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Integrated Agricultural System, Migration, and Social
Protection Strategies to Reduce Vulnerability to Climate
Change in E...
Project Objectives
• Estimate potential costs climatic changes impose on
vulnerable rural households
– yield decreases
– y...
Project Components
• 6 months into an 18 month project
• Component one – Climate, crop, income
linkages
– Identify the mon...
Component one
• Identify the monetary costs of climate changes on
the agricultural systems of Ethiopia and Zambia at
the r...
Methodology
• Mean yield decreases from climate change (Regional level)
Pr. Y = KPQp- ΔPQp
Cs. Yc= ΔPQc
• Producer losses ...
Methodology cont.
• Benefits from mean yield decreases for each
household type
• Benefits from yield variance increases
ii...
Data
• Geo-referenced rainfall and temperature data for
the 2000-2011 period to characterize drought
risk using planting a...
Table 1. Simulations of potential impacts of a 20% Maize Yield decrease and a 10% yield variance increase.
Very Severe
Dro...
Table 2. Share of losses by drought risk zone.
Total
losses
('000 US$)
Share
losses
Very
Severe
Drought
Moderate
Drought
M...
Table 3. Simulations of potential impacts of different maize yield decreases and a yield variance increases.
Very Severe
D...
Annual welfare changes from a 20% yield decreases (US $/year)
Small farms Average farms Big farms
Ethiopia -28.26 -52.08 -...
Summary
• Potential losses are considerable given that only
maize losses were simulated.
• Estimated losses vary widely de...
On-going work on component one
• Finish all major crops and use DSSAT panel
data results to estimate regional losses.
• Co...
Component two – integrated coping
mechanisms
Identify broader set of household
adaptations with long-term panel datasets
i...
• Focus on agricultural adaptation: crop shares and yields
• Three-wave national representative panel:
– Created by Zambia...
Empirical Specification
• Assume a household fixed effects model to
exploit panel dataset:
• Two dependent variables of in...
Variable Mean Std. Dev. N
Maize Share of Cropped Land 0.60 0.27 6098
Number of Adult Equivalent 5.37 2.68 6098
Female Head...
Variable Mean Std. Dev. N
Maize yield per hectare 1619.39 1308.20 9929
Number of Adult Equivalent 5.30 2.74 9929
Female He...
Climate: By Year & Specification
Maize yield per hectare 1999/2000 2002/2003 2006/2007
Climate Variables Mean Std. Dev Mea...
Zambia: Maize Share (1 of 2)
Variable Coefficient Std. Err
Number of Adult Equivalent -0.006*** 0.002
Female Headed Househ...
Zambia: Maize Share (2 of 2)
Changes in Price & Climate Variables:
• Higher sweet potato prices in previous survey year de...
Zambia: Maize yield/ha (1 of 2)
Changes in Household Characteristics:
• Increasing the number of adults significantly (p =...
Zambia: Maize yield/ha (2 of 2)
Changes in Household Characteristics & Climate Variables:
• Households in 2006/2007 season...
Ethiopia:
• Focus on broader set of adaptions
• Migration
• Off-farm labor
• Transfers
• Family
• Informal networks
• Form...
Data
• ERHS household level data
– 3 waves (1999-2004-2009), unbalanced panel
– sample size: 1836 (1999)+1263 (2004) +1467...
Ethiopian cropping calendar
Belg planting: 1/16-3/31; Belg growing: 4/1-5/31; Kiremt planting: 6/1-8/10;
Kiremt growing: 8...
Ethiopian rainfalls in Belg planting
season
02020202
2000 2005 2010 2000 2005 2010
2000 2005 2010 2000 2005 2010 2000 2005...
Preliminary results: variables
Variable name Label
dlabmig Dummy for HH with migrated member due to labor market reasons
s...
Preliminary results: summary statistics
Variable Obs Mean Std. Dev. Min Max
dlabmig 4234 0.162 0.369 0.000 1.000
sharlabmi...
Preliminary results: migration decision
dlabmig Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhhsize 0.021*** 0.004...
Preliminary results: migration share
sharlabmig Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhhsize 0.0015** 0.001...
Preliminary results: remittance former
household members
valfhhmem Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhh...
Preliminary results: formal remittances
valfgov Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhhsize 13.275 16.458 ...
Preliminary results: informal
remittance equation
valfissn Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhhsize 19....
Preliminary results: off-farm labor
equation
nddwkp4m Coef.
Robust Std.
Err. t P>|t| [95% Conf. Interval]
fhhsize 0.450 0....
Component three – distilling policy relevant implications
• Evidence of broad adaptation
• Crop choice
• Off-farm labor
• ...
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Integrated agricultural system, migration, and social protection strategies to reduce vulnerability to climate change in East Africa

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Presented by Bradford Mills (Virginia Tech), Genti Kostandini (University of Georgia), Anthony Murray (Economic Research Service, USDA), Jiangfeng Gao (Virginia Tech), Joseph Rusike (AGRA), Steven Omamo, Zhe Guo and Jawoo Koo (IFPRI) at the Livestock Systems and Environment (LSE) Seminar, ILRI, Nairobi, 28 January 2015

Publié dans : Sciences
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Integrated agricultural system, migration, and social protection strategies to reduce vulnerability to climate change in East Africa

  1. 1. Integrated Agricultural System, Migration, and Social Protection Strategies to Reduce Vulnerability to Climate Change in East Africa Bradford Mills - Virginia Tech Genti Kostandini – University of Georgia Anthony Murray – Economic Research Service, USDA Jiangfeng Gao – Virginia Tech Joseph Rusike - AGRA Steven Omamo Zhe Guo - IFPRI Jawoo Koo - IFPRI LSE Seminar, ILRI Nairobi, 28 January 2015
  2. 2. Project Objectives • Estimate potential costs climatic changes impose on vulnerable rural households – yield decreases – yield variance increases • Identify agricultural system strategies that mitigate climate change costs • Rural household use of integrated agricultural system, off- on farm employment, migration, and formal and informal safety net strategies to reduce vulnerability to climatic change • Policy briefs that assist policymakers to generate country- specific interventions to mitigate the impacts of climatic change
  3. 3. Project Components • 6 months into an 18 month project • Component one – Climate, crop, income linkages – Identify the monetary costs to households and regions that climatic change is expected to have on agricultural systems in two East Africa countries: Ethiopia and Zambia – Simulation modeling (Genti)
  4. 4. Component one • Identify the monetary costs of climate changes on the agricultural systems of Ethiopia and Zambia at the regional and household level. • Translate rainfall change patterns into climate shocks for major crops using DSSAT crop model for the 2000-2011 period. • Use a methodology that takes into account the effect on mean yields and yield variance and higher moments of yield distribution. • Produce ex-ante estimates based on forward looking plausible climate change scenarios.
  5. 5. Methodology • Mean yield decreases from climate change (Regional level) Pr. Y = KPQp- ΔPQp Cs. Yc= ΔPQc • Producer losses due to increased risk (Regional Level) • Consumer losses due to increased price variability (Regional Level)  1 2 0 2 0 2 1 ppR X B   22 )(                                                                                         EEVarPQVar                 2 2 1 )(   PVar PQd   PQs   1 2 0 2 0 2 1 YYR Y B  
  6. 6. Methodology cont. • Benefits from mean yield decreases for each household type • Benefits from yield variance increases iijjjjij PQPY   )1(.Pr (i = poor farm, average farm, rich farm: j = drought risk type) )(5.0.Pr 22 jpijijijiij sRYRB   (i = poor farm, average farm, rich farm: j = PFS)
  7. 7. Data • Geo-referenced rainfall and temperature data for the 2000-2011 period to characterize drought risk using planting and harvesting dates. • Geo-referenced farm level panel household data (The Ethiopian Rural Household Survey seven waves from 1994 to 2009 and the Zambian Central Statistical Office 2000, 2004 and 2008) to estimate the benefits for different household types. • Use 11 years of DSSAT crop model data to isolate the impact of changes in rainfall pattern on yield and yield variability. • Use 2005 baseline SPAM production data from IFPRI.
  8. 8. Table 1. Simulations of potential impacts of a 20% Maize Yield decrease and a 10% yield variance increase. Very Severe Drought Moderate Drought Mild Drought Incipient Drought No Drought Annual welfare changes from a 20% mean yield decrease (Thousand US $) Total Total PR CS PR CS PR CS PR CS PR CS Total Losses (MT) Losses (%) Ethiopia (294) (111) (23,909) (9,022) (20,686) (7,806) (11,615) (4,383) (30) (11) (77,868) (569,078) (14.71) Zambia (3,808.2) (1,878.0) - - (12,502.4) (6,165.6) (4,527.0) (2,232.5) (1.3) (0.7) (31,115.7) (156,065.7) (7.9) Subtotal (4,102.0) (1,988.9) (23,909.1) (9,022.3) (33,188.8) (13,971.8) (16,141.8) (6,615.4) (31.4) (12.0) (108,983.) (725,143.) Annual welfare changes from a 10% increase in yield variance (Thousand US $) PR CS PR CS PR CS PR CS PR CS Ethiopia (59.6) (83.7) (4,932.9) (6,924.2) (4,438.5) (6,230.2) (2,544.7) (3,571.9) (8.9) (12.6) (28,807.1) Zambia (87.3) (263.6) - - (286.6) (865.6) (103.8) (313.4) - - (1,920.3) Sub-total (146.9) (347.3) (4,932.9) (6,924.2) (4,725.1) (7,095.8) (2,648.4) (3,885.3) (8.9) (12.6) (30,727.4) Total (4,248.8) (2,336.2) (28,842.0) (15,946.5) (37,913.9) (21,067.6) (18,790.2) (10,500.8) (40.4) (24.6) (139,710.9)
  9. 9. Table 2. Share of losses by drought risk zone. Total losses ('000 US$) Share losses Very Severe Drought Moderate Drought Mild Drought Incipient Drought No Drought Variance share in total losses Producer surplus share in total losses Total production losses (MT) Production Decrease Share production losses Ethiopia (106,675) 0.76 0.01 0.42 0.37 0.21 0.00 0.27 0.64 (569,078) (0.147) 0.8 Zambia (33,036) 0.24 0.18 0.00 0.60 0.22 0.00 0.06 0.65 (156,066) (0.079) 0.2 Total (139,711) 0.05 0.32 0.42 0.21 0.00 0.22 0.64 (725,144)
  10. 10. Table 3. Simulations of potential impacts of different maize yield decreases and a yield variance increases. Very Severe Drought (50%) Moderate Drought (40%) Mild Drought (30%) Incipient Drought (20%) No Drought (10%) Welfare changes from 50%-10% mean yield decrease (Thousand US $) Total Total PR CS PR CS PR CS PR CS PR CS Total Losses (MT) Losses (%) Ethiopia (725) (274) (47,421) (17,895) (30,907) (11,663) (11,615) (4,383) (15) (6) (124,903) (918,205) (24) Zambia (9,168) (4,521) - - (18,522) (9,134) (4,527) (2,232) (1) (0) (48,105) (245,657) (13) Subtotal (9,893) (4,795) (47,421) (17,895) (49,429) (20,797) (16,142) (6,615) (16) (6) (173,008) (1,163,862) Welfare changes from 50%-10% yield variance reductions in 2016 (Thousand US $) PR CS PR CS PR CS PR CS PR CS Ethiopia (460) (498) (27,356) (31,653) (16,572) (20,471) (5,680) (7,484) (9) (13) (110,195) Zambia (699) (1,569) - - (1,092) (2,844) (234) (657) - - (7,096) Sub-total (1,159) (2,067) (27,356) (31,653) (17,665) (23,315) (5,914) (8,141) (9) (13) (117,291) Total (11,052) (6,862) (74,776) (49,548) (67,094) (44,112) (22,056) (14,756) (25) (19) (290,299)
  11. 11. Annual welfare changes from a 20% yield decreases (US $/year) Small farms Average farms Big farms Ethiopia -28.26 -52.08 -109.67 Zambia -39.19 -73.45 -182.60 Annual welfare changes from a 10% yield variance increase (US $/year) Ethiopia -13.83 -14.85 -19.71 Zambia -4.52 -5.56 -10.19 Table 4. Simulations of household annual welfare changes from a 20% mean yield decrease and a 10% yield variance increase.
  12. 12. Summary • Potential losses are considerable given that only maize losses were simulated. • Estimated losses vary widely depending on the level of drought risk. • Welfare changes due to yield variability are an important part of the overall welfare changes.
  13. 13. On-going work on component one • Finish all major crops and use DSSAT panel data results to estimate regional losses. • Complete household data analysis and estimate household losses by drought risk. • Estimate losses/benefits based on future climate scenarios .
  14. 14. Component two – integrated coping mechanisms Identify broader set of household adaptations with long-term panel datasets in Zambia and Ethiopia (Brad for Anthony and Jiangfeng)
  15. 15. • Focus on agricultural adaptation: crop shares and yields • Three-wave national representative panel: – Created by Zambian Central Statistical Office, Ministry of Agriculture and Cooperatives, and the Food Security Research Project • Survey focuses on agricultural production and household characteristics – Survey rounds cover 1999/2000, 2002/2003, and 2006/2007 agricultural seasons – 4,286 households successfully interviewed in all 3 panels (out of original 7,699) • Past research not found attrition bias (Mason and Jayne, 2013) – This analysis only looks at households growing maize • Climate Data: – African Drought and Flood Monitor: • Daily rainfall (mm) • Aggregated for Planting (Nov-Dec), Growing (Jan-Mar), and Harvest (Apr-May) seasons Integrated Household Coping Mechanisms – Zambia Data
  16. 16. Empirical Specification • Assume a household fixed effects model to exploit panel dataset: • Two dependent variables of interest: – Share of maize grown by farm household – Maize yield per hectare it it i itXy     
  17. 17. Variable Mean Std. Dev. N Maize Share of Cropped Land 0.60 0.27 6098 Number of Adult Equivalent 5.37 2.68 6098 Female Headed Household 0.21 0.41 6098 Net Income (less Maize) (US Dollars) 553.80 979.62 6098 Total Assets 71.40 188.60 6098 Owns Livestock (dummy) 0.83 0.38 6098 Total Landholdings 2.53 3.05 6098 Hectares Cultivated 1.99 2.03 6098 Had Fallow Land (dummy) 0.33 0.47 6098 Use Fertilizer (dummy) 0.40 0.49 6098 2008 Dummy 0.52 0.50 6098 Lag Groundnut Price 0.28 0.03 6098 Lag Sweet Potato Price 0.05 0.01 6098 Lag Maize Price 0.09 0.01 6098 Grew Cash Crops previous Survey Year 0.21 0.41 6098 Grew High Value Crops previous Survey Year 0.45 0.50 6098 Grew Other Staple Crops previous Survey Year 0.52 0.50 6098 Lagged Planting Season Coef. of Var. (5 yr) 0.69 0.12 6098 Lagged Growing Season Coef. of Var. (5 yr) 0.68 0.14 6098 Lagged Planting Season 10 day Rainfall (5 yr avg.) 53.14 12.55 6098 Lagged Growing Season 10 day Rainfall (5 yr avg.) 59.59 10.91 6098 Summary Statistics: Maize Share
  18. 18. Variable Mean Std. Dev. N Maize yield per hectare 1619.39 1308.20 9929 Number of Adult Equivalent 5.30 2.74 9929 Female Headed Household 0.21 0.40 9929 Net Income (less Maize) (US Dollars) 465.08 859.41 9929 Total Assets 273.26 1702.91 9929 Owns Livestock (dummy) 0.83 0.38 9929 Total Landholdings 2.63 3.07 9929 Hectares Cultivated 2.03 2.06 9929 Had Fallow Land (dummy) 0.37 0.48 9929 Use Fertilizer (dummy) 0.36 0.48 9929 Fertilizer per Hectare 101.10 203.68 9929 Grew Cash Crops (dummy) 0.21 0.40 9929 Grew High Value Crops (dummy) 0.49 0.50 9929 Grew Other Staple Crops (dummy) 0.51 0.50 9929 Share of Maize planted/Total Cropped land 0.60 0.29 9929 Total Rainfall (mm) over growing season 621.80 155.40 9929 Planting Season Coef. of Var. (5 yr) 0.70 0.12 9929 Growing Season Coef. of Var. (5 yr) 0.62 0.12 9929 Harvest Season Coef. of Var. (5 yr) 1.51 0.36 9929 Summary Statistics: Yield/ha
  19. 19. Climate: By Year & Specification Maize yield per hectare 1999/2000 2002/2003 2006/2007 Climate Variables Mean Std. Dev Mean Std. Dev Mean Std. Dev Total Rainfall (mm) over growing season 603.13 89.91 597.68 177.64 663.95 170.26 Planting Season Coef. of Var. (5 yr) 0.69 0.14 0.69 0.13 0.71 0.08 Growing Season Coef. of Var. (5 yr) 0.57 0.10 0.64 0.10 0.63 0.14 Harvest Season Coef. of Var. (5 yr) 1.65 0.39 1.36 0.24 1.53 0.37 Maize Share Specification 2002/2003 Season 2006/2007 Season Climate Variables Mean Std. Dev Mean Std. Dev Lagged Planting Season Coef. of Var. (5 yr) 0.69 0.11 0.68 0.12 Lagged Growing Season Coef. of Var. (5 yr) 0.64 0.12 0.71 0.14 Lagged Planting Season Total Rainfall (5 yr avg.) 56.73 13.39 49.79 10.68 Lagged Growing Season Total Rainfall (5 yr avg.) 59.42 10.84 59.74 10.98 N = 2943 N = 3155
  20. 20. Zambia: Maize Share (1 of 2) Variable Coefficient Std. Err Number of Adult Equivalent -0.006*** 0.002 Female Headed Household -0.002 0.017 Net Income (less Maize) (US Dollars) -1.80E-05*** 4.30E-06 Total Assets 3.73E-05 2.48E-05 Owns Livestock (dummy) -0.023** 0.011 Total Landholdings -0.001 0.001 Hectares Cultivated -0.012*** 0.003 Had Fallow Land (dummy) -0.010 0.008 Use Fertilizer (dummy) 0.026*** 0.010 2006/2007 Agricultural season (dummy) 0.101* 0.056 Changes in Household Characteristics: • Changes in number of adults significantly decreases maize share planted • Increases in income and ownership of livestock associated with crop diversification • Adding more hectares cultivated reduces maize share • Adopting fertilizer use increases maize shares • Households in 2006/2007 ag. season grew more (p = 0.10) maize as a share of crops
  21. 21. Zambia: Maize Share (2 of 2) Changes in Price & Climate Variables: • Higher sweet potato prices in previous survey year decreases maize share • Growing other crops (Cash/High Value/Staple) in previous survey year all show significantly higher share of maize in current survey year • Higher mean rainfall over past 5 years (excluding current year) for planting and growing (p = 0.10) lead to increased share of maize Lag Groundnut Price -7.03E-06 3.86E-05 Lag Sweet Potato Price -0.001*** 0.000 Lag Maize Price 9.89E-05 0.000 Grew Cash Crops previous Survey Year 0.099*** 0.011 Grew High Value Crops previous Survey Year 0.069*** 0.008 Grew Other Staple Crops previous Survey Year 0.080*** 0.009 Lagged Planting Season Coef. of Var. (5 yr) -0.072 0.045 Lagged Growing Season Coef. of Var. (5 yr) 0.057 0.077 Lagged Planting Season Total Rainfall (5 yr avg.) 0.002** 0.001 Lagged Growing Season Total Rainfall (5 yr avg.) 0.003* 0.001 Constant 0.368 0.123
  22. 22. Zambia: Maize yield/ha (1 of 2) Changes in Household Characteristics: • Increasing the number of adults significantly (p = 0.10) increases yield/ha • Increases in income increases maize yield/ha • Adding more hectares cultivated reduces yield/ha • Fertilizer/ha increases yield/ha, but at a decreasing rate • Households in 2002/2003 season have lower maize yield/ha relative to 1999/2000 Dependent Variable: Maize (kg) per Hectare Coefficient Std. Err Number of Adult Equivalent 17.527* 8.974 Female Headed Household -22.608 74.699 Net Income (less Maize) (US Dollars) 0.087*** 0.022 Total Assets 0.014 0.016 Owns Livestock (dummy) 28.712 42.012 Total Landholdings 4.618 6.831 Hectares Cultivated -103.778*** 13.262 Had Fallow Land (dummy) -9.961 34.326 Use Fertilizer (dummy) -36.883 66.145 Fertilizer per Hectare 3.134*** 0.296 Fertilizer per Hectare Squared -0.001*** 0.000 2002/2003 Agricultural season (dummy) -167.697*** 38.137
  23. 23. Zambia: Maize yield/ha (2 of 2) Changes in Household Characteristics & Climate Variables: • Households in 2006/2007 season have lower maize yield/ha relative to 1999/2000 • Changes in growing cash/other staple crops led to significantly lower yield/ha • Households with increasing shares of maize had lower yield/ha • Increased rainfall during growing season increases yield/ha, but at a decreasing rate • Higher Coefficients of Variation in Planting and Growing season associated with lower yield/ha, while higher CV for Harvest associated with higher yield/ha 2006/2007 Agricultural season (dummy) -133.739*** 41.391 Grew Cash Crops (dummy) -117.635** 58.140 Grew High Value Crops (dummy) 36.012 44.143 Grew Other Staple Crops (dummy) -175.742*** 45.782 Share of Maize planted/Total Cropped land -664.952*** 93.240 Total Rainfall (mm) over growing season 3.228*** 0.739 Total Rainfall (mm) over growing season Squared -0.002*** 0.001 Planting Season Coef. of Var. (5 yr) -659.932*** 150.862 Growing Season Coef. of Var. (5 yr) -811.947*** 231.816 Harvest Season Coef. of Var. (5 yr) 202.038*** 64.982 Constant 1534.644 280.125
  24. 24. Ethiopia: • Focus on broader set of adaptions • Migration • Off-farm labor • Transfers • Family • Informal networks • Formal networks • Rainfall shocks influence these decisions through levels and variance: • Higher rainfall levels increase mean agricultural income • Make on-farm activities more attractive • Higher rainfall variability increases variance of agricultural income and household vulnerabilty • Make urban and off-farm jobs more attractive
  25. 25. Data • ERHS household level data – 3 waves (1999-2004-2009), unbalanced panel – sample size: 1836 (1999)+1263 (2004) +1467 (2009) – demographics, assets, expenditures, migration, remittance, social safety networks, and off-farm activities • Climatic data – precipitation (mm) on a daily basis – mean and variance are calculated for each Belg/Kiremt planting and growing season
  26. 26. Ethiopian cropping calendar Belg planting: 1/16-3/31; Belg growing: 4/1-5/31; Kiremt planting: 6/1-8/10; Kiremt growing: 8/11-9/30
  27. 27. Ethiopian rainfalls in Belg planting season 02020202 2000 2005 2010 2000 2005 2010 2000 2005 2010 2000 2005 2010 2000 2005 2010 1 2 3 5 6 7 8 9 10 12 13 14 15 16 17 21 22 23 year=1999,2004,2009 Graphs byvillagecode Meanrainfall in Belgplanting seasonoverpast5 years(mm) 0 .5 1 1.5 0 .5 1 1.5 0 .5 1 1.5 0 .5 1 1.5 2000 2005 2010 2000 2005 2010 2000 2005 2010 2000 2005 2010 2000 2005 2010 1 2 3 5 6 7 8 9 10 12 13 14 15 16 17 21 22 23 sdrainbp(mm) year=1999, 2004, 2009 Graphs byvillage code Std. dev. of rainfall in Belg planting season over past 5 years
  28. 28. Preliminary results: variables Variable name Label dlabmig Dummy for HH with migrated member due to labor market reasons sharlabmig Share of HH members who migrated due to labor market reasons valfhhmem Monetary value of transfers from former HH members valfgov Monetary value of public transfers valfissn Monetary value of transfers from informal social safety nets nddwkp4m Number of person-days worked off-farm in the past 4 months fhhsize Household size before migration ratiorainbp Ratio of mean rainfall over past 5 years to mean rainfall over past 30 years in Belg planting season ratiorainbg Ratio of mean rainfall over past 5 years to mean rainfall over past 30 years in Belg growing season ratiorainkp Ratio of mean rainfall over past 5 years to mean rainfall over past 30 years in Kiremt planting season ratiorainkg Ratio of mean rainfall over past 5 years to mean rainfall over past 30 years in Kiremt growing season nsdrainbp Revised standard deviation of rainfall during Belg planting season over last 5 years (=std. dev. for above historical average rainfall, =-std. dev. for below historical average rainfall) nsdrainbg Revised standard deviation of rainfall during Belg growing season over last 5 years (=std. dev. for above historical average rainfall, =-std. dev. for below historical average rainfall) nsdrainkp Revised standard deviation of rainfall during Kirmet planting season over last 5 years (=std. dev. for above historical average rainfall, =-std. dev. for below historical average rainfall) nsdrainkg Revised standard deviation of rainfall during Kirmet growing season over last 5 years (=std. dev. for above historical average rainfall, =-std. dev. for below historical average rainfall)
  29. 29. Preliminary results: summary statistics Variable Obs Mean Std. Dev. Min Max dlabmig 4234 0.162 0.369 0.000 1.000 sharlabmig 4234 0.028 0.075 0.000 0.667 valfhhmem 4264 21.557 242.626 0.000 8500.000 valfgov 4264 57.513 780.711 0.000 49276.000 valfissn 4264 88.872 653.344 0.000 23778.290 nddwkp4m 4236 15.770 36.014 0.000 362.000 fhhsize 7.489 3.294 1.000 31.000 ratiorainbp 0.876 0.147 0.527 1.256 ratiorainbg 1.004 0.197 0.654 1.368 ratiorainkp 1.067 0.147 0.743 1.400 ratiorainkg 1.020 0.129 0.716 1.325 nsdrainbp -0.334 0.652 -1.335 1.261 nsdrainbg 0.024 1.312 -2.902 2.335 nsdrainkp 0.716 1.784 -2.078 5.031 nsdrainkg 0.460 1.755 -3.125 4.787
  30. 30. Preliminary results: migration decision dlabmig Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize 0.021*** 0.004 5.89 0 0.014 0.028 ratiorainbp -0.278*** 0.073 -3.84 0 -0.421 -0.136 ratiorainbg -0.345*** 0.069 -4.99 0 -0.481 -0.209 ratiorainkp -0.108 0.097 -1.12 0.265 -0.299 0.082 ratiorainkg -0.515*** 0.105 -4.91 0 -0.721 -0.309 nsdrainbp 0.075*** 0.016 4.65 0 0.044 0.107 nsdrainkp -0.0009 0.0095 -0.09 0.925 -0.020 0.018 nsdrainbg 0.059*** 0.011 5.56 0 0.038 0.080 nsdrainkg 0.034*** 0.009 3.96 0 0.017 0.051 _cons 1.243 0.207 6.01 0 0.837 1.649 sigma_u 0.244 sigma_e 0.342 rho 0.337
  31. 31. Preliminary results: migration share sharlabmig Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize 0.0015** 0.001 2.16 0.031 0.000 0.003 ratiorainbp -0.044*** 0.014 -3.05 0.002 -0.072 -0.016 ratiorainbg -0.060*** 0.014 -4.33 0 -0.087 -0.033 ratiorainkp -0.016 0.019 -0.83 0.409 -0.053 0.021 ratiorainkg -0.093*** 0.022 -4.34 0 -0.136 -0.051 nsdrainbp 0.014*** 0.003 4.57 0 0.008 0.020 nsdrainkp -0.001 0.002 -0.48 0.628 -0.005 0.003 nsdrainbg 0.0096*** 0.002 4.58 0 0.005 0.014 nsdrainkg 0.007*** 0.002 3.54 0 0.003 0.011 _cons 0.229 0.041 5.53 0 0.148 0.310 sigma_u 0.053 sigma_e 0.070 rho 0.359
  32. 32. Preliminary results: remittance former household members valfhhmem Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize -7.277* 3.787 -1.92 0.055 -14.706 0.151 ratiorainbp 74.963 67.574 1.11 0.267 -57.584 207.510 ratiorainbg 171.944** 67.688 2.54 0.011 39.174 304.714 ratiorainkp 101.430* 60.018 1.69 0.091 -16.296 219.156 ratiorainkg 94.008 65.476 1.44 0.151 -34.424 222.439 nsdrainbp 22.851*** 8.826 2.59 0.01 5.539 40.163 nsdrainkp -8.015 7.572 -1.06 0.29 -22.868 6.838 nsdrainbg -27.345** 10.794 -2.53 0.011 -48.518 -6.173 nsdrainkg -0.827 5.032 -0.16 0.869 -10.698 9.044 _cons -348.987 204.214 -1.71 0.088 -749.553 51.580 sigma_u 147.019 sigma_e 250.420 rho 0.256
  33. 33. Preliminary results: formal remittances valfgov Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize 13.275 16.458 0.810 0.420 -19.008 45.557 ratiorainbp -528.03*** 123.797 -4.270 0.000 -770.851 -285.198 ratiorainbg -232.247** 93.743 -2.480 0.013 -416.123 -48.371 ratiorainkp -170.022 106.027 -1.600 0.109 -377.993 37.949 ratiorainkg 113.800 576.873 0.200 0.844 -1017.740 1245.337 nsdrainbp 61.405*** 20.070 3.060 0.002 22.037 100.772 nsdrainkp 7.198 12.464 0.580 0.564 -17.249 31.646 nsdrainbg 56.836*** 11.955 4.750 0.000 33.386 80.287 nsdrainkg -3.089 20.122 -0.150 0.878 -42.559 36.381 _cons 735.959 603.127 1.220 0.223 -447.074 1918.992 sigma_u 441.287 sigma_e 847.087 rho 0.2135
  34. 34. Preliminary results: informal remittance equation valfissn Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize 19.971* 11.664 1.71 0.09 -2.908 42.850 ratiorainbp -211.014* 110.387 -1.91 0.06 -427.538 5.509 ratiorainbg 166.626 128.343 1.30 0.19 -85.118 418.370 ratiorainkp 350.320** 175.964 1.99 0.05 5.168 695.473 ratiorainkg -193.402** 81.336 -2.38 0.02 -352.943 -33.861 nsdrainbp 72.423*** 27.290 2.65 0.01 18.892 125.953 nsdrainkp -41.187** 16.278 -2.53 0.01 -73.116 -9.257 nsdrainbg 22.507* 13.218 1.70 0.09 -3.420 48.433 nsdrainkg 19.838** 9.282 2.14 0.03 1.631 38.045 _cons -165.305 325.026 -0.51 0.61 -802.844 472.234 sigma_u 713.442 sigma_e 541.430 rho 0.635
  35. 35. Preliminary results: off-farm labor equation nddwkp4m Coef. Robust Std. Err. t P>|t| [95% Conf. Interval] fhhsize 0.450 0.335 1.34 0.18 -0.207 1.106 ratiorainbp -59.914*** 8.299 -7.22 0.00 -76.191 -43.637 ratiorainbg -6.886 7.210 -0.96 0.34 -21.028 7.256 ratiorainkp -15.273* 8.467 -1.80 0.07 -31.880 1.334 ratiorainkg -56.293*** 10.082 -5.58 0.00 -76.069 -36.517 nsdrainbp 7.354*** 1.624 4.53 0.00 4.168 10.541 nsdrainkp 3.063*** 0.810 3.78 0.00 1.474 4.651 nsdrainbg 4.502*** 1.176 3.83 0.00 2.195 6.808 nsdrainkg 3.106*** 0.717 4.33 0.00 1.700 4.511 _cons 144.093 21.548 6.69 0.00 101.829 186.358 sigma_u 23.137 sigma_e 33.697 rho 0.320
  36. 36. Component three – distilling policy relevant implications • Evidence of broad adaptation • Crop choice • Off-farm labor • Migration • Safety net utilization (formal vs. informal) • Evidence of real welfare costs of • Mean rainfall decreases • Variance Increases • Further research • Simulations linking historic and predicted rainfall to crop changes • Better (varying) timeframes for climate impacts • Better specification of variance impacts • Relative size of benefits from adaptation alternatives • Guidelines for integrated policy support for adaptation • Partnering with AGRA

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