1. Monitoring Household Coping during Shocks: Evidence from Kenya and the Philippines Shantanu Mukherjee and Shivani Nayyar UNDP, October 2011 AEC, Addis Ababa October 27 th 2011

2. Aggregate Shocks and Human Development - Macroeconomic data is abundantly available - Important to monitor impacts on people, human development Source: IMF WEO September 2011

3. Monitoring impacts on households Impacts on health and nutrition Paxson and Schady (2005), Baird et al (2007), Friedman and Schady (2009), Compton et al (2011) Impacts on education Knowles et al (1999), Ferreira and Schady (2009) Survey Conceicao et al (2009) Traditionally a 3-4 year lag - Household surveys done at pre-determined intervals. - Many of these impacts take a few years to manifest. - Real time data and action needed.

4. Coping strategies mediate impacts Can lead to more effective monitoring and response - Real time behavioral changes Harmful coping strategies are precursors to adverse long term human development impacts -Impacts on children and other vulnerable groups -Harmful intra-household coping Coping strategies can be indicative of the stage and severity of a crisis -Hierarchies? Household coping – common across aggregate shocks.

5. Increasing frequency of climate shocks Source: EM-DAT, The International Disaster Database, Centre for Research on the Epidemiology of Disasters A green economy will continue to face crop failures, food price shocks, and others.

6. Six sub-locations in Tana River district -72 percent below the poverty line Standard CBMS methodology: surveyed all households. -Covered 5882 households Data collection: July 2009 to January 2010 PEP CBMS: Kenya survey

7. 81 4 1 9 1313 2 36 1212 7 1010 5 PEP CBMS: Philippines survey Covered 13 barangays (districts), 4954 households. Data collection: November 2008 to April 2009 Source: CBMS 2009

8. Coping strategies CategoryExamples Borrowing money Assets/IncomeSelling assets Using savings Consuming staple food only FoodReducing portion size Consuming own harvest Transferring for private to public school EducationWithdrawing from school Using second hand books/uniforms Shifting to generic brands HealthShifting to government clinics Shifting to alternate medication Fairly consistent surveys in the two countries asked about a range of coping strategies:

9. Kenya: the attribution question What (aggregate) shocks were the Kenyan households dealing with?

10. Results: Kenya Coping StrategyTotal Income Quintile Lowest234Highest Decline in monthly food expenditure 26.2838.8730.2518.8020.0922.67 Decline in monthly education expenditure13.298.877.147.6312.2612.59 Shifted at least one child from private to public school4.380.681.101.131.792.67 Withdrew at least one child from school 1.435.634.253.734.093.28 Decline in monthly health expenditure 15.9323.7015.0414.6413.7011.64 Borrowed money 11.756.737.9012.3913.2818.19 Used savings 15.603.506.4613.0822.7232.07 Sold belongings 20.5913.9025.2327.0420.3415.60 Sold belongings to buy food in the last month 33.4040.4138.5735.6229.0222.67 Sought additional work 3.412.054.503.643.233.36 Evidence of harmful coping behavior. Lower quintiles have much less access to credit, savings; more likely to resort to harmful coping.

12. Results: Philippines Coping StrategyTotal Income Quintile Lowest234Highest At least one food related strategy 85.9981.8585.485.7690.386.67 At least one education related strategy 25.0533.1728.324.4324.4414.67 At least one health related strategy 60.456.8557.9164.2964.4458.37 Borrowed money 37.3438.1541.7438.2639.7228.63 Used savings13.84 16.4414.612.9512.6912.56 Pawned Assets 4.082.063.924.725.594.05 Sold Assets 2.563.623.592.211.931.45 Looked for additional work 5.625.738.725.295.173.12

13. Philippines: Probit estimation Dependent variable: efood_staple Independent variableSpecification 012 pci100-0.0031-0.0005 urban0.58500.56930.5652 femalehead-0.2097-0.2070 head_highschool-0.3384-0.3415 dummy_assistance-0.1578-0.1626 fration-0.0179 childratio0.0433 Constant-0.8590-0.5698-0.5870 Observations461130573054

14. Philippines: the attribution question Panel data: 2702 households were interviewed in 2006. Appear to be hit by a large income shock, i.e. the Global Economic Crisis

15. also, self reported impact of the economic crisis However, - Does not match self reported impacts of channels such as job losses, reduced hours and business losses. - As we saw, attribution questions in Kenya remain.

16. Room for improvement Other issues: Absence of a baseline - Is some of this behavior normal (borrowing) or seasonal (reducing consumption)? Intensity of harmful coping behaviour - How frequently were meals skipped? - Value of assets sold, borrowing.

17. Conclusions relevant to policy Importance of well-designed safety nets -The vulnerable are coping in ways that reduce resilience. - Exposed in the face of aggregate, repeated shocks. Act before it is too late - Important to monitor coping behavior to gauge the long term impacts of shocks on the most vulnerable, including intra- household effects. - Policy interventions to forestall these impacts, including expanding and adjusting safety nets. New methods and technologies - Besides surveys, use mobile phones and internet technology. - UN Global Pulse – use data exhausts and detect ‘digital smoke signals’.

18. Future Work: Panel data collection 2011 - Recovery from 2009 crisis impact. -Impact of 2010-2011 high food prices. Guidance note Continued monitoring

19. Thank you Contact email: shivani.nayyar@undp.org