Agriculture’s role in the process of economic growth has framed a central question in development economics for several decades. While arguments differ regarding the specific mechanisms through which agricultural productivity increases might contribute to structural
change in the economy, it has long been theorized that advances in the agricultural sector can promote shifts in labor to higher productivity sectors that offer higher real incomes.
Empirical work in more recent years has helped inform the conceptual arguments and underscored the long-term growth and poverty reduction benefits from agriculture, especially for the most extreme forms of poverty. At the same time, recent evidence has also underscored the role of the manufacturing sector in driving structural change and long-term convergence in incomes across countries. This and other evidence regarding agriculture’s relatively low value added per worker compared to other sectors has prompted some researchers to narrow the number of developing countries in which agriculture is recommended as a priority sector for investment in light of higher prospective growth returns in non-agricultural sectors. These debates present a first-order concern for understanding why some countries have not experienced long-term economic progress and what to do about it. If agriculture can play a central and somewhat predictable role within the poorest countries, then it is a natural candidate for targeted public investment.
The theoretical and empirical literature regarding structural change is vast, yet identifying the causal role of agricultural productivity is challenging because relevant indicators of structural change trend together in the process of development; impacts on labor force structure are likely to occur after a lag; and statistical identification is not amenable to microstyle experiments. Our contribution in this paper is to focus on the role of agricultural inputs as drivers of higher yields and subsequent economic transformation, using the unique economic geography of fertilizer production in our identification strategy. Large-scale nitrogen fertilizer production occurs in a limited number of countries around the world, owing partly to the fact that the Haber-Bosch process requires natural gas. Transporting this fertilizer to each country’s agricultural heartland generates cross-sectional variation due to economic geography, akin to Redding and Venables’ model of “supplier access” to intermediate goods, which is estimated to affect income per capita. Our identification strategy exploits this variation in supplier access as well as temporal variation in the global fertilizer price to generate a novel instrument for fertilizer use. To our knowledge this is the first application of economic geography towards causally identifying the relationship between agriculture and structural change.
Our paper builds on the insights of Lagakos and Waugh, which highlight the gaps in understanding of cross-country variations in agricultural productivity. A variety of studies have estimated sources of total factor productivity (TFP) in agriculture in the poorest countries, including in sub-Saharan Africa, but agriculture is such an input-intensive sector that TFP assessments only provide one piece of the overarching crop sector puzzle. Our econometric strategy proceeds in two parts. First, we empirically assess the inputs that contributed to increased productivity in staple agriculture, as proxied by cereal yields per hectare, during the latter decades of the 20th century. Using cross-country panel data, this forms a macro-level physical production function for yield increases. We find evidence for fertilizer, modern variety seeds and water as key inputs to yield growth, controlling for other factors such as human capital and land-labor ratios. Second, we deploy our novel instrument to examine the causal link between changes in cereal yields and aggregate economic outcomes, including gross domestic product (GDP) per capita, labor share in agriculture, and non-agricultural value added per worker. We find evidence that increases in cereal yields have both direct and indirect positive effects on economy-wide outcomes. The results are particularly pertinent when considering economic growth prospects for countries where a majority of the labor force still works in agriculture.
The next section of this paper motivates the empirical work, drawing from the many contributions in the literature towards understanding structural change. Section 3 presents empirical models both for estimating the physical production function for cereal yields and for estimating the effect of yield increases on economic growth, labor share in agriculture, and non-agricultural value added per worker. Section 4 describes the data, Section 5 presents the results, and Section 6 concludes.