LT Week 10 Flashcards
Why Conflict?
Factors leading to civil war
The economic costs of violence
The limitations of cross-country data
The advantages of cross-country data
Motivation
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
To assess how different income shocks affect conflict exploiting exogenous price shocks in international commodity markets and whether different types of shocks have differential effects.
Special settings
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
- “Within country variation. Municipalities in Colombia between 1988-2005. Rich data; high incidence of conflicts (get both geographic and time variation).
- Some municipalities produce labour-intensive commodities (coffee) more intensively, while others specialize in the extraction of natural resources (oil).”
Theory
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
“Income shocks may have two opposite effects: 1) the opportunity cost:
higher wages may lower conflict by reducing labor supply to appropriation;
2) rapacity effect: higher contestible income may increase violence from raising gains from appropriation.”
Empirical design
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
“Difference in difference estimator by assessing whether changes in commodity prices affect violence disproportionately in municipalities that produce more of these commodities. The main specification uses one step via 2SLS estimation.
Post in the regression means period after the price shock, treat is being heavily engaged in a commodity production.
Possible endogeneity concerns: conflict affecting commodity prices. So, use IV for coffee prices: coffee export volume as an instrument. However, potential violation of exclusion restriction: other exporting nations adjust their exports according to what may be happening in the Colombian coffee market (e.g. prices or quantities).”
Data
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
“The dataset on the Colombian civil war includes more than 21,000 war- related episodes in over 950 municipalities during 1988-2005. Incidents are aggregated to the municipality-year level.
Oil is measured in the average barrels of crude oil produced per day in each municipality in 1988. All agricultural commodities are measured in the hectares of land used for cultivating that crop in a given year.”
Key findings
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
“Table 2: col.1-4 show that coffee price shocks have a negative relationship with conflict and that the oil price shock exerts the opposite effect on conflict.
Table 3: col. 1-2 show that coffee shock exerts substantially larger effects on both wages and work hours of rural workers in areas with more coffee cultivation, while oil interaction terms display insignificant effects on both labour outcomes; col.3 indicate that the oil price shock significantly increases capital revenue at the disposal of municipal government.”
Interpretation / policy implications
Commodity Price Shocks and Civil Conflict: Evidence from Colombia (Oeindrilla and Vargas, 2013)
“Price stabilization schemes which place a floor on the price of labour- intensive commodities can help mitigate violence in the wake of price shocks.
Since natural resource revenue is found to promote rapacity, improved monitoring may prevent these funds from fuelling conflict.
Since funds leak through local governments, fiscal structure may
interact with price shocks in affecting conflict outcomes”
Motivation
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
The relationship between economic performance and conflict has huge implications for developing countries. Due to endgoeneity of economic outcomes and civil war as well as omitted variables such as institutional quality when analysing the effect of economic shocks on conflict, overcme this issue with an IV approach.
Special settings
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
“Country level data, so not much of a special setting. 41 countries in Sub-Saharan Africa during 1980s and 1990s. Instrument of weather shcoks on GDP works only in economies that largely rely on rain-fed agriculture, don’t have robust irrigation systems nor are heavily industrialised.
Another benefit of this approach within the context of Africa is it helps overcome the issue of measurement error for African national incomes which are often unreliable. “
Theory
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
“Why Conflict?
Erupt when political institutions which enable society to make collective decisions break down
Often triggered by economic downturns - competition over scarce resources becomes more intense:
Property rights become insecure
Firm find it difficult to function
Greater food insecurity
Large-scale displacement “
Empirical design
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
“IV-2SLS approach:
First Stage regression is rainfall on Economic Growth. First stage relationship between rainfall and income growth is strongly positive: current and lagged rainfall growth are both significantly postively related to income growth at over 95% confidence
The second-stage equation estimates the impact of income growth on the incidence of violence. Higher levels of rainfall are associated with significantly less conflict in the reduced-form regression, for all civil conflicts (regression 1 in table 3), with a point of estimate of -0.122
Contemporaneous and lagged economic growth rates are negatively, though not statistically significantly, correlated with the incidence of civil conflict in probit (regression 1 in table 4) and OLS specifications with country controls (regression 2), and contemporaneous growth is negatively associated with conflict in OLS specifications with and without country fixed effects (regressions 3 and 4). See results for more and effects of controls.
Finally, they look at how economic growth affects the onset of conflict by restricting attention to country-year observations in which there was no civil conflict during the previous year.
Potential Violations/Discussion of the Exclusion Restriction (Z affects the outcome variable Y only through X (Z does not have a direct influence on Y which is referred to as the exclusion restriction): rainfall growth not significantly associated with tax revenues, indicating that changes to fiscal policy are unlikely to drive findings. Bigger issue that rainfall might directly affect civil conflict but does not harm the empirical strategy too much as bias would be in the same direciton as hypothesized –> empirically rainfall is negatively associated with conflict which would actually make this paper’s estimates would be lower bounds”
Data
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
“Uses Armed Conflict Data database recently developed by the International Peace Research institute of Oslo, Norway and the University of Uppsala, Sweden.Uniquely records all conflicts with a threshold of 25 battle deaths per year. Civil conflict was remarkably widespread in sub-Saharan Africa during the period 1981-99: there was civil conflict in fully 27 percent of all country-year observations according the PRIO definition of 25 annual battle deaths.
Uses the Global Precipitation Climatology Project (GPCP) database of monthly rainfall estimates, which stretches back to 1979. The data relies on a combination of actual weather station rainfall gauge measures, as well as satellite information on the density of cold cloud cover to derive rainfall estimates.
Main country controls: ethnolinguistic fractionalization and religious fractionalization; measures of democracy, the log of per capita income, proportion of a country that is mountainous, Log of total country population, Income and income inequality measures
Key findings
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
“Find that GDP growth is significantly negatively related to the incidence of civil conflict in sub-Saharan Africa during the period 1981–99 across a range of regression specifications, including some with country fixed effects.
A five-percentage-point drop in annual economic growth increases the likelihood of a civil conflict (at least 25 deaths per year) in the following year by over 12 percentage points - which amounts to an increase of more than one-half in the likelihood of civil war
In the second main result, we find perhaps surprisingly that the impact of income shocks on civil conflict is not significantly different in richer, more democratic, more ethnically diverse, or more mountainous African countries
An instrumental variable estimate including country controls yields point estimates of -2.25 (standard error 1.07) on lagged growth, which is significant at 95 percent confidence, and -0.41 (standard error 1.48) on current growth (regression 5 of table 4). The two growth terms are jointly significant at nearly 90 percent confidence (p-value .12).
When we focus on the IV-2SLS fixed-effects specification as our benchmark, the point estimate indicates that a one-percentagepoint decline in GDP increases the likelihood of civil conflict by over two percentage points. Thus a five-percentage-point decline in lagged growth—which is somewhat less than one standard deviation in annual per capita growth (table 1)—leads to a greater than 12-percentage-point increase in the incidence of civil war, an increase of nearly one-half of the average likelihood of conflict.
Weak results on the democracy interaction indicate that relatively non-democratic African countries hit by negative income shocks are just as prone to civil conflict as relatively democratic countries, suggesting that even democratic states in Africa typically lack the institutional capability to adequately responds to negative economic shocks. A reading of table 5 would suggest that economic factors trump all others in determining the incidence of civil conflict and, in particular, that institutional and social characteristics have minimal impact in mitigating the effect of economic shocks
“
Interpretation / policy implications
Miguel, Satyanath and Sergenti (2004) - Economic Shocks and Civil Conflicts: an IV approach
Economic outcomes are a leading cause of conflict. Robust institutions must be in place to ensure negative economic outcomes do not lead to violence. Speaks to the importance of state capacity.
Dube & Vargas (2013) vs. Miguel et al (2004)
coffee and conflict
