Table 6: Explaining Heterogeneity in the Estimated Effects of Income Shocks on Conflicts [BMA - Sub-Samples]

|||Positive A<br>BMA|gricultura|l Shocks (|AS+)<br>OLS|||Negative <br>BMA|Agricultur|al Shocks (|AS-)<br>OLS||Positi|ve Hydroc<br>BMA|arbon and|Mineral S|hocks (H<br>OLS|S+)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**(i) Baseline**|Post Mean|Post SD|PIP|Coef.|SE|p-Value|Post Mean|Post SD|PIP|Coef.|SE|p-Value|Post Mean|Post SD|PIP|Coef.|SE|p-Value|
|Publication bias (_β_1)<br>Precision (_β_0)<br>**(ii) Mechanisms and interacti**<br>_Othermechanisms(Ref)_|**-0.482**<br>0.009<br>**ve models**|**NA**<br>0.013|**1.000**<br>0.374|-0.521<br>**0.022**|0.312<br>**0.007**|0.108<br>**0.004**|**1.629**<br>0.000|**NA**<br>0.002|**1.000**<br>0.047|**1.693**<br>-0.001|**0.262**<br>0.003|**0.000**<br>0.815|**-3.283**<br>**0.133**|**NA**<br>**0.078**|**1.000**<br>**0.846**|**-2.870**<br>**0.109**|**0.718**<br>**0.039**|**0.002**<br>**0.014**|
|_._<br>Mechanism stressful<br>_Others(Ref)_|**0.045**|**0.005**|**1.000**|**0.045**|**0.005**|**0.000**|0.000|0.001|0.037|-|-|-|0.001|0.006|0.071|-|-|-|
|_._<br>Risk enhancer<br>|**0.014**|**0.001**|**1.000**|**0.014**|**0.005**|**0.008**|**0.002**|**0.000**|**1.000**|0.002|0.002|0.155|**0.002**|**0.001**|**0.798**|0.002|0.002|0.315|
|**(iii) Publication outlet**|||||||||||||||||||
|_No top 5 reviews (Ref.)_<br>Top 5<br>|-0.001|0.004|0.158|-|-|-|0.000|0.006|0.091|-|-|-|**-0.032**|**0.019**|**0.923**|**-0.027**|**0.005**|**0.000**|
|_No confict reviews (Ref.)_<br>Confict review<br>_Coreresults(Ref)_|0.002|0.005|0.150|-|-|-|**-0.017**|**0.004**|**0.998**|**-0.016**|**0.003**|**0.000**|0.001|0.004|0.158|-|-|-|
|_._<br>Appendix results<br>_Ctiibl_|0.000|0.000|0.019|-|-|-|0.000|0.000|0.026|-|-|-|0.001|0.005|0.081|-|-|-|
|_onnuous varaes_<br>Age of study|0.000|0.000|0.407|-|-|-|0.000|0.000|0.082|-|-|-|**0.008**|**0.005**|**0.820**|**0.008**|**0.001**|**0.000**|
|SJR score<br>**(iv) Geography**|**0.001**|**0.000**|**0.972**|**0.001**|**0.000**|**0.000**|**-0.001**|**0.000**|**0.931**|**-0.001**|**0.000**|**0.003**|0.000|0.001|0.302||||
|_No country focus (Ref.)_<br>Country focus<br>_Worldwide(Ref)_|0.000|0.002|0.038|-|-|-|0.000|0.001|0.058|-|-|-|**-0.057**|**0.032**|**0.866**|**-0.061**|**0.012**|**0.000**|
|_._<br>Region: Africa|**-0.028**|**0.009**|**0.993**|**-0.034**|**0.006**|**0.000**|**-0.002**|**0.002**|**0.755**|**-0.003**|**0.001**|**0.001**|0.008|0.043|0.368|-|-|-|
|Region: EAP|0.002|0.007|0.078|-|-|-|0.000|0.002|0.082|-|-|-|**0.059**|**0.058**|**0.708**|**0.056**|**0.014**|**0.001**|
|Region: LAC<br>|**-0.033**<br>|**0.010**<br>|**0.988**<br>|**-0.036**<br>|**0.005**<br>|**0.000**<br>|**-0.018**<br>|**0.005**<br>|**0.974**<br>|**-0.020**<br>|**0.005**<br>|**0.001**<br>|**0.035**<br>|**0.050**<br>|**0.628**<br>|**0.035**<br>|**0.004**<br>|**0.000**<br>|
|Region: South Asia<br>|**-0.021**|**0.012**|**0.859**|**-0.025**|**0.007**|**0.003**|**-0.041**|**0.016**|**0.938**|**-0.046**|**0.012**|**0.000**|**0.081**|**0.058**|**0.753**|**0.101**|**0.015**|**0.000**|
|**(v) Model characteristics**<br>_NoMLE(Ref)_|||||||||||||||||||
|_._<br>Maximum likelihood estimator<br>|0.000|0.000|0.021|-|-|-|0.000|0.000|0.035|-|-|-|0.000|0.002|0.058|-|-|-|
|_No specifc efects (Ref.)_<br>Specifc efects<br>|0.003|0.005|0.260|-|-|-|0.000|0.000|0.034|-|-|-|**0.047**|**0.055**|**0.520**|**0.048**|**0.021**|**0.042**|
|_Others (Ref.)_<br>Cluster unit reference<br>_Precoldwar(Ref)_|0.000|0.000|0.017|-|-|-|0.000|0.000|0.031|-|-|-|0.000|0.013|0.155|-|-|-|
|_._<br>Post cold war<br>|**0.006**|**0.001**|**1.000**|**0.006**|**0.003**|**0.095**|0.000|0.001|0.072|-|-|-|-|-|-|-|-|-|
|_No small grids (Ref.)_<br>Small grids<br>|0.000|0.001|0.052|-|-|-|0.000|0.001|0.041|-|-|-|-|-|-|-|-|-|
|_Continuous variable_<br>Sample size|0.000|0.000|0.064|-|-|-|0.000|0.000|0.043|-|-|-|**-0.011**|**0.003**|**1.000**|**-0.009**|**0.002**|**0.001**|
|**(vi) Confict characteristics**<br>|||||||||||||||||||
|_Usual confict data (Ref.)_<br>Unusual confict data<br>_Confictincidence(Ref)_|0.000|0.002|0.079|-|-|-|0.000|0.000|0.041|-|-|-|-|-|-|-|-|-|
|_._<br>Confict duration|-|-|-|-|-|-|0.000|0.000|0.319|-|-|-|-|-|-|-|-|-|
|Confict onset|0.000|0.001|0.073|-|-|-|0.000|0.000|0.097|-|-|-|-|-|-|-|-|-|
|_Nolocalconficts(Ref)_|||||||||||||||||||
|_._<br>Confict local<br>_Nonlethal(Ref)_|0.000|0.001|0.044|-|-|-|0.000|0.001|0.096|-|-|-|0.003|0.011|0.242|-|-|-|
|_._<br>Lethal<br>|0.000|0.001|0.058|-|-|-|0.001|0.002|0.210|-|-|-|-0.001|0.002|0.134|-|-|-|
|_Others (Ref.)_<br>Armed conficts|**0.005**|**0.002**|**0.930**|**0.004**|**0.001**|**0.002**|0.001|0.002|0.307|-|-|-|**-0.001**|**0.001**|**0.595**|**-0.002**|**0.001**|**0.007**|
|Crimes|0.000|0.001|0.047|-|-|-|**0.036**|**0.004**|**1.000**|**0.035**|**0.005**|**0.000**|0.000|0.002|0.034|-|-|-|
|Social unrests|**-0.006**|**0.007**|**0.522**|**-0.010**|**0.006**|**0.088**|0.000|0.001|0.103|-|-|-|0.000|0.001|0.057|-|-|-|
|Violenceagainstcitizens|0.000|0.001|0.023|-|-|-|0.000|0.000|0.026|-|-|-|0.000|0.002|0.065|-|-|-|
|<br>**(vii) Measures of shocks**<br>|||||||||||||||||||
|_No quasi experimental (Ref.)_<br>Quasi experimental<br>_NlbitiR_|**-0.003**|**0.003**|**0.545**|**-0.005**|**0.002**|**0.034**|**-0.004**|**0.001**|**1.000**|-0.004|0.002|0.105|0.009|0.014|0.377|-|-|-|
|_o aor nensve (ef.)_<br>Labor intensive resources<br>_Others(Ref)_|0.000|0.002|0.042|-|-|-|**-0.005**|**0.001**|**1.000**|-0.005|0.003|0.104|-|-|-|-|-|-|
|_._<br>Climatic shock|0.000|0.001|0.030|-|-|-|**0.006**|**0.001**|**1.000**|**0.007**|**0.002**|**0.000**|-|-|-|-|-|-|
|Price shock|0.000|0.001|0.038|-|-|-|**0.016**|**0.005**|**0.968**|**0.018**|**0.004**|**0.000**|**-0.081**|**0.037**|**0.969**|**-0.063**|**0.017**|**0.003**|
|**(viii)Modelspecifcation**|||||||||||||||||||
|<br>_No past confict (Ref.)_|||||||||||||||||||
|Control for past conficts<br>_Ntilft(Rf)_|0.000|0.000|0.024|-|-|-|0.000|0.000|0.025|-|-|-|-0.001|0.005|0.100|-|-|-|
|_o spaa acor e._<br>Control for confict spatial factor<br>_Nopopulation(Ref)_|0.000|0.001|0.030|-|-|-|0.000|0.001|0.063|-|-|-|**0.017**|**0.005**|**0.995**|0.016|0.010|0.118|
|_._<br>Controlforoulation|0001|0002|0270|-|-|-|**-0002**|**0000**|**1000**|**-0002**|**0001**|**0088**|0000|0007|0072|-|-|-|
|pp<br>_No GDP (Ref.)_|.|.|.||||**.**|**.**|**.**|**.**|**.**|**.**|.|.|.||||
|Control for GDP|0.000|0.001|0.100|-|-|-|0.000|0.000|0.055|-|-|-|-0.004|0.014|0.090|-|-|-|

Notes: AS+ sample: 808 observations and 25 studies focusing on positive agricultural shocks; AS- sample: 951 observations and 34 studies focusing on negative agricultural shocks; HS+ sample: 543 observations and 14 studies focusing on positive hydrocarbon/mineral shocks. The weights are the inverse of _SE_<sup>_pcc_</sup> . The dependent variable is the partial correlation between the type of shock and conflicts. SD = standard deviation. SE = standard error. PIP = posterior inclusion probability. Bayesian model averaging (BMA) employs the unit information and the dilution prior (UIP g-prior; uniform model prior on the BMS package by Zeugner and Feldkircher (2015)) suggested by George (2010). The frequentist check (OLS) includes only explanatory variables with a PIP above 50 percent ( _≥_ 0.50) in the BMA and is estimated using clustered standard errors (cluster at the study level). In bold, explanatory variable with a PIP above 50 percent ( _≥_ 0.50) (BMA) and/or statistically significant at 10 percent or less (OLS). _Source: Authors’ compilation from MRA database._ 34