Georgia Tech in Venice

Our great Summer Study Abroad Program on Sustainable Development and Climate Change in Venice has started!

We have already met with climatologists at CMCC in Bologna, visited the MOSE project to protect Venice from the high waters, practice glass making skills in Murano with an exclusive visit to the Seguso glass factory, and explored Venice to understand why it had a great past and how it failed over the centuries.

For some pictures, follow us on Instagram https://www.instagram.com/gtveniceprogram/.

Does harmful climate increase or decrease migration? Evidence from Rural Households in Nigeria

Totally new draft and new title for paper on migration and climate in Nigeria.

Accepted for publication on the November 2019 Issue of Climate Change Economics (updated on June 6, 2019)

Abstract: This paper analyses whether migration is an adaptation strategy that households employ to cope with climate in Nigeria. We estimate our model using cross-section variation in climate and long-term migration decisions because we are interested in the average response to long-term climatic conditions. For households that operate farms, we find that the relationship between climate and migration is non-linear. In particular, climates with closer to ideal farming conditions are associated with a higher propensity to migrate, whereas in the least favorable climatic conditions, the propensity to migrate declines. The marginal effect of rainfall and temperature changes on migration varies by season. We estimate the impact of climate change on the number of migrant households in 2031-2060 and 2071-2100, ceteris paribus. With current population levels, climate change generates between 3.6 and 6.3 million additional migrants, most of them internal. However, these estimates are not statistically significant.

The Effect of Extreme Temperatures and Adaptation across Eastern American Farms

Massetti, E., and R. Mendelsohn. 2019. “The Effect of Extreme Temperatures and Adaptation across Eastern American Farms” Revise and Resubmit.

Abstract. Previous Ricardian models of climate change impacts on agriculture have been criticized because they rely on mean temperatures and do not explicitly include extreme temperatures. This paper compares results using the entire distribution of daily temperature versus just the mean seasonal or growing season temperature in a Ricardian model. Including all temperatures does not increase measured long run damage. The warmest and coldest temperatures cause only modest harm to farmland values suggesting farmers have adapted to these extremes. The paper shows a few examples of these adaptations by farmers.

The IPCC Investment Numbers Are Correct

A comment to a paper published by Energy Policy arguing that investment data reviewed by Chapter 16 of the IPCC Working Group III Fifth Assessment Report - which I co-authored - was totally flawed.



Abstract: Trainer (2017) criticizes cost estimates of climate change mitigation presented in the Working Group III Report to the IPCC and is concerned by lack of transparency and dubious practices in summarizing the literature. This commentary shows that this critique is based on several mistakes. Trainer (2017) mixes evidence on investment changes and evidence on macroeconomic costs, which are discussed in two different parts of the report because they are different indicators of the economic impact of climate mitigation policy. This commentary also argues that when the report was prepared evidence on investments in mitigation technologies was limited but methodologically sound and transparently reported, contrary to what suggested in Trainer (2017).

Massetti, E., C. Carraro, S. Gupta, J. Harnish and R.J. Kopp. 2017. “Investments in and Macroeconomic Costs of Climate Mitigation in the Working Group III Contribution to the Fifth Assessment Report of the IPCC.” Energy Policy, 109: 414–417.

Impacts of Climate Change on Italian Agriculture

Paper on climate change impact on Italian farms is forthcoming in the European Review of Agricultural Economics.


Abstract: This research investigates the potential impact of warming on Italian agriculture. Using a detailed dataset of 16,000 farms across Italy, the study examines likely warming impacts in different regions and for different sectors of Italian agriculture. The study finds that farm net revenues are very sensitive to seasonal changes in temperature and precipitation. Livestock and crop farms have different responses to climate as do rainfed farms and irrigated crop farms. The overall results suggest mild consequences from marginal changes in climate but increasingly harmful effects from more severe climate scenarios.

Bozzola, M., E. Massetti, R. Mendelsohn and F. Capitanio. 2017. “A Ricardian Analysis of the Impact of Climate Change on Italian Agriculture.” European Review of Agricultural Economics, forthcoming.

Paper on degree days forthcoming in Energy Economics

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

Emanuele Massetti, Robert Mendelsohn, Shun Chonabayashi

Abstract

Farmland values have traditionally been valued using seasonal temperature and precipitation but degree days over the growing season offers a more compact form. We find that degree days and daily temperature are interchangeable over the growing season. However, the impact of degree days in spring and summer are quite different. Climate effects outside the growing season are also significant. Cross sectional evidence suggests seasonal temperature and precipitation are very important whereas temperature extremes have relatively small effects.

How do heat waves, cold waves, droughts, hail and tornadoes affect US agriculture?

A very first draft of a new paper on climate extremes available here. Still preliminary and incomplete.

Presented today at the ASSA meetings in San Francisco. Presentation available here.

Abstract:

We estimate the impact of extreme events on corn and soybeans yields, and on agricultural land values in the Eastern United States. We find the most harmful event is a severe drought but that cold waves, heat waves, and storms all reduce both corn and soybean yields. Over 80% of the damage from extreme events is caused by droughts and cold waves with heat waves causing only 6% of the damage. Including extreme events in a panel model of weather alters how temperature affects yields, making cold temperature more harmful and hot temperatures less harmful. Extreme events have no effect on farmland values probably because American farmers are buffered from extreme events by subsidized public crop insurance.

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.

Should we ban unconventional oil extraction to reduce global warming?

We all know that unconventional oil extraction is bad for the environment. It causes local environmental damage (check what is happening in North Dakota: here) and it generates a lot of extra carbon dioxide emissions compared to the extraction of conventional oil.

So, what about banning the extraction of non-conventional oil?

In a recent working paper  Samuel Carrara and I estimate the climate benefit of a global ban on unconventional oil using scenarios developed with the integrated assessment model WITCH.

Guess what? A global ban on the use of unconventional oil has non-negligible climate benefits but it is a very inefficient climate mitigation policy. Not using unconventional oil resources slows global warming by 0.3°C (from +4.1°C to +3.8°C in 2100 with respect to the pre-industrial level). Despite a rebound effect in conventional oil extraction, the global ban is effective because it substantially reduces oil demand, carbon dioxide emissions and the increase of temperature. However, the policy is terribly inefficient.

We find that an efficient, global uniform carbon pricing mechanism would achieve climate benefits almost four times larger, at the same cost. Analogously, an efficient pricing scheme would deliver the same climate benefit being fifteen times cheaper.

The EU has long considered a unilateral tax on oil coming from unconventional resources in Northern America.

Is this a good idea?

We check what would be the cost and the benefit (in terms of reduced carbon dioxide emissions) of a unilateral EU ban on unconventional oil. Unsurprisingly, we find that unilateral European ban of unconventional oil is both inefficient and ineffective. It will cost a lot and it will have no impact on global mean temperature. Oil would just flow to countries that do not ban its use.

The policy implications are intuitive. If the main goal is carbon mitigation, the European Union should avoid unilateral aggressive policies against unconventional oil. Diverting trade routes may be expensive for oil producers and a short-term victory is possible. However, in the long-run, with rising energy prices and technological progress in oil extraction and in oil transportation, it is likely that unconventional oil will flow where demand is and Europe alone will have a negligible impact on global patterns.

For example, starting a trade war with Canada to achieve virtually null climate benefits is not the best thing to do.

Using Degree Days to Value Farmland

A final draft of the working paper joint with Robert Mendelsohn and Shun Chonabayashi is available here.

In this paper we carefully review the use of degree days in the hedonic literature to value farmland and we are not able to confirm the hypothesis of Schlenker, Hanemann and Fisher (2006).


Here is the abstract:

Farmland values have traditionally been valued using seasonal temperature and precipitation. A new strand of the literature uses degree days over the growing season to predict farmland value. We find that degree days and daily temperature are interchangeable over the growing season. However, the way that degree days are used in these recent studies is problematic and leads to biased and inaccurate results. These new findings have serious implications for any study that copies this methodology.


The Appendix to the paper has a careful comparison of the weather data that we use (NARR) and data used by Schlenker and Roberts (2009). For those not familiar with the acronyms, NARR is the North American Regional Reanalysis generated by climatologists at the NOAA. It provides temperature and other climatic measurements over a 32x32 km grid at three hour time intervals from 1979 to present day.

Wolfram Schlenker took great care in examining previous drafts of our work (here, here and here). He has compared NARR data to his dataset and he has found that NARR data is inferior. But that comparison was not correct.

Instead of using NARR 2 meter air temperature, Schlenker used NARR  surface level temperature. This is like comparing pears and apples because Schlenker and Roberts (2009) - SR2009 - is based on weather stations. Weather stations record temperature at about 2 meters. All temperature data that is used in this literature is 2 meter air temperature and we never used surface temperature data. Surface temperature is the temperature of the “skin” of the planet. Surface temperature reflects different soil types. Daily maximum temperature can be very high in the NARR surface temperature dataset (try touching your concrete driveway on a summer afternoon). For this reason the NARR data seems inferior.

In short, both NARR and SR2009 data confirm that Schlenker, Hanemann and Fisher (2006) (SHF2006) greatly overestimate the number of degree days above 34°C. SR2009 and NARR data are quite similar (Wolfram Schlenker kindly gave us his weather data). In some tests NARR data performs better than SR2009 data, but I would not overstress this. The relevant fact is that with both NARR data and SR2009 data we reject the main hypothesis in Schlenker, Hanemann and Fisher (2006) - SHF2006. Why?

We find two problems with SHF2006. First, the weather data used in that paper is not as accurate as in the NARR and the SR2009 datasets and this may have misled the authors. Second, SHF2006 misinterprets agronomic research: farmers and agronomists do not use degree days to predict yields (and thus overall agricultural productivity). The argument in favor of degree days is based on a misreading of an agronomy result showing a linear function rising to 32°C and then abruptly falling (Figure 2-3 in Ritchie and NeSmith, 1991). However, the cited figure does not describe yield but rather the inverse of the time it takes a maize plant to develop a fifth leaf. The figure shows how degree days affect timing. A separate figure in the Ritchie and NeSmith paper reveals the traditional hill-shaped relationship between yield and temperature. In fact, farmers and agronomists use degree days to predict the duration of different stages of plants' growth, not to predict yields.

Finally, we also checked if using hourly temperatures instead of daily temperature to calculate degree days makes a difference and we are able to confirm our results, but this is technical stuff and all the details are in the Appendix.

Rethinking African solar power for Europe

Recent column with Elena Ricci on voxeu.org.

"Concentrated solar power generation in Northern African and Middle Eastern deserts could potentially supply up to 20% of European power demand. This column evaluates the technological, economic, and political feasibility of this idea. Although concentrated solar power is a proven technology that can work at scale, it is currently four or five times more expensive than fossil fuels. Concentrated solar power could play an important role in Europe’s energy mix after 2050, but only if geo-political challenges can be overcome."

Full column available here.

Revised Working Paper: A Ricardian Analysis of the Impact of Climate Change on European Agriculture

We recently revised our paper on climate change impacts on European Agriculture.

The new FEEM working paper is available here.


This new version is also circulated as CESIfo working paper here.


Abstract:

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 37,612 farms across Western Europe. We demonstrate that a median quantile regression outperforms OLS given farm level data. The results suggest that European farms are slightly more sensitive to warming than American farms with losses from -8% to -44% by 2100 depending on the climate scenario. Farms in Southern Europe are predicted to be particularly sensitive, suffering losses of -9% to -13% per degree Celsius.

New Draft: Do Temperature Thresholds Threaten American Farmland?

New draft of the paper on agricultural thresholds presented at the 2014 ASSA meetings.


I will present this new draft at the World Congress of Environmental and Resource Economists in Istanbul on Monday June 30 at 14:00.


Robert Mendelsohn and I do not find evidence of "thresholds" after which land values collapse in the East of the United States. We find instead evidence of adaptation to different climatic conditions.



Abstract:

It is widely known that temperatures have a hill-shaped effect on agriculture.  Some researchers argue that there is also a threshold effect, a temperature above which land values crash and crops fail. This paper uses flexible functional forms to estimate the effect of growing season temperature on American farmland values and crop yields. The paper finds evidence of the hill-shaped response function for both farmland value and crop yields. But there is no evidence of temperature thresholds whether temperature is measured at 3 hour intervals, daily, or for multiple days.