Coffee Price Volatility and Intra-household Labour Supply: Evidence from Vietnam
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1 Coffee Price Volatility and Intra-household Labour Supply: Evidence from Vietnam Ulrik Beck U. Copenhagen Saurabh Singhal UNU-WIDER Finn Tarp UNU-WIDER June, 2016
2 Introduction Volatility in commodity markets poses risk to smallholder farmers in developing countries HH use a variety of mechanisms to tide over temporary income fluctuations: wage employment, credit, hh enterprises, assest sales, informal networks etc. often necessitates reallocation of labor within the household
3 Introduction Volatility in commodity markets poses risk to smallholder farmers in developing countries HH use a variety of mechanisms to tide over temporary income fluctuations: wage employment, credit, hh enterprises, assest sales, informal networks etc. often necessitates reallocation of labor within the household How do poor households cope with volatility in commodity markets? What are the patterns of intra-household labor supply allocations? What is the burden borne by children and adolescents? What is the scope for public intervention to mitigate these effects?
4 Introduction Volatility in commodity markets poses risk to smallholder farmers in developing countries HH use a variety of mechanisms to tide over temporary income fluctuations: wage employment, credit, hh enterprises, assest sales, informal networks etc. often necessitates reallocation of labor within the household How do poor households cope with volatility in commodity markets? What are the patterns of intra-household labor supply allocations? What is the burden borne by children and adolescents? What is the scope for public intervention to mitigate these effects? We investigate this using a sample of coffee-farmers in the Central Highlands region of Vietnam
5 Background Coffee in Vietnam: Only Robusta (not arabica) Second largest producer of coffee in the world (largest for robusta) Almost solely produced in the Central Highlands region Coffee cultivation: the first crop can be harvested around three years after planting risky investment: costly to cut down trees - difficult to switch in and out of coffee International coffee prices are volatile Driven by supply shocks (weather); interest rates and expectations (speculation); demand shocks (technology)
6 Figures and Tables Background Figure 1 World market coffee prices, 000 real June 2014 VND/kg Robusta price, kg 12 month backward-looking MA Source: Author s presentation based on ICO (2015) and World Bank (2015). US cents per Kg (Source: International Coffee Organization) Note: The red bars denote the three-month periods of the VARHS survey rounds
7 Data Vietnam Access to Resources Household Survey (VARHS) Panel survey, conducted every 2 years Households were added in 2008, 2012 Survey conducted in 12 provinces during the same months (May-Sept) Sample restricted to: 3 provinces in the Central Highlands: Dak Lak, Dak Nong & Lam Dong HH. that harvested coffee at least once over Unbalanced panel at HH. level Low attrition: 0% - 1.6% from round to round
8 Survey Area
9 Summary Statistics Variable Mean SD Real Coffee Price/SD Real Food Exp. (monthly, 000 Dongs) Asset Index HH size Natural shock Health shock Pest attack Coffee produced, kg HH engages in wage work (=1) HH engages in household business (=1) Child engages in wage work (=1) Number of household Number of household Number of household Number of household Number of household Number of household-year observations 2355
10 Estimation Strategy y it = α + βp mt + γ c t + µx it + η i + ɛ it p mt : 12 month backward looking average of the international robusta coffee price, divided by its s.d. over the survey period (varies month-to-month) X it : HH level time varying shocks: crop loss due to pests, illness or death, natural disaster; hh size & hh size sq. γ c t: province-specific linear time trend η i : Fixed effects - household/individual standard errors clustered at commune level
11 Results: Household Level Farm-gate price/sd Food Exp. Asset Index Wage work Price/SD (0.008) (16.752) (0.020) (0.008) Constant (0.122) ( ) (0.254) (0.132) Province time trend Yes Yes Yes Yes HH controls Yes Yes Yes Yes HH FE Yes Yes Yes Yes R-Square N
12 Intra-household labor response by age Ages 6-14 Ages Ages Panel A: Wage work Price/SD *** *** (0.007) (0.005) Mean of dep. var Panel B: Agricultural work Price/SD *** *** *** (0.013) (0.017) (0.004) Mean of dep. var Panel C: Housework Price/SD *** (0.015) (0.011) (0.007) Mean of dep. var N Province time trend Yes Yes Yes HH controls Yes Yes Yes Indiv. FE Yes Yes Yes
13 Robustness The results are robust to: adding quadratic province-specific time trends clustering at the level of the district including district-specific time trends alternate coffee price measures
14 Robustness The results are robust to: adding quadratic province-specific time trends clustering at the level of the district including district-specific time trends alternate coffee price measures Other time-varying effects correlated with fluctuations in coffee price? Use the remaining nine provinces of the survey as a control group y jt = α + βp mt + γp mt CH + δ c t + µx it + η j + ɛ jt Identifying assumption: All co-varying trends affect households in the Central Highlands and elsewhere equally
15 Robustness: using all provinces Ages 6-14 Ages Ages Panel A: Wage work Price/SD*CH *** (0.007) (0.006) Panel B: Agricultural work Price/SD*CH ** *** (0.014) (0.018) (0.004) Panel C: Housework Price/SD*CH *** (0.016) (0.013) (0.009) N 11,932 9,145 38,164 Province time trend Yes Yes Yes HH controls Yes Yes Yes Indiv. FE Yes Yes Yes
16 Heterogeneity: Wage Work Ages Ages Interaction var: Female Price/SD *** *** (0.009) (0.007) Female*Price/SD *** (0.011) (0.011) Interaction var: Assets Price/SD *** *** (0.008) (0.005) Asset*Price/SD 0.024*** 0.013*** (0.006) (0.004) Interaction var: Nonkinh Price/SD *** *** (0.005) (0.006) Nonkinh*Price/SD *** ** (0.012) (0.006) N
17 Heterogeneity: Farm Work Ages 6-14 Ages Ages Interaction var: Female Price/SD *** *** * (0.017) (0.019) (0.005) Female*Price/SD (0.015) (0.016) (0.006) Interaction var: Assets Price/SD *** *** ** (0.013) (0.015) (0.004) Asset*Price/SD ** *** (0.008) (0.009) (0.003) Interaction var: Nonkinh Price/SD ** *** ** (0.015) (0.023) (0.005) Nonkinh*Price/SD (0.017) (0.028) (0.007) N
18 Heterogeneity: Housework Ages 6-14 Ages Ages Interaction var: Female Price/SD * 0.059*** (0.017) (0.015) (0.009) Female*Price/SD ** *** (0.016) (0.015) (0.011) Interaction var: Assets Price/SD ** *** (0.015) (0.011) (0.005) Asset*Price/SD * * (0.009) (0.007) (0.004) Interaction var: Nonkinh Price/SD ** 0.027** 0.039*** (0.017) (0.013) (0.005) Nonkinh*Price/SD * (0.016) (0.022) (0.007) N
19 Educational Outcomes Attending School Ages 7-14 Ages Grade Overage Attending School Grade Overage Price/SD (0.006) (0.059) (0.006) (0.013) (0.043) (0.013) Province time trend Yes Yes Yes Yes Yes Yes HH controls Yes Yes Yes Yes Yes Yes Indiv. FE Yes Yes Yes Yes Yes Yes R-Square N
20 Conclusion Drops in the coffee price results in decreased consumption, drawdown of assets and reallocation of labor to wage work Intra-household reallocation of labor: Adults take up wage work, corresponding decrease in housework Children and adolescents pick up slack on HH farm HH more likely to borrow when prices are low Policy: need for social protection program; improvement in financial infrastructure (credit, insurance)
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