Dan Miodownik (2006)
Cultural Differences and Economic Incentives: an Agent-Based Study of Their Impact on the Emergence of Regional Autonomy Movements
Journal of Artificial Societies and Social Simulation
vol. 9, no. 4
<https://www.jasss.org/9/4/2.html>
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Received: 29-Nov-2005 Accepted: 18-Jul-2006 Published: 31-Oct-2006
Hypothesis 1: Cultural differences between regions and states increase the likelihood of the appearance of regional autonomy movements. Cultural differences, however, are not a necessary condition for the emergence of regional autonomy movements.
Hypothesis 2: Strong economic incentives increase the likelihood of the appearance of regional autonomy movements.
Hypothesis 3: Cultural differences strongly increase the likelihood of regional autonomy mobilization where economic incentives are weak yet only moderately increase the likelihood of the emergence of autonomy movements where economic incentives are strong.
Hypothesis 4: Economic incentives strongly increase the likelihood of the appearance of regional autonomy movements where cultural differences are weak, and moderately increase the likelihood of the emergence of autonomy demands where cultural differences are strong.
Figure 1. A typical configuration of Ethniland at t=0 a |
Figure 2. The National Bureaucracy or Authority Structure |
Figure 3. Regional identities and authority structure |
Figure 4. State bureaucracy and regional identities in the southeast region |
Figure 5. A run with low minority support, and clustering and no political boundaries (run 1) |
Figure 6. A run with large minority support, strong clustering and political boundaries (run 38) |
Figure 7. Diffusion and decline of minority support (runs 1 vs. 38) |
Table 1: Statistical models of Minority Support, Minority Clustering, and Political Boundaries | ||||||
Model 1 (OLS) Regional Minority Support (t=end) | Model 2 (OLS) Regional Minority Clustering (t=end) | Model 3 (Logit) Political Boundaries (t=end) | ||||
(A) | (B) | (A) | (B) | (A) | (B) | |
B (S.E.) | B (S.E.) | B (S.E.) | B (S.E.) | B (S.E.) | B (S.E.) | |
Cultural Differences | .40* (.04) | .40* (.02) | -.16 (.06) | -.15* (.03) | .008* (.001) | .008* (.001) |
Economic Incentives | .17 (.14) | .14* (.04) | -1.28* (.22) | -1.17* (.04) | .021* (.003) | .021* (.003) |
Cultural Differences* Economic Incentives | -6.07×10(-5) (.00) | 8.30×10(-5) (.00) | -2.3×10(-5) * (.0000) | -2.3×10(-5) * (.0000) | ||
Regional Leadership | .62 (.78) | -4.31* (1.21) | -4.73* (1.21) | -.022 (.015) | ||
State's Bureaucracy | -.26 (.26) | -.97 (.41) | -.002 (.005) | |||
Regional ID Support | 2.19* (.29) | 2.45* (.20) | 2.16* (.45) | 2.21* (.45) | .023* (.006) | .03* (.004) |
Regional ID Clustering | .04 (.04) | .20* (.06) | .21* (.06) | .001 (.001) | ||
Time | .14* (.03) | .14* (.03) | -.18* (.05) | -.18* (.05) | .003* (.001) | |
BC transformation Probability | -5.5 X 10(-5) (.000) | |||||
Constant | -258.15* (36.41) | -255.83* (23.74) | 484.90* (56.43) | 416.12* (43.06) | -10.08* (.79) | -9.92* (.65) |
F | 70.48 | 140.37 | 140.72 | 186.54 | ||
R2 | .10 | .10 | .18 | .18 | ||
Χ2 | 542.10 | 536.56 | ||||
Log-likelihood | 2405.85 | 2408.63 | ||||
Predicted correctly | 76.7% | 76.7% | ||||
Figure 8. Effect of cultural differences on political boundaries by economic incentives |
Figure 9. Effect of economic incentives on political boundaries by cultural differences |
Region | Agent class | Repertoire | Influence | Percent |
Northwest | Regime Bureaucrats | {[Regime]} | 4 | 0.4 |
Regime Bureaucrats | {[Regime], Other} | 2, 3 | 8.5 | |
Regime supporters | {[Regime], Other} | 1 | 52.9 | |
Other agents | {Regime, [Other]} | 1 | 38.2 | |
Northeast | Regime Bureaucrats | {[Regime]} | 4 | 0.4 |
Regime Bureaucrats | {[Regime], Regional, Other} | 2, 3 | 6.1 | |
Regime supporters | {[Regime], Regional, Other} | 1 | 31.7 | |
Regional authority structure | {Regime, [Regional]} | 4 | 0.1 | |
Regional authority structure | {Regime, [Regional], Other} | 2, 3 | 2.1 | |
Regional agents | {Regime, [Regional], Other} | 1 | 35.8 | |
Other agents | {Regime, Regional, [Other]} | 1 | 23.8 | |
Southwest | Regime Bureaucrats | {[Regime], Regional} | 4 | 0.4 |
Regime Bureaucrats | {[Regime], Regional, Other} | 2, 3 | 6.3 | |
Regime supporters | {[Regime], Regional, Other} | 1 | 27.4 | |
Regional authority structure | {Regime, [Regional]} | 4 | 0 | |
Regional authority structure | {Regime, [Regional], Other} | 2, 3 | 1.7 | |
Regional agents | {Regime, [Regional], Other} | 1 | 39.9 | |
Other agents | {Regime, Regional, [Other]} | 1 | 24.3 | |
Southeast | Regime Bureaucrats | {[Regime]} | 2,3,4 | 6.0 |
Regime supporters | {[Regime], 16, 10, Other} | 1 | 11.0 | |
Regional Entrepreneurs | {[10], Other} | 2,3,4 | 1.0 | |
Regional agents | {Regime, [10], Other} | 1 | 9.1 | |
Regional agents | {Regime, [16], Other} | 1 | 12.6 | |
Other agents | {Regime, 10, 16 [Other]} | 1 | 61.2 | |
[ ] Active identity; {} identities in repertoire. | ||||
(1) |
In addition to calculating the relative weight of each identity in its neighborhood, agents must also identify candidate identities that could be discarded, rotated, swapped out, or acquired. A discard candidate is the identity with the smallest count in an agent's repertoire (including the active identity):
(2) |
A swapout candidate is the identity with the smallest count among the agents' nonactive identities (i.e., all excluding the active identity):
(3) |
A rotate candidate is the identity with the highest count among all the subscribed identities:
(4) |
Finally, an acquire candidate must not be part of the subscribed set and is the one with the highest count in the identity spectrum:
(5) |
New repertoire =
(6) |
(7) |
(8) |
(9) |
(10) |
(11) |
2 Important work on themes related to autonomy movements include: work on mobilization (Lustick et al. 2004; Bhavnani and Backer 2000; Epstein, Steinbruner, and Parker 2002; Lustick and Miodownik 2002; Srbljinovic et al. 2003); identity diffusion (Axelrod 1997; Lustick 2000; Rousseau and van der Veen 2005); the emergence of ethnocentrism (Axelrod and Hammond 2003); and the endogenization of borders and emergence of ethnic conflict (Cederman 1997, 2002).
3 PS-I is available for download without any charge at: http://ps-i.sourceforge.net. A user manual is available from the "simulation software" section at http://www.polisci.upenn.edu/abir.
4 The simulation is described in much more details in Miodownik (2005). The simulation is modeled after the simulation employed by Lustick et al. (2004). All templates used to run the simulations described in this paper are available from the author upon request.
5 Appendix A presents average distributions for each of combinations in Ethniland.
6 For conceptual debates surrounding constructivism and using agent-based modeling in developing constructivist identity theory see Lustick (2000), Lustick et al. (2004) and Rousseau and van der Veen (2005).
7 This processes have been extensively studied and described in theories on conformity, social impact, social identity and self-categorization (Asch 1956; Latané, 1981, Tajfel and Turner 1986; Turner, Hogg, Oakes, Reicher, & Wetherell 1987).
8 Agents in these experiments update synchronously. Indeed there may be some good theoretical reasons to chose one asynchronous over synchronous modes of updating (e.g. Latané and Nowak 1997 p. 56). Indeed some more work may be required in the future to explore how this specific model is affected by a different mode of updating. Nevertheless, both Latané and Nowak (p. 57) and Lustick and Miodownik (2005, pp. 29-30) show that the anticipated effect on aggregate clustering and consolidation (phenomena related to those studies here) of choosing synchronous or asynchronous modes of update is in fact not as strong as it is usually expected.
9 Full technical details and formal notations for this as well as the other rules described in this section appear in Appendix B.
10 See Appendix B for full technical details and formal notations.
11 Since the size of countries and the sizes of disaffected populations within those countries vary widely, the 10%rule for the minimum size of what we refer to as a “subordinate identity” cannot be considered absolute. Instead the rule used to calculate the minimum size of a regionally disgruntled minority capable of producing secessionism is 40%of the ratio of the population of the region to the total population of the state. Thus, the SE quadrant of the model represents 25% of the entire state. Forty percent of that is 10%, so the minimum size of an activated group in the model capable of producing secessionism is 10% of the size of the model or 409 agents. Roeder (2003) presents an extensive discussion of the statistical issues involved in coding secession for comparisons across large and small states. Roeder's findings, though arrived at with different techniques and for somewhat different purposes, are consistent with our coding rules.
12 Huckfeldt, Johnson, and Sprague (2004) recently argued and demonstrated that societal level opinion diversity is preserved even thought individuals are exposed to persuasive information that challenges their held opinion. Huckfeldt et al. attribute this persistence to the influence of one's social network on the evaluation of counter attitudinal positions. People are able to resist counter-attitudinal information because they discuss it with people supportive of their own position within their network. The seeming contradiction between the two lines of research can be resolved if one considers the network of supportive discussants as a cluster of likeminded opinions. It is important to note, however, that Huckfeldt et al. (2004) work diverges from other studies that tend to expect the elimination of diversity and find its endurance a possible yet relatively rare phenomenon (Latané and Nowak 1997, Axelrod 1997).
13 The negative signs of the coefficients for cultural differences and economic incentives in the clustering model (model 2) are in the expected direction. Recall that high scores on the clustering variable indicate low clustering while smaller values of this variable are an indication of significant clustering.
14 It did, of course, affect the likelihood that any particular agent will transform into a border-cell, and therefore probably the aggregate number of border-cells. This result, however, is not part of the analysis of this paper.
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