Workshop Trade-off Analysis - CGIAR_19 Feb 2013_Keynote Dave Harris

Wide boundaries for rural systems:

implications for household decision-making and adoption of agricultural technology.

Dave Harris

ICRISAT Nairobi

19th February 2013

Outline

1. Concepts for Research with Development Outcomes

2. Sustainable Intensification

3. Profitability and Technology;

4. Profitability, Land and Household Per Capita Income;

5. “Intensificationability” – the potential for HHs to benefit from

intensification.

6. Decision-making.

CGIAR Drylands System - Core Concepts

ICRISAT Strategic Plan:Inclusive Market-Oriented Development (IMOD)

Sustainable Intensification (SI)

General consensus (CGIAR-CRPs, USAID, etc) that this is the way forward for

rural households to:

Reduce / get people out of poverty

Improve food security

Three Propositions

1. No adoption = no impact (= no Developmental Outcomes)

2. Intensification = more investment (cash, credit, labour, effort, etc)

3. More investment = more exposure to risk (more to lose)

With the key concepts and the three propositions in mind, we need to:

• Develop better understanding of, and relationships between, risk, resilience, vulnerability, food security, sustainable intensification, investment, profitability, off-farm opportunities, surpluses, markets etc.

(Sustainable) Intensification (SI)

Some questions:

Ignoring sustainability for now, can rural households intensify their

agricultural enterprises by adopting improved technology?

Are there limits to how much they can intensify?

What are the consequences (impacts) of intensification for rural

households?

Productivity versus Profitability

We all concentrate on increasing the productivity of (rainfed) crops,

cropping systems, etc.

However, it is the net return (profitability) from investments (cash, labour,

time, etc) that may be important to a farming household and is likely to

influence adoption of new technologies.

-500

0

500

1000

1500

2000

Base Improved

Cases

Net

retu

rns

($/h

a/se

ason

)Literature survey of net returns from improved rainfed technology. Values converted to 2005

Purchasing Power Parity for comparisons across time and between countries.

Median values:Base = $186Improved = $558

Technologies exist that can substantially increase profit

There seem to be limits

Profitability, Land and Household Per Capita Income

The amount of land required for any household to achieve a given value of income per person from crop production depends on: the profitability of any cropping enterprise and the number of people in the household.

To achieve a threshold of $1.25 / person / day, the relationship is:

y = (365/x) * n * 1.25

Where:

y = land required per HH (hectares)x = net returns from the enterprise ($ / ha / year)n = number of persons in the HH

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

Net return ($/ha/yr)

Land

requ

ired

for $

1.25

(ha/

HH

)

N = 4

N = 2

N = 1

N = 6

Land required per household for a given Net Return to produce $1.25/person/day (1 season/year)

Base $186/ha/season

Improved$558/ha/season

80 % of farms in SSA are now below 2 ha (Nagayets, 2005).

“Intensificationability”

0 0.5 1 1.5 2 2.5 3 3.5 4 4.50

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Nr New tech $558/haNr/ha/seasonIPLNr/ha/seasonIPL70%Nr/ha/seasonIPL30%Income/HH/season from $558/ha

Farm size (hectares)

Net

inco

me

from

cro

ps ($

/ha/

seas

on)

Maintaining net income per hectare as farm size increases and effect of off-farm income for a family of five in relation to an IPL of $1.25/person/day (one season per year).

$2281/year required for a family of 5 to have $1.25/person/day

0 100 200 300 400 500 600 700 8000

10

20

30

40

50

60

70

80

Net returns ($/ha/season)

% H

Hs

with

$1.

25/p

/d

Tougou 4.4

D1 Tanz. 11.19

R. Valley 0.68

Makueni 10.44

Kadoma 9.61

Lawra-Jirapa 6.18

Degree to which communities can benefit from intensification - examples

Values are the slopes of the lines x 102

Impact of intensification depends on where you are, who you are and what you have

Questions:

Do we have technologies appropriate for Dryland environments?

• Almost certainly, although fine-tuning is still required and there is need for consideration of climate change.

Do we have technologies appropriate for Dryland rural households?

• Not so sure because we know very little about what criteria rural households use to make decisions about investments.

What can be done

What ‘farmers’ can do

What ‘farmers’ will do:1. Will it work?2. What’s the ‘cost’?3. What’s the risk?4. Is it worth my while?5. Is it my best option?

Agricultural technologies

Prospect theory Halo effect Risk aversionConflict (between alternatives) Judgment heuristics Asymmetry of knowns/unknowns

Intuition Sequence of exposure ConsensusOverconfidence Intensity matching Question substitution (heuristics)

Familiar narratives Content versus reliability Anchors (expectations)Comfort zones Suggestion Availability (inf. recall ease)

Natural tendencies Availability cascade (policy, public opinion)

Understanding probability

Impressions Base rates RepresentativenessCognitive ease/strain Stereotyping Conjunction fallacy

Opinions Narrative fallacies PlausibilityHunches Loss aversion Hindsight bias

Mental effort Confirmation bias Associative coherenceFear of ridicule Perception of risk Common bias in groups

Association of ideas Familiarity Regression to the meanPriming Attitude Mood

Affect heuristic (feel/think) Experience NormalityRepetition State of mind Surprise

Personal world view Morality ValuesCulture Sequence of questioning

Some issues, processes, phenomena, etc., influencing decision-making (Daniel Kahneman)

Risk and return with fertilizer application

0 Kg/ha 20KgN/ha 40kgN/ha 60 kgN/ha 80 kgN/ha

Average Yield (kg/ha) 1213 2185 2612 2666 2674Best yield (kg/ha) 2802 3399 3447 3475 3511

Optimistic Yield(kg/ha) 1568 2497 3005 3104 3136Expected Yield (kg/ha) 1207 2209 2806 2853 2874

Pessimistic Yield (kg/ha) 694 1861 2298 2466 2482Worst Yield (kg/ha) 0 903 522 472 438% years with >10 kg

grain/kg N87% 83% 74% 74%

Value cost ratio >2 73% 61% 52% 42%

Modeling risks and returns from use of N – Mwingi, Eastern Kenya, using APSIM and weather data from 1962-2006 (KPC Rao)

“Eneless Beyadi appears through a forest of maize clutching an armful of vegetables and flashing a broad smile. Beyadi cultivates about half a hectare of plots in the village of Nankhunda, high on the Zomba plateau in southern Malawi. She gets up at 4 a.m. every day to tend her gardens, as she lovingly calls them, before heading off to teach at a school.”

‘ DIRT POOR: The key to tackling

hunger in Africa is enriching its soil.

The big debate is about how to do it.’29 MARCH 2012 | VOL 483 | NATURE | 525

Full-time farmers?

No. Enterprise Turnover a

(MK/month) bOperating costs c

(MK/month)Net income f (MK/month)

Returns to labour g (MK/day)

1 Brewing local gin( kachasu) 2947 2144 1324 402 Selling goat hides 2900 2259 2435 783 Selling fried fish (kanyenya) 3600 3076 1052 444 Trading maize and flour

- ADMARC maize- flour

100

662-805

78

547-340

57

350-531

31

48-163

5 Selling cooked food (zophikaphika) 868 750 469 50

6 Selling snuff 284 241 97 367 Trading maize bran (madeya)

- wet season (town)- wet season (village)- dry season

480100

1400

41685

904

352852

8 Tailoring 3300 2410 2203 379 Village shop-keeping 8000 6771 1625 26

10 Village carpentry 675-1180 263-402 647-1152 61-6811 Building houses 1200 546 1166 5012 Agricultural labour (ganyu)

- land preparation- weeding

--

--

676312

25-40

26

13 Permanent labour - - 1024 2814 Estate labour - - 526 2215 Selling firewood 263 0.75 262 1416 Moulding bricks - - - 2917 Selling thatching grass 500 31 469 5018 Making baskets 1170 841 1003 2519 Making mats 144 196 137 720 Making granaries (nkhokwe) 195 195 195 3021 Making hoe and axe handles 20 48 18 922 Selling herbal medicine 667 171 667 208

Opportunities – even in Malawi

No. Enterprise Place of trade Customers Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

1 Brewing local gin Residence Villagers                        

2 Selling goat hides Residence Tannery                        

3 Selling fried fish Local villages Villagers                        

4 Trading ADMARC maize Local markets Traders                        

5 Trading maize flour Town Townsfolk                        

6 Selling cooked food Village school Schoolchildren                        

7 Selling snuff Residence Villagers                        

8 Trading maize bran Local villages Cattle-owners                        

9 Tailoring Local markets Villagers                        

10 Village shop-keeping Home village Villagers                        

11 Village carpentry Nearby village Villagers                        

12 Building houses Local villages Villagers                        

13 Labouring: land preparation Local villages Villagers                        

14 Labouring: weeding Local villages Villagers                        

15 Permanent labour Nearby village One household                        

16 Estate labour Mindale estate Tea plantation                        

17 Selling firewood Residence Villagers                        

18 Moulding bricks Home village Villagers                        

19 Selling thatching grass Residence Villagers                        

20 Making baskets Local markets Villagers                        

21 Making mats Residence Villagers                        

22 Making granaries Local villages Villagers                        

23 Making hoe and axe handles Residence Villagers                        

24 Selling herbal medicine Residence Villagers, townsfolk

Timing of opportunities in relation to cropping

1 2 3 4 5 6 7 8 9 104

4.5

5

5.5

6

6.5

7

7.5

Base

More non-farm

Year

Per c

apita

inco

me

(x 1

000R

s)

1 2 3 4 5 6 7 8 9 101400

1500

1600

1700

1800

1900

2000

2100

BaseMore non-farm

Year

Soil

loss

(ton

nes)

“… improved non-farm employment opportunities in the village increase household welfare in terms of increase in household income but reduce the households’ incentive to use labour for soil and water conservation leading to higher levels of soil erosion and rapid land degradation in the watershed. This indicates that returns to labour are higher in non-farm than on-farm employment.”

S. Nedumaran ‘Tradeoff between Non-farm Income and On-farm Conservation Investments in the Semi-Arid Tropics of India’

Back to Sustainability

(Some) Conclusions

All the core concepts with which we are concerned - risk, resilience, vulnerability, food security, sustainable intensification, investment, net income, etc. – are more relevant in a livelihoods context that goes beyond merely agriculture and natural resources management.

More consideration, and better understanding, of the wider context in which smallholder agriculture operates will help in targeting of technology, may improve its adoption and application to produce Development Outcomes.

However, agricultural intensification (for example) may not be as attractive an option as we would like, and we need to consider the consequences of such an outcome.

Thank you!