**Table** **<u>6: The impact of price shocks on various types of conflict in Nigeria (2004-11)</u>**

||(1)<br>CINAR<br>oth<br>PINAR<br>oth<br>Eve|(2)<br>CIBR<br>oth<br>PIBR<br>oth<br>nts with fata|(3)<br>CINAR<br>Intl<br>PINAR<br>Intl<br>lities|(4)<br>CINAR<br>oth<br>PINAR<br>oth|(5)<br>CIBR<br>oth<br>PIBR<br>oth<br>Battle events|(6)<br>CINAR<br>Intl<br>PINAR<br>Intl|(7)<br>CINAR<br>oth<br>PINAR<br>oth|(8)<br>CIBR<br>oth<br>PIBR<br>oth<br>Protests/riot|(9)<br>CINAR<br>Intl<br>PINAR<br>Intl<br>s|(10)<br>CINAR<br>oth<br>PINAR<br>oth<br>Violen|(11)<br>CIBR<br>oth<br>PIBR<br>oth<br>ce against c|(12)<br>CINAR<br>Intl<br>PINAR<br>Intl<br>ivilians|(13)<br>CINAR<br>oth<br>PINAR<br>oth<br>Fatalities|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|_CINAR (t-1)_|0.059***||0.063*|0.054***||0.017|0.080||-0.002|0.038**||0.033|0.068***|
||(0.016)||(0.033)|(0.015)||(0.034)|(0.058)||(0.041)|(0.016)||(0.032)|(0.013)|
|_PIAR (t-1)_|-0.027**||0.008|-0.043***||0.012|-0.025||0.029|-0.034**||-0.020|-0.021**|
|_N _|(0.011)||(0.023)|(0.014)||(0.028)|(0.107)||(0.026)|(0.014)||(0.024)|(0.009)|
|_CIBR (t-1)_||0.042***|||0.044***|||0.040***|||0.029**|||
|||(0.014)|||(0.012)|||(0.014)|||(0.014)|||
|_PI (t-1)_||-0.014|||-0.036**|||-0.032**|||-0.027**|||
|_BR _||(0.012)|||(0.012)|||(0.014)|||(0.012)|||
|_Oil ind (t-1)_|0.003***|0.003***|0.003***|0.004***|0.003*|0.003***|0.000|0.000|-0.001*|0.003***|0.003***|0.003***|0.001*|
|_._|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|
|_Oil ind. (t) x_|-0.004***|-0.004***|-0.004***|-0.004**|-0.004**|-0.004***|-0.003|-0.003|-0.003*|-0.002**|-0.002**|-0.002***|-0.006***|
|_post-09_|(0.001)|(0.001)|(0.001)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|(0.002)|(0.001)|(0.001)|(0.001)|(0.001)|

_All regressions include residuals from the first stage regressions of the endogenous price index on the excluded instruments as a control with appropriate standard errors (clustered at the state level) calculated; *, **, *** indicate statistical significance at the 10, 5, and 1 percent level, respectively. Data are for 37 states for 8 years (2004-11). All regressions include year and region effects, as well as region-year effects and a full set of controls as in Tables 4 and 5. The models are estimated through the populationaveraged negative binomial estimator for panel data._ In table 6 we check to what extent these results apply also to other conflict measures using the categorization of the ACLED data into various types of conflict. All the effects appear to apply to all types of conflict events, including events that result in fatalities, battle events, protests and riots, and violence against civilians. The consumption and oil price effect, but not the production price effect, also are robust to using the number of fatalities as the dependent variable (column 13).<sup>28</sup> This analysis also shows an important dichotomy in the effect of the price shocks. While the effect of CI is particularly large for protests/riots (although its standard errors are large for the narrow CI and PI), oil price shocks have no effect on this type of conflict event (and that is the only type of conflict event which oil does not affect). This result is in line with the hypothesis that oil extraction spurred a type of violence mainly organized around militant groups, which was unrelated to popular protests.

> 28 Note we are unable to run the model with fatalities using indices based on broad matching and on international prices  due to lack of convergence.

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