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Gambling on Conflict: Profiling Investments in Conflict Countries
Unformatted Document Text:  Andreea Mihalache Updated: March 20, 2008 threats from political violence; respondents located in Latin America perceive lower levels of political. Table 5 here Table 5 displays the predicted probabilities that a respondent selects herself into each of the five categories of the dependent variable: no perceived threat (1) through very high threat (5). To calculate the predicted probabilities, I use the results from the least restricted model specification, ORD5-3, allowing categories of investment and the respondent’s region to vary from their minimum to their maximum and holding the other variables, change in risk, environment, and revenue category at their mean. Figures 13-18 graph these predicted probabilities, by investment category, for each region. Figures 13-18 here Table 5 and the figures illustrate the fact that primary sector firms are less likely than both PCT and KCT investors to perceive low threats from political violence; at the same time, firms with primary sector investments are more likely to perceive high levels of political violence threat than their counterparts in the other two investment categories. This finding lends some credence to my argument, as primary sector investments are characterized by a preponderance of physical assets over knowledge capital, high exit costs, and strong reliance on foreign markets. The relationship between PCT and KCT firms, however, is different from my expectation. Although Wald tests on the estimated coefficients of the two variables, across all models, show that they are statistically equal, the actual coefficient of PCT is consistently larger than that of KCT. This inconsistency between my prediction and my findings could be explained by the weak representation of PCT investments in the sample. Another explanation could be that several of the PCT 38

Authors: Mihalache, Andreea.
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background image
Andreea Mihalache
Updated: March 20, 2008
threats from political violence; respondents located in Latin America perceive lower
levels of political.
Table 5 here
Table 5 displays the predicted probabilities that a respondent selects herself into
each of the five categories of the dependent variable: no perceived threat (1) through very
high threat (5). To calculate the predicted probabilities, I use the results from the least
restricted model specification, ORD5-3, allowing categories of investment and the
respondent’s region to vary from their minimum to their maximum and holding the other
variables, change in risk, environment, and revenue category at their mean. Figures
13-18 graph these predicted probabilities, by investment category, for each region.
Figures 13-18 here
Table 5 and the figures illustrate the fact that primary sector firms are less likely
than both PCT and KCT investors to perceive low threats from political violence; at the
same time, firms with primary sector investments are more likely to perceive high levels
of political violence threat than their counterparts in the other two investment categories.
This finding lends some credence to my argument, as primary sector investments are
characterized by a preponderance of physical assets over knowledge capital, high exit
costs, and strong reliance on foreign markets. The relationship between PCT and KCT
firms, however, is different from my expectation. Although Wald tests on the estimated
coefficients of the two variables, across all models, show that they are statistically equal,
the actual coefficient of PCT is consistently larger than that of KCT. This inconsistency
between my prediction and my findings could be explained by the weak representation of
PCT investments in the sample. Another explanation could be that several of the PCT
38


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