Improving Productivity Measurement: Lessons from a Cassava Experiment in Zanzibar, Tanzania

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1 The World Bank Improving Productivity Measurement: Lessons from a Cassava Experiment in Zanzibar, Tanzania Ministry of Agriculture and Natural Resources, Zanzibar

Cassava Productivity in Zanzibar Objectives To identify the best means of estimating productivity (yields per land area) To evaluate the data quality and costs vs.

2 Cassava Productivity in Zanzibar Objectives To identify the best means of estimating productivity (yields per land area) To evaluate the data quality and costs vs. benefits for different measurement approaches Assess the feasibility of implementing each method in national household surveys Document best practices in data collection Collaborating Partners Ministry of Agriculture and Natural Resources, Zanzibar Office of the Chief Government Statistician, Zanzibar The World Bank

3 Estimating Productivity Identification of production per unit of land area requires: 1. Accurate estimate of production 2. Accurate estimate of land area Methods - Direct measurement - Self-reporting Trade-offs - Cost: implementation challenges - Benefit: improved accuracy

Methodologies Tested: Production Cassava production

D1: Crop diaries with BEO visits 2x a week D1

BEO visits 2x per week D2: Crop diaries with

telephone calls 2x per week R1: 6-month harvest

4 Methodologies Tested: Production Cassava production Group CC: Crop-cutting with balance scales CC Method D1: Crop diaries with BEO visits 2x a week D1 Crop-cutting with balance scales Crop diaries with BEO visits 2x per week D2: Crop diaries with telephone calls 2x a week D2 Crop diaries with telephone calls 2x per week R1: 6-month harvest recall survey R1 6-month harvest recall survey R2: 12-month harvest recall survey

5 Methodologies Tested: Land Area Land area Traversing (i.e. compass-and-tape) Group CT Method GPS measurement GPS Traversing (i.e. compass-and-tape) GPS measurement Farmer self-reported area SR Farmer self-reported area

6 2 districts chosen based on large numbers of cassava-producing households: North B and Chake Chake 24 Block Extension Officers (BEOs) from North B 11 Block Extension Officers (BEOs) from Chake Chake 4 treatment arms for cassava production 36 households per BEO 9 households per treatment arm per BEO Sampling Strategy PROJECT SAMPLE 1260 households 864 households in North B District in Unguja 396 households in Chake Chake District in Pemba

7 Randomized Control Trial: Production 315 households: Crop diaries with BEO visits 2x per week (D1) 315 households: Crop diaries with telephone calls 2x per week (D2) 315 households: 6-month harvest recall survey (R1) 315 households: 12-month harvest recall survey (R2)

8 Randomized Control Trial: Production Crop-cutting with balance scales

9 Multiple Measures: Land Area All 1,260 households: Traversing (compass-and-tape) (CT) GPS measurement (GPS) Farmer self-reported area (SR)

10 Project Timeline Timeline: Training: North B and Chake Chake April month recall survey (R1A) November 2013 Pilot: North B and Chake Chake May 2013 Area measurement: Compass-and-tape GPS August 2013 January 2014 Cassava diaries: D1 BEO visit D2 CATI call Crop cutting June 2013 May 2014 August 2013 May month recall survey (R2) and 6-month recall survey (R1B) May 2014 Data entry May 2013 July 2014

11 Data Analysis Objectives Comparison of production measurement methods Recall surveys vs. cassava diaries vs. crop-cutting Comparison of land area measurement methods GPS vs. compass-and-tape vs. farmer self-reporting Implications for yield measurement

12 Cassava Production by Household Type June August September D1 D2 R1 R2 Crop Cut July October November December January February March April May TOTAL

13 Cassava Production using Crop Cutting Estimates Density 0 1.0e e e e e hh_prod_kg_cc

14 Density 0 Cassava Production by Household Type 2.0e e e e-04 D1 Density 2.0e e e-04 D hh_prod_kg_imp hh_prod_kg_imp Density 2.0e e e-04 R1 0 Density 2.0e e e e hh_prod_kg_imp 0 R hh_prod_kg_imp

15 T-Tests: Diary vs. Recall Mean D1 Mean R1 T-stat P-Value Diary-Visit vs. 6-mth Recall Mean D2 Mean R1 T-stat P-Value Diary-Phone vs. 6-mth Recall Mean D1 Mean D2 T-stat P-Value Diary-Visit vs. Diary-Phone

Area Measurement, by method 1079 m² average plot size measured by compass-and-tape 1107 m² average plot size measured by GPS 2736 m² average plot

16 Area Measurement, by method 1079 m² average plot size measured by compass-and-tape 1107 m² average plot size measured by GPS 2736 m² average plot size measured by farmer self-reporting 153.6% difference between farmers estimates & compass-and-tape 2.6% difference between GPS & compass-and-tape

17 Density 2.0e e e e Area Measurement, compass vs. GPS Compass GPS Density 2.0e e e e Area with compass (square meters) Self-report Area with GPS (square meters) 5.0e-04 Density Area with farmer estimation (square meters)

18 Area (m 2 ) by quintiles (compass): compass vs. GPS Compass GPS % Difference Q % ( m 2 ) Q % ( m 2 ) Q % ( m 2 ) Q % ( m 2 ) Q % ( m 2 ) Total %

19 Area (m 2 ) by quintiles (compass): compass, GPS and self-reporting Compass GPS SR Q ( m 2 ) Q ( m 2 ) Q ( m 2 ) Q ( m 2 ) Q ( m 2 ) Total

20 Mean yields (kg/m 2 ), by method & type Compass GPS SR Crop Cutting D D R R

21 Lessons Learned from Implementation Capacity/experience Agricultural extension officers; data entry staff Call center set-up Zantel; airtime vs. phone Connectivity Pemba Procurement delays Non-standard units Participation rates Incentive packages for staff

22 Key Lessons on Productivity Measurement Land Area: Self-reporting clearly subject to huge error GPS and compass-and-tape nearly identical GPS preferable based on time and cost implications Production: 12-month recall clearly problematic Clear benefits to reducing recall period (6-mth recall) Production diary with phone monitoring looks to be promising Crop cutting for cassava: gold standard or upper bound?

23 Next Steps Establish cost implications for each method Investigate lower reported production for D1 households Check on regularity of visits Evaluate CATI data Cross-check with harvests recorded in diaries Check on regularity of phone calls during harvest periods Investigate high crop cutting yields Number of subplots Number of plants in plots

24 Questions?

Methodological Validation and Research on Root Crops Collaboration LSMS- Global Strategy Measuring Cassava Productivity in Zanzibar and Malawi

Methodological Validation and Research on Root Crops Collaboration LSMS- Global Strategy Measuring Cassava Productivity in Zanzibar and Malawi GERO CARLETTO Development Research Group The World Bank Presented