The Crop Connection: Impact of Cell Phone Access on Crop...

The Crop Connection: Impact of Cell Phone Access onCrop Choice in Rural Pakistan

Saher Asad

Lahore University of Management Sciences

[email protected]

June 20, 2016ABCDE 2016

Saher Asad (LUMS) Crop Connection June 20, 2016 1 / 47

Motivation

Cash crops can have positive impacts on development (World Bank,2008; IFPRI,2013; FAO,2014)

Cash crops are often highly perishable Profitability

In developing countries - storage is limited, market linkages are weak

Risk of high post-harvest losses deters production

Can the cell phones mitigate this risk?


This Paper

Provides estimates for impact of cell phone access on crop choicealong the perishability dimension

Mechanisms

“Farmer-Trader Coordination (FTC)”“Price Information Effect (PIE)” - (e.g. Jensen, 2007; Aker, 2010;Goyal, 2010; Muto and Yamano, 2009; Nakasone, 2013; Mitra et al.,2013)“Weather Information Effect (WIE)” - (e.g. Cole and Fernando,2012; Fafchamps and Minten, 2012)

Distinguish effects

Income and Consumption


Context: Pakistan

Agriculture constitutes 21% of GDP in Pakistan

Punjab(study region) is the hub of agriculture

Farmers grow 4-6 crops in a year

Farmers are constrained by storage and timely sale

Traders are constrained by limited capacity and power outages


Evidence from Field

“Before I had a cell phone I harvested my crop and then had to wait for atrader to buy my crops; now I talk to the trader and harvest my cropswhen he will buy it.”- Farmer in Rural Pakistan

“I cannot buy an unlimited amount of crop in one day. The power keepsgoing out and I cannot store these crops for very long period. The retailersdont like to buy rotten crops.”- Trader in a Mandi

“Farmers can adjust the watering schedule to adjust the harvest date upto 10 days.”- Agricultural Expert


Model

Agriculture Household Model (De Janvry and Sadoulet, 2006;Dercon, 1996) highlights the role of coordination in farmer productionchoices Assumptions Baseline CellPhone

Solving the model gives the following results

Result 1:CellPhone → ProbabilityofSalec ↑→ SharetoPerishablec ↑

Result 2:CellPhone → ProbabilityofSalenc ↓→ SharetoPerishablenc ↓


Identification Strategy

Cell Phone coverage is endogenous- heavily provided to rich areas

Coverage Restricted from villagesin 10 km of border with India -“Dead Zone”

Enforced with: (a) Strategic TowerPlacement; (b) Jammer Placement

Does not coincide with the “NoMan’s Land” (500m)

Spatial Regression Discontinuity

India

µ

1:1,250,000

Legend

International Border

District Boundary

Dead Zone Boundary

Villages Without Cell Phone Coverage

Villages With Cell Phone Coverage


Village Level Data


Household Level Data


Estimation

Covariates are balanced Village

Household

Fuzzy RD for village data

Sharp RD for household data

Due to the sample size limitations Iadopt a semi-parametric estimationmethod based on Dell(2010)

Present results for quadratic, cubicand quartic polynomials inEuclidean distance and lat-long

India

µ

1:1,250,000

Legend

International Border

District Boundary

Dead Zone Boundary

Villages Without Cell Phone Coverage

Villages With Cell Phone Coverage


Discontinuity in Probability of Producing Perishable Crop

0.0

0.2

0.5

0.7

0.9

Pro

babi

lity

of G

row

ing

Ext

rem

ely

and

Hig

hly

Per

isha

ble

Cro

ps

−10 −5 0 5 10Distance from Restriction

Density Smoothness


Discontinuity in Area Allocated to Growing PerishableCrops

0.0

0.3

0.5

0.8

1.0

Are

a U

nder

Ext

rem

ely

and

Hig

hly

Per

isha

ble

Cro

ps

−5 0 5Distance from Restriction

Density Smoothness


Is this a Major Crop in the Village?

(Degree of Perishability of Crop)

(Extremely & Highly) (Least) (Extremely & Highly) ( Least)

(Probit)Cell Phone 0.31*** 0.09 0.29*** 0.12

(0.06) (0.08) (0.11) (0.16)

(Quadratic in Distance from Restriction)Cell Phone 0.23*** 0.032 0.26*** 0.02

(0.03) (0.04) (0.03) (0.04)

(Quadratic in Lat-Long)Cell Phone 0.24*** 0.012 0.25*** 0.09

(0.02) (0.09) (0.03) (0.07)

Controls Y Y Y Y

District Dummies, Crop Dummies, Dist Crop Dummies Y Y Y Y

Number of Observations 1785 1785 1094 1094Size of Band Around Restriction 10km 10km 5km 5kmMean of Control Group 0.15 0.89 0.18 0.92

∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Percentage of Area Under Crop


(Extremely) (Highly) (Least)

(OLS)Cell Phone 0.28*** 0.19*** -0.48***

(0.08) (0.06) (0.18)

(Quadratic in Distance from Restriction)Cell Phone 0.245*** 0.16*** -0.411***

(0.11) (0.02) (0.09)

(Quadratic in Lat-Long)Cell Phone 0.265*** 0.18*** -0.37***

(0.08) (0.03) (0.06)

Controls Y Y Y

District Dummies, Crop Dummies, Dist Crop Dummies Y Y Y

Number of Observations 450 450 450Mean of Control Group 0.11 0.13 0.76

∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Farmer Trader Coordination: Can the Farmer Sell Crops onFirst Trip to Market?



(Probit)Cell Phone 0.58*** 0.42*** 0.03

(0.16) (0.19) (0.07)

(Quadratic in Distance from Restriction)Cell Phone 0.40*** 0.32*** 0.06

(0.07) (0.04) (0.19)

(Quadratic in Lat-Long)Cell Phone 0.49*** 0.31*** 0.07

(0.02) (0.065) (0.17)

Controls Y Y Y



∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Number of DaysSaher Asad (LUMS) Crop Connection June 20, 2016 24 / 47

Farmer Trader Coordination: Percentage of Output Lost toPost-Harvest Losses?



(OLS)Cell Phone -0.37*** -0.21*** -0.11

(0.13) (0.09) (0.14))

(Quadratic in Distance from Restriction)Cell Phone -0.21*** -0.15*** 0.04

(0.09) (0.07) (0.11)

(Quadratic in Lat-Long)Cell Phone -0.25*** -0.13*** 0.05

(0.03) (0.045) (0.15)

Controls Y Y Y



∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Weather Information Effect: Difference Between Actualand Optimal Plantation Date?



(OLS)Cell Phone -8.5*** -4.9*** 1.3

(1.85) (0.75) (1.14)

(Quadratic in Distance from Restriction)Cell Phone -6.43*** -4.28*** -1.12

(0.97) (0.84) (0.91)

(Quadratic in Lat-Long)Cell Phone -4.73*** -3.18*** -0.98

(1.15) (1.12) (0.97)

Controls Y Y Y



∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Weather Information Effect: Log of Crop Yield



(OLS)Cell Phone 0.06*** 0.03*** 0.02

(0.03) (0.01) (0.08)

(Quadratic in Distance from Restriction)Cell Phone 0.05*** 0.04*** 0.01

(0.01) (0.009) (0.02)

(Quadratic in Lat-Long)Cell Phone 0.03*** 0.02*** 0.009

(0.01) (0.006) (0.02)

Controls Y Y Y


Number of Observations 450 450 450

∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Price Information Effect: Percentage Difference BetweenFarmers’ and Market Price



(OLS)Cell Phone -0.34*** -0.38*** -0.29***

(0.14) (0.17) (0.05)

(Quadratic in Distance from Restriction)Cell Phone -0.31*** -0.34*** -0.36***

(0.15) (0.16) (0.09)

(Quadratic in Lat-Long)Cell Phone -0.29*** -0.35*** -0.26***

(0.11) (0.12) (0.07)

Controls Y Y Y



∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Income and Consumption

(Agricultural Income) (Consumption)

(OLS)Cell Phone 0.17*** 0.14***

(0.05) (0.04)

(Quadratic in Distance from Restriction)Cell Phone 0.10*** 0.08***

(0.03) (0.02)

(Quadratic in Lat-Long)Cell Phone 0.13*** 0.10***

(0.05) (0.03)

Controls Y Y

District Dummies, Crop Dummies, Dist Crop Dummies Y Y

Number of Observations 450 450

∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1


Income By Crop Category and Mechanism


Robustness Checks

Use of higher order polynomials

Alternative identification strategy and external validity Full Country

Radio test radio

Pre-coverage placebo test Placebo


Policy Implications and Conclusion

Improving extension services - when to provide critical information?

Post-harvest risk mitigation - coordination, post-harvest Insurance?

Cell phone coverage makes farmers shift towards producing perishablecash crops

Analysis of mechanisms suggest “Farmer-Trader Coordination Effect”dominates in economic importance

Future work: Impacts on Traders, Impacts on Non-AgriculturalHouseholds


THANK YOU


Crop Profitability By Degree of Perishability

Return


Assumptions

A1: 2 crops

A2: Land normalized to 1 and all land cultivated

A3: Extreme Perishability Assumption(EPA)

A4: Participation Constraint (PC) holds

A5: Fair Trader Assumption(FTA)

A6: One Market

A7: Utility Function is: U(c) = cρ and ρ < 1

Return


Baseline Case

Based on FTA probability of sale when no one has cell phone is 1θ = k

Budget Constraint c = σbYp + (1− σb)Ynp

Maximization gives σb

σb =Ynp

Ynp+YpD−1

where D = [( k1−k )(

Yp−Ynp

Ynp)]

11−ρ

Return


Case with Cell Phones

Some fraction α gets cell phone access

Those with cell phone; k = 1

Those without cell phone; k ′ = 1−αθθ−αθ ; k ′ < k

σc = 1 ;

σnc =Ynp

Ynp+YpD−1

where D = [( k ′

1−k ′ )(Yp−Ynp

Ynp)]

11−ρ

Return


Village Level Diff of Means

ReturnSaher Asad (LUMS) Crop Connection June 20, 2016 38 / 47

Household Level Diff of Means

Return


Cell Phones versus Radios

(Probability of Being a Major Crop in the Village)


(Highly & Extremely) (Less & Least) (Highly & Extremely) (Less & Least)

Radio 0.036 0.023 0.034 0.025(0.226) (0.212) (0.242) (0.016)

R-Square 0.24 0.18 0.21 0.14

Controls Y Y Y Y

District FE, Crop FE and District-Crop FE Y Y Y Y

Number of Observations 52,378 52,378 27,059 27,059Sample Full Country Full Country Full Punjab Full Punjab

Controls include percentage of area cultivated, pre-coverage distance from pucca road network, wealth measures like roofstructure of majority of households in the village, elevation, access to agricultural credit and access to irrigation. Theregression also includes set of district specific, crop specific and district-crop specific fixed effects.∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Return


Pre-Coverage Placebo Test



(Highly & Extremely) (Less & Least)

Cell Phone 0.01 0.007(0.03) (0.04)

R-Square 0.15 0.17

Controls Y Y

District FE, Crop FE and District-Crop FE Y Y

Number of Observations 498 498

Controls include percentage of area cultivated, pre-coverage distance from pucca road network,wealth measures like roof structure of majority of households in the village, elevation, access toagricultural credit and access to irrigation. The regression also includes set of district specific,crop specific and district-crop specific fixed effects.∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Return


Farmers Lined Up at the Market to Sell Crops


Perishability Ranking of Crops

Extremely Perishable : Tomatoes, Oranges, Mangoes, Corn, SugarCane

Highly Perishable : Onion, Garlic, Potato, Taro, Peas, Fresh Turmeric

Least Perishable : Millet, Feed, Sorghum, Rice, Wheat, Cotton


Density Smooth at Village Level

0.0

2.0

4.0

6.0

8

−20 −10 0 10 20

Return


Density Smooth at Household Level

0.0

5.1

.15

−5 0 5

Return


Conditional Correlation



(Highly & Extremely) (Least) (Highly & Extremely) (Least)

Cellphone 0.29*** 0.01 0.31*** 0.04(0.004) (0.02) (0.002) (0.1)

R-Square 0.38 0.25 0.29 0.17

Controls Y Y Y Y

District FE, Crop FE and District-Crop FE Y Y Y Y

Number of Observations 52,378 52,378 27,059 27,059Mean of Control 0.12 0.78 0.17 0.85Sample Full Country Full Country Full Punjab Full Punjab

Controls include percentage of area cultivated, pre-coverage distance from pucca road network, wealth measures like roofstructure of majority of households in the village, elevation, access to agricultural credit and access to irrigation. Theregression also includes set of district specific, crop specific and district-crop specific fixed effects.∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Return


Mechanisms : FTC

(Number of Days Between Harvest and Sale)


(Extremely) (Highly) (Less and Least)

(OLS)Cell Phone -8.9*** -6.5*** 2.3*

(2.23) (1.56) (1.40)

(Quadratic in Distance from Restriction)Cell Phone -6.13*** -5.34*** 0.51

(0.05) (0.12) (0.45)

(Quadratic in Lat-Long)Cell Phone -6.96*** -6.15*** 1.23

(1.12) (1.55) (1.85)

Controls Y Y Y



∗ ∗ ∗p < 0.01, ∗ ∗ p < 0.05, ∗p < 0.1

Return


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