Pakistan Institute of Development Economics, Islamabad&

International Development Research Centre , Canada

IMPACT OF CLIMATE CHANGE ON AGRICULTURE IN PAKISTAN:

A DISTRICT LEVEL ANALYSISby

Sajid Amin, Munir Ahmad and Muhammad Iqbal

Project: Climate Change, Agriculture, and Food Security in Pakistan: Adaptation Options and Strategies

The Outline

The Project: A Snapshot of the activities underwayThe Secondary Data Analysis

Conceptual FrameworkData: The ConstructionEconometric MethodologyEstimation Techniques

Expected/Emerging ResultsSharing the Key Findings from Rural Rapid Appraisal

Evidence for Climate ChangeAdaptations and Mitigation Strategies

Pakistan is the most vulnerable countries in South Asia.

OVERVIEW

In 2010 floods, 20 million people were seriously affected – women, elderly, children, poor

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

1. Impact of Climate Change on Wheat Production: A District Level Analysis.2. Evaluating the Impact of Climate Change on Rice Production in Selected

Districts.3. Evaluating the Impact of Climate Change on Cotton Production in Selected

Districts.

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.

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

DEPENDENT VARIABLE INDEPENDENT VARIABLE

Data: The Construction

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.

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)

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)

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)

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

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

Project Outcomes

Water Point

Courtesy: PIDE-IDRC Project on “Climate Change and Agriculture in Pakistan

Houses of the communityHappy after drinking Water water

Height of self discipline

Thank You All