The Impact of Violent Civil Conflict on Gender Inequality: Evidence from Nepal

1. The Impact of Violent Civil Conflict on Gender Inequality:Evidence from Nepal Christine Valente University of Sheffield, U.K. Gender and Conflict Research Workshop – June 10th2010

2. Overview • Introduction • Data • Empirical Strategy • Results • Discussion

3. Introduction – Conflict and Gender Inequality • Although men are typically more affected by direct conflict-related mortality, women face more insidious challenges: • new roles to replace men • more vulnerable to sexual violence • in many developing societies, may have to bear more heavily the brunt of reduced family resources • Of particular concern in Nepal due to much gender inequality at start of conflict: • Adult literacy: 21% (women) vs 54% (men) • Life expectancy: 52.4 years (women) vs 55 (men) • gender development index: 0.27 (all developing countries: 0.56)

4. Introduction – Civil Conflict in Nepal • Maoist insurgency from 1996 to 2006. Escalation in 2001. • Comparatively high intensity: 13,000 deaths for a 2001 population of 23.2 Million. 200,000 displaced. • The insurgency started in February 1996 in the Rolpadistrict. By the end of the war, conflict-related casualties recorded in 73 out of the 75 Nepalese districts. • The Maoist presence varied from total control (where they organised their own local governments and law courts) to sporadic attacks. • Principal objective of the insurgents: obtain the creation of a constituent assembly to draft a new constitution and establish a Communist republic. Other important aims were stated to be: land redistribution and equality for all castes, language groups, and women.

5. Introduction – Civil Conflict in Nepal • Maoists attacked government targets such as army barracks, police posts, local government buildings (Do and Iyer, 2007). They were also reported to terrorise, loot, abduct, and physically assault civilians (Watchlist on Children and Armed Conflict, 2005; Bohara et al., 2006). • government security forces also killed civilians and were accused of using children for spying, torturing, displacing and summarily convicting civilians (Bohara et al., 2006).

6. Introduction – the Nepali Puzzle • very little is known so far of the impact of the conflict, both at the aggregate and gender-differentiated levels • Puzzle: • steady growth in real gross GDP (5% per year between 1995/96 and 2003/04) • sharp decrease in poverty over the period (from 42% in 1995/96 to 31% in 2003/04) • improvement in human development indicators such as primary school enrollment (up from 57% to 73%) and child mortality, which decreased by 5% per year

7. Data • Micro data: • Demographic and Health Surveys 2006 and 2001. Part of the worldwide Measure DHS project. • Several datasets per survey: • Household dataset (basic information on all household members, anthropometric data for children under 5 years old). >=44,000/survey • Individual datasets (more detailed information on women and men eligible for individual interviews). Ever-married women/men in 2001; small sample of men in 2001 and 2006. • Conflict data: • Conflict-related casualties per district/month during whole conflict period. Source: INSEC, independent human rights NGO. As in Bohara et al. (2006) and Do and Iyer (2007).

8. Empirical Strategy Four types of difference-in-difference, according to data availability. • First 2 identify any within-district effect of conflict, but do not rule out potential confounding factors extensively: • DID1: DHS 2006 only, compares 2 control/treated cohorts (separated by at least 6 years) Yijt = α j + cohort t + β1 (cohortt*casualtiesj) [+ intermediate*trendjt+ intermediate*trend2jt + high*trendjt+ high*trend2jt]+ εijt • DID2: compares outcomes in 2001 and 2006 for a given year of birth cohort Yijt = α j + year t + δ1 (conflict_before_surveytj) + δ2ageijt + δ3age2ijt+ δ4dhs2006 + εijt

9. Empirical Strategy • Last 2 are more “water-tight”, but may rule out relevant transmission channels: • DID3: DHS 2006. Comparison of contiguous cohorts experiencing the same total exposure to conflict, but at different periods in their lives. Yijt = α j + year t + γ1 casualties_period1jt + γ2 casualties_period2jt [+ γ3 casualties_period3jt] [+ intermediate*trendjt+ intermediate*trend2jt + high*trendjt+ high*trend2jt]+ εijt • DID4: DHS 2006 and 2001. Comparison of contiguous cohorts experiencing different degrees of exposure during their entire lives. Yijt = αj + year t + θ1 (life_conflict_intensityjt) + θ2ageijt + θ3age2ijt+εijt

10. Selected Results 1 – Child Height-for-Age

11. Selected Results 1 – Child Height-for-Age

12. Selected Results 2 - Education Caution: districts where the conflict has been more intense started off with lower primary education rates, but that the gap had started to close before the conflict could have much impact. Indeed, the convergence appears to start for children born in Nepali year 2041 (dashed vertical line), who were 12 years old at the start of the conflict in 1996.

13. Selected Results 2 - Education

14. Selected Results 2 - Education

15. Selected Results 3 – Marriage

16. Selected Results 3 – Marriage

17. Other Results • Family Formation: • No effect of overall exposure to conflict on age at marriage (men and women). Some effects of exposure at specific periods, e.g., delayed marriage when exposure at entrance in marriage market for men. • No effect on age differential between spouses • No effect on age at first birth and number of births • Labour Market: • Increase in paid work (cash or kind) for men but not women • Woman Empowerment: • Increased control over cash earned • No effect on other aspects of decision power within household • Attitudes towards domestic violence: increased acceptability (women, not men)

18. Discussion • Despite having gone through one of the highest intensity civil conflicts in recent times between 1996 and 2006, Nepal as a whole has also surprisingly enjoyed one of the best periods in its history in terms of economic growth and poverty reduction, among others. • Using within-country variation in conflict intensity, find no robust evidence of an effect of exposure to conflict on human capital, namely child long-term nutritional status and educational attainment, for neither females nor males. • Displaced individuals who had not come back home by 2006 not included in analysis. Adverse microeconomic effects of conflict may be concentrated on them. • Education: conflict is likely to have disrupted schooling (mass abductions, child soldiers), despite potentially positive Maoist influence on schooling of deprived castes and girls (Lama-Tamang, 2003). However, these results indicate that quantity of schooling not affected for most children. Further research needed on impact on quality.

19. Discussion • Marriage: decreased much less in districts more affected by the conflict than elsewhere, possibly due to an attempt of parents to keep their sons out of the Maoist army and to pass on their daughters’ protection to someone else • Reassuringly not been accompanied by what would have been detrimental to female bargaining power within the household, namely a systematically lower age at marriage or higher age gap between spouses • in line with a stronger influence of Maoist ideology where conflict was more intense, decrease in the proportion of men (but not women) working for no pay where conflict intensified most between 2001 and 2006 • consequences of conflict on female empowerment are not clear: gained bargaining power over the use of cash earnings, but not gained “final say” over a number of household expenditure decisions, including their own health care, and they even appear more acceptant of certain forms of domestic violence. More detailed research needed on whether daily political violence affects the acceptability of daily domestic violence