How Well Do Degree Days over the Growing Season Capture the Effect of Climate on Farmland Values?

Totally new draft of paper on degree days:

This paper presents an analytical framework to study the economics of adaptation to climate change, reviews the alternative methodologies that have been used to measure adaptation, and briefly summarizes the empirical results. The paper concludes with some general guidance for policy makers on climate adaptation and with some observations of promising areas for additional research.

Massetti, E., R. Mendelsohn and S. Chonabayashi. 2015. "How Well Do Degree Days over the Growing Season Capture the Effect of Climate on Farmland Values?"

New draft: "Migration and Climate Change in Rural Africa"

Climate change is expected to severely affect people’s livelihoods through, among others, rising temperatures and changing precipitation patterns. Here we show that average temperature and precipitations significantly affect migration decisions of farm households in Ghana and Nigeria. We find that farmers that live in the least favorable climates for agriculture have the lowest propensity to migrate among all farm households. As climatic conditions worsen, farm households are likely to migrate less. Our result are consistent with the widely accepted conclusions of two large bodies of literature which have been only marginally connected before. Many migration studies suggest that lower incomes and lower assets reduce migration rates in developing countries. There is also general agreement that climate change will reduce agricultural productivity in low-latitude developing countries. Taken together, these two streams of literature, lead to assume that climate change, especially in areas that will become less hospitable but not uninhabitable, could reduce migration rates. In the literature this is known as the environmental-capital hypothesis, whereby increased productivity due to better conditions provides the capital to finance costly migration, while a worsening in the climate could be associated with lower chances of migration.


Cattaneo, C. and E. Massetti. 2015. “Climate and Migration in Rural Ghana and Nigeria.”

The economics of adaptation to climate change

This paper presents an analytical framework to study the economics of adaptation to climate change, reviews the alternative methodologies that have been used to measure adaptation, and briefly summarizes the empirical results. The paper concludes with some general guidance for policy makers on climate adaptation and with some observations of promising areas for additional research.


Massetti, E. and R. Mendelsohn. 2015. "The Economics of Adaptation to Climate Change"

Using Cross-Sectional Analysis to Measure the Impact of Climate on Agriculture

This paper examines the strengths and weaknesses of using cross-sectional methods to study climate impacts on agriculture. The paper addresses concerns about missing variable bias, irrigation, prices, and carbon fertilization. The paper then reviews the predicted marginal climate impacts of cross-sectional Ricardian models from around the world. The qualitative results are quite similar to findings from agro-economic models. The quantitative results suggest a hill-shaped relationship with respect to both temperature and precipitation. This implies warming will be especially harmful in the low latitudes but possibly beneficial in the mid to high latitudes. The impacts vary between rainfed and irrigated farms and between crop and livestock farms. The expected damage from warming for the next century on global production is about the same magnitude as the likely benefit of carbon fertilization.

Mendelsohn, R. and E. Massetti. 2015. "Using Cross-Sectional Analysis to Measure the Impact of Climate on Agriculture"

Local Pollution and Carbon Pricing

This paper presents economic benefit estimates of air quality improvements in Europe that occur as a side effect of GHG emission reductions. We consider two climate policy scenarios from two Representative Concentration Pathways (RCPs), in which radiative forcing levels are reached in 2100. The policy tool is a global uniform tax on all GHG emissions in the Integrated Assessment Model WITCH. The resulting consumption patterns of fossil fuels are used to estimate the physical impacts and the economic benefits of pollution reductions on human health and on key assets by implementing the most advanced version of the ExternE methodology with its Impact Pathway Analysis. The mitigation scenario compatible with +2°C (RCP 2.6) reduces total pollution costs in Europe by 84%. Discounted cumulative ancillary benefits are equal to about €1.7 trillion between 2015 and 2100, or €17 per abated tonne of CO2 in Europe. The less strict climate policy scenario (RCP 4.5) generates benefits equal to €15.5 per abated tonne of CO2. Without discounting, the ancillary benefits are equal to €51 (RCP 2.6) and €46 (RCP 4.5) per tonne of CO2 abated. For both scenarios, the local benefits per tonne of CO2 decline over time and vary significantly across countries.

Ščasný, M., E. Massetti, J. Melichar and S. Carrara. 2015. “The ancillary benefits of the Representative Concentration Pathways on Air Quality in Europe.” Environmental and Resource Economics, 62(2): 383-415.

Did farmers in the Eastern US adapt to climate change?

Better ask first if climate has changed in the Eastern US.

A note on the the long-difference method – Burke and Emerick (2013)

Burke andEmerick (2013) study if corn and soybeans growers in the Eastern US have adapted to climate change from 1980 to 2000. Instead of climate they consider five-year weather and crop yield averages from 1978 to 1982 and from 1998 to 2002. For each county they calculate the differences of average yields between the five-year averages centered on 1980 and 2000 and regress it on the difference between 1980 and 2000 of the average number of degree days below and above 29 °C during April-September. They find that the coefficient of degree days above 29 °C is negative and significant, as expected. However, the coefficient is not significantly different from the coefficient estimated using a traditional panel model with fixed effect. It thus seems that the response function of yields is the same whether it is estimated using weather fluctuations or longer term temperature changes. They argue this is evidence of lack of adaptation.

I argue instead that this is just what one would expect to observe. Because climate has not changed in the Eastern US. Burke and Emerick (2013) captures noisy weather signals rather than a stable climate pattern.

See here for a longer discussion, references to the scientific literature and maps of climate patterns in the Eastern US.

Adaptation to extreme heat?

A note on the interpretation of results in Deschênes and Greenstone (2011) by Dell, Jones, and Olken (2014)

Deschênes and Greenstone (2011) use interannual weather fluctuations to identify the effect of temperature on mortality. They find that days with temperature above 90 F sharply and significantly increase the mortality rate. Note that days with mean temperature above 90 F are very rare. In several regions the number of days is close to 0.1 (one day every ten years on average).

Deshênes and Greenstone divide the sample in nine regions and repeat the panel estimate for each of them. (Dell, Jones, and Olken 2014)regress the nine regional coefficients of temperature above 90 F on the average number of days in which temperature above 90 F is observed in each region.

One would expect a significant negative relationship, indicating that regions with more extreme temperature events have adapted at the extensive margin to reduce mortality. However, they do not find a significant relationship and this is taken as evidence of lack of adaptation. This conclusion is questionable.

The regional regressions reveal that days with temperature above 90 F are significantly harmful only in regions where the extreme temperatures are observed with some frequency. In the other regions the estimates are not precise and sometimes the coefficients are negative, which is a counter-intuitive result. The estimates of six of out nine coefficients are thus not precise. It is not a surprise that Dell, Jones, and Olken (2014) do not find a significant relationship and this should not be taken as evidence that hottest regions do not adapt to the extreme temperatures.

For a more detailed discussion see here.

Will climate change increase or decrease migration in rural Africa?

In a recent working paper Cristina Cattaneo and I examine how climate affects migration decisions at the household level in rural Ghana and Nigeria. Contrary to most of the other papers in the literature, we deal with climate - i.e. the long-run average of weather - rather than with climate shocks.

Is migration an adaptation that households in Ghana and Nigeria use to cope with current climate?

If the answer is yes, it is reasonable to expect that migration will also be an adaptation to future climate change.

The data to test these predictions are drawn from two different household surveys: the Nigeria General Household Survey and the Ghana Living Standard Survey. We find a hill-shaped relationship between temperature in the dry season and the propensity to migrate in households that operate farms. We also find a significant hill-shaped relationship between precipitations in the wet seasons and the propensity to migrate in farm households. Climate has instead no significant impact on the propensity to migrate in non-farm households. Climate change scenarios generated by General Circulation model reveal that, ceteris paribus, migration may decline in Ghana and in Nigeria.

I copy below maps of marginal effects of temperature and of precipitations on the probability of a household to have at least one migrant member.

Cattaneo, C. and E. Massetti. 2015. “Climate and Migration in Rural Ghana and Nigeria.” FEEM and Georgia Institute of Technology, mimeo.