Agricultural Productivity and Natural Resource Endowments

Philip Pardey University of Minnesota

The National Academies workshop A Sustainability Challenge: Food Security for All, May 2, 2011

Venable LLP Conference Center, Washington D.C.

Critical Questions

• What are the past and prospective rates of agricultural productivity growth?

• Is growth slowing, stagnating, or increasing?

• Where in the world is this happening (at what scale)?

• What commodities are performing better than others?

• What is the (past and prospective) relative rates of growth of productivity (supply) vs demand

Critical Questions (contd).

• How has, and likely will, the endowment of natural resources change over time?

• within and outside the extent of agriculture

• What is the link between

• the nature, size, and location of natural resource endowments and the flows of services from those natural resources, and

• the flow of services and agricultural productivity (and vice versa)

Vice versa? -- Productivity to Natural Resources Linkages

Put another way, thanks to the agricultural productivity increases made possible through research and new technology development since 1990, an area greater than all the land in the 26 states east of the Mississippi River, has been spared for other uses. Imagine the environmental disaster that would have occurred if hundreds of millions of environmentally fragile acres, not suited to farming, had been ploughed up and brought into production. Think of the soil erosion, loss of forests and grasslands, and biodiversity, and extinction of wildlife species that would have ensued!

Norman Borlaug, Foreword

Persistence Pays 2001

Critical Indicators

• What is produced?

• Crop and livestock choice (variety and breed)

• Where is it produced?

• Location, location, location

• How is it produced?

• Input composition and intensity

• “Intensive” vs “extensive”

• Continuous cropping vs rotation vs intercropped

• Crop-livestock interactions

• Land, labor •Capital, materials • Farm produced (seed,

feed, traction) •Natural inputs

ECON 101 – Measures of Productivity

TFP (total factor productivity) = Q

X

MFP (multi-factor productivity) = i

i

QX i = included outputs and inputs

ee

Qq

Q (excluded outputs as a share of total outputs)

ee

Xx

X (excluded inputs as a share of total inputs)

i e

i e

Q Q QTFP

XX X

Difference between growth in TFP and growth in MFP

ln ln ( ln ln ) ( ln ln )e e i e e id TFP d MFP q d Q d Q x d X d X

Natural Inputs • Key to the nexus between productivity and

environmental endowments and flows

• Weather (rainfall, sunlight, day length, wind)

• Terrain (slope, elevation)

• Soil (type, depth, organic and nutrient content)

• Pests and diseases (Exputs)

All these natural inputs vary across time and space

Getting the Temporal Calibration Right

(i.e., changes the technical relationship between inputs and outputs)

Productivity Change Technical Change R&D

Aggregate R&D Spending -Productivity Lag

Source: Alston, Pardey and Ruttan (2008) and Alston et al. (2010)

34

5 years

0.00

0.02

0.04

0.06

0.08

0.10

0 10 20 30 40 50

Lag Weights

Year

Gamma (Alston, Andersen, James & Pardey 2010)

Trapezoidal (Huffman & Evenson 1993 & 2006)

(Griliches 1959)

(Pardey and Craig 1989) ≥ 30 Years

50 Years

Illustrative Technology Development Lags

Source: Alston, Pardey and Ruttan (2008) and Alston et al. (2010)

1877Beal conducts first controlled

crosses/hybrid vigor

1905-1912Shull developed correct understanding of

inbreeding and cross breeding

1917 James developed double cross-hybrid

1922Iowa State station began corn in-breeding

program

1933First commercial planting of Hybrid Iowa

939 developed by Merle Jenkins

1936

First release of a widely popular double-

cross hybrid developed at Purdue

University

1960Vastly improved in-breds led to shift to

single-cross hybrids

1960 95 percent of U.S. corn acreage in hybrids

Hybrid Corn

1901Bacillus thuringiensis (Bt) discovered in

Japan (and 1911 in Germany)

1950s Bt used as a control agent and registered

1986 Cry1Ab gene sequence published

1986Cry1Ab cloned into root colonyzing

Pseudomonas bacteria

1992YieldGard insect protected corn event

Mon810 produced by "gene gun"

1996FDA, USDA & EPA approvals for Yield

Guard

1997Bt corn (corn borer protection)

commercialized in U.S.

1998Stacked with other traits (e.g. herbicide

tolerance)

2004U.S. patent issued to Monsanto for

Mon810

2008 Regulatory approval in 20 countries

Bt Corn

1970Glyphosphate shown to have herbicidal

activity

1976 Roundup herbicide commercialized in U.S.

1980Idnetification of 3 mechanisms to infer

glyphosphate tolerance

Late 1980sSeveral genes encoding glyphospate

insensitivity isolated

1987 First soybean transformation achieved

1990 & 91 Glyphosphate tolerant seeds evaluated

1996 Roundup Ready Soybeans commercialized

Roundup Ready Soybean

59 years 96 years 26 years

U.S. Maize Technology Adoption Lags

Source: Beddow (2011 forthcoming)

0

20

40

60

80

1001

93

0

19

35

19

40

19

45

19

50

19

55

19

60

19

65

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

20

10

Per

cen

tage

of

U.S

. Mai

ze A

cres

Hybrid Maize

Nitrogen

Nitrogen (rate, index)

Herbicide

Irrigation

18 years 17 years

20 years

13 years

30 years

12 years

Some Indications of (Global)

Productivity Patterns

Global Crop Yields Averages, 1920-2008 (Beta version)

0

1

2

3

4

5

61

92

0

19

25

19

30

19

35

19

40

19

45

19

50

19

55

19

60

19

65

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

Yie

ld (

MT/

Ha.

)

barley maize millet oats rice

rye sorghum soybeans wheat

Maize

Wheat

Rice

Source: Pardey, Beddow, Xudong and Hurley (forthcoming)

1920-1960

Commodity Rate Maize 0.69% Wheat 0.99%

Rice 0.49%

1990-2008

Commodity Rate Maize 1.78% Wheat 0.97%

Rice 1.07%

1960-1990

Commodity Rate Maize 1.73% Wheat 2.57%

Rice 2.19%

A Century of Global Crop Yield Distributions (Beta version)

Source: Pardey, Beddow, Rao and Hurley (forthcoming)

Wheat

Maize Rice

Groupings

Land Productivity Labor Productivity

1961-90 1990-08 Difference 1961-90 1990-08 Difference

Percent per year

World (simple av.) 1.78 1.55 -0.23 1.74 1.84 [0.09]

World 1.95 2.01 0.06 0.92 1.52 0.62

World minus China 1.79 1.53 -0.26 1.09 0.75 -0.35

80% (N = 22) 1.98 2.21 0.23 0.97 1.78 0.82

80% minus China 1.96 1.88 -0.08 2.68 3.06 0.38

< 80% (N= 158) 1.82 1.17 -0.64 1.11 0.24 -0.87

Partial Factor Productivity Growth, 1961-1990 vs 1990-2008

Source: Pardey (forthcoming)

Global Slowdown in Multifactor Productivity Growth?

“I see no evidence of a general slowdown in sector-wide agricultural TFP [growth]. At

least through 2006. If anything, the growth rate in agricultural TFP accelerated in

recent decades….

Despite this generally optimistic conclusion, it is also clear that agricultural productivity

growth has been very uneven… TFP growth may in fact be slowing in developed

countries while accelerating in developing countries.”

Fuglie (2008, p. 440)

Sample of Regional and Global Productivity Studies

Authors

Publication year

Data Year(s) Countries

Method

Hayami and Ruttan

1970 1955, 1965 38 & 1970

Econometric

Antle 1983 1965 45 Econometric

Lau & Yotopolous 1989 1960, 1970 43 & 1980

Econometric

Block 1994 1963-1998 39 (6 intervals)

Econometric

Craig, Pardey & Roseboom

1997 1961-1990 98 Econometric

Fulginiti & Perrin 1998 1961-1985 18 Econometric Malmquist

Coelli & Rao 2005 1980-2000 93 Malmquist/DEA

Fuglie 2008 1961-2006 171 Growth accounting

O’Donnell 2010 1970-2001 88 Hicks–Moorsteen/DEA

Common Denominator– FAO and World Bank Data

Land – count of arable, permanently pastured and cropped area

Labor – head count of economically active population in agriculture

Capital – count of tractors in use/on farm

– percent of irrigated acres

Livestock – weighted head count of buffalo, cattle, pig, sheep, and goat

Materials – fertilizer (nitrogen, phosphate and potash and use in units of active ingredients)

FAO and World Bank Data

Fuglie Factor Weights

Developing World U.S. InSTePP

(percent per year)

Agg. Input -0.22 0.07 0.54 -0.07

MFP 1.94 1.65 1.18 1.73

Estimated U.S. Aggregate Input and MFP Growth Rates, 1961-2006

Source: Pardey (forthcoming)

U.S. Multifactor Productivity, 1949-2007

State MFP Growth Distributions

0

4

8

12

16

20

24

28

-2.5 -1.5 -0.5 0.5 1.5 2.5 3.5 4.5 5.5

1949-1990 US = 2.02%pa

0

4

8

12

16

20

24

28

-2.5 -1.5 -0.5 0.5 1.5 2.5 3.5 4.5 5.5

1990-2007 US = 1.18%pa

Percent per year

InStePP Production Accounts Outputs

Crops 61 Livestock (9) Miscellaneous (4)

Inputs Land (3)

Cropland, irrigated cropland, pasture and grassland Labor (32)

Family labor Hired labor Operator labor (30)

Education: 0–7 years, 8 years, 1–3 years of high school, 4 years of high school, 1–3 years of college, 4 years or more of college Age: 25–34, 35–44, 45–54, 55–64, or 65 or more years of age

Capital (12) Machinery (6)

Automobiles, combines, mowers and conditioners, pickers and balers, tractors, trucks

Biological capital (5) Breeding cows, chickens, ewes, milking cows, sows

Buildings Materials (11)

Electricity, purchased feed, fuel, hired machines, pesticides, nitrogen, phosphorous, potash, repairs, seeds, miscellaneous purchases

Some Big (Largely) Unknowns

• The Location of Production • The Spatial Dynamics of Agriculture

• The Prevalence (and consequences) of Pests and Diseases

Spatial Distribution of Crop Yields, 2000 (SPAM ver 3.0)

Panel a: Maize

Panel d: Rice Panel c: Soybean

Panel b: Wheat

Source: HarvestChoice (2010)

Share of World’s High-Yielding Area

US Africa

(percent)

Maize 32 2.5

Wheat 28 3.6

Soybean 25 5.6

Rice 5.3 5.7

Which cropland extent?

MODIS Africover

0

100

200

300

400

500

600

1908 1930 1960 2008

Africa Asia (exclude Japan) Europe+NorthAm+Oceania Latin America Other

Global Value of Field Crops Production, 1908-2008 (beta)

$81.6 b $113.7 b

$191.7 b

$534.2 b

Africa 6.6 percent Asia 43.9 percent Europe etc 26.2 percent LAC 13.3 percent

Africa 3.7 percent Asia 18.1 percent Europe etc. 52.0 percent LAC 5.2 percent

Crops included (15 field crops)

Barley Buckwheat Cassava Maize Millet Oats Potatoes Rice Rye Sorghum Soybean Sugarbeet Sugarcane Sweet potatoes Wheat

Source: Pardey (forthcoming)

Intl dollars (billions, 1999-2001)

Changing Location of Agriculture

Panel a: Cropland Extent, 1700

Panel b: Cropland Extent, 2000

Panel c: Movement of Regional Cropland Centroids, 1700 – 2000

Source: Beddow, Pardey, Koo and Wood (2010)

U.S. Maize Production, 1880 and 2007

1880

2007

Source: Beddow (2011 forthcoming)

Spatial Concentration of Global Agricultural Production, 2006-08 average

0

10

20

30

40

50

60

70

80

90

100

0 4 8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

96

10

0

10

4

10

8

11

2

11

6

12

0

12

4

12

8

13

2

13

6

14

0

14

4

14

8

Shar

e (

pe

rce

nta

ge)

Number of countries

World Value of Production

Cumulative Country Share (%)

China 22.5 USA 33.3 India 43.8 FSU 49.4 Brazil 54.9

Maize 2008

1 United States 37.2

2 China 20.1

3 Brazil 7.1

4 Mexico 2.9

5 Argentina 2.7

Top 5 total 70.0

top 10 total 79.2

Wheat 2008

1 China 16.5

2 India 11.5

3 United States 10.0

4 Russia 9.3

5 France 5.7

Top 5 total 52.9

top 10 total 70.9

Rice 2008

1 China 28.2

2 India 21.6

3 Indonesia 8.8

4 Bangladesh 6.8

5 Viet Nam 5.6

Top 5 total 71.1

top 10 total 86.0

Source: Pardey (forthcoming)

Spatial Variation in Abiotic Productivity Constraints

Steeplands

Drylands

Poorly drained Soils

Low Nutrient Capital Soils

Explore more at http://labs.harvestchoice.org/2010/12/updating-soil-functional-capacity-classification-system/

Global Probability of Occurrence of Wheat Rust (pre-release version)

Puccinia striiformis (Stripe Rust)

Puccinia triticina (Leaf Rust)

Puccinia graminis (Stem Rust)

Source: Pardey et al. (2011 forthcoming)

Growth Index

Crop Disease – Stem Rust Example

KS& ND 20.4 MMT ~ 100% Oz output

Final Thoughts

“Since we know little about the causes of productivity increase, the

indicated importance of this element may be taken to be some sort of

measure of our ignorance about the causes of economic growth in the

United States.” Abramovitz (AER 1956, pp. 5-23)

In an idea he attributed to Zvi Griliches, Schultz argued that the

economically ideal output-to-input ratio would stay at or close to one,

the notion being that “… the closer we come to a one-to-one

relationship in our formulation, the more complete would be our

(economic) explanation *of the sources of output growth+.”

Schultz (1956, p.758)

Final Thoughts

Agricultural economists and other social scientists tend to take data as facts.

The problem is the data are not facts. Facts are what is really there. Data are

quantitative representation of facts, which statistical workers and

economists concoct.

I call the study of how primary statistical information is made into economic

data “factology.” The neglect of factology risks scientific ruin.

The bottom line is, for data producers, that full disclosure of procedures and

labeling of data series are essential; and, for data users, be careful and

investigate the data before using them.

Bruce Gardner (1992, AAEA Waugh Lecture)

Alston, J.M., BA. Babcock and P.G. Pardey. The Shifting Patterns of Agricultural Production and Productivity Worldwide, 2010. (Especially chapters 2, 3, 13 and 15)

Alston, J.M., M.A. Andersen, J.S. James, and P.G. Pardey. Persistence Pays: U.S. Agricultural Productivity Growth and the Benefits from Public R&D Spending. New York: Springer, 2010.

Thanks!

www.harvestchoice.org www.instepp.umn.edu

Pardey , P.G. and P.L. Pingali. “Reassessing International Agricultural Research for Food and Agriculture.” Report prepared for the Global Conference on Agricultural Research for Development (GCARD), Montpellier, France, 28-31 March 2010.

Selected Sources