Agricultural Land Elasticities in the United States and Brazil

Barr, Kanlaya Jintanakul; Babcock, Bruce A.; Carriquiry, Miguel; Nassar, André M.; Harfuch, Leila

doi:10.1093/aepp/ppr011

Cited by 84 publications

(70 citation statements)

References 9 publications

(8 reference statements)

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“…The variable of interest, price, shows the expected positive relationship with cropland. The magnitude of the elasticity of cropland to prices, 0.066, is small but comparable to other estimates from the literature (Barr, 2011;Evans, 2015). Using the dynamic multiplier, the long run elasticity is 0.104.…”

Section: Resultssupporting

confidence: 68%

The Impact of Agricultural Land Use Change on Lake Water Quality: Evidence from Iowa

Meyer¹

2018

Stud. Agr. Econ.

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Section: Resultssupporting

confidence: 68%

The Impact of Agricultural Land Use Change on Lake Water Quality: Evidence from Iowa

Meyer¹

2018

Stud. Agr. Econ.

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“…After accounting for set-aside programs, they find a statistically insignificant extensive margin response to price (see their table 3). Barr et al (2011) also estimate a small price elasticity of the total acreage of major crops in the United States as a whole.…”

Section: Resultsmentioning

confidence: 99%

Crop Supply Dynamics and the Illusion of Partial Adjustment

Hendricks

Smith

Sumner

2014

American J Agri Economics

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We use field-level data to estimate the response of corn and soybean acreage to price shocks. Our sample contains more than eight million observations derived from satellite imagery and includes every field in Iowa, Illinois, and Indiana. We estimate that aggregate crop acreage responds more to price shocks in the short run than in the long run, and we show theoretically how the benefits of crop rotation generate this response pattern. In essence, farmers who change crops due to a price shock have an incentive to switch back to the previous crop to capture the benefits of crop rotation. Our result contradicts the long-held belief that agricultural supply responds gradually to price shocks through partial adjustment. We would not have obtained this result had we used county-level panel data. Standard econometric methods applied to county-level data produce estimates consistent with partial adjustment. We show that this apparent partial adjustment is illusory, and we demonstrate how it arises from the fact that fields in the same county are more similar to each other than to fields in other counties. This result underscores the importance of using models with appropriate micro-foundations and cautions against inferring micro-level rigidities from inertia in aggregate panel data. Our preferred estimate of the own-price long-run elasticity of corn acreage is 0.29 and the cross-price elasticity is -0.22. The corresponding elasticities for soybean acreage are 0.26 and -0.33. Our estimated short-run elasticities are 37 percent larger than their long-run counterparts. 2 How much more land gets allocated to a crop when relative prices change? The answer to this question is the central parameter for understanding world food prospects, the impacts of farm subsidies, and the environmental consequences from land use change, among other public and policy issues (e.g., Roberts and Schlenker 2013;Lichtenberg and Zilberman 1986;Searchinger et al. 2008;Donner and Kucharik 2008). We provide a new and better answer for an important set of commodities in the world food system. We use a conceptual approach that accounts for crop rotations, a massive sample of individual fields, and econometric methods that account for heterogeneous incentives to rotate crops and heterogeneous responses to prices. Moreover, we show that supply response is seriously misestimated when standard econometric methods are applied to county-level panel data. One consequence of this bias is a mistaken understanding of supply dynamics and, in particular, the relationship between short-run and long-run supply response.A typical agricultural field in the United States Corn Belt tends to alternate between growing corn in one year and soybeans the next. This pattern reflects a common agronomic feature of crop production: planting a crop on the same field in consecutive years decreases the productivity of the soil for growing that crop and increases pest populations. These features generate dynamic complementarity in crop production because the marginal valu...

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“…To our knowledge, there are few studies that estimate acreage elasticity at the country level (e.g. Barr et al, 2009;Hausman, 2012), and none at the global level. The effect of price volatility is usually considered as a microeconomic problem for producers.…”

Section: Introductionmentioning

confidence: 99%

Short-Term Global Crop Acreage Response to International Food Prices and Implications of Volatility

2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractUnderstanding how producers make decisions to allot acreage among crops and how decisions about land use are affected by changes in prices and their volatility is fundamental for predicting the supply of staple crops and, hence, assessing the global food supply situation. The innovations of the present paper are estimates of monthly (i.e. seasonal) versus annual global acreage response models for four staple crops: wheat, soybeans, corn and rice. We focus on the impact of (expected) crop prices, oil and fertilizer prices and market risks as main determinants for farmers' decisions on how to allocate their land. Primary emphasis is given to the magnitude and speed of the allocation process. Estimation of intra-annual acreage elasticity is crucial for expected supply and for input demand, especially in the light of the recent short-term volatility in food prices. Such aggregate estimates are also valuable to verify whether involved country-specific estimations add up to patterns that are apparent in the aggregate international data. The econometric results indicate that global crop acreage responds to crop prices and price risks, input costs as well as a time trend. Depending on respective crop, short-run elasticities are about 0.05 to 0.25; price volatility tends to reduce acreage response of some crops; comparison of the annual and the monthly acreage response elasticities suggests that acreage adjusts seasonally around the globe to new information and expectations. Given the seasonality of agriculture, time is of the essence for acreage response: The analysis indicates that acreage allocation is more sensitive to prices in northern hemisphere spring than in winter and the response varies across months.JEL classifications: O11, O13, Q11, Q13, Q18, Q24

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Agricultural Land Elasticities in the United States and Brazil

Cited by 84 publications

References 9 publications

The Impact of Agricultural Land Use Change on Lake Water Quality: Evidence from Iowa

The Impact of Agricultural Land Use Change on Lake Water Quality: Evidence from Iowa

Crop Supply Dynamics and the Illusion of Partial Adjustment

Short-Term Global Crop Acreage Response to International Food Prices and Implications of Volatility

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