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Gambling on Conflict: Profiling Investments in Conflict Countries
Unformatted Document Text:  Andreea Mihalache Updated: March 20, 2008 are located, the base category is North America. Model ORD5-2 adds the control for the respondent’s assessment of the investment environment. Model ORD5-3 includes an additional control, for the size of the global network of the respondent’s organization, revenue category. Table 4 here Across all the models, my expectation that investment characteristics affect perceptions of threat from political violence receives statistically significant support. Holding all else equal, investors in knowledge capital tertiary industries perceive lower threats from political violence than investors in the primary sector. This difference is significant at the 90% confidence level in models ORD5-1 and ORD5-3, and at the 95% level in model ORD5-2. Investors in physical capital tertiary industries also perceive political violence less threatening than their counterparts in the primary sector. The coefficient for PCT industries is significant at the 95% confidence level in all three models. However, across all model specifications, the difference between the estimated coefficients for KCT and PCT investments fails to attain statistical significance. Among the control variables, both the investment environment variables have the expected negative effect on the dependent variable—better environment reduces the probability that the respondent perceives high threat from political violence; however, only the effect of change in risk is statistically significant, at the 95% confidence level in model ORD5-1 and at the 99% level in models ORD5-2 and ORD5-3. Similarly, while the coefficient of revenue category has the expected negative sign, it is statistically null. Finally, relative to respondents located in North America, respondents in Eastern Europe, Western Europe, Asia, and Africa and the Middle East are more likely to perceive high 37

Authors: Mihalache, Andreea.
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background image
Andreea Mihalache
Updated: March 20, 2008
are located, the base category is North America. Model ORD5-2 adds the control for the
respondent’s assessment of the investment environment. Model ORD5-3 includes an
additional control, for the size of the global network of the respondent’s organization,
revenue category.
Table 4 here
Across all the models, my expectation that investment characteristics affect
perceptions of threat from political violence receives statistically significant support.
Holding all else equal, investors in knowledge capital tertiary industries perceive lower
threats from political violence than investors in the primary sector. This difference is
significant at the 90% confidence level in models ORD5-1 and ORD5-3, and at the 95%
level in model ORD5-2. Investors in physical capital tertiary industries also perceive
political violence less threatening than their counterparts in the primary sector. The
coefficient for PCT industries is significant at the 95% confidence level in all three
models. However, across all model specifications, the difference between the estimated
coefficients for KCT and PCT investments fails to attain statistical significance.
Among the control variables, both the investment environment variables have the
expected negative effect on the dependent variable—better environment reduces the
probability that the respondent perceives high threat from political violence; however,
only the effect of change in risk is statistically significant, at the 95% confidence level in
model ORD5-1 and at the 99% level in models ORD5-2 and ORD5-3. Similarly, while
the coefficient of revenue category has the expected negative sign, it is statistically null.
Finally, relative to respondents located in North America, respondents in Eastern Europe,
Western Europe, Asia, and Africa and the Middle East are more likely to perceive high
37


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