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Evaluating Development Impacts with Local Economy-wide Models

Evaluating Development Impacts with Local Economy-wide Models. Mateusz Filipski International Food Policy Research Institute May 2014. Outline. 1 - General Equilibrium Large and Small 2 - LEWIE: Local Economy-wide Impact Evaluation 3 - Application 1: Kenya’s CT-OVC

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Evaluating Development Impacts with Local Economy-wide Models

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  1. Evaluating Development Impacts with Local Economy-wide Models Mateusz Filipski International Food Policy Research Institute May 2014

  2. Outline • 1 - General Equilibrium Large and Small • 2 - LEWIE: Local Economy-wide Impact Evaluation • 3 - Application 1: Kenya’s CT-OVC • 4 - Other recent applications • 5 - Preview of Current work in China • Conclusions

  3. Part 1: General Equilibrium, Large and Small

  4. A local spillover story • “Once upon a time in Mexico … • …“I don’t get Progresa, but tomorrow buyers will be lining up here” Spillovers Local GE effects

  5. Rest of the country Treatment household Shock Market Rest of Zimbabwe Rest of World Control household?

  6. Local spillovers • Villages can have their own markets (& prices) • Factor markets (land, labor) • Commodities (non-tradables, specific varieties, etc.) • Interventions can have spillovers in the village • From target households to non-target households • From target sector to other sectors • What’s a great way to research such spillovers? • Computable General Equilibrium methods • Can be applied to economy of any scale

  7. In comes LEWIE • Local Economy-wide Impact Evaluation • Central idea = local economies also experience general equilibrium effects. • CGE analysis is applicable to an economy of any size (household, hamlet, village, region, country, multiple countries) Book (Forthcoming): Taylor and Filipski (2014): Beyond Experiments in Development Economics: Local Economy-Wide Impact Evaluation. Oxford University Press. Most of this talk is based on material in the book

  8. LEWIE models • What are they? • Systems of equations representing economies • What are they not? • Not econometrics = no statistical significance • Not a forecasting tool • How we build them? • Computer code such a GAMS

  9. LEWIE models • What do we do with them? • “Laboratory for economic experiments”, “Flight Simulator” • All about markets and linkages. “General Equilibrium effects”, “Higher-order effects”, “Spillover effects”, etc... • Are they a CGE? • “Computable”, “General”, “Equilibrium” => in essence yes

  10. LEWIE vs. CGE differences (?) More similarities than differences. Models akin in spirit, very similar equations

  11. When do we want to use LEWIE? • When you arrive ex-post • When you need results ex-ante • When you cannot randomize your treatment • When outcomes are multifaceted, with winners and losers • When you need to know why there is an effect, not just whether (i.e. structure) • When you expect spillovers

  12. Part 2: LEWIE basics

  13. LEWIE Basics • Start from the household model • Nest up to a village/region/island/[…] model • Calibrate the model, usually from household data • Perform simulations

  14. Household-farm economy Production and Consumption behavior

  15. Treated Economy Non-Treated Treated 3 x • Marketed Surplus (for household) Produced Consumed Used as Inputs Marketed Surplus Endowments

  16. Treated Economy Treated Non-Treated Rest of World Crops, livestock, retail, services, labor Manufactured goods, purchased inputs • Market Closures (for village)

  17. LEWIE system of equations (simplified) Indexing allows us to greatly increase number of variables and equations without complicating the model.

  18. Part 3: Cash Transfer in Zambia

  19. CGP – Cash Grants Program • “Standard” cash transfer intervention • Targets the most vulnerable

  20. Treatment household Transfer Market Rest of Zimbabwe Control household? Rest of World

  21. From Protection to Production • Most evaluations look at the beneficiary households • They are a conduit through which cash enters local economies • Does the whole local economy, then, become a beneficiary of the CGP • …including those who do not get transfers?

  22. Beneficiaries: The Point of Entry into the Local Economy

  23. The CGP Has an Income Multiplier of 1.79 Every Kwacha transferred to a poor household generates an additional 0.79 Kwacha in spillovers Most Spillovers Go To Non-beneficiaries

  24. Real Income Multipliers Are Smaller But Significant* *Real-income multipliers (Kwacha) if land, capital, and liquidity constraints limit the local supply response

  25. Spillovers Result from Productive Impacts

  26. Good News • The economic impacts of social cash transfers are likely to significantly exceed the amount transferred • There may be less of a tradeoff between protection and production than we once thought • Non-beneficiaries should be interested in seeing the transfer programs continue—and expand

  27. A Caveat • Positive spillovers depend on having a good supply response • Interventions may be needed to make sure this happens • Micro-credit, extension, etc.

  28. References - FAO From Protection to Production Project http://www.fao.org/economic/PtoP/en/ The Transfer Project http://www.cpc.unc.edu/projects/transfer FAO Report: Impact of the CGP program on productive activities and labour activities. Benjamin Davis, Silvio Daidone, Josh Dewbre and Mario Gonzalez

  29. Part 4: Other applications Mostly from “Beyond Experiments” book (Taylor and Filipski, forthcoming 2014)

  30. Irrigation project in Tanzania

  31. Irrigation project in Tanzania

  32. Irrigation project in Tanzania

  33. Irrigation project in Tanzania • Irrigation increases yields in the target zone… but creates spillovers through the region. • Ultimately affects all consumers (+), affects non-irrigated producers (-), affects food processors (+), livestock producers (+) • Milling capacity outside of the irrigated region => regional spillovers • Urban households may be the biggest winners Reference: Filipski, M., Manning, D., Taylor, J. E., Diao, X., & Pradesha, A. (2013). Evaluating the Local Economywide Impacts of Irrigation Projects: Feed the future in Tanzania. IFPRI publications.

  34. The true cost of Corruption

  35. The true cost of Corruption • Mexico’s leaky Pro-Campo program • Payments are proportional to land ownership • Two databases: payments due / payments received • => there exist discrepancies • Reverse of a Cash Transfer • Creates negative spillovers: each $1 not received by a supposed beneficiary means $1.2 dollars of real income foregone in the economy

  36. The true cost of Corruption

  37. Galapagos: the Myth of Eco-tourism

  38. Galapagos: the Myth of Eco-tourism • Tourism on the Galapagos islands • Construction ban supposed to control tourism and environmental degradation • Small share of tourist expenditures • Can we assume a small impact? => No, because of local migration

  39. Galapagos: the Myth of Eco-tourism • LEWIE model with migration • Labor comes from the mainland of Ecuador • Increased demand for tourism services triggered increases: • 58% increase in labor migration to the islands • 77% increase in income from fishing activities • 67% in income from agriculture on the islands Full economic impact much larger than tourist expenditures alone suggest

  40. What’s a corral reef worth?

  41. What’s a corral reef worth? • Roatan Corral Reef (Honduras, Caribbean) • Many aspects to value: use value (fishing), non-use value (“existence”), potential value (future scientific knowledge?) etc… • We value is only by tourist expenditures = conservative lower bound

  42. What’s a corral reef worth? • We value is only by tourist expenditures… • Accounting for spillovers • Yearly tourist expenditures = $80 million • Net Present Value over 30 years = between$1.3 billion and $4.5 billion (more than the country’s national debt)

  43. Part 5: Preview of work in China With Dr. Yumei Zhang from CAAS-AIRI (张玉梅博士,中国农业科学院农业信息研究所)

  44. Model for Puding (普定,贵州)

  45. Background – Income sources • Figure 1:Rural household income source (%) Local off farm income share increased from 30% to 35% during 2004-2011

  46. Background - Subsidies The transfer income share in rural HH increased from 3.7% to 8.7% during 2003-2012. Low income HH: the transfer income share reached 14%.

  47. Background: Local odd job market • About 20% of laborers worked local odd jobs in 2011. • The wage rate increased from 10~15 yuan to 80~100 yuan per day between 2004 and 2011. • The per capita local odd job income increased from 258 yuan to 926 yuan between 2004 and 2011 with annual real growth rate of 20%. Fig. Per capita local odd job income (yuan at 2004 constant price

  48. Objectives: • Reveal the hidden impacts of rural China’s safety-nets, and understand how they have participated to the dramatic evolution of the country-side. • How have the different safety-nets influenced the growth of rural activities? • How did they impact the supply of labor and the shift towards urban employment?

  49. Model for Puding (普定,贵州) • Look forward to those results!

  50. Part 6: Conclusions

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