Santi Sanglestsawai, North Carolina State U Roderick M. Rejesus, North Carolina State U

1. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Santi Sanglestsawai, North Carolina State U Roderick M. Rejesus, North Carolina State U Jose M. Yorobe, Jr. University of the Philippines- Los Banos

2. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Introduction • Chemical pesticides have been used extensively in developing countries like the Philippines. • Chemical (mis-)use have caused serious problems to ecosystem and human health. • Integrated pest management (IPM) is an alternative option to reduce the use of pesticides.

3. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Objectives • Examine the impact of IPM-FFS on yields, pesticide expenditures, labor expenditures, herbicide expenditures, fertilizer expenditures, profit, and farmer’s self-reported health status, with a focus on onion production in the Philippines.

4. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • As reported before, initial FFS impact assessments in the Phil. used the before-after and with-without comparisons, not controlling for endogeneity and/or selection bias. • In our report last year (published in an international journal), we used instrumental variables on cross section data to control for the bias. The results revealed a significant reduction in pesticide expenditures (more than P5,000/ha)..

5. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Other studies using other methods to control for the bias have generated conflicting results. • For this study, impacts on inputs and output have been included as outcome variables – yield, fertilize use, labor use, herbicide use, profit and health. • Propensity Score Matching and regression based method were used to control for the bias – serve also as robustness check of our earlier IV method.

6. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Data • We used the same data as in our IV paper before coming from the farm-level survey in 2009. • 197 (69 IPM-FFS and 128 non-IPM) onion growers were selected randomly from 8 major onion locations in Nueva Ecija, 4 where IPM training has been conducted and 4 where IPM training has not been conducted.

7. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Fig. 1. Location of Study Sites, Philippines

8. The Impacts of Integrated Pest Management (IPM) Farmer Field School on Inputs and Output: Evidence from Onion Farmers in the Philippines • Propensity Score Matching • Matching non-IPM farmers and IPM farmers that have similar propensity score (probability to adopt) given set of observed variables X. This controls for the “selection on observables” bias • The “Rosenbaum bounds” is used to test the effect of “selection on unobservables” bias.

9. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • The regression-based method • This method based on the function: • The parameters of this function are estimated by OLS. • The procedure by Altonji et al. (2005) was used to see the impact of the “selection on the unobservables”

10. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • First Stage Probit Result for the PSM Approach.

11. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • Comparison of means of the observable variables between IPM-FFS and Non-IPM-FFS farmers.

12. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • Comparison of means of the observable variables between IPM-FFS and Non-IPM-FFS farmers (continued).

13. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • Comparison of means of the observable variables between IPM-FFS and Non-IPM-FFS farmers (continued).

14. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • Comparison of means of the observable variables between IPM-FFS and Non-IPM-FFS farmers (continued).

15. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • The impacts of IPM-FFS : PSM Approach.

16. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • The impacts of IPM-FFS : PSM Approach (continued).

17. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • The impacts of IPM-FFS : PSM Approach (continued).

18. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Result • The impacts of IPM-FFS : PSM Approach (continued).

19. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Result Parameter Estimates from the Regression-based Method.

20. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Result The ATT impacts of IPM-FFS: Regression-based Method.

21. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Result Parameter Estimates from the Regression-based Method using the Instrumental Variables (IV) technique.

22. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Result The ATT impacts of IPM-FFS: Regression-based Method using the Instrumental Variables (IV) technique.

23. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Conclusion • The IPM-FFS significantly reduces the level of insecticide use of participating farmers. • No strong evidence that IPM-FFS farmers receive higher profits than non-IPM-FFS farmers. • The PSM and regression-based results are consistent with our previous IV results.

24. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines • Future Plans • Need a better measure of health status. • Coordinate with the Philrice IPM-CRSP group for the next study using panel data or randomization • Study the inclusion on the impact of IPM-FFS on the environment.

25. The Impacts of Integrated Pest Management (IPM) Farmer Field Schools on Inputs and Output: Evidence from Onion Farmers in the Philippines Thank You