The Capitalist Peace: Why a Capitalist World Means a World At Peace

[BrentWil]

54. This is what he uses and the rational

I bolded the parts that directly tell the reader what he used.


Democracy: Democracy: Researchers differ over how to measure democracy, both monadically and dyadically. I rely on three different datasets and three variable construc- tions to represent dyadic democracy. The standard in democratic peace research is the Gurr Polity IV data (Jaggers and Gurr 1995). I first prepared monadic val- ues by combining Polity democracy (DEMOC) and au- tocracy (AUTOC) scales as follows: [(DEMOCi – AUTOCi ) + 10]/2, (where i ∈ [A,B]). The variable differs mod- estly from Oneal and Russett in that I add 10 so that all values are nonnegative and divide by 2 to yield the 0–10 range of Polity variables. DEMOCRACY (LOW) and DEMOCRACY (HIGH), respectively, report the lower and higher of democracy values in the dyad. DEMOC- RACY A×B is the product of monadic values. BOTH DEMOC. (≥7) equals one (“1”) if each dyad member has a monadic score of at least seven and zero (“0”) otherwise.


Markets: Democratic peace research examines trade interdependence (Oneal et al. 1996, 2003; Oneal and Russett 1997, 1999a, 1999b, 1999c; Russett and Oneal 2001). Capital and monetary integration may be more relevant to conflict than trade (Gartzke and Li 2003; Gartzke, Li, and Boehmer 2001). Liberalization cre- ates valuable linkages and institutional constraints on a state’s ability to intervene in market processes. Be- cause states may be tempted to interfere with market responses to interstate crises, both robust markets and laissez-faire policies matter.
The International Monetary Fund (IMF) pro- vides several indicators of market size, robustness, and liberalization. The IMF publication Annual Reports on Exchange Arrangements and Exchange Restrictions (AREAER) lists a series of variables measuring eco- nomic openness. I use an index evaluated in previous studies that takes the difference between eight and the sum of eight types of government restrictions on for- eign exchange, current, and capital accounts (Gartzke and Li 2003; Gartzke, Li, and Boehmer 2001). IMF FIN. OPEN. (LOW) reports the lower monadic score in the dyad.40 High values of IMF FIN. OPEN. (LOW) are thus expected to reduce the likelihood of militarized dis- putes. The IMF only reports data on member countries, systematically reducing variance and biasing against statistical significance.
I also include indicators of trade to assess whether trade influences militarized disputes independent of capital liberalization. I use both the trade data pro- vided by Oneal and Russett, and data from Gleditsch (2002).41 Again, I follow the Oneal and Russett op- erationalization. Monadic values are first constructed using a ratio of bilateral trade over GDP to measure the importance of trade relative to a state’s total economy. TRADE DEP. (LOW) denotes the lower trade dependence statistic in the dyad (Bliss and Russett 1998; Oneal and Russett 1997, 1999a, 1999b). Trade interdependence is expected to modestly decrease MID propensity.

Development:Economic development leads to a secular decline in the valuation of conquerable resources while intellectual and financial capital critical to productiv- ity in modern economies must be enticed rather than coerced. Conversely, wealth and the technology effect allow for greater power projection. Poor countries sel- dom fight abroad because they cannot, and becausetheir governments are preoccupied with existing terri- tory. Development brings with it the ability to project power, encouraging contests over both policy and re- sources, while the richest states lose much of their will- ingness to steal resources associated with territory.
Early quantitative studies of the democratic peace included GDP/pop (the consensus measure of develop- ment), but the variable was not found to be significant (Maoz and Russett 1992). I argue that per capita GDP has contrasting effects on disputes. Gartzke and Rohner (2006b) examine this argument directly by splitting the sample of disputes between territorial and nonterrito- rial conflicts, and by looking at initiators and targets. Here, however, I need to adhere to an established re- search design. To parse out the contrasting effects of development on war and peace, I include two variables. GDPPC (LOW) measures the lower of the two monadic population weighted gross domestic product statistics for a given dyad (Gleditsch 2002). I also examine the natural log of GDPPC (LOW) to limit multicollinearity among variables.42 A second variable isolates the effect of wealth on likely subjects of territorial aggression. GDPPC × CONTIG (LOW) interacts contiguity and the development variable. It is most likely that a decline in the value of conquest will manifest itself in relations with neighbors, where territorial claims are most com- mon and aggression most practical.43

Interest Similarity: Many students of international re- lations reject as excessively narrow the realist empha- sis on uniform, monolithic interests and argue instead that state objectives vary with a complex variety of factors (cf. Moravcsik 1997). Relations between the United States and Israel, and between the United States and India have been quite different in the post–World War II period, even accounting for capabilities, geog- raphy, regime type, and so on. National interests also change over time; elections in Bolivia and Germany re- sulted in two very different leaders, one who is moving her country closer to the United States, and one who is moving farther away.
Ideally, researchers in international relations would possess a model of state interests that would estimate the effects of a number of relevant causal variables. The same could be said for democracy, however, and for measures of national capabilities, economic devel- opment, alliance ties, and so on. There exists no consen-us theory of national preferences, nor is one likely to be constructed in a reasonable time. Empirical research on conflict must thus choose between measuring inter- ests imperfectly, and not measuring them at all. I have chosen the former, while being mindful of the many potential pitfalls involved in this approach. The argu- ment supplied here is consistent with other research in arguing that variable state interests are an impor- tant indicator of foreign policy behavior (cf. Bueno de Mesquita 1981; Voeten 2000). If we cannot know the myriad causes of preferences, we can at least go some way in measuring their manifestation and their effects.
Measuring interests provides a number of empiri- cal challenges. Preferences are not directly observable, so one must identify conditions that appear to reflect state preferences. Using data on United Nations Gen- eral Assembly voting available for the period covered by the Oneal and Russett (1999a) data (1946–96), I construct an AFFINITY index. Data on “revealed” pref- erences are an imperfect representation of an actor’s real ranking over outcomes. Still, UN voting arguably distorts preferences less than available alternatives such as alliance portfolios (Gartzke 1998, 2000). I examine other indicators in the appendix (I also use the residuals of AFFINITY as a proxy, after regressing the interest vari- able on democracy and other variables, and show that the residuals have similar effects). The Affinity index reports the similarity of dyadic UN voting patterns, us- ing the “S” coding (Signorino and Ritter 2001). Values range between one, “most similar,” and negative one, “least similar.” I expect a threshold effect of interests. AFFINITY should be negatively associated with disputes, with the more dissimilar values (closer to −1) being disproportionately likely to fight.44