Not Just Water

… also resource economics, policy analysis and why not, music!


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State Struggles to Enact More Robust Climate Targets

This post was originally published at The PPIC Blog on October 13, 2015

California’s efforts to cut greenhouse gas emissions thus far have made the state a national leader. But the momentum may be slowing. A struggle over recent climate legislation resulted in a less-ambitious version of the Clean Energy and Pollution Reduction Act (SB 350) being signed into law by Governor Brown last week and the deferment of a bill (SB 32) that would have strengthened the state’s 2006 climate law.

The Global Warming Solutions Act of 2006 (AB 32) established the foundation of California’s plan to address climate change by reducing GHG emissions to 1990 levels by 2020. The state is on track to meet the 2020 limit, and now policy efforts are shifting to longer term goals. Emission-reduction targets of 40 percent below 1990 levels by 2030 and 80 percent by 2050 are already set forth in executive orders (former Gov. Schwarzenegger’s S-3-05 and Gov. Brown’s B-30-15) but have not yet been incorporated into law.

SB 350 is seen as a major step toward reducing GHG emissions in the longer term. It mandates that half of the state’s electricity come from renewable resources and that buildings double their energy savings by 2030. But a third piece of the original plan, which proposed to cut petroleum use in cars and trucks by half over the next 15 years, was dropped. Since the transportation sector is a major contributor to GHG emissions (37% in 2013), this is could make it more challenging to meet long term emissions reductions. To make up for the loss, the Air Resources Board adopted a modified version of its Low Carbon Fuel Standard that requires a 10 percent reduction in carbon intensity of transportation fuels by 2020.

The second slowdown was the deferment of SB 32 until at least next year. The bill would amend the California Global Warming Solutions Act of 2006 to include the 2030 and 2050 emission-reduction targets from the executive orders. It failed to pass in the assembly.

Our July PPIC Statewide Survey found that solid majorities of Californians (69% adults, 62% likely voters) favored the proposal to reduce GHG emissions to 80 percent below 1990 levels by 2050. When asked about the original goals of SB 350, 82 percent of adults supported the increase of electrical generation from renewables, 70 percent favored doubling energy efficiency in buildings, and 73 percent supported reducing petroleum use in cars and trucks by 50 percent by 2030. Although Democrats are more likely than Republicans to support these goals, majorities of Republicans support the goals of increasing renewables and energy efficiency. Overwhelming majorities who favor these policies also view global warming as a serious threat to the economy.

The state’s approach to reducing GHG emissions has achieved important results. The mix of policies has resulted in a cleaner economy, while population and GDP have continued to grow. Looking ahead,a study for the California Energy Commission shows that with the mix of technologies and practices proposed by state agencies, emission reductions of 26–38 percent below 1990 levels could be achieved by 2030 at a cost of $8 per household per month (or $14 if commercial and industrial costs are all passed on to households).

California’s multi-faceted approach to combating global warming has placed it in the vanguard of worldwide policies. Yet 2020 is just around the corner, and clear targets to reduce GHG emissions for the longer term still evade us. To remain on the leading edge of global climate regulations, the state will need to adopt more robust and forward-looking policies. It would also be worthwhile to explore a new narrative to reduce the partisan divide on this issue, given Californians’ widespread support for the state’s energy goals.


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Analyzing different approaches to understand the causes of the 21st century food price spikes*

Abstract

After a long-term decline and relative stability in staple food prices since the 1973 oil crisis, two large spikes in 2007-08 and 2010-11 seasons have shaken the world troubling food security in developing countries and affecting related-commodity markets. Many reasons have been offered to explain the causes of these spikes, and because of the complexity of the topic and the interference by the factors affecting commodity prices there is not a clear and generally accepted explanation. Besides the spikes, there is a concern about if price volatility might be increasing and which factors could be behind this increase, because of the huge consequences of that volatility in a globalized world. In order to better understand the causes in this paper we review three recent publications focused on food price spikes using two different approaches: a literature review method to describe and assess the likelihood of the different causes attributed to the spikes; and an econometric approach using a structural vector autoregression (SVAR) model. As a main conclusion I think that both approaches are necessary and they are not exclusive because a good and correctly specified econometric model has to be based on strong literature review, and a literature review based method has to review econometric studies to find evidence of their hypotheses.

  1. Agricultural markets

Agricultural commodities, as every other commodity, are subject to the sometimes whimsical market rules. But differently than many other commodities, agricultural commodity markets are inherently volatile because of their strong links with natural shocks (Joachim von Braun and Getaw Tadesse, 2012). The increased trade of agricultural commodities since the industrial revolution of the eighteenth century has linked the world markets and globalized not only the benefits, but also the sensitivity to external shocks.

Demand has been exponentially increasing mainly because of population increase in the 20th century, while food supply increased due to the growth both in acreage and yields obtained because of technical change. Although demand is increasing with a steady rate every year, world supply might have sharp changes reflecting extreme weather conditions suffered in producers’ regions.

A very important issue about agricultural markets is that the products traded are essential for human life, therefore there is (or it should be) a special consideration of these products by the respective governments and protectionism is a key feature affecting this market.

  1. Food price trends, spikes and consequences

Food prices in real terms for bulk commodities have been steadily decreasing since the second half of the 20th century, although they have had some previous variations with the notorious example of 1973 spike associated with the oil crisis.

The declining long-term trend in food prices shown above might be explained because the marginal cost of increased food supply has been lower than the increase in marginal demand. Even that population has increased so much, there is much more available food (obtained by technological change or new land cultivated) to feed that population.

But this long-term declining trend in the second half of the 20th century has shifted in the beginning of the 21st century. As we can see in Figure 1 the real food price has grown in the first decade of the 21st century, with two very steep spikes in 2008 and 2011.

FAO food price index

Figure 1: FAO food price index in nominal and real terms.

As a consequence of that and because of the high sensitivity of poor people to staple food prices (because their higher budget share spent on food, and their higher share of food budget spent on staple food) political instability has arisen in many countries. Figure 2 shows the number of riots occurred in several countries directly related with increased staple food prices, and we can see how price spikes in 2008 and 2011 triggered the proliferation of these riots.

FoodPrice&Riots

Figure 2: FAO food price index from January 2004 to May 2011. Red dashed vertical lines correspond to beginning dates of “food riots” and protests associated with the major unrest in North Africa and the Middle East (Marco Lagi et al, 2011)

  1. Causes of the new price trends and volatility

Many explanations have been offered about the causes of the new price trend and price stability that have appeared in the 21st century. Below, I try to review the arguments offered by the scientific community:

  • New agricultural market features:
    • Demand side: increased per capita income in several developing countries (mainly China and India) is increasing demand not only for staple foods, but also for meat, that uses much more resources than staple food. Besides that, the new policies encouraging use of biofuels has brought a new competing demand of agricultural products, and also for the competing resources (land, water and other inputs) needed to grow food.
    • Supply side: marginal costs for food supply have been decreasing historically because of new arable land and technical improvement to obtain higher yields. But most of the best land is now used, and the rates of yield increase have decreased in the last decades, therefore is very likely that the marginal cost to obtain new food supply has increased last years. Besides the new characteristics of the supply, there is always a concern about the sensitivity of agricultural supply to weather shocks, and even in a globalized world with much agricultural trade, major producers’ shocks can affect sharply the world supply of some commodities.
  • Relation with economic activity: there are many relations of the “apparently exogenous” economic activity with the agricultural markets. On the demand side higher growth rates yields a higher demand from consumers, and on the supply side higher cost of production because increased prices in a more competitive economy (energy and fertilizers are related directly with oil prices, and also labor is more expensive). Besides the direct effects, there are other indirect effects as lower interest rates in an exporter country makes marginal storage costs more inexpensive and might also depreciate the exchange rate encouraging exportation, increasing prices of local products.
  • Speculative demand: demand that is not used for direct consumption, but rather to obtain benefits from current lower prices to sell afterwards at a higher price. There are two types of speculative: a traditional one motivated by the storage economic model; and a second one that has grown lately driven by the financial markets.
    • Precautionary demand: as some of the staple food (mainly grains) is storable, competitive storage models ( D. Wright and J. C. Williams, 1982) states that firms will hold inventories of storable commodities such that the current price equals the discounted value of the expected price in the future. Low prices induce storability, whereas higher prices can result in empty inventories.
    • Financial speculation: portfolio diversification of investments has turn the eyes of the commodity index trader to food futures markets. The recent financialization of commodity futures markets and the presence of commodity index traders has been associated with these alternative food market speculation (Joseph P. Janzen et al., 2014).
  • Increased volatility because low inventories: the competitive storage model mentioned above predicts that high inventories can provide a buffer against supply and demand shocks, whereas when inventories are low market is vulnerable and prices will respond directly to the shocks without protection.
  • Policy responses: in a situation of a volatile world commodity prices most countries try to protect themselves by enhancing barriers to trade, reducing the flexibility of the market and producing most of the times an even worse scenario.
  1. Different approaches to analyze the causes of the food price spikes

In this section we try to summarize the different approaches that we have reviewed to analyze the causes of the food price spikes. The first is a literature-review-based approach, whereas the second approach obtains results developing an econometric model using a panel data from different sources that tries to capture the variation of the prices of wheat from an expected trend.

  • Literature review approach

We have analyzed two recent publications using this approach to assess the causes of the food price spikes. In the first one C. A. Carter et al. (2011) do an exhaustive review of the agricultural economics literature comparing the price spikes of 2007-08 and 1973-74, obtaining that there are many similarities (concurrence of energy and other commodities’ rise in prices) but also some differences (in 1973 peak agricultural commodities led the spike, whereas in 2008 prices moved concurrently). To strength their hypotheses they develop a two-stage model to understand actors’ behavior in a boom-bust cycle including producers, consumers, processors and speculators. Based on this theoretical model, but without using any empirical test, they conclude that 1973-74 and 2007-08 spikes shifts in supply and demand were the major contributors of the spikes (73-74 because of inward shift in supply that resulted in a crude oil price spike and all refinery energy products related with the OPEC embargo on the United States concurrently with El Niño weather shock reducing available supply and several policy failures elsewhere, whereas in the 2007-08 spike was caused mainly because of shifts in demand because increased income of developing countries and appearance of biofuels as a competing demand, concomitantly with precedent multiyear Australian drought and reduction in metals supply because of the closing of South African underground mines). Following the same model they state that speculative demand, even though it could have a small effect on the spikes, is mostly beneficial because forward contracting reduces the risk faced by producers encouraging production and mitigating boom-bust cycles.

After the development and explanation of their two-stage model, reviewing the literature about competitive rational storage model (R. L. Gustafson, 1958, J. B. Williams, 1936, B. D. Wright and J. C. Williams, 1982) they provide evidence that inventories decreased sharply with increased prices in the beginning of both spikes and when the inventories were almost empty the agricultural markets were unprotected against new increases in prices.

The next section offers a macroeconomic explanation about commodity price in these price spikes: movements in interest rates have large effects in production processes for many of the capital intensive commodities at the same time that storable commodities are very sensitive to interest rates; whereas exchange rates play a high role in demand shifts because international agricultural trade. In both of the spikes, it was a previous inflationary period that the governments try to interrupt by reducing interest rates, what caused a depreciation in the currency of principal exporting countries (US and EU) and that caused a upward shift in world importing demand.

  1. A. Carter, G. C. Rausser and A. Smith (2011) present later other cause affecting price spikes that is the cross-commodity linkages. In this point they relate the increasing costs of production with the energy prices, and after they state again the increased competition in demands because the appearance of biofuels. The main conclusion is that historical prices of grains have been related with petroleum, but with the current relation of agricultural commodities with fossil-based fuels this link is closely tied.

Finally both boom-and-bust cycles have some policy responses that worsen the situation. To face a volatile world commodity market, many countries tried to protect themselves by enhancing trading restriction. There are many examples in 1973-74 and 2007-08 and in both cases the authors present evidences that most of these policies were costly not only for the world as a whole, but also for the countries that enacted these restrictions (for example the US soybean export embargo in 1973 or the increase in soybean export taxes in Argentina in 2007-08).

To conclude C. A. Carter, G. C. Rausser and A. Smith (2011) state that both boom-and-bust cycles were very similar and the main causes were the supply and demand shocks, low inventories, a period of strong economic growth in lower-middle-income concurrently with low interest rates in rich countries, cross commodity linkages that increased costs of production and increase demand because of biofuel production, and a bad policy response that exacerbate rather than mitigate the situation. They find very little support to the speculative arguments in the literature reviewed.

In the second paper reviewed J. P. Chavas et al. (2012) presented in an introductory chapter nine papers that relate directly with the economics of price volatility: first they document the recent and historical patterns of price volatility because demand and supply conditions including technological change and analyzing elasticity of aggregate supply and demand; second section studies how food price volatility relates to linkages between food markets and energy markets looking for the effects recent biofuel policies and its implications, and in a macro scale how market linkages across sectors (agricultural, energy and others) are important; third section assess the impact of storage and speculation by presenting the role of storage as a means of reducing price volatility and how “financialization” of commodity market is affecting prices concluding that these did not cause massive bubbles in future prices; fourth section explores the role of international markets analyzing the relationship between stabilization policies in developing countries; and finally two studies analyze the welfare implications of price crisis, and the effects of trade insulation against price volatility urging for caution against policy positions that would condemn trade insulation practices.

  • Econometric model

The second approach that we reviewed is an econometric model of the wheat price spikes in the United States presented by Joseph P. Janzen, Colin A. Carter, Aaron d. Simth and Michael K. Ajemian (2014).

In this paper three different futures market prices of wheat (hard red winter, Kansas City; hard red spring, Minneapolis: and soft red winter, Chicago) are analyzed. The authors develop a model to understand how the prices in each of the futures market deviates from an expected trend, and they attribute that deviation to four factors that they identify: global real economic activity and commodity demand; wheat-specific supply-and-demand factors; speculative or precautionary demand; and financial speculation, Commodity Index Trading and Comovement.

These four factors are taken after a review of the literature and the authors attribute all the deviation from the expected prices to these factors. In order to do that they pose a structural vector autoregression (SVAR) model that analyzes the residual variation from the expected trend of an initial simple system of linear equations to represent the observed variable included in the model as a function of past variables in the system plus some unanticipated variation. They use exogenous variables as ocean freight rates (as an index of real economic activity), price of oil (as an proxy for speculation-induced comovement) and the difference between deferred futures contract price and the nearby futures prices based on the working curve relationship (as a proxy for stockholding). Finally the rest of the variation is attributed to net supply shocks.

Using panel data from the early 90s to 2011 they obtain a really insightful impulse-response functions (how isolated factors affect over time the main variables) and the historical decomposition of the factors affecting price variation. They also do a counterfactual analysis looking of how prices did move if one of the factors was not affecting over time.

The main findings are that most of the variation comes from the net-supply shocks, a small effect from precautionary demand and real economy activity, and finally that commodity index traders had a very little effect on the price variation.

  1. Analysis of the approaches

The literature-review-based approaches presented summarize the causes offered by the scientific community to explain the commodity price spikes. C. A. Carter, G. C. Rausser and A. Smith (2011) did a stronger work than J. P. Chavas, D. Hummels and B. D. Wright (2012) presenting much more evidence based analysis because the second paper was only an introductory chapter in a larger book.

The strength of this approach is that they have a lot of flexibility to present all the causes that they think that affected price volatility and in this sense they did a very good job reviewing the literature of boom-and-bust economics and comparing and finding evidence of the great similarities of 1973-74 and 2007-08 cycles, and they do not have to look for data to develop and support a concrete model.

The weaknesses of the literature-review-based approach is that they are looking for many isolated effects studies that probably are underestimating the linkages between the causes and consequences, and because of that they are probably attributing to some causes the effects that are produced from other causes. Other problem that I see in this approach is that it might be some overlapping between causes-effects attribution: for example they are presenting twice the same evidence about the effects of increased costs of production for agricultural products, first when they offer the macroeconomics explanation and after when they are presenting the linkages between markets.

From my point of view other weakness from the C. A. Carter, G. C. Rausser and A. Smith (2011) is that they present and develop this two-stage model including producers, consumers, processors and speculators and they obtain some insights from there but without present any empirical-based evidence of the use of this model. They should explain better how this model is used.

I think that the main advantage from the econometric approach presented by Joseph P. Janzen, Colin A. Carter, Aaron d. Simth and Michael K. Ajemian (2014) is that they are using real data and trying to explain a real case. They used the literature-review-based approach to identify the causes and then they presented a model to explain how the effects are related with the causes that they identified, exposing their approach not to a speculative formulation, but rather to a real situation.

Even though that the approach is really interesting I think that there are many weaknesses in the methods and data that they use to explain the complete situation created in the 2007-08 food price spike. First they are looking only for the wheat market, forgetting the linkages with other substitute markets (other grains or food) that are directly related with wheat futures market prices. Second I think that they are miss-specifying the model only including these four factors, and even worse they are attributing to the net-supply shocks all the leftover from the other three factors, probably overestimating the net-supply effect (and probably they could uses some proxy to net supply using estimated production from acreage and weather conditions). Third, they are not using long-term demand shifts, even when they recognize that this demand has been shifting upwards because demand increase by low and middle income countries.

  1. Conclusions

As a main conclusion I think that both approaches are necessary and they are not exclusive because a good and correctly specified econometric model has to be based on strong literature review, and a literature review based method has to review econometric studies to find evidence of their hypotheses, and from that point of view they are almost inseparable

Even though, if a correctly specified econometric model is developed including all the variables that are affecting price volatility and using real data I think that the results that we would obtain from a case study would be closer to the reality than those results that are just inferring the results from other studies as the literature-review-based approach is doing.

This is not the case in the comparison that we have done because the econometric approach that we reviewed has many weaknesses, mostly that it is partial because only include wheat and probably miss-specified, and probably the results of the literature-based-approach is providing more insights about the causes of the food price spikes analyzed.

References

Carter, C. A.; G. C. Rausser and A. Smith. 2011. “Commodity Booms and Busts.” Annual Review of Resource Economics, Vol 3, 3, 87-118.

Chavas, J. P.; D. Hummels and B. D. Wright. 2012. “The Economics of Food Price Volatility. University of Chicago Press. National Bureau of Economic Research.”.

Gustafson, R. L. 1958. “Implications of Recent Research on Optimal Storage Rules.” Journal of Farm Economics, 40(2), 290-300.

Janzen, Joseph P.; Colin A. Carter; Aaron d. Simth and Michael K. Ajemian. 2014. “Deconstructing Wheat Price Spikes: A Model of Supply and Demand, Financial Speculation, and Commodity Price Comovement, Err-165, U.S. Department of Agriculture, Economic Research Service, April 2014.”.

Lagi, Marco; Karla Z. Bertrand and Yaneer Bar-Yam. 2011. “The Food Crises and Political Instability in North Africa and the Middle East. New England Complex Systems Institute. Cambridge, Ma.”.

von Braun, Joachim and Getaw Tadesse. 2012. “Global Food Price Volatility and Spikes: An Overview of Costs, Causes, and Solutions, Zef Discussion Papers on Development Policy, No. 161.”

Williams, J. B. 1936. “Speculation and the Carryover.” Quarterly Journal of Economics, 50, 436-55.

Wright, B. D. and J. C. Williams. 1982. “The Economic-Role of Commodity Storage.” Economic Journal, 92(367), 596-614.


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When water meets behavioral economics (or: it is not all about money!)*

IA0112_RetPlanning_MI-resize-380x300

Water engineers do not like people; we are better with numbers, equations and models where people behavior is only a variable, usually constant, or in the best case a probabilistic approximation. On the other side, most economic studies relate to people’s behavior, and when economists develop engineering-based models, engineers usually think that econometric approaches are too simple to represent complex systems that engineers like to work with.

Besides this simple-minded cliche, there is a lot of field to explore in the intersections of both disciplines. Even though the development of infrastructure cost-benefit analyses after Dupuit’s work, or the more recent growth of hydroeconomic modeling, we are still missing a lot of potential synergic benefits from integrating behavioral economics and water infrastructure design and management.

To present a simple example: urban water infrastructure design is based on water peaks, so reservoirs, pump stations and pipe dimensions have to be built to serve these peaks; water-related energy assessment studies have shown that there is a lot of energy used for every drop of water used in our houses, farms, and industries, and energy peaks are even larger that water peaks, creating expensive troubles for energy supply; and all this energy consumption means greenhouse gas emissions. Therefore we agree that reducing water peaks might create a lot of benefits, but could water customers change their behavior? Which incentives do they need? It is only about money, or it may be managed with better information?

Beyond this example there are many other promising economic topics that could help in our daily water problems, such as: game theoretic approaches to understand decisions; science-based agent models that help us to understand the performance of a system as the sum of agents’ actions and interactions; or the analysis of institutional-driven management to avoid the tragedy of the commons that depletes groundwater resources globally.

And no need to remind that all resource scarcity problems will increase with population growth, so it would be better to begin work sooner on these problems.

 

*Abstract presented to the “Special Students Pop-Up Talk Session in Water Sciences” of AGU Fall Meeting 2014.


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Data! Data! Data!

“Data! Data! Data! … I can’t make bricks without clay.” Sherlock Holmes
exclaimed in The Adventure of the Copper Beeches (Arthur Conan Doyle)

A few weeks ago I was invited to the kick off meeting of a new effort in Fresno (CA) that tries to get together water people from academia, business and government agencies in order to develop a water tech hub in the Central Valley of California, taking advantage of the current knowledge about water infrastructure and technology that they already have and trying to enhance their economy highly dependent on water management. One of the main points that would characterize this endeavor will be water data releasing from public agencies and private firms in order to attract the attention of researchers in a clear win-win strategy where scientists will obtain raw material to research whereas the agencies and firms will get the results from these investigations, and the final benefits from better understanding of water, environmental and economics problems will impact in the whole society.

Word Cloud "Big Data"Even in this 21st century when we are witnesses of the Big Data boom in many fields related with public governance, water scientists have to deal with the problem of harvesting data to test their hypotheses as Dr. Maximilian Auffhammer pointed out clearly in this other blog.

The emphasis in data availability that the people from Fresno are proposing brought to my mind an episode happened a few months ago: I found a very interesting research done by a spanish public agency and totally completed and I got so excited that immediately contacted the authors of the research to try to get the data from the survey and as you might be expecting, they just answered me that they cannot share that data. I do not want to seem naive, and probably if they do not share the data they must have very good reasons because previous problems or because they are still exploiting the results from this dataset, but I am looking beyond this concrete event: in Spain (and in many other countries I guess) we are wasting many opportunities because the private treatment that we give to data that has been collected with public funding. I completely understand that it has to be a given time to the researchers that are collecting the data through surveys to complete their studies, but after this comprehensive period the data must be released publicly and furthermore it is necessary to make it easy to access and download it in order to multiply the potential benefits.

As an example of that the government of the United States has established some laws (or amendments to previous laws) as the so called Shelby Amendment to the Freedom of Information Act that “mandated the Office of Management and Budget (…) to require federal agencies to ensure that all data produced under a [federally funded] award will be made available to the public”. To the same conclusion arrived the Organisation for Economic Co-operation and Development (OECD) in a report released in 2006. As far as I know, the Spanish government does not have any law following the same concept, and just looking hard helped by google I found a short reference in the 2013-2020 Spanish Science, Technology and Innovation Strategy.

This is a very easy move, a small regulation modification that does not bother any politic party, and from these kind of small steps sometimes the world makes a jump ahead. And it is well known that we need some new fresh air right now in Spain… let’s breathe!


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WEC Mexico 2014 Presentation: Modeling residential water, energy, GHG emissions and costs in California.

This is the presentation that I gave at Water, Energy and Climate Conference organized by the International Water Association, on May 23rd, 2014, in Mexico City.


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When water fails: Economic considerations of water scarcity on food, energy and the environment (Part 3 of 3)*

*This is the last post related with the potential effects of the current California’s drought. In this one I will claim about the necessity of multidisciplinary research proposing promising research topics, and I will develop some conclusions from the research including some global considerations. Take a look at the previous posts (First, Second).

Crossing the edges

Beyond quantification of interactions, new approaches taking advantage of the synergies of these interrelated systems and thus avoiding the implications of isolated management strategies should be implemented to improve global efficiency. There are many promising fields where scientists from different disciplines are crossing the edges, searching for integrative approaches that take the system as a whole into account.

The relationship between urban water, energy and GHG emissions (Escriva-Bou et al., ongoing research); agricultural responses to shocks in water and energy prices and/or availability (Medellin-Azuara et al., 2011); reconciliation ecology (Rosenzweig, 2003); GHG emission reduction from agricultural practices (Smith et al., 2007) or environmental policies related with water, energy and food production are some of the encouraging fields where more multidisciplinary research is needed.

Beyond California: from local conclusions to global considerations

California’s intertied water network has improved the robustness of statewide water demands and its economic profits to protect against potential short-term shocks such as the current drought and even long-term trends such as climate change which may bring uncertain effects. As has been shown, one of the main features characterizing the system is that most of the demands have diversified their water source portfolio in order to increase their economic reliability, even creating institutional tools including water markets.

But when water fails, normality is altered, hydropower generation diminishes, the agricultural sector uses more energy to pump or convey water, raising GHG emissions at the same time, and food production input costs increases. Only through urban demand-side policies can water be saved without direct costs —just a temporal loss in the living-standards utility function— and achieving a significant water-related energy and GHG emissions savings.

All those interrelations have non-trivial economic implications: from the perspective of the ordinary citizen, urban water rates would increase if DSMP are implemented, and food and energy prices would have some price effect due to reduced hydropower production and increased input costs for the food production sector; water and energy utilities will incur some extra costs because of the drought, but they will be relatively small due to improved water and energy source portfolios; from the agricultural sector, and assuming that prices will vary slightly because of the international trade, the increased input costs will cause significant economic losses and a reduction in the labor market, especially in those counties that are largely dependent on the agricultural sector; and finally accounting for statewide general consequences, GHG emissions will increase from reduced hydropower production and increased urban and agricultural pumping and conveyance, whereas the expected decrease will depend on the effectiveness of the urban conservation policies taken.

The conclusions above are strictly determined by local water, energy and food production systems present in California today, but from these arguments we might develop some final thoughts relevant for other water-stressed regions where some of the assumptions do not hold exactly as in California:

  • Less developed countries with a greater share of the gross product determined by the agricultural sector should expect larger impacts of economic and labor market losses from water scarcity.
  • Countries highly dependent on hydropower could suffer significant problems of energy supply due to water shortages, and a severe drought could imply a significant effect on final energy prices. Therefore, improvements of the energy portfolio should be a priority for countries with uncertain climate projections.
  • Agricultural regions not shaped by the international trade are expected to suffer high price volatility for food commodities.
  • Less integrated water systems or those dependent on a unique water source will be more vulnerable to droughts.

Therefore, integrated approaches are essential to assess the interrelated effects of water, food production, energy and environment systems in more vulnerable regions to minimize economic losses and potential damages.

Acknowledgements

This study has been developed as a result of a mobility stay funded by the Erasmus Mundus Programme of the European Commission under the Transatlantic Partnership for Excellence in Engineering – TEE Project.

I would like to thank my advisors Dr. Jay R. Lund (University of California, Davis) and Dr. Manuel Pulido-Velazquez (Universitat Politècnica de València), as well as Dr. Josue Medellin-Azuara as well, for their thought-provoking comments.

Finally, I want to thank specially my friend Dr. Stephen Pearce, who reviewed the final version and contributed with helpful suggestions.

References

Escriva-Bou A, Lund J, Pulido-Velazquez M (ongoing research) Modeling residential water, energy, carbon footprint and costs in California. University of California Davis.

Medellin-Azuara J, Howitt RE, MacEwan DJ, Lund JR (2011) Economic impacts of climate-related changes to California agriculture. Climatic Change 109:387-405.

Rosenzweig ML (2003) Reconciliation ecology and the future of species diversity. Oryx 37:194-205.

Smith P, Martino D, Cai ZC, Gwary D, Janzen H, Kumar P, McCarl B, Ogle S, O’Mara F, Rice C, Scholes B, Sirotenko O, Howden M, McAllister T, Pan GX, Romanenkov V, Schneider U, Towprayoon S (2007) Policy and technological constraints to implementation of greenhouse gas mitigation options in agriculture. Agr Ecosyst Environ 118:6-28.