understand how the political world around me works. Generally, this involves developing new ways of looking at the world and building interesting theoretical models which can produce testable hypothesis. Of course we can debate Hypothetical-Deductive Reasoning, but that is not the point of this post. Simply put, I want to explain the world and morality rarely plays a huge role as an independent variable. I am not saying that morality cannot play a role in politics; in fact, we can easily model morality or altruistic based incentives. But denying theoretical explanations and empirical evidence because it does not fit with our normative priors does not help us explain the world.

Take the Prisoner’s Dilemma (PD) as an example. This simple model can be used to explain arms races, common-pooled resource problems, and noncooperation in international relations. The model is of course a simplification and illustrates how individual incentives can lead to collectively poor outcomes. People often have trouble believing that both actors would defect on each other. The reason is often based on some type of moral exhortation about how the actors will cooperate because that is the “right thing to do”. But the fact remains that in many cases one shot PD games are very useful for describing the behavior of individuals. One may think that the world looks more like the Stag Hunt than a PD game, but it is still based on incentives, not morality.

For example, economists have argued that the rise in SUV purchases can be explained by a PD game. Given that SUVs are larger than other vehicles and weigh more, it can be argued that they are safer when experiencing an accident with smaller cars. When people begin to buy SUVs it makes those with smaller cars less safe. A rational response to an increase in SUVs on the road would be to purchase an SUV for oneself as to not be at a safety disadvantage. In the aggregate this means more SUVs on the road which may increase emissions and decrease safety for everyone. Of course a lot more goes into SUV purchases, but using the PD game is still a useful and interesting way to look at the world.

The House is  considering the Smith/Amash Amendment which will alter the NDAA so that  the military may not imprison terrorism suspects captured on United States soil without trial. I recently had a discussion with someone who argued that the the U.S. should pass this amendment because the NDAA violates the natural rights of human beings – for both citizens and non-citizens. Support of the NDAA, for this person, implies that we are relegating fundamental human rights to the state. Philosophically, I tend to agree. But the fact is that the state has a monopoly on force and power is primary in politics. Even if the NDAA violates our “natural rights” it does not prevent the state from passing such as law and implementing it. My ultimate point was that we needed to understand the way the law was written in order to understand the protections it provides for U.S. citizens; if there is going to be a fight it will most likely take place in the courts and understanding the language of the law can be a powerful tool for those trying to combat it.

There is also the implication that democracy is normatively better than other systems and thus ought to do the right thing and stop suppressing civil liberties. But this overlooks several times in history when the U.S. and other democracies used their power to suppress civil rights and liberties. For example Japanese Interment camps during WWII, the institution of slavery, the separate but equal doctrine, the suppression of women’s rights, and we can go on. People often wonder why the U.S. hasn’t intervened in Darfur based on morality. The answer is quite simple, those in power are unwilling to risk blood and treasure in an area which holds little interest for U.S. foreign policy.

I tend to talk about politics outside of morality – although I am aware that it can in fact play a role. Some people take this to mean that I am promoting amoral ideas. I am not promoting anything. I am simply trying to understand the world for what it really is and this means distilling it down to what I (and others) hypothesize are the most important factors. Even so, if you really want to impact public policy you would be better off spending your time learning about how the world really works so that you find strategic points of entry in the policy process and make a difference. Otherwise, debating the morality of theoretical explanations and empirical evidence seems futile – or at least relegated to philosophy.

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10
Apr

New Graduate Student Conference on the EU and World Politics!

I am the co-adviser to the University at Buffalo’s SUNY Model European Union organization, which is a transatlantic collegiate simulation of the European Union in the US. At this year’s simulation, held at the University of Exeter in the UK, several colleagues from Buffalo State College and I decided to organize an inter-campus graduate student conference on the European Union’s role in world affairs.

I am happy to announce that the conference will take place this fall on October 5-6, 2012. The conference is open to all relevant disciplines and sub-disciplines including political science, international law, European law, international political economy, economics, policy sciences, international studies and history. We are hoping to make this an annual event.

Papers may cover any policy area of interest, including topical issues such as, the EU’s response to recent conflicts in the Middle East, the Eurozone crisis, the EU’s foreign policy and role in global affairs after the Lisbon Treaty, and the general interaction between domestic politics of member states and EU foreign policy-making.

There will also be an undergraduate panel and an award for best undergraduate paper.

For more information, the call for papers, and to submit a paper, please visit our conference website here. Also, Please pass the word on to those that might be interested.

Information:

Title:

The European Union and World Politics: The EU, its Member States, and International Interactions

Dates:

October 5th and 6th 2012

Location:

University at Buffalo and Buffalo State College

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21
Mar

Media Bias and the Ability to Uncover the Truth

Media Bias

Those of you familiar with my Wartime Elections model know that I assume the actor, I call the Media (M), to be “unbiased”. Specifically, Nature send a noisy signal to M, and M sends that “unbiased” but potentially noisy signal to the Electorate (E) about the “true” state of the war.

You may already be thinking, “the Media is clearly biased, so that assumption is wrong”. I am not going to present a rant about why simplifying assumptions need only be useful, not necessarily true, in order to tell us something interesting about the way phenomena works (although I do believe this to be true).

Moreover, when we think about the democratic process, we often think that if citizens were better informed they would be better democratic citizens. And of course – whether it is true or not - journalists often claim that “the central purpose of journalism is to provide citizens with accurate and reliable information they need to function in a free society” (Project for Excellence in Journalism, 2007). Thus, my assumption of an unbiased, yet potentially inaccurate, Media is not far from what we think the world should look like based on normative evaluations. In fact, I find it interesting that such tragic possibilities (see here and here) are possible given the assumption of an unbiased Media.

More Bias, Yet Closer to the Truth?

Nevertheless, I have just come across an interesting and revealing formal model of news consumption and media bias, by Xiang and Sarvary, which actually demonstrates that the ability to uncover the true state of the world is higher (what they call information efficiency) when the media is more biased! Yes, when competing media outlets are more biased “conscientiousness consumers”, who seek the truth, are actually better able to uncover reality – but they must pay a higher price for said media because they must purchase from multiple media outlets.

The authors assume that there is some true state of the word – $\theta$ – which is bound between 0 and 1 – this parameter can be whether the war is actually worth fighting or the true value of a new healthcare law. The true state of the world is not observable to the Media, rather they they have to collect data which is modeled as a series of random draws from a Bernoulli process. The draws make up a string (D) which consists of 0s or 1s; these represent negative or positive signals about the truth, respectively. Thus, assume the string $d=[1,0,0,1,1,1,0,0,1,1]$. The unbiased estimate of the truth is $\hat{\theta} =\frac{6}{6+4} = 0.6$. Thus, is the string $d$ contains $n_{1}$ of 1′s and $n_{0}$ of 0′s, the unbiased estimate of the truth is $\frac{n_{1}}{(n_{1}+n_{0})}$. The authors then assume that the Media can “slant” what they report by selectively omitting parts of the string and thus changing $\hat{\theta}$ or the estimated true state of the world. But slanting is costly for the Media because they have to collect more data (which are random draws) to be able to slant. Moreover, the Media cannot manufacture data; slanting is constrained by the truth and the cost of data collection.

In the authors’ model there are two types of consumers – “biased” and “conscientiousness”; the former uses mass media for entertainment purposes, while the later actually seeks the truth. Media outlets can report how biased their messages are in order to attract specific consumers ($m = \theta$ or $m = s$) – $\theta$ being as close as possible to the real state of the world and $s$ being some purported amount of slant.

Under monopolist media conditions the media simply caters to whichever consumer represents a larger portion of the population – biased or conscientiousness . Under a duopoly there exists an interesting equilibrium. When there exists a significant number of conscientiousness consumers and their disutility for biased media is high, media outlets will actually collect more data in order to present highly slanted views. The existence of a significant amount of conscientious consumers with a high disutility for bias forces them to buy both pieces of media and thus the media outlets are more willing to increase prices to capitalize on this consumer segment. In fact, these media sources also report news which is more biased than the average “biased” consumer desires.

What is even more interesting is that Xiang and Sarvary show that under these conditions information efficiency is also very high. Because biased consumers’ consumption preferences are heterogeneous the conscientiousness consumer knows that the truth will be on the the left of the message $m <s$ and on the right of messages $m> s$. Thus, when consuming both slanted news sources (which share the same random draws of information) the conscientiousness consumer can come closer to the “true state of the world”.

Thus, the punch line of the model is that a significant number of conscientiousness consumers can actually drive media to be more biased in a competitive setting, but these same consumers “may actually recover more information from multiple, increasingly biased news than from a single nonpartisan news provider” (Xiang and Sarvary 2007, p. 623).

Interesting Implications

Xiang and Sarvary’s model has some interesting implications. The most provocative implication is that increasing media bias may actually make it easier (albeit more costly) for “truth-seeking” consumers to figure out the true state of the world. Moreover, this model rejects the notion that media bias is driven by consumer demand for bias; rather increased bias is a function of more truth-seeking consumers and competing media outlets ability to drive up price, knowing these consumers will purchase both types of media in order to maximize their utility for unbiased media.

This model would also imply that given a biased media environment (as so many scholars contend) those that want to find the truth can do so with more, not less, efficiency. Thus,  my “unbiased” media actor assumption may not be so problematic if we look at the ability of truth-seeking consumers to gather unbiased data in the context of the authors’ model.

We can also look at my assumption another way. Instead of Nature reporting a noisy signal to the Media who faithfully reports that signal with accuracy $\alpha \in [0.5,1]$, we can think of the Media as being predictably biased with the same parameter $\alpha \in [0.5,1]$. Either way the math is the same. Nevertheless, given the discussion in this blog post, the reality may very well be that “truth-seeking” consumers can use multiple media outlets to gather an unbiased signal from the “mass media” writ large.

References

Xiang, Yi and Miklos Sarvary. (September-October, 2007). “News Consumption and Media Bias.” Marketing Science. Vol. 26, No. 5: pp. 611-628.

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16
Mar

LaTeX Math WordPress Plugin: Jetpack vs. Simple Mathjax

Jetpack LaTex vs. Simple-Mathjax

I just recently discovered the Simple Mathjax plugin. I was suggesting to someone that they could use HTML code to embed math into their blogger blogs using the HTML editor and Peter Krautzberger (one of the developers of the Simple Mathjax plugin for WordPress) suggested this plugin for WordPress (Mathjax also has a plugin for Blogger and others). I figured I would give it a try and let those interested see the Jetpack and Mathjax presentation side-by-side.

This is the in-line math code for a basic multiple regression equation with JetPack: \hat{Y} = \alpha + \hat{\beta}_{1} x_{1} + \hat{\beta}_{2} x_{2} + \hat{\beta}_{3} x_{3} ... \hat{\beta}_{n} x_{n} + \epsilon . The Jetpack font is darker and I think slightly larger than my blog’s default font.

This is the in-line math code for a basic multiple regression equation with MathJax: $\hat{Y} = \alpha + \hat{\beta}_{1} x_{1} + \hat{\beta}_{2} x_{2} + \hat{\beta}_{3} x_{3} … \hat{\beta}_{n} x_{n} + \epsilon$. It is clear that the MathJax presentation looks more like my blog’s default font – which is really nice. The Mathjax presentation does not increase the horizontal space between lines either.

Mathjax also has this nice equation feature which automatically centers the equation and places it on the next line: $$\hat{Y} = \alpha + \hat{\beta}_{1} x_{1} + \hat{\beta}_{2} x_{2} + \hat{\beta}_{3} x_{3} … \hat{\beta}_{n} x_{n} + \epsilon$$

However, from this test they look very similar. Let’s look at some other examples. How about, $\frac{1}{2}$ vs. \frac{1}{2} . The first fraction is the MathJax presentation, while the second is the Jetpack presentation. It is clear, the MathJax is nicer and does not look out of place like the Jetpack presentation.

It seems like MathJax has a more fluid feel when using it in-line. For example, here is the The Cauchy-Schwarz Inequality (sample code I was able to pull right from the Mathjax website) written in-line with Jetpack: \left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right).

Here is the same inequality written in-line with MathJax: $\left( \sum_{k=1}^n a_k b_k \right)^2 \leq \left( \sum_{k=1}^n a_k^2 \right) \left( \sum_{k=1}^n b_k^2 \right)$. Again, I think that MathJax just looks nicer and fits better with my blog’s default .CSS.

This is true especially when I write an inequality within a paragraph. Here the Paradox of Voting inequality: $(p_{i})\beta_{i} \geq c_{i}$. Look how nicely the text and the math just flow together seamlessly. When I do the same thing with Jetpack (p_{i})\beta_{i} \geq c_{i} the .PNG images look out of place and forced.

Here is a proposition from a pooling EQ from one of my recent posts: \exists a pooling equilibrium where the true value of \omega = \underline{\omega}; \xi\leq 0; O signals \rho=c regardless of \omega; M mistakenly reports s=h; and E elects O with the belief q_{h} \geq \hat{q}, where \frac{-(\underline{\omega} + \xi)}{\overline{\omega} - \underline{\omega}} \equiv \hat{q^{e}}.

Here is that same proposition with Mathjax: $\exists$ a pooling equilibrium where the true value of $\omega = \underline{\omega}$; $\xi\leq 0$; O signals $\rho=c$ regardless of \omega; M mistakenly reports $s=h$; and E elects O with the belief $q_{h} \geq \hat{q}$, where $\frac{-(\underline{\omega} + \xi)}{\overline{\omega} – \underline{\omega}} \equiv \hat{q^{e}}$.

What a difference! The second proposition looks much nicer and flows with the text, rather than standing out. I am really impressed with this plugin, which works not only with WordPress but Blogger as well. Thanks to Peter Krautzberger for telling me about it. It is definitely superior to the Jetpack $\LaTeX$ plugin.

The only thing I have noticed is that the page takes a little longer to load – but not too much longer. In the end, I think I am sold on the Simple Mathjax plugin.

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Posted in LaTeX, Uncategorized | 1 Comment
28
Feb

Link Between Wealth and Homo Economicus Behavior?

Do individuals who earn higher income behave more like John Stewart Mill’s Economic Man? In other words, does wealth increase the likelihood of greedy predispositions and thus increased “unethical behavior”? New research published in the early edition of  the Proceedings of the National Academy of Sciences seems to suggest this very result.

Researchers from the the University of California, Berkeley and Rotman School of Management, University of Toronto have conducted a series of studies (several of the them experimental) which suggest that wealthier people participate in more unethical behaviors; specifically because they view greed in a more positive light.

In the first two studies Piff et. al. (2012) literally observe whether vehicles cut-off other vehicles at a four way intersection. Research assistants coded the age, make, and model of the vehicles in each case to index social class (with the assumption that more expensive cars indicate higher social status. They also looked at whether cars would cut-off crossing (confederate) pedestrians. Both behaviors defy California Vehicle Code. They find that people driving cars associated with higher socioeconomic status (SES) were (statistically) significantly more likely to participate in both “unethical behaviors”. OK, not convinced?

In the third study participants reported their SES and other demographic information. Participants then read eight stories about actors “unrightfully” benefiting or taking something and then asks respondents if they would be likely to participate in the same behavior. One again, individuals with higher SES were more likely to say they would participate in the same behaviors (the behaviors were not reported but I can only assume they involved monetary benefits of some sort).

The fourth experiment is the best. Essentially, “Participants experienced either a low or high relative social-class rank by comparing themselves to people with the most (least) money, most (least) education, and most (least) respected jobs… This induction primes subjective perceptions of relatively high or low social-class rank” (Piff et. al. 2012, p. 2). This process activated social-class mindsets in the participants. The researchers then presented the participants with a bowl of candy and told them it was for children in the study in the next room, but they could have some if they wanted. The number of pieces of candy was then self-reported by the participants after a series of mock tasks unrelated to the experiment. Yep, you guessed it, people with a higher SES mindset took more candy from children – what is more unethical than that! Again, the candy can be looked at as something of monetary value or material benefit.

Study five linked positive attitudes toward greed to unethical behavior. Participants not only reported their SES but also took a survey which gauged the extent to which they believed it is justified and moral to be greedy. Participants were then placed in the position of bargaining over salary with an employee seeking “long-term” employment at their organization. However, the participants had a vital piece of information, the job position was only “short-term”. Would the participants tell the applicant? Once again, those of higher SES status were less likely to tell the applicant. But there is a twist, once “greed” was taken into account SES was no longer a statistically significant predictor of telling the applicant about the short-term position. Thus, the researchers conclude that it is actually one’s predisposition toward greed that accounts for “unethical” behavior and predisposition toward greed tends to be highly correlated with wealth. Negotiating over salary for a long-term position vs. a short-term position is very different and the private information can be a valuable during the negotiation. Again this relates to monetary value.

In study six, participants were told to roll a fair die (on a computer simulation) several times and then report the total number of points from all rolls. They were told that higher rolls would give them a higher chance of “winning” money. The participants didn’t know that the simulation was rigged and capped at 12 total points every time. Those with higher predispositions toward greed were more likely to lie and say their total was higher than 12 – again without the greed measure in the regression SES was significant, but once the greed measure was included SES no longer mattered. This was blatant monetary incentive.

In the final study, the researchers primed participants of both high and low SES to be greedy. They asked participants three things about their day (which was the neutral group) or three benefits of greed (the treatment group). After the prime, the researchers measured attitudes toward greed. Again SES was reported as well. The researchers then asked questions which gauged their propensity toward greed (i.e. stealing cash, receiving bribes, or overcharging customers). They found that those that were primed to be greedy were more likely to participate in unethical behavior. In fact,

“lower-class individuals were as unethical as upper-class individuals when instructed to think of greed’s benefits, suggesting that upper- and lower-class individuals do not necessarily differ in terms of their capacity for unethical behavior but rather in terms of their default tendencies toward it” (Piff et. al. 2012, p. 3).

Once again, the “unethical behaviors” were in relation to greater monetary incentives.

This study has garnered a lot of press today and has been interpreted broadly with what I would call normative  biases (i.e. see I told you rich people were evil). A lot of people including the researchers have used the 2008 crisis as anecdotal evidence of wealthy people partaking in unethical behavior. The researchers also remind us that, “Religious teachings extol the the poor and admonish the rich with claims like, ‘It will be hard for a rich person to enter the kingdom of heaven’”.

However, I think it is important to note that the study demonstrates evidence that greed is linked with unethical behavior – not necessarily wealth. It may very well be that higher SES is correlated with greed, but we don’t know whether a default predisposition toward greed leads to greater wealth over one’s lifetime rather than increased wealth leading to greed. In fact, I think the former is more compelling that the latter. After all, we do live in a capitalist economy where greed tends to be rewarded.

What I find strange is the title of the piece, “Higher Social Class Predicts Increased Unethical Behavior”. This is not what the study finds, however. It is clear that the researchers find that “greed” trumps SES – as people with lower SES are just as likely to participate in unethical behavior when primed to believe that “greed is good”. Moreover, outside of the vehicle behavior studies, the research seems to equate wealth seeking behavior with unethical behavior.

After all, Homo Economicus, according to Mill, “is concerned with him [man] solely as a being who desires to possess wealth, and who is capable of judging the comparative efficacy of means for obtaining that end.”

References

Mill, John Stuart. (1836) “On the Definition of Political Economy, and on the Method of Investigation Proper to It.” London and Westminster Review.

Piff, Paul K., Daniel M. Stancato, Stéphane Côté, Rodolfo Mendoza-Denton, and Dacher Keltner. (2012). “Higher Social Class Predicts Increased Unethical Behavior”. PNAS (Early Edition).

 

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27
Feb

Prolonging Defeat (Wartime Elections)

Yesterday there was an interesting blog post by Phil Arena discussing how the costs of war are distributed within democracies. The idea behind distributing the costs of war is that,

“By shielding the average voter from the worst of war’s ravages, which they can do through a variety of strategies, not the least of which is avoiding conscription, leaders of democracies may be slip loose of the constraint electoral accountability supposedly provides.”

Phil cites Johnathan Caverley’s work which argues that during wartime states can shift the burden of war onto higher income citizens. He then extends this argument for the case of Vietnam and suggests that the U.S. not only shifted the burden from the costs of war onto higher income citizens, but also onto lower income citizens as well – creating a broad base of support from the middle class. He uses the 1972 ANES to look at the relationship between income and responding that the US should have stayed out of Vietnam, controlling for Party ID. He uses a quadratic fit and finds that,

“at least in 1972, respondents from both high income and (especially) low income households were more inclined to say that the US should have stayed out of Vietnam than were middle income voters… This suggests that democracies can potentially build a broad base of support for war among the middle class. If the human costs of war fall disproportionately on the lower class and the financial costs of war fall disproportionately on the upper class, the median voter may well indeed feel that war is cheap.”

This argument is interesting given the amount of scholarship which (in some form or another) argues that as the cost of war increases the public’s attitude toward war inevitably sours. But if the costs of war can be distributed unevenly away from the Median Voter (Middle Class), what causes their beliefs (positive or negative) about the current war? In my own research I am looking at this very question.

In a previous post I laid out a signalling game which modeled the public’s decision to keep the Incumbent (and thus continue the ongoing war) based on two distinct signals: (1) From the Media, which is potentially inaccurate but unbiased and (2) The Opposition Party, which knows the true state of the war, is biased in favor of getting elected, but also cares about the national interests. The Electorate also cares about other issues besides the war (such as the economy) which is a parameter that is know by all actors. I demonstrated that a semi-separating equilibrium exists where the war is worth continuing, the Media correctly reports that the war is worth fighting, the Opposition Party signals that they will end the war if elected, and the Electorate elects the Opposition effectively ending a war that was worth continuing. Thus, the democratic process causes the Electorate to end a war worth fighting.

In this post I want to articulate another (even more tragic) circumstance where the Democratic Process induces an unfortunate outcome. I am not going to reiterate the model here, but you can see all the details here.

Proposition

\exists a pooling equilibrium where the true value of \omega = \underline{\omega}; \xi\leq 0; O signals \rho=c regardless of \omega; M mistakenly reports s=h; and E elects O with the belief q_{h} \geq \hat{q}, where \frac{-(\underline{\omega} + \xi)}{\overline{\omega} - \underline{\omega}} \equiv \hat{q^{e}}

In words, this says there can be instances where the true state of the war is not worth fighting, the Media incorrectly reports that that the war is worth fighting, the Electorate favors the Opposition on issues other than the war, the Opposition Party signals that the war is worth continuing regardless of the the true state of the war, the Electorate believes the war is worth fighting and votes  for the Opposition Party, which then continues a war which is actually not worth fighting.

This occurs because of the Opposition’s desire to get elected. E will elect elect I when O sends signal \rho = c iff: q_{h}^{c} (\overline{\omega} + \xi) + (1-q_{h}^{c}) (\underline{\omega} + \xi) \geq q_{h}^{c}(\overline{\omega}) + (1 - q_{h}^{c})(\underline{\omega}) \Rightarrow \xi \geq 0. In other words, E elects I if they favor them on issues other than the war when the Opposition signals the war should continue. This is untrue by definition. However, what if the Opposition signaled to end the war?  E will elect I when O sends signal \rho = e iff: q_{h}^{e}(\overline{\omega} + \xi) + (1- q_{h}^{e})(\underline{\omega} + \xi) \geq 0 \Rightarrow q_{h} \geq \hat{q^{e}}, which we have assumed to be true. Thus, because the Electorate believes the war to be worth fighting, they will elect the Incumbent when the Opposition signals to end the war. Thus, the Opposition – in order to get elected – signals they will continue a war that they know isn’t worth fighting! For good measure we can see that  O will abide by the stipulated strategy iff: \beta+(\omega \iota) \geq \omega \iota \Rightarrow \beta \geq 0. This will be true for any value of \omega and \iota. Again, see the previous post for to understand the parameters of the model.

The beliefs the Electorate must hold for this equilibrium are their beliefs prior to seeing the Opposition’s signal but after they have seen the Media’s signal or,

q_{h} = Pr(\omega = \overline{\omega} | s = h) = \frac{\alpha q}{\alpha q + (1 - \alpha) (1-q)}

q_{l} = Pr(\omega = \overline{\omega} | s = l) = \frac{(1 - \alpha)q}{(1 - \alpha) q + \alpha (1-q)}

Discussion

The above equilibrium demonstrates a tragic outcome where a war that is not worth fighting is continued by the next administration. The costs of war will continue to mount and the public will support the war because they believe their side is winning. This instance is interesting in the context of research by Gelpi, Feaver, and Reifler which have have shown evidence for the hypothesis that while the public is adverse to casualties, the tolerance for the human costs of war are shaped by two attitudes: (1) Whether the war justified and (2) Whether the war is likely to be a success – the later being more important than the former. In this case the public is led to believe that the war is likely to be a success, when in reality defeat may be imminent. What causes this? Again, it is the democratic process, specifically the Opposition Party’s desire to get elected.

I am not arguing that the costs of war are unimportant. However, I am arguing that there is more to the story – specifically the way the pubic forms their beliefs based on elite cues. The “reality” the public sees may be a function of the democratic process and not “reality” at all.

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Posted in Formal Modeling, International Relations, My Dissertation | 1 Comment
13
Feb

Wartime Elections

Motivation

How does war (or any highly significant policy) affect the electorate’s vote choice? Moreover, how do different signals regarding the state of the war (success or failure) help the electorate to form their belief about the incumbent’s war policy? The political science literature regarding the affect of war on elections has a long history, beginning with John E. Mueller’s famous finding that as (the log of) casualties in war increases, favorable public opinion of the war decreases. Recently, Gelpi, Feaver, and Reifler have hypothesized that while the public is adverse to casualties, the tolerance for the human costs of war are shaped by two attitudes: (1) Whether the war justified and (2) Whether the war is likely to be a success – the later being more important than the former. See their book for the full argument.

We also know that the electorate often formulates their belief by using heuristics (cues) from elite sources. See Popkin’s The Reasoning Voter and Lupia and McCubbins’s The Democratic Dilemma (the latter uses a formal modeling and experimental approach). We also know from Zaller’s The Nature and Origins of Mass Opinions that public opinion is heavily influenced by elite discourse; however, for Zaller’s theory, elite cues are not necessarily differentiated (i.e. the effect of cues from the media, incumbent, and opposition party on the electorate is not investigated separately). My research is focused on separating multiple (and potentially competing) cues in the belief formation process.

Accurate vs. Biased Signals

I have developed a theory which looks at how different elite cues interact during the electorate’s belief formation about public policies which have especially high significance – with war being my primary focus. My signalling model blends objective but potentially inaccurate cues about the state of a policy (i.e. is the war on track for success or failure?) with biased cues from fully informed actors regarding the continuation of the policy (i.e. should the war be ended or not). The biased actor desires to get elected but also has preferences over the national interest . The noisy but objective signal comes from an actor I am calling the “Media”, while the biased signal comes form the “Opposition Party”.

Now I am sure that some people are already discounting my model because I am assuming that the “Media” is an unbiased actor. I don’t think this assumption is so crazy. I am mealy assuming that the electorate receives some objective (but possibly inaccurate) information from a news source. For example, casualties are reported, battle outcomes are reported, the taking of city is reported, etc. I would consider what some people call “New Media Sources” – which are often highly partisan and biased – to be a part of the actor I am calling the “Opposition Party”. These sources have a biased partisan opinion, but probably want what is best for the U.S.’s national interest as well. Thus, I think the assumptions of my model are reasonable. Even so, assumptions do not have to be perfectly accurate as long they are useful in telling us something interesting about the world. The empirical implications of my model will be judged by my experimental and large-N statistical tests (which I hope to post some info on soon).

The Model

The game begins with Nature (N) selecting the value of continuing the war, \omega . There are two states of the world, \omega = \overline{\omega} and \omega = \underline{\omega} , where \overline{\omega} is the value for a war that is worth continuing and \underline{\omega} is the value for a war which isn’t worth fighting. In the game, q is the probability that \omega = \overline{\omega} > 0, while (1-q) is the probability that \omega = \underline{\omega} < 0.

Next, N sends a noisy signal, s \in \{l,h\}, to the Media (M), about \omega. With probability \alpha \in (0.5,1), M receives an accurate signal and with probability (1-\alpha), M is given an inaccurate signal. Therefore, Pr(s = h | \omega = \overline{\omega}) = Pr (s = l | \omega = \underline{\omega}) = \alpha; in other words, \alpha signifies the probability that the state of the world matches the signal given by M. Also, Pr(s = l | \omega = \overline{\omega}) = Pr(s = h | \omega = \underline{\omega}) = (1-\alpha); thus, (1-\alpha) is the probability of  M being given an inaccurate signal which fails to match the state of the world. This means that, Pr(s = h) = \alpha q + (1- \alpha)(1-q), while Pr(s = l) = \alpha(1-q) + (1- \alpha)q. This implies that Pr(\omega = \overline{\omega} | s = h) and Pr(\omega = \overline{\omega} | s = l) follows from Bayes’ rule:

Pr(\omega = \overline{\omega} | s = h) = \frac{\alpha q}{\alpha q + (1 - \alpha) (1-q)}

and

Pr(\omega = \overline{\omega} | s = l) = \frac{(1 - \alpha)q}{(1 - \alpha) q + \alpha (1-q)}

Upon observing s, the Opposition (O), announces their desire to either continue or end the war, \rho \in \{c,e\}. I assume that \rho predicts what O would do if elected. O is electorally motivated but also values the national interest at a rate of \iota \sim u[0,\overline{\iota}].

In the final move of the game, the Electorate (E) decides whether to retain the incumbent or elect O. When E retains the incumbent, O receives \omega\iota while E receives \omega+\xi, where \xi \in [-1,1] represents the value of the incumbent relative to O with respect to economic or other domestic issues. This term may represent retrospective evaluations, prospective evaluations, differences in policy platforms, or combination thereof. The value of \xi is common knowledge.

If E elects O and O had set \rho=c, O receives \beta \in (0,1), which reflects the benefit of holding office plus \omega \iota , while E receives \omega. If O sets \rho=e, deciding to end the war, O receives \beta and E receives 0.

In the game, I assume that O knows \omega while E does not. However, E knows that O knows the true value of \omega, and may update their prior belief q to q_{s}^{\rho}, which reflects the information revealed by M and the signal given by O. Specifically,

Pr(\omega=\overline{\omega} | s = h, \rho=c) = q_{h}^{c}
Pr(\omega = \overline{\omega} | s = h, \rho = e) = q_{h}^{e}
Pr(\omega = \overline{\omega} | s = l, \rho = c) = q_{l}^{c}
Pr(\omega = \overline{\omega} | s = l, \rho = e) = q_{l}^{e}

There several general equilibria in the game; however I am only focusing on one (which I think is the most interesting) semi-separating equilibrium, which I call Opposing Victory.

Opposing Victory

Proposition

There exists a semi-separating equilibrium where the Opposition party signals they want to end the war (\rho = e) with probability \frac{\beta}{\overline{\iota} \ \overline{\omega}} if \omega = \overline{\omega} and signals that they want to end the war (\rho = e) if the actual state of the war is not worth fighting (\omega = \underline{\omega}). Thus, the Opposition is semi-separating when the true state of the war is worth fighting. Moreover, the Opposition Party’s behavior is irrespective of the signal the Media sends (i.e. s = h or s = l). The Electorate retains the Incumbent iff their belief that the true state of the war is going well (q_{h}^{e} \geq \hat{q^{e}}) when the Media says it is going well (s = h) and the Opposition Party wants to end the war (\rho = e); iff the their belief that the true state of the war is going well (q_{l}^{e} \geq \hat{q^{e}}) when the Media says it is going poorly (s = l) and the Opposition Party wants to end the war (\rho = e); and with certainty if the Opposition Party wants the was to continue (\rho = c), irrespective of the Media’s signal (s).

Because O values the national interest at a rate of \iota \sim U[0, \overline{\iota}], we can find the probability that \iota is above or below \frac{\frac{\beta}{\omega}}{\overline{\iota}}, which is the same as \frac{\beta}{\overline{\iota} \ \overline{\omega}}.

Assuming that O and E abide by the strategies outlined above, then Bayes’ rule tells us that,

Pr(\omega = \overline{\omega} | s = h,\ \rho = c) =

q_{h}^{c} = \frac{q (1 - \frac{\beta}{\overline{\iota} \ \overline{\omega}})(\alpha)}{q (1 - \frac{\beta}{\overline{\iota} \ \overline{\omega}})(\alpha) + 0 (1-q)(1 - \alpha)} \Rightarrow q_{h}^{c} = 1

and

Pr(\omega = \overline{\omega} | s = l,\ \rho = c) =

q_{l}^{c} = \frac{q (1 - \frac{\beta}{\overline{\iota} \ \overline{\omega}})(1 - \alpha)}{q (1 - \frac{\beta}{\overline{\iota} \ \overline{\omega}})(1 - \alpha) + 0 (1-q)(\alpha)} \Rightarrow q_{l}^{c} = 1

and

Pr(\omega = \overline{\omega} | s = h,\ \rho = e) =

q_{h}^{e} = \frac{q \frac{\beta}{\overline{\iota} \ \overline{\omega}}(\alpha)}{q \frac{\beta}{\overline{\iota} \ \overline{\omega}}(\alpha) + 1 (1-q)(1 - \alpha)}

and

Pr(\omega = \overline{\omega} | s = l,\ \rho = e) =

q_{l}^{e} = \frac{q \frac{\beta}{\overline{\iota} \ \overline{\omega}}(1 - \alpha)}{q \frac{\beta}{\overline{\iota} \overline{\omega}}(1 - \alpha) + 1 (1-q) (\alpha)}

Now that we have E’s beliefs we can see if the Opposing Victory equilibrium holds. If \xi > 0 and O advocates for continuing the war, then E always retains the incumbent. If q_{h}^{e} < \hat{q^{e}} and q_{l}^{e} < \hat{q^{e}}, O is willing to play the strategies constructed by the Opposing Victory equilibrium. Provided these inequalities hold, the semi-separating equilibrium is established. O always advocates for ending the war when the war is not worth fighting but can also advocate ending the war when it is worth fighting with probability \frac{\beta}{\overline{\iota} \ \overline{\omega}}; thus, O’s strategy depends on \iota when \omega=\overline{\omega} but not when \omega=\underline{\omega}.

What Does This Tell Us?

This equilibrium suggests that it is possible for the Media to mistakenly report that the war is not worth continuing, the Opposition then advocates ending the war, and the Electorate replaces the incumbent with the Opposition effectively ending the war, even though, in truth, the war was worth continuing.

This equilibrium also suggests that the Media can correctly report that the war is worth continuing, but the Opposition still advocates ending the war  and the Electorate replaces the incumbent with the Opposition, effectively ending the war that, again, would have been worth continuing and M revealed was worth continuing.

Thus, we can get a rather tragic outcome when the Electorate’s belief is conditioned on both signals. Much of this is driven by the Opposition’s value of the national interests vs. the benefits of getting elected. Interestingly, in the initial stages of a war we often see a “rally” effect where the Opposition party backs the Incumbent and we perceive a unified foreign response. However, we also observe that as the war continues, the Opposition party can begin to pull away from the Incumbent’s foreign policy and criticize the Incumbent’s policy. More often than not, the party of the Incumbent is inconsequential to the criticism. In other words, what matters more is not whether the Incumbent is a Democrat or a Republican, but simply that one party is in office while one is out. As already stated most explanations revolve around casualties or citizen beliefs about the success of the war. My explanation demonstrates that, under conditions of competing information, biased signals can be dominant, leading the electorate terminate an other wise successful war. More importantly, what leads to the competing signals and to the tragic outcome is the democratic process – or at least the desire of the Opposition Party to get elected.

Policy Extension

This suggests a rather tragic outcome where biased signals are dominant, whereby the democratic political process and the Opposition Party’s desire to get elected, has them advocate ending a public policy (in this case war) which is actually successful. I believe that this model can be extended to any public policy which carries significant weight with the electorate. For example, in the 2012 presidential election Obama’s healthcare policy is likely to be one of those issues where the opposition party will attack its ability to be successful. The Media in this case will likely report on the achievements (or non-achievements) of the legislation. My model suggests that any policy (which carries significant weight with the electorate) can be terminated based the electorate’s beliefs, even though the policy is objectively successful. Of course I am not saying Obama’s healthcare legislation is successful or not. What I am saying is the democratic process can lead perfectly successful legislation to be terminated because the Opposition Party has an incentive to get in office.

Suggestion are welcome.

 

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3
Feb

The Importance of (Formal) Theory and the Theoretical Consistency Assumption

Hello Again Everyone,

I have just received my copy of A Model Discipline: Political Science and the Logic of Representations by Clarke and Primo. I have not yet begun to read the book; however, the  idea that the emphasis political scientists put on testing (formal) models and the way that practice may distort how we view models has been an interesting recent discussion in political science. I am sure I will have more to say about the topic as I read through the book. Nevertheless, the topic of theories and the empirical evaluation of theories has inspired this post.

I have recently begun putting the finishing touches on my appendix for the first chapter of my dissertation, which I will be presenting at this year’s Midwest Political Science Association (MPSA) conference. As I go through my comparative statics (I hope to present some initial findings here soon) I am also beginning to design the experiment I will use to test the predictions from my formal model. As I went through the process of developing a formal model and thinking about how to test it, I could not help but think about the reasons why a “formal model” is preferable to a non-formal model.

I have heard many scholars argue that theory isn’t as important as the subsequent test. Some have even argued that theory is everywhere and easy to develop (yes I have heard people say this). They argue that the best way to advance the disciplined is with empirical investigation which will reveal whether the evidence corroborates our theory or whether our theory has been falsified and should be discarded. I am sure you have heard someone at some time say, “let the data speak”. If you have read previous posts of mine you probably know that this way of thinking can have severe consequences, especially when our observable data does not take into account strategic behavior, which can be thought of as omitted variable bias.

In this post I want to talk about what Morton and Williams have called the Theoretical Consistency Assumption (TCA) and how it relates to the way we test our theoretical predictions with causal inference as our intention. I have already spoken about the Neyman-Rubin Causal Model (RCM) here, but essentially RCM researchers, when testing non-formal models (and also formal models under most conditions), must assume TCA. Which means that the “assumptions underlying the causal predictions evaluated are consistent with the assumptions that underlie the methods used by the researcher to infer causal relationships” (Morton and Williams, p. 198).

In general, this means that the assumptions used in one’s empirical model (statistical or experimental) used to test the predictions of one’s theoretical model must be consistent with the assumptions that underline the predictions of one’s theory. This would also require that the assumptions of our theory be as explicit as possible. For example, if one uses matching to test the predictions of one’s theory, one is assuming ignorability of the treatment (the method of collecting data, the nature of the missing data, and the nature of unobservables are not systematically dependent on each other; in other words the observations collected  are independent of missing data and unobservables conditional on the observed data). The important take-away is that for TCA to hold the assumptions of the empirical test (functional form,  Gauss–Markov, etc.) must be consistent with the theoretical model. How often do we believe that the assumptions in our empirical investigations are consistent with our theoretical predictions? Naturally, one can see why formal models and experimental analysis has an advantage in this regard.

Of course I am about to advocate what Clarke and Primo’s new book urges us to reconsider. That aside, researchers using formal models can begin with a precise set of assumptions about the data generating process (DGP) (in symbolic mathematical terms) which are solved to derive predictions about the DGP (Morton and Williams, 2010; Morton 1999). Formal models allow for precise predictions about the variables in the model when it is in equilibrium. We can then draw relationship predictions about how two variables in the model are related and causal relationship predictions about how the change in one variable “causes” the changes in the other variables (via comparative statics).

When using observational data, some scholars such as Signorino have argued that scholars should derive statistical estimators from their formal models. Nevertheless, if one has the ability to conduct an experiment they can come as close to TCA as possible. In fact we can design an experiment which allows us to make the assumptions underlying the empirics as equivalent as possible to those of the formal model underlying the predictions. Moreover, one can relax the assumptions in a controlled manner in order to investigate the consequences of relaxing those axioms.

This gives us the ability to conduct what Morton and Williams (2010) call “theory tests” and “stress tests“. Theory tests are when we hold all the assumption in the empirical study as close as possible to those of our formal model. A stress test is when we relax some of the assumptions and allow them to vary in order to see what happens under these conditions (much like a robustness test). Now I have read much of what Clarke and Primo have already written on models and I am anxious to read their new book. I, too, believe that models have more than one use (in fact I have used models for “Foundational”, “Generative”, and other purposes). Nevertheless, I am compelled by the use of models for drawing predictions which are then tested (using experiments or otherwise) with a strong focus on causal inference.

Most importantly, I think that the Theoretical Consistency Assumption is important and often overlooked; especially by those that “let the data speak”. Getting the wrong answer is rather easy with observational data and the neglect of a consistency between theoretical and empirical assumptions. Of course, adhering to TCA is not always possible and can be cumbersome under many conditions and I am not completely dogmatic about it (as in I won’t believe any claim that is not first derived by a formal model and then tested with an empirical model that has consistent assumptions with the theoretical predictions), but I do think it is an important consideration, at least for studies with causal intent (wait… isn’t that a lot of studies… or at least I have read a lot of studies studies that claim causation…?).

Have a great weekend! GO GIANTS!

Best Regards,
Nicholas P. Nicoletti

References

Morton, Rebecca B., and Kenneth C. Williams. (2010). Experimental Political Science and the Study of Causality: From Nature to Lab. New York, NY: Cambridge University Press.

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30
Dec

Should Political Scientist Prescribe Public Policy?

Happy Holidays!

I hope everyone is having a great holiday season and enjoying time with family and friends.

Prescriptive Realism

I just received the December 2011 copy of Perspectives on Politics. As I was flipping through an article immediately caught my eye: “A Realist Foreign Policy for the United States” by Rosato and Schuessler. In this piece the authors set out to. “develop a prescriptive realist theory that tells great powers such as the United States how they should behave if they want to ensure their security” (p. 805).

Daniel Drezner had a post in which he was sympathetic to the argument that political scientists (specifically IR scholars) should play a larger role in (foreign) policy. However, his postulated reason that this doesn’t happen is because the IR policy community fails to reach a consensus on whether political science is valuable (also see here). In fact, he compares the way policy communities view economic and IR theories and methodology and argues that,

“[T]he fundamental difference between economic policy and foreign policy is that the former community accepts the idea that economic methodologies and theory-building enterprises have value, and are worth using as a guide to policymaking. This doesn’t mean economists agree on everything, but it does mean they are all speaking a common language and accept the notion of external validity checks on their arguments”

Drezner’s post was a response to an article written by  James Lee Ray which was also arguing that political scientists require a greater role in foreign policy. Ray argues that had more political scientists been in on the surge decision in Afghanistan the Obama administration would have come to a different conclusion. But the truth is that political scientists did not have a consensus on the effectiveness of the surge either. Speaking about the decision to replicate a “surge” strategy in Afghanistan Drezner writes.

“had Obama consulted more international relations scholars, he would have received perfectly muddled advice… The evidence… relevant to the decision by the Obama Administration about the surge in Afghanistan tends to point in diverse directions. Some of it casts doubt on the prudence of the Obama Administration’s decision to send 30,000 more troops to Afghanistan, while other findings could be used to support that decision.”

These are two great points: (1) Policymakers do not view political science theories and methodology with as much value as they do economics and (2) political science is often divided within its own community on theories, methods, and findings. Moreover, it is also possible that policymakers will simply use whatever political science theories and empirical evidence to simply add credibility to desired policy actions (possible like using democratic peace theory to justify invading Iraq).

The recent PS article is another attempt, from political scientists, to influence or “advise” public policy. The prescription from the authors is to balance against other super powers and strategic (i.e. located in regions with natural resources such as oil) minor powers, while taking a more relaxed view toward minor powers which are not in a strategic region. Minor powers should be contained while the U.S. should build up its military and economic resources to balance against great powers. The scholars sum their argument by quoting Glaser,

“All else being equal, a state is more secure when it possess the military capabilities required to protect its territory from attack. These capabilities could include those required to directly protect the state” (p. 805)

and Mearsheimer

“Balancing also has a crucial signaling component to it… “the balancer draws a line in the sand and warns the aggressor not to cross it” (p. 806).

After laying out their theory (which they acknowledge is basically Waltz’s structural or what is sometimes called modern realism) and the liberal alternative, the authors use a series of important cases and claim that had balancing been used war may not have broken out. These cases include World War I, World War II, Vietnam, and the second Iraq War.

One criticism of the piece is that the authors tend to conflate liberalism (democratic peace, economic interdependence) with neo-liberal institutionalism; when describing “liberal” theories they do state that there are many variants , but when comparing realism and liberalism in regards to the cases they are much less careful. These theories are based on different levels of analysis and make different assumptions and thus should be compared separately to realism. This point is a minor one. My real concern is that this policy perception fails to take into account new research, specifically from the bargaining literature.

Balancing, Bargaining, and Information

Since Fearon (1995) scholars have understood the importance of information. Reed (2003) formalized the logic of both balance of power and power transition theory. The former argues that when states are at power parity war is least likely (which is what the above prescriptive realism relies on) and the later argues that when one state has a preponderance of power war is least likely. Reed’s formal analysis is based on the ultimatum bargaining game where the challenger is uncertain about the defender’s reservation value for war. The theoretical analysis demonstrated that when states approached power parity, uncertainty was at its greatest, and the probability of conflict was at its highest. The empirical analysis which followed corroborated the theoretical implications.

The theoretical conclusions logically followed from similar assumptions which  Rosato and Schuessler claim to rely on when developing their prescriptive realism:

“We begin with three core assumptions. First, the international system is anarchic – there is no government above states to enforce agreements among them or to protect them form one another. Second, states cannot know the present and, especially, the future intentions of others. Third, interstate war is an unpredictable enterprise with potentially devastating consequences” (pp. 804-805).

Those familiar with the ultimatum bargaining game will see the similarities. The game is non-cooperative (anarchic); the challenger does not know the reservation value of the outside option – war- of the defender (uncertain intentions over the value of war and peace); and war is represented as a costly lottery (war is an unpredictable enterprise with potentially devastating consequent). Another assumption in the bargaining game is that the good in dispute (territory, policy, etc.) is divisible. Thus, the logically consistent conclusion which follows from these assumptions is that parity is associated with an increased risk of conflict. Thus, it would seem to be that advocating “balancing” as a prescriptive foreign policy may be a little premature.

Recent research by Reed et. al. (2008) also suggests that the effect of power on war may depend on the distribution of benefits within the international system. Essentially, when the distribution of power is equal to the distribution of benefits the probability of war will be at its lowest. Reed et. al. (2008) presents an interesting test of this theory which is formally derived from the work of Powell (1999). Again, balancing may not be be effective in situations where states that are rapidly growing in power are also failing to receive an increased distribution of benefits. These are two (of what I think are some of the best) examples of recent research which directly looks at the balance of power, power transition, and the distribution of power relative to the distribution of benefits in a bargaining context.

I am in no way claiming that we have a perfect understanding of power, information, and the probability of war. However, I do think that recent research has presented some problems with balance of power theory (and the prescriptive policy of balancing). It seems logical to conclude that if power balances have a higher probability of war, a foreign policy of super power (internal or external) balancing  would lead to similar conclusions. Moreover, if realism is supposed to be a descriptive theory, then why do we need to prescribe anything to foreign policy actors. Of course theories in the social sciences are probabilistic and I do not expect actors to always act in the ways a theory describes. However, the “way the world actually works” and “outcomes that are preferable by policymakers” are not always the same thing. Nevertheless, it seems to me that research suggests that balancing isn’t associated with greater peace and thus may not be the “correct” foreign policy to prescribe to policymakers.

This brings me to the final part of this rather long blog post: Should Political Scientists be in the business of prescribing public policy?

Prescriptive Theory and Public Policy?

First, I would like to note that I do believe that a lot of political science is policy relevant (see Bennett and Ikenberry (2006) for a discussion of the APSR’s relevance for U.S. foreign policy since 1906) . What I do not necessarily think is that political scientists should be trying to actively participate in policy debates under the premise that they know the correct policy action.

Rosato and Schuessler seem to think that political scientists as a community are biased against policy relevant work and have “retreated to an ivory tower”. Rosato and Schuessler argue that policy makers use “theory” when they make policy even if it is an unconscious effort, so political scientists might as well shed some light on which theories are more useful.*

Thus, given that theory can be useful, should political scientists participate in policy debates (see Farr et. al. (2006) for a discussion of Lasswell’s “Policy Scientist of Democracy”)?  Before asking ourselves this question we should ask ourselves what criteria we should use to designate a theory good enough to be advocated to policymakers. Rosato and Schuessler state that political scientists are in the best position to give advise to policy makers as scholars because, “they must be attentive to logic and evidence”. They go on to say that scholars that want to give good prescriptive theory should complete two tasks:

“First we must take a handful of plausible assumptions and logically deduce a set of foreign policy prescriptions. Second, we must show – through a detailed examination of the historical record – that had states adhered to these prescriptions, they would likely have enhances their security without going to war, and conversely, that their embrace of alternative theories of action led them down the path to war” (p. 804).

As I have already outlined, others, using bargaining theory, have logically deduced conclusions from a set of plausible assumptions and come to different conclusions than the authors. These same scholars have also examined the historical record with the same outcome.

Nevertheless, if we argue that these are the criteria for good prescriptive theory we should also consider how confident we are in our empirical work.  As some of my previous posts have discussed observational data (and even poorly designed experiments) can give us the wrong conclusions (let alone counterfactual reasoning based on what states should have done and what outcome could have arisen given alternative actions). I am not saying that political science cannot be policy relevant – it can. What I am saying is that as a scientific enterprise we do not need to be policy relevant nor should that be our aim. In fact, political scientists (in foreign policy especially) – let alone the policy community – have not formed a consensus on which theories or methodologies have value. There are competing theories and even if these theories are presented to policymakers they would still have to decide which one to use when addressing a given situation. This also means that the people which surround a given policymaker will be able to filter the information that these people view (not to mention the intentions of policy entrepreneurs). Those in the policy world may not be so interested in the insights of political science as much as the “credibility” that it may bring to already concocted policies (see this post by Erik Gartzke from Daniel Drezner for more details on this and other views).

I study the policy process and I want to understand why policymakers do the things they do. I want to increase our understanding of the world via positive research. I also think there is a place for policy analysis and an objective look at specific public policies. Yet it is up to policymakers (and those that surround them) to decide whether research is policy relevant . But don’t be surprised if policymakers pick and choose which theory is relevant based on which policy track they are already on. Also, I am not so sure that political scientists should be so quick to think that they have the policy answers to political problems.

 Notes

* I would agree but refine the argument slightly. Policy makers have a tendency to use simplified heuristics when deciding which policy to choose; instead of well thought-out theorizing, officials often make comparisons between the status quo policy and some change which alters the status quo only slightly or has already been proven to work in past circumstances (much like Lindblom’s incrementalism).

References

Bennett, Andrew and G. John Ikenberry. (2006). “The Review’s Evolving Relevance for U.S. Foreign Policy 1906-2006.” The American Political Science Review 100(4):  651-658.

Farr, James , Jacob S. Hacker, and Nicole Kazee. (2006). “The Policy Scientist of Democracy: The Discipline of Harold D. Lasswell.” The American Political Science Review 100(4): 579-587.

Powell, Robert. 1999. In the Shadow of Power: States and Strategies
in International Politics. Princeton, NJ: Princeton University
Press.

Reed, William. (2003). “Information, Power, and War.” The American Political Science Review 97(4): 663-641.

Reed, William, David H. Clark, Timothy Nordstrom, and Wonjae Hwang. (2008). “War, Power, and Bargaining.” Journal of Politics (4): 1203-1216.

Rosato, Sebastian, and John Schuessler. (2011). “A Realist Foreign Policy for the United States.” Perspectives of Politics 9(4): 803-817.

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A Quick Note: The current hosting provider for my website (which is a pretty big name in the industry) has informed me that the server on which my WordPress database is located is having some kind of problem. Thus, if my website or blog gives you an error this is the cause. It is currently being resolved…

Best,
Nick

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Posted on December 16, 2011 | Leave a comment