Katrina Jessoe, the University of California at Davis, and Reena Badiani, The World Bank
Electricity Prices, Groundwater and Agriculture:
The Environmental and Agricultural Impacts of Electricity Subsidies in India
In this paper Jessoe and Badiani estimate the causal effect of agricultural electricity subsidies in India on groundwater extraction and agricultural output. Their empirical approach exploits changes in state electricity prices over time controlling for aggregate annual shocks and fixed district unobservables. Electricity subsidies meaningfully increase groundwater extraction, where the implied price elasticity is -0.18. This subsidy-induced change in groundwater extraction impacted agricultural output and crop composition, increasing the value of water-intensive output and the area on which these crops are grown. These subsidies also increase the probability of groundwater exploitation, suggesting that they may come at an unintended and long-term environmental cost.
Sofia Villas-Boas, Rebecca Taylor, and Hannah Krovetz, the niversity of California at Berkeley
Willingness to Pay for Low Water Footprint Food Choices During Drought
In the context of recent California drought years, Krovetz, Taylor, and Villas-Boas investigate empirically whether consumers are willing to pay for more efficient water usage in the production of four California agricultural products. They implement an internet survey choice experiment for avocados, almonds, lettuce, and tomatoes to elicit consumer valuation for water efficiency via revealed choices. The researchers estimate a model of consumer choices where a product is defined as a bundle of three attributes: price, production method (conventional or organic), and water usage (average or efficient). Varying the attribute space presented to consumers in the experimental choice design gives us the data variation to estimate a discrete choice model both conditional logit specifications and random coefficient mixed logit specifications. They find that on average consumers have a significant positive marginal utility towards water-efficiency and estimate that there is an implied positive willingness to pay (WTP) of about 12 cents per gallon of water saved on average. Moreover, informing consumers about the drought severity increases the WTP for low water footprint options, but not significantly. The researchers find that there is heterogeneity in the WTP along respondents' education, race, and also with respect to stated environmental concern. The researchers' findings have policy implications in that they suggest there to be a market based potential to nudge consumers who want to decrease their water footprint and follow a more sustainable diet, namely, by revealing information on the product's water footprint in a form of a label. Simulations of removing low water footprint labels from the choice set attributes imply significant consumer surplus losses, especially for the more educated, white, and more environmentally concerned respondents.
Hsing-Hsiang Huang, Environmental Protection Agency, and Michael Moore, the University of Michigan
Farming Under Weather Risk: Adaptation, Moral Hazard, and Selection on Moral Hazard
Farmers in the American Midwest decide on agricultural land use (cropping pattern) and crop insurance in springtime after observing pre-plant precipitation. Huang and Moore examine cropping-pattern adaptation to pre-plant precipitation as a natural experiment. In tandem with the weather experiment, they also exploit a quasi-experiment created by a federal program that sharply reduced insurance deductibles to examine both risk-taking in cropping pattern as a moral hazard of insurance and selection of insurance coverage in response to the risk-taking. Using a 2001-2014 panel of high-resolution spatial data on land use and weather, the researchers present evidence of heterogeneous adaptation in cropping pattern across the large agricultural states of Illinois, Iowa, Nebraska, and North Dakota. They also find evidence of heterogeneous risk-taking in cropping pattern during the federal program in 2009-2011, with farmers in Nebraska and North Dakota much more responsive to pre-plant precipitation in both their adaptation and risk-taking than farmers in Illinois and Iowa. Using a 2001-2014 panel of county-level data on crop insurance expenditures, the researchers find limited evidence of selection on moral hazard in insurance expenditures in response to pre-plant precipitation. Farmers in Illinois and Iowa increase (decrease) the rate of insurance expenditures on corn when they increase (decrease) corn acres. They do so to a lesser degree with soybeans. The interaction of adaptation, moral hazard, and selection on moral hazard provides new insight into incentives, hidden actions, and hidden information in major cropland and insurance markets.
Wyatt Brooks and Kevin Donovan, the University of Notre Dame
Eliminating Uncertainty in Market Access: The Impact of New Bridges in Rural Nicaragua
Brooks and Donovan estimate the impact of new infrastructure in rural Nicaraguan villages facing seasonal flooding risk that unpredictably eliminate access to outside markets. The researchers build bridges designed to eliminate this risk. Identification exploits small engineering requirements that preclude construction in some villages, despite their need for a bridge. The researchers collect detailed annual household surveys over three years and weekly telephone followups with a subset of households for sixty-four weeks, both before and after construction. Bridges eliminate uncertainty in market access driven by floods: during flood episodes in control villages labor market earnings decrease by 15 percent, while there is no change in treatment villages. They also find substantial reallocation of activities between farming and wage work, increased fertilizer spending and yields on farms, and lower savings. The researchers show that these results are outcomes of a model with occupational choice and risky farm investment, where bridges act as a consumption smoothing technology by providing more consistent off-farm labor market access.
Cecilia Bellora, CEPII; Elodie Blanc, Massachusetts Institute of Technology; Jean-Marc Bourgeon, INRA; and Eric Strobl, Ecole Polytechnique
Estimating the Impact of Crop Diversity on Agricultural Productivity in South Africa
Christine L. Carroll, Colin A. Carter, Rachael Goodhue, and C.-Y. Cynthia Lin Lawell, the University of California at Davis
Crop Disease and Agricultural Productivity
Crop diseases and how they are managed can have a large impact on agricultural productivity. This paper discusses the effects on agricultural productivity of Verticillium dahliae, a soil borne fungus that is introduced to the soil via infested spinach seeds and that causes subsequent lettuce crops to be afflicted with Verticillium wilt. Carroll, Carter, Goodhue, and Lin Lawell use a dynamic structural econometric model of Verticillium wilt management for lettuce crops in Monterey County, California, to examine the effects of Verticillium wilt on crop-fumigation decisions and on grower welfare. The researchers also discuss their research on the externalities that arise with renters, and between seed companies and growers due to Verticillium wilt, as these disease-related externalities have important implications for agricultural productivity.
Jayson L. Lusk, Oklahoma State University; Jesse B. Tack, Mississippi State University; and Nathan P. Hendricks, Kansas State University
Heterogeneous Yield Impacts from Adoption of Genetically Engineered Corn and the Importance of Controlling for Weather
Concern about declining growth in crop yields has renewed debates about the ability of biotechnology to promote food security. While numerous experimental and farm-level studies have found that adoption of genetically engineered crops has been associated with yield gains, aggregate and cross-country comparisons often seem to show little effect, raising questions about the size and generalizability of the effect. Lusk, Tack, and Hendricks attempt to resolve this conundrum using a panel of United States county-level corn yields from 1980 to 2015 in conjunction with data on adoption of genetically engineered crops, weather, and soil characteristics. The researchers' panel data contain just over 28,000 observations spanning roughly 800 counties. They show that changing weather patterns confound simple analyses of trend yield, and only after controlling for weather do they find that genetically engineered crops have increased yields above trend. There is marked heterogeneity in the effect of adoption of genetically engineered crops across location, partially explained by differential soil characteristics which may be related to insect pressure. While adoption of genetically engineered crops has the potential to mitigate downside risks from weeds and insects, The researchers find no effects of adoption on yield variability nor do they find that adoption of presently available genetically engineered crops has led to increased resilience to heat or water stress. On average, across all counties, they find adoption of GE corn was associated with a 17 percent increase in corn yield.
Mark Brown, Statistics Canada; Shon M. Ferguson, Research Institute of Industrial Economics (IFN); and Crina Viju, Carleton University
Agricultural Trade Reform, Reallocation and Technical Change: Evidence from the Canadian Prairies
Brown, Ferguson, and Viju decompose the impact of trade reform on technology adoption and land use to study how aggregate changes were driven by reallocation versus within-farm adaptation. Using detailed census data covering over 30,000 farms in Alberta, Saskatchewan, and Manitoba, Canada, the researchers find a range of new results. They find that the reform-induced shift from producing low-value to high-value crops for export, the adoption of new seeding technologies, and reduction in summerfallow observed at the aggregate level between 1991 and 2001 were driven mainly by the within-farm effect. In the longer run, however, reallocation of land from shrinking and exiting farms to growing and new farms explains more than half of the aggregate changes in technology adoption and land use between 1991 and 2011.
Sebastian Sotelo, the University of Michigan
Domestic Trade Frictions and Agriculture
Sotelo develops a model of heterogeneous land quality and studies the relation between trade, farming productivity and welfare in Peru, where high domestic and international trade costs pose a major barrier to efficient farming. To quantify the model, Sotelo uses a new dataset on spatially disaggregated crop prices, yields, and land allocations. He then uses the model to measure the welfare and productivity effects of two shocks to trade opportunities. First, Sotelo studies a policy of paving roads, which raises average productivity and welfare (16% and 4%), but causes some regions to lose due to increased competition from remote suppliers. Second, he studies a shock to international prices that spreads unevenly across regions, generates heterogeneous price adjustments and, therefore, has distributional consequences that differ from those of a standard small open economy model.
Sun Ling Wang, V. Eldon Ball, Richard Nehring, and Ryan Williams, Department of Agriculture, and Truong Chau, Pennsylvania State University
Impacts of Climate Change and Extreme Weather on U.S. Agricultural Productivity
Under climate change, the average daily temperature and the frequency of extreme weather occurrences are expected to increase in the United States. This paper employs a stochastic frontier approach to examine how climate change and extreme weather affect U.S. agricultural productivity using 1940-1970 historical weather data (mean and variation) as the norm. Wang, Ball, Nehring, Williams, and Chau have four major findings. First, using temperature humidity index (THI) load and Oury index for the period 1960-2010 they find each state has experienced different patterns of climate change in the past half century, with some states incurring drier and warmer conditions than others. Second, the higher the THI load (more heat waves) and the lower the Oury index (much drier) will tend to lower a states productivity. Third, the impacts of THI load shock and Oury index shock variables (deviations from historical norm fluctuations) on productivity are more robust than the level of THI and Oury index variables across specifications. Fourth, the researchers project potential impacts of climate change and extreme weather on U.S. regional productivity based on the estimates. They find that the same degree changes in temperature or precipitation will have uneven impacts on regional productivities, with Delta, Northeast, and Southeast regions incurring much greater effects than other regions, using 2000-2010 as the reference period.