1

Total factor productivity (TFP) is the broadest measure of productivity. It compares the total output of a sector to the total land, labor, 

capital, and material inputs used to produce that output. Increases in TFP imply more output is forthcoming from a given level of inputs, 

or, equivalently, fewer inputs are required to produce the same output. Growth in TFP is considered to be an indicator of the rate of 

technical change in a sector.

 Major Findings Major Findings

•	 By 2050, global agricultural demand is projected to grow by 70-100 percent due to population growth,

energy demands, and higher incomes in developing countries. Meeting this demand from existing

agricultural resources will require raising global agricultural total factor productivity (TFP)1 by a similar

level. Maintaining the U.S. contribution to global food supply would also require a similar rise in U.S.

agricultural TFP.

•	 TFP growth in U.S. agricultureis predicated on long-term investments in public agriculturalresearch and

development (R&D). Productivity growth also springs from agricultural extension, farmer education,

rural infrastructure, private agricultural R&D, and technology transfers, but the force of these factors is

compounded by public agricultural research.

•	 The rate of TFP growth (and therefore output growth) of U.S. agriculture has averaged about 1.5

percent annually over the past 50 years. Stagnant (inflation-adjusted) funding for public agricultural

research since the 1980s may be causing agricultural TFP growth to slow down, although statistical

analyses of productivity growth trends are inconclusive.

•	 ERS simulations indicate that if U.S. public agricultural R&D spending remains constant (in nominal

terms) until 2050, the annual rate of agricultural TFP growth will fall to under 0.75 percent and

U.S. agricultural output will increase by only 40 percent by 2050. Under this scenario, raising output

beyond this level would require bringing more land, labor, capital, materials, and other resources into

production.

•	 Additional public agricultural R&D spending would raise U.S. agricultural productivity and output

growth. Raising R&D spending by 3.73 percent annually (offsetting the historical rate of inflation in

research costs) would increase U.S. agricultural output by 73 percent by 2050. Raising R&D spending

by 4.73 percent per year (1-percent annual growth in inflation-adjusted spending) would increase

output by 83 percent by 2050.
Heisey, Paul, Sun Lin Wang, 

and Keith Fuglie. Public 

Agricultural Research Spending 

and Future U.S. Agricultural 

Productivity Growth: Scenarios 

for 2010-2050, 

EB-17, U.S. Department of 

Agriculture, Economic 

Research Service, July 2011. 

Recommended citation 

format for this publication:

ECONOMIC BRIEF Public Agricultural Research Spending and Future U.S. Agricultural Productivity Growth:

Scenarios for 2010-2050

UNITED STATES DEPARTMENT OF AGRICULTURE 2

Productivity growth accounts for nearly all U.S. agricultural growth 

Total factor productivity (TFP) is a good indicator of technological change. It measures the efficiency with

which all inputs (land, labor, capital, and materials) are combined to produce total outputs (all crop and

livestock commodities). In U.S. agriculture, growth in TFP is nearly synonymous with growth in output

since the overall size of the resource base has barely increased over the last 60 years. Between 1948 and

2008, the average annual growth rate in U.S. agricultural output was 1.58 percent and the average annual

growth rate in TFP was 1.52 percent. As a result, total agricultural output in 2008 was 2.5 times that of

1948 (figure 1).

R&D spending spurs TFP growth

Growth in TFP is strongly associated with the adoption of new technologies that raise yields or lower

costs. Public investment in agricultural R&D is a major source of new agricultural technology; it

also complements (raises returns to) other productivity-enhancing activities like extension, education,

infrastructure, and private R&D. While private-sector investment in agricultural R&D also contributes

new technology, much of this contribution is already accounted for in the way the inputs are measured

in constructing the estimates of TFP.2 Moreover, studies have shown that private R&D depends critically

on government and university investments in science and technology.3Thus, even if the quality-adjusted

measures of TFP do not fully net out the contributions of private R&D, if private R&D follows (responds

positively to) trends in public R&D, then simulations using public R&D as the primary policy lever for

future productivity growth should not be unduly biased. Nonetheless, the simulations reported here

depend on these assumptions about private R&D: that its impacts are partially netted out of the TFP

measure and that it follows trends in public R&D.

Statistical models of TFP growth treat R&D spending as “knowledge capital.” As with physical capital, an

R&D investment can affect productivity growth for several years (even decades), buteventually depreciates

as technologies grow ineffective (e.g., new pests and diseases evolve) or obsolete. R&D investments

typically begin boosting TFP within 3-5 years, with benefits peaking after 10 to 20 years, and with some

impacts lasting as long as 50 years (Huffman and Evenson, 2006; Alston et al., 2010).

2

Figure 1

U.S. agricultural output, input, and TFP indexes

Source: U.S. Department of Agriculture, Economic Research Service. 

Base year 1948 = 100

Output

TFP

Input

1950 1960 1970 1980 1990 2000 2010

300

250

200

150

100

50

0

2

New technologies from private R&D 

are partially embodied in the quality 

of the inputs (chemicals, machinery, 

seed, etc.) purchased by farmers. The 

TFP measure used in this study adjusts 

for such quality improvements in these 

inputs. In other words, it already nets 

out many of the productivity effects of 

private R&D.

3

Public-sector research opens up new 

technological opportunities for the 

private sector to commercialize. One 

recent study found that “government 

expenditures in both basic biological 

research and agricultural and 

medical science create substantial 

spillovers for private firms...Indeed, 

opportunities created through public 

research are the principal source 

of growth in industry life sciences” 

(Wang, Xia and Buccola, 2009). 

Fuglie and Walker (2001) also found 

complementarity between public and 

private investments in crop genetic 

improvement, with public research in 

basic plant breeding spurring more 

private investment in crop variety 

development.
ECONOMIC BRIEF

3 ECONOMIC RESEARCH SERVICE

Public Agricultural Research Spending and Future U.S. Agricultural Productivity Growth:

Scenarios for 2010-2050

Agricultural R&D spending scenarios account for inflation in research costs

Between 1927 and 2009 (the period for which we have data), total spending by Federal and State

agricultural research institutes on productivity-related agricultural research (excluding R&D on postharvest, environmental, and rural development issues) rose at an average annual rate of 7.49 percent in

nominal terms. If adjusted by the Consumer Price Index, then research spending rose by 4.37 percent per

year. However, if inflation adjustments reflect the cost of doing research (i.e., scientist salaries, laboratory

equipment, etc.), then real research spending rose by only 3.03 percent per year (i.e., research costs have

been rising faster than the average price level of goods and services in the economy).

Estimates of R&D knowledge capital are based on real research spending (adjusted by the rate of inflation

in the cost of research resources). Growth in public agricultural research spending slowed dramatically

after the early 1980s and has declined by more than 20 percent since peaking in 1994 (figure 2). The

growth in the stock of agricultural knowledge capital, which follows trends in research spending with a

lag, peaked around 2005. Since then, knowledge capital stock has started to decline as current spending

(creation of new knowledge capital) has failed to keep up with knowledge capital depreciation.

We simulate three possible scenarios for future public agricultural R&D expenditure for 2010-2050 (see

Box for a description of thesimulation model). Thesescenarios includetotalexpenditures on productivityoriented agricultural research by USDA research agencies and State agricultural experiment and veterinary

medicine colleges from all sources of funding (USDA, other Federal and State governments, and others).

Scenario 1: Public research spending is constant in nominal terms at the 2005-09 average ($2.5 billion

per year). This implies a decline in real research expenditure by 3.73 percent per year (the inflation rate

in the cost of research resources over 1983-2009).4In other words, under this scenario, inflation reduces

the effective amount of research effort.

Scenario 2: Public research spending is constant in real terms at the 2005-09 average. This implies that

nominal expenditures for public agricultural research rise by about 3.73 percent per year to offset inflation

in the cost of research.

Figure 2

Productivity-oriented agricultural research expenditures

Source: Historical data from Huffman (2010) and 2010-2050 data from U.S. Department of Agriculture,

Economic Research Service simulations.

Constant $/year (billions)

Scenario 1: R&D constant, nominal $

Scenario 2: R&D constant, 

real $

Scenario 3: R&D increases 1%/year, real $

Historical

1920 1940 1960 1980 2000 2010 2040 2060

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

4

While the average rate of inflation in 

research costs over 1927-2009 was 

4.46 percent, this has slowed in more 

recent years. To project research 

cost inflation in the future, we chose 

the average inflation rate in research 

costs during 1983-2009, or 3.73 

percent per year. 
ECONOMIC BRIEF Public Agricultural Research Spending and Future U.S. Agricultural Productivity Growth:

Scenarios for 2010-2050

UNITED STATES DEPARTMENT OF AGRICULTURE 4

Scenario 3: Public research spending increases by 1 percent per year in real terms (implying a nominal

increase of about 4.73 percent per year). This 1-percent real growth rate is roughly equivalent to the rate of

U.S. population growth (a proxy for growth in domestic agricultural demand). Real research expenditures

rise, but more slowly than the rapid growth in real spending observed before the 1980s.

R&D Spending Must Rise to Maintain Historical Agricultural TFP Growth Rate 

The resulting TFP projections under the three public R&D spending scenarios are shown in

figures 3 and 4. Figure 3 shows the projected annual growth rate in agricultural TFP. The estimated

historical trend based on our model shows a declining rate of TFP growth since peaking at just

over 2 percent per year in the mid-1980s. By 2008, annual TFP growth was about 1.3 percent.5

In each of the scenarios, rates of TFP growth increase or decrease from present levels and then level off

after 2030 or 2040. Under scenario 1, theTFP growth rate declines to under 0.75 percent per year. Under

scenario 2, TFP growth stabilizes at about 1.4 percent per year. Under scenario 3, TFP growth accelerates

and reaches 1.6 percent per year by 2040.

Figure 4 translates TFP growth into an agricultural TFP index (base year of 2008=100) under alternative

funding scenarios. It also shows the agricultural output level (relative to 2008 production) achievable

if agriculture’s current resource base remains unchanged. Under scenario 3, by 2050 U.S. agricultural

output would be 83 percent higher than 2008 levels and under scenario 2, output would grow by 73

percent. As a point of comparison, current estimates suggest global food demand will increase between 70

and 100 percent by 2050 (Food and Agriculture Organization, 2006). Under scenario 1, however, with

constant R&D funding (in nominal terms), U.S. agricultural output would increase by only about 43

percent between 2008 and 2050 using the current agricultural resource base. This would barely outpace

the projected growth in U.S. population. By contrast, U.S. agricultural output would likely keep up with

the growth in global demand under the higher R&D investment scenarios.

Another recent study (Alston et al. 2010) used different data and modeling assumptions to independently

derive statistical relationships between public agricultural R&D spending and TFP growth. Their findings

are broadly similar to our own: public spending on agricultural R&D will need to rise to maintain

historical rates of productivity growth in U.S. agriculture.

Figure 3

TFP growth rate projections

* The graph shows the TFP growth rate predicted from the statistical model rather than the actual TFP 

growth rate for 1980-2008. Actual TFP growth is highly variable, ranging between -15% and + 15% for 

individual years. This variability is mainly due to weather.

%/year

Scenario 1: R&D constant, nominal $

Scenario 2: R&D constant, real $

Scenario 3: R&D increases 1%/year, real $

Historical trend predicted from model*

1980 1990 2000 2010 2020 2030 2040 2050

2.25

2.00

1.75

1.50

1.25

1.00

0.75

0.50

0.25

0.00

5

This apparent decline in TFP growth 

is based on the model used to 

project future TFP growth. All other 

factors were kept fixed except for the 

changes in R&D “knowledge capital” 

stock; therefore, the decline in the 

TFP growth rate reflects the erosion 

of R&D stocks, as hastened by the 

stagnation in R&D funding that began 

in the 1980s (see figure 2). Thus, the 

slowing of TFP growth in figure 3 after 

the mid-1980s reflects this model 

assumption; actual agricultural TFP 

growth may not have slowed if other 

contributing factors offset the decline 

in R&D capital.
ECONOMIC BRIEF

5 ECONOMIC RESEARCH SERVICE

Public Agricultural Research Spending and Future U.S. Agricultural Productivity Growth:

Scenarios for 2010-2050

Implications of a decline in the long-term growth rate in U.S. agricultural productivity are significant

for both the United States and the world. Slower productivity growth will likely cause agricultural prices

to rise, which would reduce global economic welfare and raise poverty in urban areas and among fooddeficit rural households, especially in developing countries (Nelson et al., 2010). Rising prices would also

increase pressure to expand agricultural cropland at home and abroad and input use on cropland would

likely intensify. Such agricultural resource expansion and intensification could come with significant

environmental costs, such as further impairment of soil and water quality, loss of biodiversity, and

increased emissions of greenhouse gases (Foresight, 2011). Finally, agricultural exports may also decline

as U.S. farmers lose competitiveness in international markets (Ball et al., 2010). 

Figure 4

TFP index projections

Source: 

Base year 2008 = 100

Scenario 1:

R&D constant, nominal $

Scenario 2: R&D constant, real $

Scenario 3: R&D increases 1%/year, real $

Historical actual

Historical trend

1980 1990 2000 2010 2020 2030 2040 2050

200

180

160

140

120

80

60

40

20

0

How the estimates were derived 

We use a model developed by ERS (Wang et al., 2010) along with research expenditures data from Wallace Huffman at Iowa State 

University. Huffman isolates the component of total public agricultural R&D associated with raising crop and livestock productivity 

and excludes other kinds of R&D (Huffman et al., 2001; Huffman and Evenson, 2006; Huffman, 2010).

Statistical models that link TFP to these investments treat R&D spending as “knowledge capital.” Like physical capital, knowledge 

capital contributes to growth over a long period of time but eventually depreciates; it requires new R&D investment to be 

maintained and expanded. We use the assumptions developed by Huffman and colleagues to convert annual R&D investments, 

or flows, into R&D capital, or stocks. Under these assumptions, R&D investments influence R&D stocks, and therefore TFP, for up to 

35 years. 

We assume alternative scenarios for future public R&D funding to simulate future growth in U.S. agricultural total factor productivity 

to 2050. We use statistical relationships based on different productivity and investment patterns across States over 1980-2004 

to estimate the effects of R&D stocks on productivity growth. These estimated relationships are used to project future TFP growth 

patterns given alternative assumptions about future R&D spending. Changes in current levels of public R&D spending affect 

future TFP growth only gradually since most of today’s “knowledge capital stock” is the result of past, accumulated investment 

in R&D. In order to model the effects of different scenarios for R&D spending on future TFP growth, we hold the contributions to 

agricultural productivity from other sources—such as agricultural extension, farmer education, infrastructure, economies of scale, 

and technology transfer—constant and allow only the effects from public agricultural R&D to change.
ECONOMIC BRIEF Public Agricultural Research Spending and Future U.S. Agricultural Productivity Growth:

Scenarios for 2010-2050

UNITED STATES DEPARTMENT OF AGRICULTURE 6

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