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Corrigendum to “Climate triggers: Rainfall anomalies, vulnerability and communal conflict in Sub-Saharan Africa” [Pol Geo 31 (2012) 444–453]
Political Geography 45 (2015) 98e99
Contents lists available at ScienceDirect
Political Geography journal homepage: www.elsevier.com/locate/polgeo
Corrigendum
Corrigendum to “Climate triggers: Rainfall anomalies, vulnerability and communal conflict in Sub-Saharan Africa” [Pol Geo 31 (2012) 444e453] Hanne Fjelde*, Nina von Uexkull Department of Peace and Conflict Research, Uppsala University, Box 514, SE-75120 Uppsala, Sweden
The authors regret that in the above paper an error occurred relating to the coding of one of the temporal control variables. We sincerely apologize for this error, for which Fjelde is responsible, and we are grateful to Siri Aas Rustad for pointing it out. In this correction, we report the results with the corrected variable and provide a brief summary of the implications for the conclusions in the published article. In the article we evaluate the relationship between rainfall anomalies and the risk of communal conflict. We presented three hypotheses concerning this relationship: H1: Rainfall anomalies increase the likelihood of communal conflict. H2: The effect of rainfall anomalies on communal conflict is larger in regions with high poverty levels. H3: The effect of rainfall anomalies on communal conflict is larger in regions inhabited by politically excluded ethno-political groups. Table 1 displays the revised results concerning hypothesis 1, using the corrected variable. Whereas the signs of the coefficients do not change with the corrected data and the magnitude of the effects remain roughly similar, the changes in the estimated standard errors imply differences with regards to significance tests in two of the six models. In Model 1 we look at the effect of inter-annual negative rainfall anomalies. With the revised data, the p-value for the coefficient for interannual negative rainfall anomalies drops from 0.042 to 0.050, and just misses significance at the 5% confidence level. The result for the inter-annual positive rainfall anomaly variable (Model 2) was not significant in the published version of the article, and this result remains the same with the corrected data. The result for the inter-annual positive rainfall anomaly variable and its squared term (Model 3) was not significant in the published version of the article, and this result remains the same with the corrected data. The result for the intra-annual negative rainfall deviation was positive and significant at the 5% confidence level in the published article. The coefficient remains positive, gains slightly in magnitude, and remains significant at the 5% level using the corrected data (p-value ¼ 0.016). The p-value for the coefficient of the inter-annual negative rainfall anomaly variable in the fixed effects specification drops from 0.045 to 0.062 using the corrected data and is thus only significant at the 10% level (Model 5). The coefficient for the intra-annual negative rainfall anomaly variable in the fixed effects regression (Model 6) remains positive and significant at the 5% level, using the corrected data (p-value ¼ 0.036). Table 2 displays the revised results concerning hypothesis 2 and 3, using the corrected data. Hypothesis 2, which concerns the moderating role of poverty, is evaluated in model 7 and 8. As reported in the original article, the coefficient for the interaction term (both for the inter- and intra-annual rainfall measure) is far from statistical significance. The conclusion that poverty levels do not seem to condition the role of negative rainfall anomalies thus remains the same, using the corrected data. Hypothesis 3, which concerns the moderating role of political exclusion, is evaluated in model 9, 10 and 11. The results are consistent with those reported in the published article. The interaction term between political exclusion negative rainfall anomalies is positive across all the models, but only significant at the 10% level in the model using the intra-annual negative rainfall anomaly and a fixed effects specification. In sum, our main conclusion e that negative deviations from normal rainfall patterns increase the risk of communal conflict e still holds up. The results are, however, not as robust as reported in the published article. Specifically, while annual negative rainfall anomalies appear to be consistently linked to a higher risk of communal conflict, the impact of inter-annual negative rainfall anomalies is surrounded with somewhat more uncertainty. The authors would like to apologize for any inconvenience caused.
DOI of original article: http://dx.doi.org/10.1016/j.polgeo.2012.08.004. * Corresponding author. E-mail address: [email protected] (H. Fjelde). http://dx.doi.org/10.1016/j.polgeo.2015.01.005 0962-6298/© 2015 Elsevier Ltd. All rights reserved.
H. Fjelde, N. von Uexkull / Political Geography 45 (2015) 98e99
99
Table 1 Logit models, rainfall anomalies and communal conflict in Sub-Saharan Africa, 1990e2008. Model 1 Inter-annual neg. rainfall anomaly
Model 2
Model 3
Model 4
0.207 (0.106)*
Inter-annual pos. rainfall anomaly
0.050 (0.087)
0.079 (0.217) 0.012 (0.083)
Intra-annual neg. rainfall anomaly, (SPI-6) t1
Populationlog Spatial lag, communal conflictt1 Time since communal conflict Spatial lag, civil wart1 1995e99 2000e04 2005e08 Constant Administrative-unit fixed effects Number of observations
Model 6
0.248 (0.133)*
Inter-annual pos. rainfall anomaly, sq
Income per capitalog
Model 5
0.106 (0.052)** 0.541 (0.102)*** 0.941 (0.157)*** 0.612 (0.111)*** 0.451 (0.147)*** 0.551 (0.283)* 0.642 (0.289)** 0.751 (0.287)*** 9.562 (1.442)***
0.108 (0.052)** 0.553 (0.102)*** 0.924 (0.159)*** 0.617 (0.111)*** 0.462 (0.149)*** 0.473 (0.283)* 0.630 (0.289)** 0.692 (0.292)** 9.570 (1.445)***
0.109 (0.053)** 0.553 (0.103)*** 0.923 (0.158)*** 0.616 (0.111)*** 0.461 (0.150)*** 0.473 (0.283)* 0.631 (0.291)** 0.692 (0.292)** 9.570 (1.445)***
0.153 (0.063)** 0.116 (0.051)** 0.528 (0.101)*** 0.932 (0.159)*** 0.605 (0.109)*** 0.445 (0.147)*** 0.554 (0.279)** 0.796 (0.289)*** 0.915 (0.301)*** 9.388 (1.427)***
9986
9986
9986
9860
0.396 (0.154)** 1.212 (1.155) 0.181 (0.188) 0.470 (0.111)*** 0.305 (0.218) 0.430 (0.262) 0.322 (0.241) 0.821 (0.291)***
0.172 (0.082)** 0.367 (0.153)** 1.316 (1.157) 0.149 (0.188) 0.484 (0.111)*** 0.316 (0.219) 0.421 (0.262) 0.150 (0.252) 0.661 (0.302)**
Yes 1731
Yes 1731
*p < 0.1; **p < 0.05; ***p < 0.01 Three cubic splines are included in all regressions. Robust standard errors, clustered by administrative unit.
Table 2 Interaction models, negative rainfall anomalies and communal conflict in Sub-Saharan Africa 1990e2008. Model 7 Inter-annual neg. rainfall anomaly Poor, 50th pct Inter-annual neg. rainfall anomaly*poor
0.082 (0.155) 0.004 (0.249) 0.222 (0.209)
Intra-annual neg. rainfall anomaly, (SPI-6)
Model 8
Model 9
Excluded
0.437 (0.223)** 0.009 (0.222)
Inter-annual rainfall anomaly*excluded SPI-6*excluded Income per capitalog
0.511 (0.098)*** 0.932 (0.158)*** 0.609 (0.106)*** 0.555 (0.146)*** 0.587 (0.271)** 0.688 (0.288)** 0.821 (0.291)*** 9.846 (1.468)***
0.501 (0.097)*** 0.920 (0.159)*** 0.597 (0.104)*** 0.552 (0.147)*** 0.584 (0.270)** 0.848 (0.286)*** 0.976 (0.304)*** 9.751 (1.446)***
0.125 (0.053)** 0.520 (0.100)*** 0.895 (0.158)*** 0.618 (0.111)*** 0.318 (0.143)** 0.521 (0.279)* 0.634 (0.283)** 0.749 (0.284)*** 8.881 (1.443)***
9986
9860
9590
t1
Populationlog Spatial lag, communal conflictt1 Time since communal conflict Spatial lag, civil wart1 1995e99 2000e04 2005e08 Constant Administrative-unit fixed effects Number of observations
Model 11
0.202 (0.079)**
0.274 (0.099)***
0.286 (0.194)
1.393 (0.457)***
0.183 (0.134) 0.124 (0.052)** 0.505 (0.098)*** 0.880 (0.161)*** 0.612 (0.110)*** 0.300 (0.144)** 0.534 (0.278)* 0.797 (0.286)*** 0.918 (0.298)*** 8.798 (1.429)***
0.264 (0.160)* 0.304 (0.151)** 1.365 (1.184) 0.119 (0.190) 0.459 (0.113)*** 0.267 (0.220) 0.215 (0.273) 0.160 (0.269) 0.306 (0.318)
9518
0.018 (0.230)
0.049 (0.089) 0.156 (0.128)
SPI-6*poor
Model 10
0.201 (0.132)
Yes 1731
*p < 0.1; **p < 0.05; ***p < 0.01 Three cubic splines are included in all regressions. Robust standard errors, clustered by administrative unit. Note: the indicator for poor regions is coded 1 for non-poor regions and 0 for poor regions; the indicator for exclusion is coded 1 for non-excluded groups and 0 for excluded groups.
Contents lists available at ScienceDirect
Political Geography journal homepage: www.elsevier.com/locate/polgeo
Corrigendum
Corrigendum to “Climate triggers: Rainfall anomalies, vulnerability and communal conflict in Sub-Saharan Africa” [Pol Geo 31 (2012) 444e453] Hanne Fjelde*, Nina von Uexkull Department of Peace and Conflict Research, Uppsala University, Box 514, SE-75120 Uppsala, Sweden
The authors regret that in the above paper an error occurred relating to the coding of one of the temporal control variables. We sincerely apologize for this error, for which Fjelde is responsible, and we are grateful to Siri Aas Rustad for pointing it out. In this correction, we report the results with the corrected variable and provide a brief summary of the implications for the conclusions in the published article. In the article we evaluate the relationship between rainfall anomalies and the risk of communal conflict. We presented three hypotheses concerning this relationship: H1: Rainfall anomalies increase the likelihood of communal conflict. H2: The effect of rainfall anomalies on communal conflict is larger in regions with high poverty levels. H3: The effect of rainfall anomalies on communal conflict is larger in regions inhabited by politically excluded ethno-political groups. Table 1 displays the revised results concerning hypothesis 1, using the corrected variable. Whereas the signs of the coefficients do not change with the corrected data and the magnitude of the effects remain roughly similar, the changes in the estimated standard errors imply differences with regards to significance tests in two of the six models. In Model 1 we look at the effect of inter-annual negative rainfall anomalies. With the revised data, the p-value for the coefficient for interannual negative rainfall anomalies drops from 0.042 to 0.050, and just misses significance at the 5% confidence level. The result for the inter-annual positive rainfall anomaly variable (Model 2) was not significant in the published version of the article, and this result remains the same with the corrected data. The result for the inter-annual positive rainfall anomaly variable and its squared term (Model 3) was not significant in the published version of the article, and this result remains the same with the corrected data. The result for the intra-annual negative rainfall deviation was positive and significant at the 5% confidence level in the published article. The coefficient remains positive, gains slightly in magnitude, and remains significant at the 5% level using the corrected data (p-value ¼ 0.016). The p-value for the coefficient of the inter-annual negative rainfall anomaly variable in the fixed effects specification drops from 0.045 to 0.062 using the corrected data and is thus only significant at the 10% level (Model 5). The coefficient for the intra-annual negative rainfall anomaly variable in the fixed effects regression (Model 6) remains positive and significant at the 5% level, using the corrected data (p-value ¼ 0.036). Table 2 displays the revised results concerning hypothesis 2 and 3, using the corrected data. Hypothesis 2, which concerns the moderating role of poverty, is evaluated in model 7 and 8. As reported in the original article, the coefficient for the interaction term (both for the inter- and intra-annual rainfall measure) is far from statistical significance. The conclusion that poverty levels do not seem to condition the role of negative rainfall anomalies thus remains the same, using the corrected data. Hypothesis 3, which concerns the moderating role of political exclusion, is evaluated in model 9, 10 and 11. The results are consistent with those reported in the published article. The interaction term between political exclusion negative rainfall anomalies is positive across all the models, but only significant at the 10% level in the model using the intra-annual negative rainfall anomaly and a fixed effects specification. In sum, our main conclusion e that negative deviations from normal rainfall patterns increase the risk of communal conflict e still holds up. The results are, however, not as robust as reported in the published article. Specifically, while annual negative rainfall anomalies appear to be consistently linked to a higher risk of communal conflict, the impact of inter-annual negative rainfall anomalies is surrounded with somewhat more uncertainty. The authors would like to apologize for any inconvenience caused.
DOI of original article: http://dx.doi.org/10.1016/j.polgeo.2012.08.004. * Corresponding author. E-mail address: [email protected] (H. Fjelde). http://dx.doi.org/10.1016/j.polgeo.2015.01.005 0962-6298/© 2015 Elsevier Ltd. All rights reserved.
H. Fjelde, N. von Uexkull / Political Geography 45 (2015) 98e99
99
Table 1 Logit models, rainfall anomalies and communal conflict in Sub-Saharan Africa, 1990e2008. Model 1 Inter-annual neg. rainfall anomaly
Model 2
Model 3
Model 4
0.207 (0.106)*
Inter-annual pos. rainfall anomaly
0.050 (0.087)
0.079 (0.217) 0.012 (0.083)
Intra-annual neg. rainfall anomaly, (SPI-6) t1
Populationlog Spatial lag, communal conflictt1 Time since communal conflict Spatial lag, civil wart1 1995e99 2000e04 2005e08 Constant Administrative-unit fixed effects Number of observations
Model 6
0.248 (0.133)*
Inter-annual pos. rainfall anomaly, sq
Income per capitalog
Model 5
0.106 (0.052)** 0.541 (0.102)*** 0.941 (0.157)*** 0.612 (0.111)*** 0.451 (0.147)*** 0.551 (0.283)* 0.642 (0.289)** 0.751 (0.287)*** 9.562 (1.442)***
0.108 (0.052)** 0.553 (0.102)*** 0.924 (0.159)*** 0.617 (0.111)*** 0.462 (0.149)*** 0.473 (0.283)* 0.630 (0.289)** 0.692 (0.292)** 9.570 (1.445)***
0.109 (0.053)** 0.553 (0.103)*** 0.923 (0.158)*** 0.616 (0.111)*** 0.461 (0.150)*** 0.473 (0.283)* 0.631 (0.291)** 0.692 (0.292)** 9.570 (1.445)***
0.153 (0.063)** 0.116 (0.051)** 0.528 (0.101)*** 0.932 (0.159)*** 0.605 (0.109)*** 0.445 (0.147)*** 0.554 (0.279)** 0.796 (0.289)*** 0.915 (0.301)*** 9.388 (1.427)***
9986
9986
9986
9860
0.396 (0.154)** 1.212 (1.155) 0.181 (0.188) 0.470 (0.111)*** 0.305 (0.218) 0.430 (0.262) 0.322 (0.241) 0.821 (0.291)***
0.172 (0.082)** 0.367 (0.153)** 1.316 (1.157) 0.149 (0.188) 0.484 (0.111)*** 0.316 (0.219) 0.421 (0.262) 0.150 (0.252) 0.661 (0.302)**
Yes 1731
Yes 1731
*p < 0.1; **p < 0.05; ***p < 0.01 Three cubic splines are included in all regressions. Robust standard errors, clustered by administrative unit.
Table 2 Interaction models, negative rainfall anomalies and communal conflict in Sub-Saharan Africa 1990e2008. Model 7 Inter-annual neg. rainfall anomaly Poor, 50th pct Inter-annual neg. rainfall anomaly*poor
0.082 (0.155) 0.004 (0.249) 0.222 (0.209)
Intra-annual neg. rainfall anomaly, (SPI-6)
Model 8
Model 9
Excluded
0.437 (0.223)** 0.009 (0.222)
Inter-annual rainfall anomaly*excluded SPI-6*excluded Income per capitalog
0.511 (0.098)*** 0.932 (0.158)*** 0.609 (0.106)*** 0.555 (0.146)*** 0.587 (0.271)** 0.688 (0.288)** 0.821 (0.291)*** 9.846 (1.468)***
0.501 (0.097)*** 0.920 (0.159)*** 0.597 (0.104)*** 0.552 (0.147)*** 0.584 (0.270)** 0.848 (0.286)*** 0.976 (0.304)*** 9.751 (1.446)***
0.125 (0.053)** 0.520 (0.100)*** 0.895 (0.158)*** 0.618 (0.111)*** 0.318 (0.143)** 0.521 (0.279)* 0.634 (0.283)** 0.749 (0.284)*** 8.881 (1.443)***
9986
9860
9590
t1
Populationlog Spatial lag, communal conflictt1 Time since communal conflict Spatial lag, civil wart1 1995e99 2000e04 2005e08 Constant Administrative-unit fixed effects Number of observations
Model 11
0.202 (0.079)**
0.274 (0.099)***
0.286 (0.194)
1.393 (0.457)***
0.183 (0.134) 0.124 (0.052)** 0.505 (0.098)*** 0.880 (0.161)*** 0.612 (0.110)*** 0.300 (0.144)** 0.534 (0.278)* 0.797 (0.286)*** 0.918 (0.298)*** 8.798 (1.429)***
0.264 (0.160)* 0.304 (0.151)** 1.365 (1.184) 0.119 (0.190) 0.459 (0.113)*** 0.267 (0.220) 0.215 (0.273) 0.160 (0.269) 0.306 (0.318)
9518
0.018 (0.230)
0.049 (0.089) 0.156 (0.128)
SPI-6*poor
Model 10
0.201 (0.132)
Yes 1731
*p < 0.1; **p < 0.05; ***p < 0.01 Three cubic splines are included in all regressions. Robust standard errors, clustered by administrative unit. Note: the indicator for poor regions is coded 1 for non-poor regions and 0 for poor regions; the indicator for exclusion is coded 1 for non-excluded groups and 0 for excluded groups.