Wolfram Schlenker

Climate Trends and Global Crop Production Since 1980

Climate change has decreased global maize and wheat production, while soybean and rice production have remained stable. Efforts to anticipate how climate change will affect future food availability can benefit from understanding the impacts of changes to date. We found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability. Models that link yields of the four largest commodity crops to weather indicate that global maize and wheat production declined by 3.8 and 5.5%, respectively, relative to a counterfactual without climate trends. For soybeans and rice, winners and losers largely balanced out. Climate trends were large enough in some countries to offset a significant portion of the increases in average yields that arose from technology, carbon dioxide fertilization, and other factors.

Robust negative impacts of climate change on African agriculture

There is widespread interest in the impacts of climate change on agriculture in Sub-Saharan Africa (SSA), and on the most effective investments to assist adaptation to these changes, yet the scientific basis for estimating production risks and prioritizing investments has been quite limited. Here we show that by combining historical crop production and weather data into a panel analysis, a robust model of yield response to climate change emerges for several key African crops. By mid-century, the mean estimates of aggregate production changes in SSA under our preferred model specification are − 22, − 17, − 17, − 18, and − 8% for maize, sorghum, millet, groundnut, and cassava, respectively. In all cases except cassava, there is a 95% probability that damages exceed 7%, and a 5% probability that they exceed 27%. Moreover, countries with the highest average yields have the largest projected yield losses, suggesting that well-fertilized modern seed varieties are more susceptible to heat related losses.

Will U.S. Agriculture Really Benefit from Global Warming? Accounting for Irrigation in the Hedonic Approach

Will U.S. Agriculture Really Benefit from Global Warming? Accounting for Irrigation in the Hedonic Approach. Wolfram Schlenker, W. Michael Hanemann, and Anthony C. Fisher ∗ There has been a lively debate about the potential impact of global climate change on U.S. agriculture. Most of the early agro-economic studies predict large damages (see, for example, Richard M. Adams, 1989; Harry M. Kaiser et al., 1993; and Adams et al., 1995). In an innovative paper Robert Mendelsohn, William D. Nordhaus and Daigee Shaw (1994) - hereafter MNS - propose a new approach: using the variation in temperature and precipitation across U.S. counties to estimate a reduced form hedonic equation with the value of farmland as the dependent variable. A change in temperature and/or precipitation is then associated with a change in farmland value which can be interpreted as the impact of climate change. Adams et al. (1998) characterize the hedonic approach as a spatial analogue approach, and acknowledge that ”the strength of the spatial analogue approach is that structural changes and farm responses are implicit in the analysis, freeing the analyst from the burden of estimating the effects of climate change on particular region-specific crops and farmer responses.” On the other hand, one of the potential disadvantages of the hedonic approach is that it is a partial equilibrium analysis, i.e., agricultural prices are assumed to remain constant. 1 While year-to-year fluctuations in annual weather conditions certainly have the potential to impact current commodity prices, especially for crops produced only in a relatively localized area, (such as citrus fruits which are grown mainly in California and Florida), changes in long-run weather patterns (i.e., changes in climate) might have a smaller effect on commodity prices because of the greater potential for economic adaptation, particularly shifts in growing regions. 2 The hedonic approach as implemented by MNS predicts that existing agricultural land on average might be more productive and hence result in benefits for U.S. farmers. 3 The hedonic approach has received considerable attention in our judgment in part because the conclusions are at variance with those of some other studies

Greater sensitivity to drought accompanies maize yield increase in the U.S. Midwest

Predicting Responses to Drought The U.S. Corn Belt accounts for a sizeable portion of the worlds maize growth. Various influences have increased yields over the years. Lobell et al. (p. 516; see the Perspective by Ort and Long) now show that sensitivity to drought has been increasing as well. It seems that as plants have been bred for increased yield under ideal conditions, the plants become more sensitive to non-ideal conditions. A key factor may be the planting density. Although todays maize varieties are more robust to crowding and the farmer can get more plants in per field, this same crowding takes a toll when water resources are limited. Selective breeding focused on increasing corn and soybean yields has left a weakness in corn drought tolerance. [Also see Perspective by Ort and Long] A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level data set on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased carbon dioxide and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale.

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of data sets available, and then we discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions

We link farmland values to climatic, soil, and socioeconomic variables for U.S. counties east of the 100th meridian, the historical boundary of agriculture not primarily dependent on irrigation. Degree days, a nonlinear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield, gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust, and more than 75 of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.

Consumer and Market Responses to Mad Cow Disease

We examine how consumers and financial markets in the United States react to two health warnings about mad cow disease: the first discovery of an infected cow in December 2003 and an Oprah Winfrey show on the potentially harmful effects that aired seven years earlier. Using a unique product-level scanner data set of a national grocery chain, we find a pronounced and significant reduction in beef sales following the first discovered infection, which dissipates slowly over the next three months. Cattle futures show a comparable pattern of abnormal price drops to the scanner data. Contracts with longer maturity show smaller drops, suggesting that the market anticipated the impact to be transitory. Cattle futures show abnormal price drops after the Oprah Winfrey show that are more than 50% of the drop following the 2003 discovery of an infected cow.

Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields

Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO2 could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO2 and temperature or precipitation to have little effect on mean yield changes.

Consistent negative response of US crops to high temperatures in observations and crop models

High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 °C. Elevated CO2 can only weakly reduce these yield losses, in contrast to irrigation.

Asylum applications respond to temperature fluctuations

Warming stresses developing countries Weather-induced conflicts in developing countries spill over to developed countries through asylum applications. One approach to estimating the future impacts of climate change is to look at the effects of weather fluctuations. These transient shocks can be interpreted analytically as randomly distributed treatments applied to countries around the world. Missirian and Schlenker analyzed the relation between these localized shocks to agriculture and applications by that countrys migrants for asylum in the European Union. When temperatures in the source country deviated from a moderate optimum around 20°C that is best for agriculture, asylum applications increased. Thus, the net forecast is for asylum applications to increase as global temperatures rise. Science, this issue p. 1610 The number of migrants seeking asylum in the European Union will increase as the climate warms. International negotiations on climate change, along with recent upsurges in migration across the Mediterranean Sea, have highlighted the need to better understand the possible effects of climate change on human migration—in particular, across national borders. Here we examine how, in the recent past (2000–2014), weather variations in 103 source countries translated into asylum applications to the European Union, which averaged 351,000 per year in our sample. We find that temperatures that deviated from the moderate optimum (~20°C) increased asylum applications in a nonlinear fashion, which implies an accelerated increase under continued future warming. Holding everything else constant, asylum applications by the end of the century are predicted to increase, on average, by 28% (98,000 additional asylum applications per year) under representative concentration pathway (RCP) scenario 4.5 and by 188% (660,000 additional applications per year) under RCP 8.5 for the 21 climate models in the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).