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Persistence Pays

U.S. Agricultural Productivity Growth and the Benefits from Public R&D Spending

verfasst von: Julian M. Alston, Matthew A. Andersen, Jennifer S. James, Philip G. Pardey

Verlag: Springer New York

Buchreihe : Natural Resource Management and Policy

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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gricultural science policy in the United States has profoundly affected the growth and development of agriculture worldwide, not just in the A United States. Over the past 150 years, and especially over the second th half of the 20 Century, public investments in agricultural R&D in the United States grew faster than the value of agricultural production. Public spending on agricultural science grew similarly in other more-developed countries, and c- lectively these efforts, along with private spending, spurred agricultural prod- tivity growth in rich and poor nations alike. The value of this investment is seldom fully appreciated. The resulting p- ductivity improvements have released labor and other resources for alternative uses—in 1900, 29. 2 million Americans (39 percent of the population) were - rectly engaged in farming compared with just 2. 9 million (1. 1 percent) today— while making food and fiber more abundant and cheaper. The benefits are not confined to Americans. U. S. agricultural science has contributed with others to growth in agricultural productivity in many other countries as well as the Un- ed States. The world’s population more than doubled from around 3 billion in 1961 to 6. 54 billion in 2006 (U. S. Census Bureau 2009). Over the same period, production of important grain crops (including maize, wheat and rice) almost trebled, such that global per capita grain production was 18 percent higher in 2006.

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Inhaltsverzeichnis

Frontmatter

CONTEXT

Chapter 1. Introduction

Abstract

Agricultural science policy in the United States has profoundly affected the growth and development of agriculture worldwide, not just in the United States. Over the past 150 years, and especially over the second half of the 20th Century, public investments in agricultural R&D in the United States grew faster than the value of agricultural production. Public spending on agricultural science grew similarly in other more-developed countries, and collectively these efforts, along with private spending, spurred agricultural producproductivity growth in rich and poor nations alike.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 2. A Brief History of U.S. Agriculture

Abstract

Almost 150 years have passed since U.S. public-sector agricultural research and development (R&D) began in earnest with the establishment of the U.S. Department of Agriculture and the passage of the Morrill Land Grant College Act in 1862, to be followed 25 years later by the passage of the Hatch Experiment Station Act in 1887. During that time, and especially in the more recent decades, U.S. agriculture changed dramatically. Public and private agricultural R&D played a major role in bringing about those changes, and the R&D systems and institutions evolved alongside and as part of agriculture.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

INPUTS, OUTPUTS AND PRODUCTIVITY

Chapter 3. Agricultural Inputs

Abstract

The structure of U.S. agriculture changed dramatically over the past 100 years, and these changes coincided with large increases in agricultural productivity. Revolutionary technological advancements transformed inputs such as seed, fertilizers, and agricultural chemicals, and the quality of agricultural inputs—notably capital, labor and land—increased generally, especially during the latter half of the 20th Century. The apparent decline in the use of conventional agricultural inputs, particularly over recent decades and especially labor, is offset somewhat when we account properly for the changing composition and quality of inputs over time. For example, farmers are much better educated and more experienced on average compared with 50 years ago, and a higher proportion of cropland is irrigated. Identifying these important structural changes in the nature of inputs helps in constructing an informative picture of U.S. agricultural production and the sources of output growth during the 20th Century; particularly developments during the post-1948 period, which is the subject of more detailed analysis in this volume.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 4. Agricultural Outputs

Abstract

Over the past 100 years and more, U.S. agricultural production grew rapidly and the composition and location of production changed markedly, too. Different measures of agricultural output give different perspectives on these changes. This chapter provides a detailed assessment of the temporal and spatial patterns in the quantity and value of U.S. agricultural production and its composition. The chapter concludes with a presentation of Fisher indexes of output quantities. These indexes are used with the corresponding indexes of input quantities from Chapter 3 to compute the productivity indexes for 1949–2002 that are presented in Chapter 5 and used in the econometric models in subsequent chapters.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 5. Agricultural Productivity Patterns

Abstract

At the center of our empirical work is a model of state-specific productivity growth as a function of investments in agricultural research. While the notions of productivity and changes in productivity are intuitive, it is not easy to develop meaningful measures of productivity or to identify the productivity consequences of investments in agricultural R&D. Schultz (1953) argued that the root reason for an interest in the sources of productivity growth is an interest in the sources of output growth. And, expressing an idea he attributed to Zvi Griliches, Schultz (1956, p. 758) wrote.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

AGRICULTURAL R&D FUNDING AND POLICIES

Chapter 6. Research Funding and Performance

Abstract

How has public and private sector participation in agricultural R&D in the United States changed over the decades, and how has research spending on agriculture fared relative to research spending in all areas of science? Given the international interdependencies in agricultural R&D, how has research spending in the United States evolved relative to spending elsewhere in the world? This chapter describes public and private investments in R&D directed to agriculture in the United States, placing them in the context of both the overall spending on all sciences, and global spending on agricultural R&D. Then, we explore patterns of public spending on agricultural R&D within the United States, both in aggregate and among the states, with attention to the separate and joint roles of the federal government through its USDA intramural labs and the State Agricultural Experiment Stations. We consider the evolving sources of funding as well as the evolving patterns of spending. In Chapter 7, these trends in the funding and performance of agricultural R&D are linked to legislative and other policy changes.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 7. The Federal Role

Abstract

The history of agricultural R&D and related government policy in the United States is one of jointly evolving state and federal, public- and private-sector roles. The private role has always emphasized more-patentable inventions, or at least innovations from which the returns seem more appropriable by a variety of intellectual property rights or other means. In agriculture, in particular, however, it is difficult for individuals to fully appropriate the returns from their research investments, leading to a general consensus that some government action is warranted to ensure an adequate investment in R&D.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

MODELS OF R&D AND PRODUCTIVITY

Chapter 8. Research Lags and Spillovers

Abstract

Modeling and measuring the productivity consequences of R&D is a tricky business. The challenge in attributing productivity to R&D is to establish which research, conducted by whom, and when, was responsible for a particular productivity increase. In other words, in modeling the effects of research on agricultural productivity the two principal areas of difficulty are in the treatment of knowledge spillovers (i.e., the “by whom” part of the attribution problem) and in identifying the lag structure linking research spending, knowledge stocks, and productivity (i.e., the “when” part).

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 9. Models of Research and Productivity

Abstract

In this chapter we develop the structure of our models for estimating the effects of U.S. public agricultural research on U.S. agricultural productivity. We begin by laying out a general model relating research spending to agricultural productivity. Because this general specification includes too many parameters to be estimated individually with any degree of precision, some restrictions must be imposed. A conventional approach is to model productivity as a function of knowledge stocks that are created as a result of past research and can be represented using a distributed lag model defined by a small number of parameters. In this chapter we describe our approach for creating research knowledge stocks, including the specification of the research lag structure and state-to-state (and federal-to-state) spillovers used to construct the knowledge stocks. In later chapters we evaluate the effects of specification choices on our estimates and the implied benefit-cost ratios.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 10. Econometric Estimation and Results

Abstract

The implementation of the general model developed in Chapter 9 requires some specific choices about the detail of the model, beginning with the functional form. In the present chapter we discuss those choices, and present and interpret the resulting econometric estimates, along with the results of some analysis of the sensitivity of the estimates to model specification choices. In Chapter 11 we report the results from using the econometric estimates to compute a range of benefit-cost ratios for alternative types of research spending, and in Chapter 12 we interpret and assess the results from both the econometric estimation and the benefit-cost analysis.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 11. Productivity Patterns and Research Benefits

Abstract

In Chapter 10 we reported the results from estimating models of productivity as a function of variables representing agricultural research and extension knowledge stocks. Various transformations of these models can be used to derive implications that are of interest to economists and policymakers. For instance, we can use the estimated model to evaluate the roles of policies in influencing the pas time path and spatial pattern of agricultural productivity. Alternatively, we can use the model to evaluate the future time path and spatial pattern of agricultural productivity given actual past and likely future research spending patterns or alternative counterfactual spending patterns. Or, we can compare productivity patterns under alternative scenarios of research spending patterns and infer measures such as benefit-cost ratios or internal rates of return.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

INTERPRETATION AND SYNTHESIS

Chapter 12. Interpretation and Assessment of Benefit-Cost Findings

Abstract

Agricultural production, input use, and productivity have been evolving over time, with substantially different patterns among U.S. states; so, too, has the pattern of spending on agricultural research and extension by the federal and state governments. In our econometric models linking these patterns of R&D spending and agricultural productivity, we have imposed a great deal of structure on the research lag and state-to-state spillover relationships. So long as they are appropriate and do not lead to estimation bias, these restrictions are helpful in reducing the number of free parameters to be estimated and improving the precision with which they are estimated. The resulting estimates indicate strong linkages between research and extension spending and productivity, and high payoffs to past investments. They also signal slower future productivity growth, especially if the past slowdown in the rate of growth in spending on farm-productivity-oriented research and extension spending will be sustained into the future.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Chapter 13. Synthesis

Abstract

The history of American agriculture is one of continuing growth and constant change. During the first three hundred years, beginning with the settlement at Jamestown in 1607, growth and development in U.S. agriculture was achieved by doing more with more, at the extensive margin. As the frontier expanded and more land was brought into production by more people, the number of farms and farmers grew. Over time, these farms became more productive through the development and adoption of a host of biological and mechanical innovations, mainly developed without much government involvement. Some of the earlier innovations are visibly evident today—such as barbed wire and steel plows. But many of the crop variety innovations were to counter co-evolving pest and disease pressures or to adapt varieties to new environments, and their impacts are not revealed in aggregate yields that grew very slowly before 1935.

Julian M. Alston, Jennifer S. James, Matthew A. Andersen, Philip G. Pardey

Backmatter

Titel: Persistence Pays
verfasst von: Julian M. Alston
Matthew A. Andersen
Jennifer S. James
Philip G. Pardey
Copyright-Jahr: 2010
Verlag: Springer New York
Electronic ISBN: 978-1-4419-0658-8
Print ISBN: 978-1-4419-0657-1
DOI: https://doi.org/10.1007/978-1-4419-0658-8

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