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.

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.

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.

Do Temperature Thresholds Threaten American Farmland?

On January 4 I presented the paper titled "Do Temperature Thresholds Threaten American Farmland?" joint with Robert Mendelsohn at the ASSA meetings in Philadelphia.

The presentation is available here.

In short:

In this paper we use flexible functional forms to estimate the marginal effect of mean temperatures during 3-hour, daily and longer time intervals on land values. We use US Agricultural Census Data and detailed climate data obtained from the NARR model, a very large dataset that contains climatic data on 3-hour time intervals, at fine spatial resolution, from 1979 to present day. The paper finds no evidence of temperature threshold effects on land values and in the Eastern United States. The flexible functional forms suggest inverted-U shaped or almost constant marginal effects at different levels of temperature whether one is using average temperature over 3-hour, daily, continuous days or the growing season. We find instead evidence that land values in areas that are frequently affected by extreme heat waves reflect large expected productivity losses. Using annual yields and weather data we find evidence that both cold and high temperatures reduce corn, soybeans, and to a lesser extent, cotton yields. The downward sloping section of the relationship that relates temperature and yields is steeper than the upward sloping section but we do not find evidence of sudden discontinuities.

Trade of Woody Biomass for Electricity Generation Under Climate Mitigation Policy

The paper on woody biomass trade is now published online by Resource and Energy Economics:

Favero, A. and E. Massetti. 2013. “Trade of Woody Biomass for Electricity Generation Under Climate Mitigation Policy.” Resource and Energy Economics, published online.

Here is the abstract:

Bio-energy with carbon capture and sequestration (BECCS) has the potential to be a key mitigation option, because it can generate electricity and absorb emissions at the same time. However, biomass is not distributed evenly across the globe and regions with a potentially high demand might be constrained by limited domestic supply. Therefore, climate mitigation policies might create the incentive to trade biomass internationally. This paper uses scenarios generated by the integrated assessment model WITCH to study trade of woody biomass from multiple perspectives: the volume of biomass traded, its value, the impact on other power generation technologies and on the efficiency of mitigation policy. The policy scenarios consist of three representative carbon tax policies (4.8 W/m2, 3.8 W/m2 and 3.2 W/m2 radiative forcing values in 2100) and a cap-and-trade scheme (3.8 W/m2 in 2100). Results show that the incentive to trade biomass is high: at least 50% of biomass consumed globally is traded internationally. Regions trade 13-69 EJ/yr of woody biomass in 2050 and 55-81 EJ/yr in 2100. In 2100 the value of biomass traded is equal to US$ 0.7-7.2 Trillion. Trade of woody biomass substantially increases the efficiency of the mitigation policy. In the tax scenarios, abatement increases by 120-323 Gt CO2 over the century. In the cap-and-trade scenario biomass trade reduces the price of emission allowances by 34% in 2100 and cumulative discounted policy costs by 14%.

Chaos in climate change scenarios means chaos in climate change impact estimates?

I finished a first complete draft of the paper "Chaos in climate change impact estimates".


Why the 2011-2030 years averages of temperature anomaly in December, January, February are so different for the same General Circulation model that uses virtually identical emissions trajectories?

(Thanks to Paola Marson for generating these maps!)

What are the implications for the impacts literature?

Is it really possible to use high-resolution climate change scenarios to predict impacts at sub-regional level?

These are the questions that I address in this paper at the cross-road of climate science, economics and the impacts literature.


I copy the abstract below. The draft of the paper on GCM scenarios is ready and available here. A lot of maps and other Supplementary Material is available here.

Global Circulation Models incorporate chaotic dynamics to reflect real-world weather patterns. This implies that extremely small perturbations of the climate system may generate very different weather patterns. Here I show that the SRES climate change scenarios generated by the Coupled Model Intercomparison Project phase 3 (CMIP3) - ubiquitous in the impact literature - display strong chaotic dynamics at regional and sub-regional level, at least until 2065. Chaos is triggered by changes to historic forcing in the year 2000 to reflect different emissions trajectories. This suggests that large uncertainty exists on how to link local climate change and global forcing. Furthermore,  short- and mid-term differences in local climate change across different SRES emission scenarios reflect chaotic dynamics rather than different forcing patterns. I show that the "chaos" in the climate scenarios generates a "chaotic" relationship between exogenous forcing and local economic impacts. "Perturbed exogenous forcing" model ensemble would resolve this uncertainty.

Using Degree Days to Value Farmland?

We revisit the use of degree days to estimate land values in the United States using the rich NARR weather reanalysis. With temperature data at 3-hour time intervals since 1979 we compute degree days more precisely than in previous papers. We also review the agronomic literature to see if it appropriate or not to use degree days to predict plants' growth.



Using Degree Days to Value Farmland?

by Emanuele Massetti, Robert Mendelsohn and Shun Chonabayashi

Abstract: Farmland values have traditionally been valued using seasonal temperature and precipitation. A new strand of the literature argues that degree days over the growing season provide more accurate predictions of farmland value than seasonal temperature and that farmland values fall precipitously at 34⁰C. The paper shows that these hypotheses of the degree day literature fail when accurate measures of degree days are used.

The paper is available here. Supplementary material is available here.

The impact of climate change on European Agriculture

A recent paper on the impact of climate change on EU agriculture just came out as FEEM WP.

We use for the first time the Ricardian method at a continental EU scale. Things get bad for Mediterranean countries


Steven Van Passel, Emanuele Massetti, Robert Mendelsohn. 2012. "A Ricardian Analysis of the Impact of Climate Change on European Agriculture." FEEM Note di Lavoro 2012.083, November 2012.

Abstract:

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Data on climate, soil, geography and regional socio-economic characteristics were matched for 37 612 individual farms across the EU-15. Farmland values across Europe are sensitive to climate. Even with the adaptation captured by the Ricardian technique, farms in Southern Europe are predicted to suffer sizeable losses (8% -13% per degree Celsius) from warming. In contrast, agriculture in the rest of Europe is likely to see only mixed impacts. Increases (decreases) in rain will increase (decrease) average farm values by 3% per centiliter of precipitation. Aggregate impacts by 2100 vary depending on the climate model scenario from a loss of 8% in a mild scenario to a loss of 44% in a harsh scenario.

Green Perspectives: a special issue of Energy Economics

Open access available to the new paper on investments under climate policy: here.

The whole special issue on "green perspectives", edited by Brian Flannery and Richard Tol is open access.

Here is the table of content with links:

Foreward
Page S1
Brian Flannery

From “Green Growth” to sound policies: An overview Original Research Article
Pages S2-S6
Richard Schmalensee

Energy and technology lessons since Rio
Pages S7-S14
James Edmonds, Katherine Calvin, Leon Clarke, Page Kyle, Marshall Wise

Investments and public finance in a green, low carbon, economy
Pages S15-S28
Carlo Carraro, Alice Favero, Emanuele Massetti

Financing for climate change
Pages S29-S33
Richard N. Cooper

Clean energy: Revisiting the challenges of industrial policy
Pages S34-S42
Adele C. Morris, Pietro S. Nivola, Charles L. Schultze

The elusive and expensive green job
Pages S43-S52
Diana Furchtgott-Roth

The potential role of carbon labeling in a green economy
Pages S53-S63
Mark A. Cohen, Michael P. Vandenbergh

Reducing greenhouse gas emissions through operations and supply chain managementArticle
Pages S64-S74
Erica L. Plambeck

Greening Africa? Technologies, endowments and the latecomer effect
Pages S75-S84
Paul Collier, Anthony J. Venables

Green growth and the efficient use of natural resources
Pages S85-S93
John M. Reilly

Investments and Public Finance in a Green, Low Carbon Economy

The paper on "Investments and Public Finance in a Green, Low Carbon Economy" joint with Carlo Carraro and Alice Favero is forthcoming on Energy Economics. A pre-print is available here.

I copy here the abstract of the paper:

The paper evaluates the impacts on investments and public finance of a transition to a green, low carbon, economy induced by carbon taxation.  Four global tax scenarios are examined using the integrated assessment model WITCH.  Taxes are levied on all greenhouse gases (GHGs) and lead to global GHG concentrations equal to 680, 560, 500 and 460 ppm CO2-eq in 2100. Investments in the power sector increase with respect to the Reference scenario only with the two highest taxes. Investments in energy-related R&D increase in all tax scenarios, but they are a small fraction of GDP. Investments in oil upstream decline in all scenarios. As a result, total investments decline with respect to the Reference scenario. Carbon tax revenues are high in absolute terms and as share of GDP. With high carbon taxes, tax revenues follow a “carbon Laffer”curve. The model assumes that tax revenues are flawlessly recycled lump-sum into the economy. In all scenarios, the power sector becomes a net recipient of subsidies to support the absorption of GHGs. In some regions, with high carbon taxes, subsidies to GHG removal are higher than tax revenues at the end of the century.


Carraro, C., A. Favero and E. Massetti. 2012. “Investments and Public Finance in a Green, Low Carbon Economy.” Energy Economics, forthcoming.

Incentives and stability of international climate coalitions: an integrated assessment

On June 12 2012 I presented the paper "Incentives and stability of international climate coalitions: an integrated assessment" joint with Valentina Bosetti, Carlo Carraro, Enrica De Cian and Massimo Tavoni at the Cowles Foundation Summer Conference on "Macronomics and Climate Change” at Yale University.

 Full presentation in pdf here.

In the paper we show why cooperation among world countries to reduce GHG emissions is possible if targets are not to stringent.


We find that cooperation is possible and profitable but:

• The 2°C target is not supported by cost-benefit analysis even under extreme assumptions on damages and discounting
• Even with more modest targets coalitions are not stable
• International transfers are needed to «bribe in» reluctant countries

Policy implication: be less ambitious when negotiating the post-2020 climate architecture

Caveats:

• Alternative bargaining rules might deliver different results
• Much cheaper mitigation costs might induce more cooperation
• Ethical considerations might be used to assess impacts instead of monetary evaluations of future damages

The paper was recently published as CEPR working paper here and a short-article appeared on voxeu.org here.

Special Issue on INEA: Reconciling Domestic Energy Needs and Global Climate Policy: Challenges and Opportunities for China and India

Carlo Carraro and I have recently edited a special issue of INEA. We collect a set of articles that take stock of the current status of the negotiations and suggest an unconventional, pragmatic way forward.

All the articles recognize that China and India will not enter a textbook-style international climate agreement soon. They are also aware that the future international climate architecture will be fragmented and incomplete at least until 2020. Therefore, the inability to build a large binding agreement with absolute targets is not seen as a tragedy, but rather as a fact that should be considered as a starting point for future steps towards global emission reductions. For this reason all articles take a long-term perspective. As Zhang notes in his article, the real question when dealing with China and India is post‑2020 and not pre‑2020.

 

In the free-access editorial we trace a well-defined pathway to include China and India in the international effort to control global warming. With a more active participation of the two large developing economies, developed countries would find it hard to avoid a more active engagement and the Gordian knot of climate policy could be cut.

We summarize this pathway through six key messages.

First, at least in the next decade, negotiators should focus more on sustainable development goals than on targets and timetables. 

Second, China and India will have a remarkably different impact on global climate change for several decades to come. At the same time, they follow different development paths and therefore should proceed along different negotiating trajectories.

 

Third, China may take on absolute emissions caps around 2030.

Fourth, there are many opportunities in China and India to reduce emissions by a large amount, and at low cost, between 2020 and 2050.

Fifth, in order to achieve consensus on very ambitious climate agreements it is necessary to agree on a new shared definition of the “common but differentiated responsibilities” (CBRD) principle.

Sixth, clear rules that deal with the non-compliance of OECD countries with Kyoto and other climate commitments must be established.

Table of contents:

Reconciling Domestic Energy Needs and Global Climate Policy: Challenges and Opportunities for China and India

Guest Editors: Carlo Carraro and Emanuele Massetti

Editorial, Carlo Carraro and Emanuele Massetti
 

Carbon tax scenarios for China and India: exploring politically feasible mitigation goals, by Emanuele Massetti
 

Climate agreements and India: aligning options and opportunities on a new track, by P. R. Shukla and Subash Dhar

In what format and under what timeframe would China take on climate commitments? A roadmap to 2050,  by Zhongxiang Zhang

China and India’s participation in global climate negotiations, by Sean Walsh, Huifang Tian, John Whalley and Manmohan Agarwal

Estimating Ricardian Models With Panel Data - NBER WP

The paper "Estimating Ricardian Models with Panel Data", joint with R. Mendelsohn, was published as NBER working paper last week.

Abstract:

Many nonmarket valuation models, such as the Ricardian model, have been estimated using cross sectional methods with a single year of data. Although multiple years of data should increase the robustness of such methods, repeated cross sections suggest the results are not stable. We argue that repeated cross sections do not properly specify the model. Panel methods that correctly specify the Ricardian model are stable over time. The results suggest that many cross sectional methods including hedonic studies and travel cost studies could be enhanced using panel data.

Massetti, E. and R. Mendelsohn (2011). “Estimating Ricardian Functions with Panel Data.” NBER Working Paper No. 17101, June 2011.

The greening of development: no growth without energy

A short article for the World Bank Development Outreach Magazine, issue on Emerging Issues in Development Policy: The winding road to growth and equity, April 2011.

Economic development increases the demand for energy. This is true for countries at all income levels, although as economic growth progresses, the demand tends to increase more in the low- and middle-income countries than in high-income ones. But energy remains a key ingredient for economic growth at all stages of development.
With 5.4 billion people living in low and middle-income countries—out of  a global population of 6.5 billion—energy demand will very likely continue to grow at a fast pace for many years to come. [...]

Download the article.