ECONOMIC GROWTH: LESSONS FROM TWO CENTURIES OF AMERICAN AGRICULTURE

International Development,

On the intersectoral migration of agricultural labor

Labor is the single most important factor in determining national income. As economies grow, agricultural labor declines as a share of total labor and converges to a level of 2 or 3 percent. Off-farm migration facilitates the development of nonagriculture, but historically the process spans decades. The authors argue that the pace of the process is a fundamental outcome of a dynamic equilibrium based on expectations of lifetime earnings and the cost of migration. The authors present an empirical model of the determinants of intersectoral migration. One fundamental determinant is income differences across sectors. As such, migration should stop when income differences reach a certain level. The authors provide a method of measuring the level at which intersectoral migration will cease. While there are credible reasons for a permanent difference to exist between sectoral incomes, the authors find no empirical evidence of a permanent wedge.Environmental Economics&Policies,Labor Policies,Banks&Banking Reform,Municipal Financial Management,Health Economics&Finance,Banks&Banking Reform,Economic Theory&Research,Municipal Financial Management,Environmental Economics&Policies,Health Economics&Finance

On the relevance of world agricultural prices

This report is part of an attempt to model the global markets for primary commodities and to use these models for forecasting purposes as well as for policy analysis. In a free market, domestic prices on agricultural products could be expected to vary with world prices. But intervention is so common with agricultural products that prices vary between countries and gaps exist between world and domestic prices. International prices are often used as a proxy for domestic prices. But it is often claimed that world prices are irrelevant to agricultural development in countries that intervene in agricultural pricing. This paper examined the appropriateness of this substitution in measuring, for example, the agricultural supply response to price changes - particularly in the long run. It concluded that on the whole, world prices are indeed relevant. The results - for 18 countries and 17 commodities - are surprisingly robust, and invariant to both data sources and time/commodity pooling.Access to Markets,Environmental Economics&Policies,Economic Theory&Research,Pharmaceuticals&Pharmacoeconomics,Markets and Market Access

The determinants of agricultural production : a cross-country analysis

In this analysis of capital's role in agricultural production, a new construction of data on capital allowed the authors to advance the cross-country study of production functions. The model reveals the relative importance of capital, a finding quite robust to modifications of the model and the disaggregation of capital to its two components. The model is also consistent with the view that lack of physical capital serves as a constraint on agricultural growth. The shift to more productive techniques is associated with a decline in labor, reflecting labor-saving technical changes. This is not news, but it is emphasized here because it comes out an integral view of the process which distinguishes between the core technology and the changes that took place over time and between countries. Not only is capital important to agricultural production, and agricultural development dependent on the economic environment, but agriculture is more cost-capital-intensive than nonagriculture. Capital is all the more important as a factor of production in that land (also important) varies little over time. The availability of agricultural capital determines whether the gap between available and applied technologies can be closed. Prices have little direct, immediate impact on agricultural growth, beyond their impact through inputs and choice of technology. The legacy of past policies that distorted the relative returns to economic activity is enshrined in current stocks, which may respond slowly to policy reform. The analysis assumes that the production technology is heterogeneous and the implemented technology is endogenous and determined jointly with the level of unconstrained inputs. Thus, a change in the state variables affects both the technology and the inputs, so the production function is not identified. To overcome that problem, changes in productivity are decomposed to three orthogonal components caused by the fundamentally different processes underlying panel data. The statistical framework explains the unstable results observed in production functions derived from panel data. Statistically, the results depend on how the data are projected. Comparisons between units over time or of deviations from unit-means or time-means all describe different processes. This is based on theory but has an intuitive appeal as well. In this case, the spread in productivity among countries is different from the spread in productivity for a country through time. The factors explaining the spread will differ. The modeling approach should explicitly recognize the fact that panel data measure a combination of economic phenomena.Labor Policies,Environmental Economics&Policies,Economic Theory&Research,Agricultural Knowledge&Information Systems,General Technology,Economic Theory&Research,Environmental Economics&Policies,Agricultural Knowledge&Information Systems,Economic Growth,Scientific Research&Science Parks

Agricultural dynamics in Thailand, Indonesia and the Philippines

The introduction of new high‐yielding varieties of cereals in the 1960s, known as the green revolution, dramatically changed the food supply in Asia, as well as in other countries. In the present paper we examine, over an extended period, the growth consequences for agriculture in Indonesia, Thailand and the Philippines. Despite geographical proximity, similar climate and other shared characteristics, gains in productivity and income differed significantly among the countries. We quantify these differences and examine their determinants. We find that the new technology changed the returns to fertilisers, irrigated land and capital, all of which proved scarce to varying degrees. Complementing technology‐related changes in factor use were investments, public and private, driven in part by policy. We find that factor accumulation played an important role in output growth and that accumulations from policy driven investments in human capital and public infrastructure were important sources of productivity gains. We conclude that policies that ease constraints on factor markets and promote public investment in people and infrastructure provide the best opportunities for agricultural growth.International Development,

Heterogeneous technology and panel data : the case of the agricultural production function

The paper presents empirical analysis of a panel of countries to estimate an agricultural production function using a measure of capital in agriculture absent from most studies. The authors employ a heterogeneous technology framework where implemented technology is chosen jointly with inputs to interpret information obtained in the empirical analysis of panel data. The paper discusses the scope for replacing country and time effects by observed variables and the limitations of instrumental variables. The empirical results differ from those reported in the literature for cross-country studies, largely in augmenting the role of capital, in combination with productivity gains, as a driver of agricultural growth. The results indicate that total factor productivity increased at an average rate of 3.2 percent, accounting for 59 percent of overall growth. Most of the remaining gains stem from large inflows of fixed capital into agriculture. The results also suggest possible constraints to fertilizer use.Economic Theory&Research,Labor Policies,Economic Growth,E-Business,Rural Development Knowledge&Information Systems

Measures of fixed capital in agriculture

Capital is a fundamental component of agricultural production, and the accumulation of capital is key to growth in agriculture and the process of development. Unfortunately, cross-country data sets on agricultural fixed capital are rare. Using a common methodology that allows comparisons across countries, as well as over time, this paper introduces a data series on fixed capital in agriculture, based on national accounts data. The fixed capital measure differs remarkably from the Food and Agriculture Organization's data series on tractors, which has been widely utilized as a proxy for agricultural fixed capital. The authors construct comparable measures of capital in livestock and tree stock. They examine the evolution of the capital stocks from 1970 to 2000, paying particular attention to the changing composition of agricultural capital, as well as differences in the accumulation of capital for high-income and middle and lower-income countries. Using the capital measures in agricultural productivity analyses, the data yield estimated input elasticities substantially different from those found previously in the literature. The authors show explicitly that this is due to the improved data set on agricultural capital stocks, as well as the methodology used in the study.Economic Theory&Research,Investment and Investment Climate,Rural Development Knowledge&Information Systems,Economic Growth,Emerging Markets

Incentives and constraints in the transformation of Punjab agriculture:

Economic growth is driven by technical change. Understanding the many factors that influence technical change is therefore key to an understanding of economic growth and its potential. Technical change has two aspects first, it has to be generated, and second, it has to be implemented. Incentives and Constraints in the Transformation of Punjab Agriculture, Research Report 87, by Anya McGuirk and Yair Mundlak, examines the factors that determined the pace of implementation of new techniques in agriculture in Punjab, India, from 1960 to 1979.It is widely recognized that new crop varieties usually take many years to fully come into use. The same is true of other new practices; for instance, the mechanization of agriculture or, more recently, cultivation under plastic. This time lapse has several explanations. Producers have to learn to grow the new varieties, or more generally, to use the new techniques, which requires information. The use of more sophisticated techniques requires human capital, and farmers with inadequate schooling will be unable to adopt them quickly. At the learning stage, there is uncertainty as to the performance of the new techniques, so farmers consider them risky and are cautious about using them. Another element of risk may be that more productive varieties sometimes perform well under very specific climatic and soil conditions, but when such conditions are not met their performance may be poor.Agriculture Economic aspects India Punjab.,

A new database on investment and capital for agriculture and manufacturing

In this paper, the authors document a new database on sectoral investment and capital, providing details about sources of investment data and the method used to convert those data series into capital stock series. They also provide a copy of the computer program used to implement the method. The data set is available for electronic distribution and will soon be posted on the World Wide Web. They broadly define agricultural capital and calculate series for fixed capital as well as capital embodied in livestock and treestock.Agricultural Research,Banking Law,Economic Theory&Research,International Terrorism&Counterterrorism,Fiscal&Monetary Policy,Economic Theory&Research,Agricultural Research,International Terrorism&Counterterrorism,National Governance,ICT Policy and Strategies