Understanding Technology Adoption and diffusion: Fertilizer

in Western Kenya14.74-Lecture 13, March 29, 2004

Prof. Esther Duflo

The questions

• Why do some technologies that seem very good do not spread in some environment, and spread in others? – Deworming medicine– Condoms to protect from AIDS

• Fertilizer: cheap, divisible, well understood by scientists, very profitable, adopted in some countries/areas, and not in others.

Raising Productivity in Kenyan Agriculture

• Chemical fertilizers give excellent results in model farms, and this suggests they could be extremely profitable.

• They are suitable for the environment.• They are recommended by the ministry of

agriculture and promoted by agricultural extension agents

• They are widely used in some parts of the developing world (India –green revolution--, regions of Kenya)

• Yet, in the Western Province in Kenya, very few people use them (10%-20%).

Possible Reasons of Low Usage

1. -2. -3. -4. -

Field Trials• 5 pilot projects, in 5 successive seasons, on randomly selected

maize farms in Busia district: • Farmers are randomly selected from parents in a school parents’

list to participate in each of the intervention. Comparison farmers are parents from the same parents’ list who have not been selected.

• On each farm, the farmers select 2 or 3 contiguous small plot ofland.– Control plot: everything as usual– Treatment plot(s): fertilizer, sometimes hybrid seed

• We apply the treatment with the farmer and measure yield differences.

• We discuss all results with the farmers• We monitor adoption in future years of these farmers,

comparison farmers, and their neighbors

Results: Is Fertilizer Profitable?• Pilot 1 and 2: we experimented with two

treatments:– “full recommended package”: hybrid seed, fertilizer at

planting, fertilizer at top dressing– Fertilizer only at top dressing

• Rates of returns (not annualized)– Full treatment: 23% pilot 1;-21 % pilot 2– Top dressing: 44% pilot 1; 93% pilot 2

• The “recommended” option is less profitable for these farmers. A much simpler option is more profitable, but they may not know it.

Treatment pilot1 pilot2 pilot3 pilot4 pilot51 teaspoon top dressing -0.40 0.43 -0.231/2 teaspoon top dressing 0.44 0.93 1.481/4 teaspoon top dressing 0.59full treatment 0.23 -0.21

Table 1: Rate of Returns of Using Fertilizer

Is Fertilizer Profitable ?• Pilot 3, 4 and 5: Effect of the quantity of Fertilizer• Two set of “recommended” quantities of fertilizer. • Pilot 1 and 2 were using the low quantity, Pilot 3 and 4

were using the high quantity.• Rate of Returns:

– Pilot 3: -40%– Pilot 4: 43%

• Pilot 5 and 6: we try 3 quantity to determine the optima quantity to use per hole. We confirm that the middle quantity is the most profitable. Rate of returns in pilot 5– -23% for the high quantity– 148% for the middle quantity– 59% for the lowest quantity

Learning by doing

• Did the participation to the trials lead to an increase in adoption?

• We compare adoption of pilot farmer with adoption of comparison farmers, the season after the adoption and in the following seasons

• Adoption increases by 17% first year after pilot, and 9% in second year after pilot.

• Correlate of adoption among pilots: larger returns on own plot, prior use.

one season later two seasons later three seasons later(1) (3) (5)

Pilot 0.172 0.092 0.101(4.01)** (1.65) (1.11)

Constant 0.206 0.241 0.207(7.42)** (7.50)** (5.32)**

Observations 433 284 142

Table 2: Fertilizer Adoption in Future Years

Year 1 Year 2(1) (2)

Rate of returns 0.029 0.031(1.61) (1.46)

Ever use fertilizer? 0.315 0.124(3.40)** (0.91)

Yrs education household 0.005 0.039(0.47) (2.19)*

Ever use any treatment?

Constant 0.226 0.021(3.25)** -0.2

Observations 132 56R-squared 0.12 0.17

Table 3: Impact of Rate of Returns on Future Adoption

Diffusion of adoption

• Pilot 1 had a small sample but large impacts on adoption. No diffusion on agricultural contact.

• Pilot 2 & 3 have larger samples, we interviewed both neighbors and persons listed by farmers as “agricultural contacts”.

• More data is expected from pilot 4 and 5.

Pilot 1 adoption (Top Dressing)

Pilot (%) Comparison (%) DifferenceA. BEFOREEver used TD Fertilizer before? 5.00 3.53 1.47

(4.80)Used TD during season before pilot, Spring (LR) 2000? 0.00 10.00 -10.00

(7.26)

B. AFTERUsed TD during season after pilot, Spring (LR) 2001? 36.67 9.48 27.18

(7.00)Used TD two seasons after pilot, Fall (SR) 2001? 20.00 9.91 10.09

(7.13)Used TD three seasons after pilot, Spring (LR) 2002? 23.08 10.92 12.15

(7.29)

Friends of pilot Friends of comparison Difference

Used TD during season after pilot, Spring (LR) 2001? 10.81 13.97 -3.16(6.34)

use fertilizer use fertilizer or seeds(1) (2)

PANEL A: AGRICULTURAL CONTACTS (PILOT 2 and 3)Contact of Pilot 0.071 -0.007

(0.91) (0.08)Constant 0.182 0.318

(2.86)** (4.52)**Observations 135 134

PANEL B: NEIGHBORS (PILOT 2)Neighbor of Pilot -0.147 -0.099

(2.10)* (1.33)Constant 0.282 0.302

(6.31)** (6.37)**Observations 144 145

one season later

Table 4: Diffusion

Why was there no diffusion?

• 1-• 2-• 3-• 4-

Why doesn’t technology diffuse ?

• Learning by doing is not critical – We invited Neighbors to agricultural trials.– Adoption of invited neighbors is as large as adoption of pilot

farmers themselves!• Farmers are able to learn by themselves

– We distributed “starter kits” – Adoption after starter kits almost large as after pilot

• Farmers know very little about each other:– 46% farmers correctly state when their neighbor planted– 39 % farmers agree about whose harvest was better.– Pilot farmers and their neighbors do not have more accurate

information about each other than comparison farmers and their neighbors

(1) (5)pilot vs comparison 0.172

(4.01)**Invited pilot friend vs. comp. friend 0.178

(2.12)*Invited pilot friend vs. uninvited pilot friend 0.107

(1.56)Constant 0.206 0.182 0.253

(7.42)** (2.65)** (5.24)**Observations 433 133 180

one season lateruse fertilizer

Table 5: Impact of Being Invited to the Agricultural Trials

use fertilizer use fertilizer or seeds

(1) (2)Treatment 0.073 0.127

(1.54) (2.45)*Constant 0.16 0.189

(4.84)** (5.25)**Observations 277 276

Starter kits Table 6: Impact of Starter Kits

Understanding technology adoption: Key facts

• Low level of fertilizer adoption in Western Kenya• Fertilizer adoption increases when farmers experiment

with fertilizer, but not to 100%• Adoption level decrease over time (“forgetting”)• There is little or no diffusion of adoption to neighbors or

“agricultural contacts”• Farmers know little about each other’s farms. • It is possible to learn from watching your neighbor:

farmers who were invited to the trials adopt as much as other farmers

• On all of these dimensions, the situation seems to be better elsewhere (pineaple in ghana, HYV in India).

Outline of a model • The model endogeneizes flows of information

between people. • Key features:

– There is some cost of meeting other people and exchange news:

• Have to go out to meet them• Have to take the responsibility if the idea is bad and fail

– People “forget” ideas or die– Not everybody can implement ideas (e.g. there is a

necessary investment and there is little savings in the environment).

Key intuition and results

• There may be multiple equilibria. • Why? • High adoption, high diffusion:

––

• Other equibrium?

The model• There is a population of size N. • Probability to acquire information exogenously in

each period is p. • People die or forget information with probability

D.• Meeting cost c. • With probability q, a meeting result in an idea

being exchanged, learnt and adopted. • The value of a piece of information that is

exchanged is normalized to 1.

Conditions for an equilibrium where everybody stays home

Suppose the equilibrium is such that everybody stays home. Then the number of ideas held by an individual evolved according to dN/dt= p - DN

• so in steady state, average N is p/D• Given this, the average information that would

be gained by meeting someone is p/D. • If p/D < c meeting someone is not worthwhile

and there is an equilibrium• Low p, high D, high c make it more likely.

Conditions for an equilibrium where people seek each others

• If Ni if the number of idea of individual i, the evolution of idea for i is:

E[∆Ni]=p+qE[N]-DNi

Hence, in steady state, for the population:p=(D-q)E[N]

N*=p/(D-q) if q<, or N=∞ if q>D (complete diffusion)

It will be worth meeting other people if qp/(D-q) >c

Multiple steady states• If p/D < c and qP/(D-q) >c, then there can be

multiple steady states.• In one steady states, people do not meet, they

do not exchange ideas there are few ideas around.

• In one steady state, people, meet, they exchange idea, and the flow of ideas is large

• Examples: – Route 128 vs Sillicon Valley (Saxenian).– Western Kenya vs other areas in Kenya.

Application to the case of fertilizer in Kenya

• Low level of adoption, low level of information transmission.

• Low saving make q low: adoption after having seen the returns only 17% higher, even though everybody would like to use fertilizer after our experiment. The adoption rate increases dramatically when we offer the commitment savings product to pilot farmers (take up of scheme is 50% to 80% among pilot farmers).

• Low savings rates and high death rates also increase the “death rate” of ideas: rate at which people forget over time: 50%

• If many not so great ideas circulate, this is equivalent to increase c (since value of ideas is normalized to 1). Main idea that circulates is that using fertilizer+hybrid is the most profitable investment (plus, overuse) which turns out to be wrong according to our data.

Summary: Learning• Low adoption and low diffusion of fertilizer• Possibly stuck in a bad steady state, where

there is nothing to discuss and therefore nobody discusses anything

• Temporary introduction of new ideas may help the economy switch to a permanently higher equilibrium.

• Role for (better) agricultural extension and starter kits. We are starting a larger school-based intervention combining demonstration, debriefing, and starter kits.

Why not everybody?• Adoption only go up by 17% after the initial

experiments. We have seen this can be a reason for low diffusion.

• Can we take the explanation “we have no money” seriously.

• Even a little bit of money is enough to start: Fertilizer can be used in small quantities. Credit constraint is unlikely to be the only reason.

• Help farmers to save by offering them a commitment device: we offer to sell them fertilizer right after harvest, when they still have money, and to store them until they need it.

SAFI: Savings and Fertilizer Initiative

• Farmers complain about lack of money• SAFI: help farmers to save to use fertilizer.• First SAFI: we visited 54 farmers right after

harvest and offered them to sell them fertilizer and deliver it to them when they need it. Came back after 2 days to get the money and confirm order.

• 34 farmers agreed and asked us to come back. 12 farmers eventually purchased fertilizer.

• Even if all those who were previously using fertilizer took up the scheme, adoption has increased by 12%.

Combining Learning and SAFI

• After pilot IV, we bought everybody’s maize on pilot and treatment plots.

• For half the farmers, we proposed to sell them a fertilizer voucher right away

• We offered the scheme to 35 farmers, and 29 accepted it.

• Compare adoption in pilot I (33%) to this number (83%). A large effect…

Value of comitment

• After pilot 5, we offered SAFI, in three groups:– One group was offered the scheme right away– One group was told that we would come back in a few

days (if they were interested)– One group was told that we would come back at

Harvest time (if they were interested). • In all three cases, 50% of farmers expressed

interest. After 2 days, only half of those who were offered the money buy fertilizer. After several months, nobody does.

Conclusions

• Learning is slow, in part because low savings slow adoption. Simple, effective technology does not diffuse.

• Remaining questions:– What role do the family and the neighbors

play? – Does maize itself serve as a commitment

device (in turn slowing down fertilizer purchase and adoption)?