NATURAL ENDOWMENTS, CHOICE, AND PRODUCTIVITY

Donald F Larson, Development Research Group, World Bank

Going Beyond Agricultural Water Productivity Workshop

Washington, December 8, 2014

Research website

Q: Is it possible to value water used for agriculture?

A: Sure, here’s one way

2

Start with the notion of choice

Farmers choose what to produce and how to produce it (endogenous technology)

Conditional on a decision environment, S

Fixed things (climate, roads, markets, social norms, etc.)

Quasi-fixed stuff (capital, knowledge, social network)

Constraints (missing markets, weak institutions)

Productivity model (frontier version)

𝑃∗ 𝑥, 𝑠 = 𝑙𝑛𝑦 − 𝐵 𝑥, 𝑠 − 𝑢(𝑠), Where 𝑢 𝑠 = 𝑃∗∗ − 𝑃∗

Difference from top

Need good measures of s, x, and y

And a flexible form

Climate is an s, irrigation systems are in s (quasi-fixed)

water through a canal is an x

weather is an x

From Larson and Leon (2006)

An example from Ecuador Data on 108,000 farms, price, climate and endowment data at Canton level

3

Fertilizer use Annual precipitation

From Larson and Leon (WBER 2006)

Q: Is that useful?

A: For some things 4

But average water MVPs depends on fixed geographic features and fixed climate

This value is place specific

Going from a “moist” climate adds about 20

percent to revenue per hectare over a

“humid” climate”

Using irrigation increases value by about

21percent

A one percent increase in rain variability

decreased revenue by 5 percent

Hired labor is more productive than family

labor

Being isolated reduces revenue by 1.3

percent

From Larson and Leon (WBER 2006)

Q:What about climate as a policy outcome?

A: Local water MVP is part of the answer. 5

You need a

climate model

to tell you how

the climate

parts of s will

change

Then you can

assess spatial

impact on

producers

IF future is

within the

realm of the

present

Source: http://berkeleyearth.lbl.gov/regions/ecuador

Q: Is knowing what happens to production and revenue helpful?

A: Only partially; what about prices?

6

Source: Minot N., B. Baulch, and M. Epprecht, in collaboration

with the Inter-Ministerial Poverty Mapping Task Force 2003.

Census data 1994 and 1999/Household Survey data 1998.

Value output pe r plante d surface, thousands

[0.04,0.10]

(0.10,0.16]

(0.16,0.20]

(0.20,0.26]

(0.26,0.35]

(0.35,0.46]

(0.46,0.62]

(0.62,1.04]

(1.04,12.71]

No data

100 k m

From Larson and Leon (WBER 2006)

Q: Production and prices are local (but prices are not)

A: Need a global model that accounts for water supply, water demand,

surface and below ground flows …..

7

Changes in water scarcity Changes in yield

From Growth, Climate Change and the Role of Water in the South Asian Economy: A General

Equilibrium Modeling Approach (ESMAP study)

A (continued): and also resource reallocations and

trade …. 8

Keep in mind

that the

climate

models are

filled with

uncertainty

So this

outcome is

one possible

world

From Growth, Climate Change and the Role of Water in the South Asian Economy: A

General Equilibrium Modeling Approach (ESMAP study

Q: Where do I invest locally to adapt to a different water future?

A: It’s a gamble.

9

Take climate scenarios

Demographic scenarios

Combine a global model with a hydrological model

Simulate a variety of scenarios

Least regret outcomes?

Avoid disaster outcomes?

Wait for better information? (Real options)

From Growth, Climate Change and the Role of Water in the South Asian Economy: A

General Equilibrium Modeling Approach (ESMAP study)

Q: Given the global linkages, given the potential for adaptation, how should

water be evaluated in locally? (I have a price for food, but not water)

A: Tough question

10

The monetary cost of a strategic storage food storage problem

Implicit in the stored imported wheat is stored rainfall

14.0

14.5

15.0

15.5

16.0

16.5

0

500

1,000

1,500

2,000

2,500

3,000

0.00 0.50 1.00 1.50

CV

of

dom

est

ic p

rice

s

$U

S m

illion p

er

year

Target storage as share of annual consumption

Monetary cost

Cost of reserves ($US million ) Price variability

14.0

14.5

15.0

15.5

16.0

16.5

-

50

100

150

200

250

0.00 0.50 1.00 1.50

CV

of

dom

est

ic p

rice

s

billion c

ubic

mete

rs p

er

year

Target storage as share of annual consumption

Water stored

Blue water Green Water

Grey water Price variability

From Larson (Aquatic Procedia 2013); Larson et al. (WBER 2014)

Q: How do you value the water embedded in trade?

Example, Average embedded water in domestic and imported wheat, total

and by type

11

- 500 1,000 1,500 2,000 2,500 3,000

Argentina

Australia

Russia

Ukraine

United States

Average in trade

Egypt

cubic meters of water per ton of wheat

Water content of domestic and traded wheat

Blue

Green

Grey

Source: FAO (2012) and Mekonnen and Hoekstra (2010)

Conclusions: The bottom line policy question is

unanswered…

12

Recovering a partial, conditional value for water

can be accomplished (conceptually)

Local value of climate on production (within history)

Local value contingent on global markets for food

Local value contingent on adapting local or regional

hydrology and landscapes

Also orders of uncertainty

Calculating an implicit value of water embedded in

food trade is really hard to do

What price should the shadow price of water be for policy?