Abstract Despite wide availability of publicly reported price and quantity movements of agricultural commodities, these data alone do not easily allow one to determine whether and to what extent changing market conditions are due to shifts in underlying supply and demand curves. Such information, however, is needed to determine contemporaneous changes in consumer and producer well-being. To address these issues, this paper derives supply and demand indices, links the indices to structural parameters in equilibrium displacement models, and shows how the measures can be used to calculate welfare changes over time. Empirical applications are presented for the US cattle, hog, and chicken sectors and for county-level corn supply. We show that supply and demand improvements have led to significant gains in beef producer and consumer welfare over time. Hog, and especially chicken, supply indices have increased markedly over the past four decades, reflecting significant productivity gains, whereas growth in cattle supply index has stagnated in recent years. We test the validity of the supply and demand indices for livestock, and find they correlate in hypothesized directions with factors such as corn prices, drought, aggregate agricultural total factor productivity, gross national product, and exchange rates. Trends in disaggregate corn supply indices reveal marked heterogeneity across US counties with the largest gains since 1980 being observed in the Dakotas, Kansas, Missouri, and the Mississippi Delta. Many areas of Ohio and Indiana have experienced negative corn supply shocks in 2016–8 relative to 2000. The approaches illustrated in this paper potentially have wide application in the study of many agricultural markets. For example, the supply index is an easy to calculate commodity- and geography-specific alternative to commonly used aggregate total factor productivity measures. The demand, supply, and welfare indices can provide timely information about the economic fundamentals in a market that can be coupled with other data to analyze structural adjustment patterns and rapidly determine changes in the well-being of producers and consumers.
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