the global supply and demand for land in 2050: a perfect storm in the making?

The Global Supply and Demand for Land in 2050:

A Perfect Storm in the Making?1

By Thomas W. HertelPurdue University

with assistance from Uris Baldos

1 CIFAD seminar, Cornell University. Previously presented Presidential Address at the AAEA Annual Meeting, July 25-27, 2010, Denver, Colorado. To be published in the American Journal of Agricultural Economics, Forthcoming, January 2011. A longer version of the paper, including the technical appendix is available at AgEcon Search (http://ageconsearch.umn.edu/handle/92639)

Motivation • Recent worldwide commodity crisis underscored vulnerability

of global agricultural system to exogenous shocks- Continued pop growth, coupled with dietary upgrades- Growth in bio-energy: mandates and oil prices- Climate change impacts as well as mitigation policies - Increased demand for other environmental services

• Confluence of adverse shocks can have devastating impact on poor and risk degrading global land resource base

• Are we heading to a perfect storm over the next 40 years?

Hertel, T. W. (2010). The Global Supply and Demand for Land in 2050: A Perfect Storm in the Making?

Motivation (II)• Perception of a perfect storm is reinforced by increased

interest in farmland investments from non-traditional sources• Hedge funds:

- Investors see farmland as complementary to other assets in their portfolio

- Potential hedge against inflation- Actively seeking investment advice in this new area

• Net food importers seeking to assure supplies of food• Biofuel producers seeking to secure potential capacity• Concern for ‘land grab’ reinforced by weak institutional

protection for local/traditional land owners


Implications of this paper for the role of economics in global land use analyses:• Literature on global land use change makes limited

use of economics• Where economic considerations are reflected in the

analysis, it is often limited by two factors:- The perspective is near term, not long run- Spatial resolution is inadequate to capture the

biophysical and environmental heterogeneity at play in land use decisions and policy impacts


Outline of the Talk

• Historical perspective• Analytical framework• Factors shaping demand for land• Factors shaping supply of land• Critical evaluation• Conclusions


Long Term Perspective

Source: Foley et al. (2005)


“At one extreme, a world covered with agricultural crops, interspersed with human settlements, would seem the most productive of worlds. It would probably not function in a way consistent with human well- being, however. At the other extreme, the largely undisturbed world of 10,000 years ago would probably have sustained hunters and gatherers indefinitely, but at population levels considerably below current levels. Where, between these two extremes, is the balance of managed and natural systems optimal for the human enterprise?”

R.A. Houghton, BioScience, 1994

There is a fundamental tension between agricultural and ecological land use

Agriculturalists and Ecologists also organize their data differently

An agricultural perspective An ecological perspectiveSource: Houghton (1994)

Cropland cover changes: 1700-1900

Source: Ramankutty, N. McGill University


Population density per cropland hectare has increased greatly from 1900 to 1990

Source: Ramankutty et al. (2002)

Steeper line = greater pop density, more output/ha.

Divergences from line permitted by increased trade:Intensification of production in Asia

Most regions lie close to global pop/ha. ray


• Lepers et al. (2005) survey “hotspots” of change over 1980-2000 period:- Changes in cropland cover: small in aggregate, but

considerable changes in composition- Deforestation - Soil degradation

• While deforestation is not new, the current pace is unprecedented

Near Term Historical Perspective


Cropland cover change over 1980–1990

Source: Lepers et al. (2005)

Forest-cover hotspots concentrated in tropics (1980–2000)



Areas of degraded land over 1980–2000


Hertel, T. W. (2010). The Global Supply and Demand for Land in 2050: A Perfect Storm in the Making? Presented at the AAEA Annual Meeting, July 25-27, Denver, Colorado.

Outline of the Talk



Analytical Framework

• Consider global agriculture as a single sector– produces all food, fiber and fuel from agriculture– employs land and variable inputs; the prices of the latter are

determined by exogenous (nonfarm) considerations in long run– Farmers minimize costs, entry/exit results in zero economic profits

• Examine the long run equilibrium % change in agricultural land, and commodity prices as a function of three exogenous drivers: – demand growth, includes food, fiber, fuel– “trend” yield growth, alters derived demand for land – reductions in supply of agr land (e.g., urbanization)


Analytical Framework: Single Global Sector

• Exogenous drivers of land use change: – demand growth, includes food, fiber, fuel ( )– “trend” yield growth, alters derived demand for land ( )– Reductions in supply of agr land (e.g., urbanization) ( )

• Three key margins of economic response (price elasticities)– Price elasticity of demand for agr products ( ) – intensive margin of supply response – yield response to price ( )– extensive margin of supply response – area response to price ( )

• Together, these determine the resulting percentage price change:

– aggregate economic response acts as a shock absorber on the system– if underestimate elasticities, overestimate price impacts


Long Run Equilibrium Land Use Change (see paper for details)

• A number of key insights from this simple economic model• Land use depends on relative, not absolute, size of intensive and

extensive margins: large intensive response will not limit land use change if extensive margin is also large

• Stronger economic response (larger demand- and intensive-supply elasticities) diminishes demands on biophysical system

• In the special case where the intensive supply and demand elasticities are zero, the long run land use change simplifies to:

in which case we can simply deflate demand by yield growth (this has been the FAO approach); exaggerates predicted change in land use


Outline of the Talk



Factors shaping demand: Population • UN (2010) estimates

population rising by 50% during 2000-2050 period: 6 to 9 billion people

• However:– Annual growth rate

diminishes:• from 1.3% in 2000 • to just 0.36% in 2050

(Tweeten and Thompson, 2008)– Over past 25 years, fertility

in many middle income Asian nations below replacement levels (Southgate et al,. 2010)

• Global population could begin to decline by 2050

• China remains question mark• Bulk of growth will be in

additions to urban population developing countries

Correspondence to model:


Income growth is also an important driver of global demand for land

Source: Southgate, Graham, and Tweeten (2010)

LivingStandards& Land Intensity

Plant Proteins(beans, lentils, etc.)

Cereals andOther Carbohydrates

FreshFruit and

Vegetables

LivestockProducts

Quantity of Food Consumed

Sugar,EdibleOils,etc.



Predicted per capita budget shares for China: 1997-2025

Source: Reimer and Hertel, 2004; assuming constant prices.

China:projected budget shares

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et s

hare

CropsMeatDairyOthFoodBevTextApparHousUtilsWRTradeMnfcsTransCommFinServiceHousOthServ

Income growth changes hhld spending patterns

Crops budget share falls, while meat dairy stays high

Up to 2025, population growth dominates as a driver of food demand

Source: Tweeten and Thompson (2008)

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Year

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Population variants for 2025

Food demand growth due to income growth

Food demand due to population only



Income growth contributes relatively more to food demand growth as horizon lengthens

Source: Tweeten and Thompson (2008)

100

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Low Medium High

Year

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Population variants for 2050

Food demand growth due to income growth

Food demand due to population only



Biofuels are another driver of demand• US ethanol accounted for half of global increase in cereals

consumption: 2005/06 - 2007/08 (Westhoff, 2010)

• FAO/OECD (2008) project large share of growth in coming decade derived from biofuels - maize = 52%- oilseeds = 32%

• Depends in part on subsidies and government mandates

Correspondence to model: ,


Source: Fischer (2009)

Current govt biofuel targets are very ambitious: IIASA projections of biofuel demand



But oil prices hold the key to long run biofuel demand as well as its price responsiveness

• Governments budget constrained - will limit subsidies, environmental concerns may limit mandates

• But sustained high oil prices would give a big boost to biofuels

• CAST report notes that, at high oil prices: “the potential demand for farm output is nearly unlimited” - will boost total demand elasticity(Buchanan, Herdt, and Tweeten, 2010)

• Oil price forecast is highly uncertain: Introduces an important new source of uncertainty into long run agricultural demand Source: Energy Information Agency (2010)



Price responsiveness of LR food demand is likely to diminish with income growth

00.10.20.30.40.50.60.7

abs value elasticity

Source: Seale, Regmi and Bernstein (2003)

Average for high income nations is about 0.25;expect price responsivenessof food demand to diminish as world becomes richer.



Factors shaping derived demand for land: What scope for increasing yields?• FAO estimates (Bruinsma, 2009) over past 50 years

- 77% of production growth from yields- 9% from increased cropping intensity- Just 14% from area expansion - Can this be maintained for next 40 years?

• Yield growth has been slowing- wheat and rice 3-5%/yr in 80’s; just 1-2%/yr in last decade

(Byerlee and Deininger, 2010)- yield growth in 2 dozen breadbasket regions has slowed to less

than 0.5%/yr (Fischer, Byerlee and Edmeades, 2009)• Is this simply due to slowing demand growth? Or is it a

function of shrinking yield gaps?Correspondence to model:


Evaluating global yield gaps

• Lobell et al. (2009) survey findings on this topic:- irrigated areas at 80% of potential yields- rainfed areas less than 50% of potential

• Licker et al. (2010) use global data set on area/yields- disaggregate globe into 100 climatic zones- within grid cell compare to 90th percentile = max yield

with current technology- Gap = (1 – Actual yield/Climatic potential yield)


Yield gap fraction values for rice

Source: Licker et al. (2010)

Yield gap fraction values for soybean


Yield gap fraction values for wheat


Yield gap fraction values for maize



Evaluating global yield gaps • Licker et al. (2010) use global data set on area/yields

- disaggregate globe into 100 climatic zones- within grid cell compare to 90th percentile = max yield

with current technology• Closing yield gaps boosts production of maize (50%),

rice (40%), soybeans (20%), wheat (60%)• So why don’t producers close this yield gap?


Factors affecting maize production efficiency vary greatly across regions

Source: Neumann et al. (2010), frontier production function estimated based on the Monfreda et al. (2008) data set

Darkened areas are more efficient – serve to “set the frontier”. Circled areas are inefficient; primary source of production inefficiency is identified


Yield gaps depend on economic incentives

• Robert Herdt’s bottom line from in-depth IRRI (1979) study of yield gaps – it’s all about the economics:“the overall weight of the evidence examined suggests that it is relatively easy to account for the dramatic gap between what is technically possible and what has been achieved: what is technically possible is more modest than most observers admit; the economics of substantially higher yields is not attractive.”



Environmental consideration may limit intensification in the future

• Nitrogen fertilizer applications offer a case in point• Just 8.5% of global cropland receiving nitrogen

fertilizer applications receives 50% of the total applications

• Nitrogen run-off has created problems with eutrophication: ‘dead zones’ in many estuaries and coastal areas


Global N applications reflect great differences in intensification of crop production: Largely a function of economic incentives

Huge disparities in N applications: 50% global cropland < 2.5kg/ha8.5% of fertilized land > 36 kg/ha, accounting for 50% total N

Source: Potter et al. (2010)

Hertel, T. W. (2010). The Global Supply and Demand for Land in 2050: A Perfect Storm in the Making? Presented at the AAEA Annual Meeting, July 25-27, Denver, Colorado.

Areas of high N applications linked to hypoxia areas

Source: Potter et al. (2010)

Outline of the Talk

• Historical perspective• Analytical framework• Factors shaping demand for land• Factors shaping supply of land• Synthesis and critical evaluation


Factors shaping supply of land: Urbanization over the past 50 years

Source: Nordpil and the UN Population Division (2010): urban areas with more than 750,000 inhabitants


Urbanization over the next 50 years will be more concentrated in developing countries

Source: Nordpil and the UN Population Division (2010): urban areas with more than 750,000 inhabitants


Virtually all net growth will be in developing countries; additions to urban populations

Source: UN Population Division (2010)

Increasingly land will be withheld from agriculture for environmental purposes

• An illustration of the environmental Kuznets curve by Kauppi et al. (2006) who find $4600/capita is turning point for forest carbon

• Setting aside productive land can be a source of conflict (Thailand)

• Farming is biggest threat to bird species (Green et al., 2005), but biodiversity is hard to quantify/value: benefits are uncertain; will likely limit its impact

Trends in modern French forest area and population. The vertical bar marks a forest transition (Mather et al., 1999).


Climate change will also alter the effective supply of land to agriculture• Very complex chain of analysis from GHGs to crop production• Several studies focus on 2050 (w/out CO2 fert)

- IFPRI: Yield declines in most LDCs, South Asia hardest hit, sharp price rises

- Fischer (2009): Southern Africa hit hardest, global yields drop 5%, prices rise 10%

- Schlenker and Lobell (2010) focus on SSAfrica; maize most severely affected – rule of thumb is 1 degree C rise translates into setback of 5 years trend yield growth


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In addition to gradual climate change, climate volatility is expected to increase

• Heat waves become more frequent and more intense (longer)• Longer droughts (extreme dry)• Rainfall becomes more concentrated (extreme wet)• These factors lead to heightened stress on agricultural crops –

reduced yields• The next slide shows evidence of increased frequency and

intensity of these variables with % changes showing the increase from late 20th century to late 21st century climate


Ahmed, Hertel and Diffenbaugh, ERL, 2009

Heat stress has been shown to reduce crop yields historically

• Schlenker and Roberts (2009) paired selected US counties’ crop yields with a fine-scale weather dataset that incorporates the distribution of temperatures within each day and across all days in the growing season

• Yields increase with temperature:‾ up to 29° C for corn ‾ up to 30° C for soybeans‾ up to 32° C for cotton

• Temperatures above these thresholds are very harmful to yields

GHG mitigation efforts will also alter the effective supply of land to agriculture• Agr, forestry and land use change account for 30% of GHG

emissions, but are estimated to supply 50% of global abatement at $27/tCO2e (Golub et al. 2009)

• McCarl (2009): loss of 50 million acres of cropland to forest sequestration under US climate leg., doubling of corn prices

• Reilly et al. (2010): world food prices could rise by 80% if adopted land-based carbon pricing

• Seto et al. (2010): carbon forest sequestration is land-intensive: - To regulate global carbon emissions at current levels need to

allocate additional land to forests on the order to current cropland area (1 – 2 billion ); this forest will be satiated after 100 years


Water availability and agri. land supply

• Irrigated agriculture is extremely important- accounts for 42% global crop production- accounts for 70% of global freshwater withdrawals

• McKinsey & Co. (2009) released a recent study of global water use (building on IFPRI model for agriculture)

- At current efficiency, water demand will exceed existing, sustainable, reliable supplies by 40% in 2030

- One-third of world’s pop in 2030 will live in river basins with water gap > 50%

- Efficiency improvements only close 40% of global gap• Water prices will have to rise in future, limiting lands on

which irrigation will be profitable


Global map of irrigated lands: 2000

Source: Siebert et al. (2007)

Critical Assessment• I believe that work to date has erred in two

related dimensions:– Too much is rendered exogenous (e.g., yield trends,

biofuel demand growth, both of which are fundamentally endogenous)

– Elasticities used in models are not truly long run; rather short run in nature – like the ecologists, economists tend to measure what they can readily follow (e.g., 2007/2008 commodity crisis)

– Long run drivers are fundamentally different


Critical Assessment: Perfect storms likely to be localized• Land is, by definition immobile in supply – yet

demand for its services are increasingly global• Dramatic spatial variation in key agronomic, market

and environmental characteristics• Therefore cannot assess supply and demand in the

absence of spatial resolution• Need for spatially explicit global data base

infrastructure for long run analysis of global land use: UK Foresight proposal for global data base infrastructure


Thank you for your attention!


Bibliography (1)Bruinsma, J. (2009). The resource outlook to 2050. By how much do land, water use and crop yields need to increase by 2050? In Session

2: The resource base to 2050: Will there be enough land, water and genetic potential to meet future food and biofuel demands? Presented at the FAO Expert meeting on How to Feed the World in 2050, Rome, Italy.

Buchanan, G., Herdt, R., & Tweeten, Luther. (2010). Agricultural Productivity Strategies for the Future - Addressing U.S. and Global Challenges (Issue Paper No. 45) (pp. 1-16). Council for Agricultural Science and Technology.

Byerlee, D., & Deininger, K. W. (2010). The global land rush: Can it yield sustainable and equitable benefits? Washington, D. C.: The World Bank.

Energy Information Agency. (2010). Annual Energy Outlook 2010 (Annual Energy Outlook No. DOE/EIA-0383(2010)). Washington, DC, USA: US Department of Energy.

Fischer, G. (2009). How do climate change and bioenergy alter the long-term outlook for food, agriculture and resource availability? In Session 2: The resource base to 2050: Will there be enough land, water and genetic potential to meet future food and biofueldemands? Presented at the FAO Expert meeting on How to Feed the World in 2050, Rome, Italy.

Fischer, R., Byerlee, D., & Edmeades, G. (2009). Can technology deliver on the yield challenge to 2050? In Session 4: The investment challenge and the technology challenge to 2050. Presented at the FAO Expert meeting on How to Feed the World in 2050, Rome, Italy.

Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., Chapin, F. S., et al. (2005). Global Consequences of Land Use. Science, 309(5734), 570-574.

Food and Agriculture Organization, & Organization for Economic Co-Operation and Development. (2008). Agricultural Outlook: 2008-2017. Paris and Rome: Food and Agriculture Organization of the United Nations / Organization for Economic Co-Operation and Development.

Golub, A., Hertel, T., Lee, H., Rose, S., & Sohngen, B. (2009). The opportunity cost of land use and the global potential for greenhouse gas mitigation in agriculture and forestry. Resource and Energy Economics, 31(4), 299-319. doi:10.1016/j.reseneeco.2009.04.007

Green, R. E., Cornell, S. J., Scharlemann, J. P. W., & Balmford, A. (2005). Farming and the Fate of Wild Nature. Science, 307(5709), 550-555. doi:10.1126/science.1106049

Hertel, T. W., Golub, A. G., Jones, A., O'Hare, M., Plevin, R., & Kammen, D. (2010). Global Land Use and Greenhouse Gas Emissions Impacts of US Maize Ethanol: Estimating Market-Mediated Responses. BioScience, (March).

Hertel, T., Burke, M., & Lobell, D. (2010). The Poverty Implications of Climate-Induced Crop Yield Changes by 2030. Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.

International Rice Research Institute. (1979). Farm-Level Constraints to High Rice Yields in Asia: 1974–1977. Los Baños, Laguna, Philippines: International Rice Research Institute.

Kauppi, P. E., Ausubel, J. H., Fang, J., Mather, A. S., Sedjo, R. A., & Waggoner, P. E. (2006). Returning forests analyzed with the forest identity. Proceedings of the National Academy of Sciences, 103(46), 17574-17579. doi:10.1073/pnas.0608343103

Lepers, E., Lambin, E. F., Janetos, A. C., DeFries, R. S., Achard, F., Ramankutty, N., & Scholes, R. J. (2005). A Synthesis of Information on Rapid Land-cover Change for the Period 1981–2000. BioScience, 55(2), 115-124.

Bibliography (2)Licker, R., Johnston, M., Barford, C., Foley, J. A., Kucharik, C. J., Monfreda, C., & Ramankutty, N. (2010). Mind the Gap: How do

climate and agricultural management explain the “yield gap” of croplands around the world?Lobell, D. B., Cassman, K. G., & Field, C. B. (2009). Crop Yield Gaps: Their Importance, Magnitudes, and Causes. Annual Review of

Environment and Resources, 34(1), 179-204. doi:10.1146/annurev.environ.041008.093740Mather, A. S., Fairbairn, J., & Needle, C. L. (1999). The course and drivers of the forest transition: The case of France. Journal of Rural

Studies, 15(1), 65-90. doi:10.1016/S0743-0167(98)00023-0McCarl, B. A. (2009, July). Estimating the Intensive and Extensive Margins of Crop Land Yields in the United States. Presented at the

AAEA/AERE Annual Meeting, Milwaukee, Wisconsin.McKinsey & Co. (2009). Charting Our Water Future: Economic frameworks to inform decision-making. 2030 Water Resources Group:

McKinsey & Co.Monfreda, C., Ramankutty, N., & Foley, J. A. (2008). Farming the planet: 2. Geographic distribution of crop areas, yields, physiological

types, and net primary production in the year 2000. Global Biogeochemical Cycles, 22, 19 PP. doi:200810.1029/2007GB002947Neumann, K., Verburg, P. H., Stehfest, E., & Müller, C. (2010). The yield gap of global grain production: A spatial analysis. Agricultural

Systems, 103(5), 316-326.Potter, P., Ramankutty, N., Bennett, E. M., & Donner, S. D. (2010). Characterizing the Spatial Patterns of Global Fertilizer Application

and Manure Production. Earth Interactions, 14(2), 1-22.Ramankutty, N., Foley, J. A., & Olejniczak, N. J. (2002). People on the Land: Changes in Global Population and Croplands during the

20th Century. AMBIO: A Journal of the Human Environment, 251-257.Schlenker, W., & Lobell, D. B. (2010). Robust negative impacts of climate change on African agriculture. Environmental Research

Letters, 5(1), 014010. doi:10.1088/1748-9326/5/1/014010Seale, J., Regmi, A., & Bernstein, J. (2003). International Evidence On Food Consumption Patterns. United States Department of

Agriculture, Economic Research Service. Retrieved from http://ideas.repec.org/p/ags/uerstb/33580.htmlSeto, K. C., Groot, R. D., Bringezu, S., Erb, K., Graedel, T. E., Ramankutty, N., Reenberg, A., et al. (2010). Stocks, Flows, and Prospects

of Land. In T. Graedel & E. V. D. Voet (Eds.), Linkages of Sustainability, Strüngmann Forum Reports (Vol. 4, pp. 71-96). Cambridge, MA: MIT Press.

Southgate, D., Graham, D., & Tweeten, L. (2010). The World Food Economy (Second.). Oxford: Blackwell.Tweeten, L., & Thompson, S. (2009). Long-term Global Agricultural Output Supply-Demand Balance and Real Farm and Food Prices.

Farm Policy Journal, 6(1).UN Population Division (2010). World Population Prospects: The 2008 Revision, http://esa.un.org/unpp, Sunday, May 16, 2010; 7:53:30

PM.Westhoff, P. (2010). The Economics of Food. New Jersey, USA: Financial Times Press.

the global supply and demand for land in 2050: a perfect storm in the making?

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