The NRVA surveys are nationally representative, with the 2011 edition providing detailed information on 18,399 households across all but two provinces. The data include household composition, household expenditures, educational attainment, and a range of other socioeconomic indicators. The NRVA surveys also contain information on variables related to fragility, including perceptions on security, revenues from opium, and shocks from violence. In addition, they indicate the household location and report information on the occurrence of local shocks such as severe weather.

The credibility of the proposed approach hinges on the consistency of the data used in the models. Since the databases used in each case are built on unrelated primary sources, disconnects cannot be ruled out. One key indicator that the two models share is the local intensity of conflict. A high correlation between the conflict-related indicators in the two databases should give some reassurance about the consistency of the two models. A further assessment of the reliability of the data used in the analysis comes from its consistency with data from extraneous sources.

The provincial database used to estimate Model 1 includes information on conflict intensity, the number of incidents, and the number of terrorism-related casualties. The NRVA survey used to estimate Model 2 includes data on theft and violence directly suffered by households and on household perceptions of insecurity. This data can be aggregated at the province level using survey weights. To ensure that correlations are meaningful, all seven indicators are scaled by population. Separately, the Asia Foundation Survey of the Afghan people (2015) includes questions regarding the household’s fear for safety and the household concern about bad security conditions. These survey data can also be aggregated at the province level using survey weights.

Some of the correlation coefficients between the various indicators of conflict are quite high (table 1). Not surprisingly, households that report having suffered from theft or violence also have higher perceptions of insecurity. Similarly, conflict intensity is higher in provinces experiencing a larger number of conflict-related incidents. While these two correlation coefficients involve indicators from the same database, there is also a relatively high and statistically significant correlation between conflict intensity reported by the provincial database and the perception of insecurity estimated based on the NRVA survey. This pattern is corroborated by households’ perception of security from the Survey of the Afghan People.

# **4. Modeling conflict intensity**

The econometric specification of Model 1 builds on the analyses by Biddle, Friedman, and Shapiro (2012) and Hultman, Kathman, and Shanon (2013). The model focuses on changes in conflict intensity at the local level and how they are affected by changes in the presence of troops on the ground. Conflict intensity is measured by the number of casualties. To allow for richer dynamics, the specification considers two periods: the current year and the previous year. It also differentiates between international troops and Afghan troops, as their effectiveness at reducing conflict may be different. Troops and casualties are deflated by provincial population.

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