Conflict, Climate, and Cells: A Disaggregated Analysis Flashcards
Harari and La Ferrara
motivations of harari
- as climate change intensifies, research is concerned with the impact of climate change on aggregate scenarios
- correlation between vulnerability to weather shocks and propensity to conflict (researchers looking for a causal link)
opportunity cost effect
- negative shock to local economy decreases returns from labour market participation relative to fighting (makes it more attractive to join a rebellion)
- or conversely the incentive to fight is lowered, reducing attractiveness of rebellion
state capacity effect
economic shocks reduce tax base, weakening government capacity and reduced infrastructure leads to more conflict
what are harari’s three research questions
- how do agriculture-relevant weather shocks affect conflict incidence at a subnational level
- are there spatial and temporal spillovers in conflict
- what are the mechanisms through which climate shocks affect conflict incidence
what is harari’s empirical strategy
- georeferenced grid approach, dividing Africa into 110 x 110 km cells as the unit of analysis rather than using political boundaries
- it is a more precise examination of subnational conflict dynamics and how climate shocks influence violence at the local level
whats the goal of the harari paper’s methodology
investigate how conflict in a cell spills over to neighbors and how such effects persist over time, something that is more naturally assessed with incidence
harari focuses on
conflict incidence, not onset or termination
- incidence better captures ongoing conflict dynamics and spillover effects
how many models does harari have
three
what is harari’s baseline model
contains only regressors specific to the cell (climate shocks, topography, year, country fixed effects)
harari’s spatial lag model
includes a spatial lag of the regressors, allowing for spillover effects from neighboring cells
harari’s full model
incorporates lags of the regressors in both time and space, providing a more complete picture of conflict persistence and diffusion
conflict data in harari is coded with
PRIO Uppsala ACLED, listed as any event
climate data
the main climate indicator is the Standardized Precipitation-Evapotranspiration Index (SPEI)
- SPEI growing season is computed by averaging SPEI over the growing season months of a cell’s main crop in a given year
three implications for climate change and agriculture
- agriculture as a crucial link between climate shocks and conflict
- by focusing on climate shocks occurring specifically during the crop growing season, the study isolates the role of agricultural yields and opportunity costs
- this suggests that disruptions to agricultural livelihoods can be a driver of conflict
two implications for local level dynamics
- the correlates of civil conflict exhibit strong local dimensions and the likelihood of conflict varies in both time and space, even within the same country
- this highlights the need to move beyond aggregate, country level analyses to understand the nuances of conflict
three implications for temporal and spatial spillovers
- conflict is not an isolated phenomenon
- conflict in on area can increase the likelihood of conflict in neighboring areas, and conflict can persist over time
- policy interventions should be carefully targeted in space and time, based on an understanding of local conflict dynamics and considering broader regional contexts
three key takeaways for harari
- local level agriculture-relevant climate shocks during the growing season increase the likelihood of conflict
- the opportunity cost channel seems most consistent with the data as indicated by the significant effects of weather shocks on rebel recruitment
- underlying vulnerabilities can worsen the risk of climate related conflict
