Pakistan Institute of Development Economics, Islamabad &

1. IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN PAKISTAN:A DISTRICT LEVEL ANALYSISbySajid Amin, Munir Ahmad and Muhammad IqbalProject: Climate Change, Agriculture, and Food Security in Pakistan: Adaptation Options and Strategies Pakistan Institute of Development Economics, Islamabad & International Development Research Centre , Canada

2. The Outline • The Project: A Snapshot of the activities underway • The Secondary Data Analysis • Conceptual Framework • Data: The Construction • Econometric Methodology • Estimation Techniques • Expected/Emerging Results • Sharing the Key Findings from Rural Rapid Appraisal • Evidence for Climate Change • Adaptations and Mitigation Strategies

3. In 2010 floods, 20 million people were seriously affected – women, elderly, children, poor OVERVIEW • Pakistan is the most vulnerable countries in South Asia.

4. OVERVIEW OF THE PROJECT: THE EXPEDITIONS UNDERWAY • HOUSEHOLD FARM LEVEL SURVEY • Punjab, Sindh and KPK (Baluchistan excluded for security reasons) • UNIT: Farm Household (Male, Female and Village level questionnaires) • SELECTED DISTRICTS (THROUGH PPS) • Punjab—7, Sindh—4 and KPK—3 • SAMPLE SIZE—200 households from each district • Random selection of Union Council (UC) from districts • Random selection of Village from UC—12 from each district • 17-18 households from each village • SECONDARY DATA ANALYSIS: • Panel Data Estimations -- Four studies underway • Impact of Climate Change on Agriculture in Pakistan: A District Level Analysis • Impact of Climate Change on Wheat Production: A District Level Analysis. • Evaluating the Impact of Climate Change on Rice Production in Selected Districts. • Evaluating the Impact of Climate Change on Cotton Production in Selected Districts.

5. OVERVIEW OF THE PROJECT: THE EXPEDITIONS UNDERWAY • HOUSEHOLD FARM LEVEL SURVEY • Punjab, Sindh and KPK (Baluchistan excluded for security reasons) • UNIT: Farm Household (Male, Female and Village level questionnaires) • SELECTED DISTRICTS (THROUGH PPS) • Punjab—7, Sindh—4 and KPK—3 • SAMPLE SIZE—200 households from each district • Random selection of Union Council (UC) from districts • Random selection of Village from UC—12 from each district • 17-18 households from each village • SECONDARY DATA ANALYSIS: • Panel Data Estimations -- Four studies underway • Impact of Climate Change on Agriculture in Pakistan: A District Level Analysis • Impact of Climate Change on Wheat Production: A District Level Analysis. • Evaluating the Impact of Climate Change on Rice Production in Selected Districts. • Evaluating the Impact of Climate Change on Cotton Production in Selected Districts.

6. IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN PAKISTAN: A DISTRICT LEVEL ANALYSIS • Theoretical Framework • Economic Model • Ricardian Approach • Land Value, Land Rent, Land Profits as dependent Variable • Production Function Approach • Yield, Aggregate output, Agriculture Production Index as dependent variable • Primal approach • Dual Approach • WHY PRODUCTION FUNCTION APPROACH, • Ill-structured and semi-structured agriculture markets in the developing countries (Land rent or value do not reflect land returns) • Allows the direct estimation of the extent of impact of climate changes through incorporation of temperature and precipitation • While controlling the outcome for physical and biological variables using historical data. • Data Limitations

7. Data: The Construction DEPENDENT VARIABLE INDEPENDENT VARIABLE DATA:District level panel n=123 districts, t= 1980-2010 (30 years), Agriculture Production Index Laspeyres’ Quantity Index Temperature Each 3 months mean ( 20 years moving average) (climate impact) Year to year 3 month mean (Weather impact) Precipitation Total rainfall (annual) Standardized precipitation) tractors, tube-wells, irrigated area (as share of total area) Total cultivated area, shared area of crop, fertilizers, and quadratic and interaction terms of temperature and precipitation.

8. IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN PAKISTAN: A DISTRICT LEVEL ANALYSIS: THE METHODOLGY • Econometric Techniques: The Options • Fixed Effect (FE) or Random Effect (RE) • Heterogeneity of the sample • FE or RE • Hausman Test • GENERALIZED METHOD OF MOMENTS • The justification • Time-invariant county characteristics such as geography and demographics may be correlated to those explanatory variables. • Lagged yield (determines the level of fertilizers used etc.) • Prices (in agriculture production index, fertilizers price index) • Endogeniety • The solution • Instrumental Variable approach • Arellano-Bond (Difference GMM) • Blundell and Bond- System GMM (N>T)

9. GMM-The Execution • Instruments (internal) • Lagged yield (shocks) , Weather (temperature variance), all exogenous variables in the model • Robustness of the estimates: • Across time (decade wise analysis) • Region (Province or Agro-ecological zones) • Irrigated vs. Non irrigated area • Sensitivity Analysis (different specifications) • Misspecification tests and Residual Analysis • Sargan Stat (j-stat) • Validation of instruments used • Higher order Serial Correlation test • Q and Adjust Q test • Hetroskedasticity and Auto-correlation Corrected (HAC) Standard Errors (Robust SE)

10. Expected (Emerging Results) • Temperature (growing season & degree days): Negative & non-linear • Precipitation: Positive but non-linear • Temp*Precipitation • Positive and significant (may be negative in terms of humidity) • Special context of this study • A summation crops (API) may dampen the climate change impact • Fertilizers • positive (impact will also be controlled for irrigation and non-irrigation land) • Expected to vary in significance and impact magnitude • Tractors (number): Positive • Tube wells (number): Positive • Total area under cultivation: Positive • 4 variables—shares of cropped area under wheat, Rice, cotton & sugarcane (Increase in crop cultivation) • Positive but uncertain (depends on profitability and impact on soil)

11. RRA: KEY FINDINGS—farmers’ perceptions • Climate Change- The evidence from Rural Pakistan • Winter shortened—sets late & ends early and Summer prolonged • Temperature increased—both in winter & summer • Late monsoon rains—more heavy in certain areas. • Frost reduced but may occur in late winter months • Climate Change- The Adaptation and mitigation strategies • Use of deep tillage for rainwater harvesting/moister conservation • Building small check dams & wells/Tubewell increased in water stress areas • Deep rooted crop mustard adopted—planting delayed 15-30 days • Wheat sowing delayed by 20-30 • Water conserving technologies adopted—ridge sowing, laser leveling, zero-tillage, wheat in standing cotton, cotton-mustard intercropping, sugarcane-wheat intercropped, sugarcane-mustard intercropped and other intercropping combinations

12. Project Outcomes • Policy & research gaps identified; Institutional capacity enhanced through training; • Comprehensive knowledge on adverse climate events happened overtime documented for different agro-ecologies; • Experimental data interpreted in relation to CC variables; • Emerging challenges for R&D specified from CC perspective • Impacts of adoption technological packages analysed at household and regional levels • Critical factors influencing adoption identified • Preparation of HH and area specific action plans to combat CC effects • Feasibilities of best practices developed for replication under relevant situations

13. Thank You All