Taking a closer look at the full costs of energy acquisition and dissipation
I find it very interesting to examine the first two limitations of developing economic impacts of climate change from more of an environmental standpoint. The first limitation of developing economic impacts of climate change noted is our still incomplete understanding of climate change. This topic arises and causes difficulty in all areas of environmental policy, even thinking outside of economic terms. Science can only offer us so much advice. Climatologists can approximate what levels of emission cuts are required to prevent unacceptable consequences in their terms, but only when governments are ready to decide which consequences they are willing to accept (globally). Can we deal with worldwide food shortages, rising sea levels, mass extinctions, etc? And how do we put these in economic terms?? Even after these consequences are defined, there is still not scientific certainty concerning exactly how much of a temperature change will trigger these consequences as well as how much greenhouse gas emissions will need to be cut (and how quickly to prevent this change). All that can really be offered is a range of probabilities/scenarios. The second limitation is incredibly important because the need to better understand vulnerability is pressing, particularly in the case of developing countries. While this understanding is being developed primarily in poverty policy, a greater understanding of the relationship between poverty and vulnerability arising from external shocks such as climate change needs to be addressed. Over the next few decades, it is predicted that billions of people (particularly those in developing countries) will face shortages of water and food and greater risks to health as a result of global climate change. The author recognizes that adaptation will be difficult because of the complex “behavioral, technological, and institutional adjustments” that must be implemented across different levels of society. Adaptation is hard to capture in the author’s assessment but concerted global action is needed to enable these developing countries to adapt to the possible effects of climate change that will only continue to worsen in the future. This urgency has only been heightened by the projections released by the IPCC in 2007. The UNFCCC secretariat has estimated that by 2030 “developing countries will require USD 26-67 billion funds to enable adaptation to climate change. This corresponds to .2-.8% of global investment flows, or just .06-.21% of projected global GDP. Developing countries have fewer resources to adapt- I imagine that access to these kinds of funds will be a lengthy and complex process. It will be difficult for economic impacts to be developed as each developing country will require a different level of international assistance in the context of planning for sustainable development, transfer of technology and funds, and systematic planning/capacity building to reduce the risk of future disasters.
This paper was written in response to the concern that abatement costs must be in line with the costs climate change could cause. It is much simpler to calculate emission reduction costs. One can use monetary measures, which is applicable to the entire world. When comparing climate policies monetary valuation is not as sufficient in measuring avoided costs from climate alteration. This paper is not a study itself, but reviews previous studies on the marginal damage costs of emissions. The author finds that it is very difficult to find a study encompasses an entire global impact of emissions. He mentions that reporting is scarce and unreliable from developing countries. I think that this is especially important because the majority of damages are taking place in these exact countries. The section on the ability to adapt and vulnerability was particularly interesting. The author begins with the separate issue of malaria, which can be related to climate change. He mentions that the growing pressure on natural resources may lead to improved management, and I think improved innovation. The vulnerability to climate change may decrease if we are successful at this as a population. His results are a little hard to interpret because each study he examines uses different assumptions. Expected impacts from climate change are still highly speculative, but there are some areas that are being studied more than others. In reporting the damage costs the author is extremely careful in how he weights each study. Even with this careful weighting, however, it is very difficult to estimate marginal damage costs. The best guess and mean costs compiled from the studies vary significantly. It may appear to some readers that this paper really concluded nothing. But I think that it actually is a very important piece of work. It proves that we are still extremely uncertain about the costs of climate change. This fact should point out to the public that much more research is needed in the field.
It was interesting to read about the issue of quantifying social factors in an econometric study. I believe these social factors are most important in assessing the different goals across countries. Because these goals lead to the determination of adaptation costs and residual impacts, assessing them accurately is essential to creating a function for the costs of climate change. The limitations involved with quantifying these factors seem very severe. From what I have learned from statistics and cultural studies it is difficult to accurately represent qualitative measures with quantitative measures. I wonder if it would be better to use a series of qualitative yes/no variables in an econometric equation in order to include social factors.Another interesting part of the paper was that some of the studies are based on “optimistic assumptions about adaptive capacity and baseline development trends”. Shouldn’t the researchers use conservative assumptions and present a range of best case and worst case? This way the reader can assess the numbers and assumptions without an optimistic bias.
Richard Tol's formation of a probability density function from 28 published studies on the marginal damage costs of carbon dioxide emissions emphasizes the reality that their is uncertainty in climate change literature. We understand that climate change depends on a lot of "if this..." The study particularly focuses on emission reduction and abatement costs and notes that there is much fluctuation in actual costs. This, according to Tol, is due to uncertainties involved in the discount rate and the aggregation of monetized impacts over countries. The fact of the matter, however, is that the studies that used better methods with smaller standard deviations yielded lower estimates than others. This reveals that the more "pessimistic" beliefs of climate change may be too large.In spite of this data, the author is clear to note how uncertain we are. While there are many studies out there, it is often difficult to make comparisons between each one as there is different criteria used in each scenario. Additionally, aggregate estimates pose problems by often underestimating while simultaneously leaving out the positive impacts of climate change.
In his article on energy policy, Richard Tol shows the wide range in the differences in the prices that economists believe will be the marginal damage costs of carbon dioxide emissions. Tol emphasizes that understanding the impacts of global climate change on the margin are the most important in understanding the effects of small increments of greenhouse gas emissions on the earth. However, Tol mentions that there are limitations to our understanding of the economics of climate change because we still lack knowledge of the environmental aspects of climate change and of human ability to adapt to these changes. Using 28 studies done by other climate change economists, Tol used the data from these studies to try to find some averages of what the scientific community believed would be the price for a ton of carbon and weighted them according to criteria that he believed reflected the certainty of their study. Although it is hard to offer an accurate dollar amount per ton of carbon dioxide, Tol believes that accounting for the discount rate and equity rating, the price of a ton of carbon emissions will probably be below $50 per ton.
I honestly found this paper pretty confusing, and I think the uncertainty surrounding estimating marginal damage costs only exacerbated this. The paper examines 28 studies to estimate of the marginal damage costs of carbon dioxide emissions. The estimates varied as a result of uncertainty and the “notion that negative surprises are more likely than positive ones” (2072). Richard Tol argues that it is good to differentiate between studies because those with better methods produced lower estimates with reduced uncertainties. Tol concludes that although the effects of climate change are uncertain, it is unlikely the marginal damage costs of carbon dioxide emissions will be greater than $50/tC and he believes they will be considerably smaller. As our understanding of climate change impacts grows, we will likely know more about the costs of damages from carbon dioxide emissions.
I found Tol's incorporation of health issues into the climate change cost framework interesting. None of the articles we have read so far discuss the potential impacts of climate change on health and disease, which can be especially problematic in the developing world. Tol uses the example of malaria and developing effective medications; malaria as noted by Sachs,creates an enormous disease burden in the developing world, through short run decreases in savings due to health costs and long term decreases in human capital. As climate change occurs, ecosystems can be destroyed which may hold potential cures to diseases. The rain forest and coral reefs are two examples of unique environments with a high volume of biodiversity which have yielded chemicals which may be beneficial in pain or disease treatments. As temperature increase on a global scale, the incidence of malaria may rise, which would be highly detrimental in developing countries. Because of the uncertainty in terms of the degree of effects from climate change, the true marginal damages cannot be accurately valued. Since most empirical studies also have trouble valuating these health effects, the damage functions are likely under rather than overvalued in terms of the true social costs.
I fully agree with Katie’s argument that Tol’s study of the uncertainties surrounding the assessment of marginal damage costs did little to clarify the lack of agreement in the scientific community on the issue of climate change. Interestingly, Tol begins his study the caveat that “current climate change scenarios and current climate change impact studies use crude spatial and temporal solutions, too crude to capture a number of essential details that determine the impacts.” Thus, while I think his efforts to aggregate the current body of work on the marginal damage costs of climate change is an interesting approach to take, I do not think that it is a meaningful way to contextualize or clarify what proves to be largely divergent results. It seems that this study is a bit ahead of its time. Only once more complex and accurate climate modeling methods and technologies are developed can we make significant observations about the marginal damage costs of climate change.
There are no formal policies for tyring to discover environmental impact from carbon emissions. The reason for this being that with different goals for limiting carbon emissions, there leads to different adaptation costs and different residual impacts. This shows huge fluctuations in actual abatement costs to reduce carbon emissions. It is therefore hard to take all studies into account, because they also use different methods and different standard deviations. Marginal damage costs varies among all these studies, so it is very difficult to get a correct one.
Tol addresses the problem of the uncertainties of climate change and acknowledges that this makes it very hard for us to place economic values on CO2 emissions because we do not know exactly how this will affect the climate. I understand the argument of the economist that without placing any value on environmental goods, they will be valued at zero. However, I am still skeptical of the usefulness of climate valuation because there are so many unknowns, and it does not seem like a wise decision to use a number in cost benefit analyses that could potentially be completely wrong. For example, out of the four studies shown in table 1, two of these studies (Mendelsohn et al. and Tol) show that climate change will bring mostly positive economic impacts, while the other two (Pearce et al. and Nordhaus/Boyer) show mostly negative impacts. Our CO2 emissions could melt the ice caps and flood our cities, or it could cause thermohaline circulation to stop and send us into another ice age, thus lowering sea level. Another theory is that the Earth is headed into another ice age, but our CO2 emissions are keeping this from happening. The bottom line is that I don’t see how we can make use of an economic valuation of climate change when there are so many different things that could happen that would have opposite economic implications.
Uncertainty plays a huge role in the discussion about climate change. The majorities of scientist studying climate change agree that the climate is changing and largely caused by humans. However, uncertainty in their estimates for how much the temperature will increase makes it very difficult for politicians to act. Tol’s paper attempts to assign a value to the marginal damage cost of carbon dioxide by looking at other’s estimates. One of the difficulties that Tol faced was that there is little consistency between the authors of the other papers in the way they estimated the marginal damage cost. These uncertainties are largely due to the fact that we still have a very incomplete understanding of the climate. This makes it very difficult to judge what is going to happen. Many of the consequences of climate change, such as ice caps melting and habitat loss, are difficult to put in economic terms because there is no market value.
I am obviously not an expert on economic modeling, and each of the estimates of marginal emissions cost comes from models that were independently developed by specialists in this area. I am concerned about the huge variability in the findings. Even after weighting and removing the worst models there is still a great deal of variation. This reflects the great deal of uncertainty in many of the variables included in the models. These models seem to at best give us an idea of the order of magnitude of emissions costs.There are two aspects of these models that I am troubled by. First, it does not seem like they take into account non-market ecosystem level consequences of climate change. I realize these are hard to estimate and their costs are mostly accounted for though agricultural economic costs. This is not sufficient in many cases considering the potential for climate change to completely change ecosystems faster than they can naturally adapt. Second, I do not like the assumption that marginal emission costs are linear. The models calculate total emissions costs and then divide by tons of carbon to come up with an average cost per ton of carbon. This does not seem realistic. I would predict that costs/ton C with increase with increasing carbon in the atmosphere. These cost will increase even faster past a doubling of atmospheric CO2, which seems like a realistic possibility. Extrapolating a low estimate of cost/tC linearly past a doubling of CO2 could lead to some very poor policy decisions.
The uncertainty that surrounds the marginal damage costs of CO, can make policy creation a nightmare. While the complex econometrics of it are confusing, I thought Tol did a good job of combining general figures from past studies in an attempt to present a best guess at future marginal damage costs of CO2 per tonne. As research continues, and we discover more about the damages as well as ways to abate them, studies like this will have a key part in creating new policies and setting new fees, like carbon taxes, in order to account for these costs.
It did not surprise me that between the twenty-eight studies conducted on the marginal damage cost per ton of carbon there was a great amount of ambiguity, especially considering the highly variable estimates and theories on climate change in general. However, what I did find striking was the statement that the less pessimistic tests generally had better methodology and were peer-reviewed. The article states "The mean marginal damage cost, for instance, is $50/tC in the peer-reviewed literature but $93/tC in all literature (and $129/tC without quality weighting)". Typically in climate change it seems that preparing for the worst is the more desirable course of action, but this article argues that the more optimistic estimates of marginal damage cost tend to boast the better methodologies and greater reliability due to peer-review. The final conclusive statement of the article also surprised me: "One can therefore safely say that, for all practical purposes, climate change impacts may be very uncertain but is unlikely that the marginal damage costs of carbon dioxide emissions exceed $50/tC and are likely to be substantially smaller than that". Considering the great variability in the 28 studies' results, including extremely high estimates such as $350/tC in some non-peer reviewed literature, I found it encouraging that the article concluded so confidently that the likely cost would not exceed $50/tC, and was even more likely to be less than this. However the article's admitted uncertainty amongst scientists and their conducted studies still leaves questions in my mind as to how confidently we may trust in the current carbon marginal damage cost estimates and leads me to believe that there is much to still be studied.
I think Richard Tol put a lot of effort into this paper, but I still walk away convinced that the estimates of the marginal damage costs of carbon dioxide are so uncertain that attempts to predict the marginal damage costs are moot. To validate my conviction I point to the uncertainty of scientific predictions. As soon as scientists can develop a more defined picture of the effects of increased carbon dioxide, economists will be able to make meaningful predictions about the MDC of carbon dioxide. Also, when standard deviations of the mean MDC are twice as large as the mean MDC value, my uncertainty of Tol's certainty of the uncertainty is confirmed.
In his work, Tol boldly attempts to approximate a monetary value for marginal damage costs through the interpretation of 28 separate studies. His conclusion is optimistic in that the likely cost would not exceed $50/tC, however, the inconclusiveness of his study is illustrated by the extreme variance in many other of his approximations. For instance, within peer-reviewed literature the mean marginal damage costs are $50/tC. Yet, taking into account all literature the amount is $93/tC and $129/tC without quality weighting. Thus, the obvious uncertainty in the scientific community and elsewhere makes Tol's valuation of marginal damage costs hard to apply great meaning to. On the other hand, it is an important concept with obvious political implications as the variation in the scientific community narrows to a smaller range.
I certainly agree with many of the post that preceed this one, in that, there is a great deal of uncertainty involved with these estimates, which I argue is to be expected. First of all, when estimating the marginal damage per ton of carbon (tC) is being estimated, there must be an underlying rate of global temperature change associated with each additional ton of carbon added. Secondly, the marginal damage will greatly affected if a threshold were to be past, such as a scenario where the methane in the permafrost of siberia were to be released. Additionaly, there are many non-market activities that are likely to affected, which means that there may be some subjective measures included in the marginal cost estimates, such as the value of a human life or the value of an entire species. In any sense, I feel that it does not hurt to look some ball-park estimates of how much each additional ton of carbon will cost us, despite the uncertainties.
I thought Tol made an interesting point when he said that it “is necessary to express the benefits of mitigated climate change in the same metric as the costs of emission reduction”. It is very easy, and obvious, to assign monetary costs when considering the costs of emission reduction. However, when we think about the benefits of mitigated climate change, it is much harder to assign a dollar-value, because many of the benefits are just improvements to quality of life, or ecological benefits that are hard to measure. Because it is so hard to assign a dollar-value to the potential benefits of mitigated climate change, these benefits are rarely expressed in the same metric (money) as the costs of emission reduction. Without a money value, I think it makes it very hard for people to see just how great the benefits of mitigated climate change could be. Also, since usually only the costs are given dollar-values, without any dollar-value benefits, people are quick to think that the costs automatically outweigh the benefits. I think that this was a really good point that Tol made, and we should make more of an effort to express the costs and benefits in the same metric. Maybe, if benefits are assigned a dollar-value, people will consider how important mitigating climate change really is.
Some parts of this article were interesting, especially the beginning, because the author addressed the importance of using the same metric for costs and benefits, mentioned about the difficulties of attributing value to non-market effects and how hard it is to assess regional impact throughout the world when the ideal model should "provide a coherent global picture" as well as simultaneously take a local approach into consideration.The article then becomes a disturbing crescendo of uncertainties until it reaches an uncertain conclusion. It was probably one of the most confusing articles I have ever read in terms of literature review, methodology and conclusion. Moreover, there is a strong presence of value judgment, and I was unable to understand where the econometric model came from.I do agree with the author when he talks about the importance of better institutions to manage dwindling resources as a way to mitigate part of the problem. I also agree that lack of technical, economic and institutional resources might be major obstacles for the adaptation of developing countries.However, I certainly do not agree with the perspective that developing countries might be more severely affected due to their reliance on "climate-sensitive activities". In my opinion, it is a very shortsighted statement because it comprises mostly the economic point of view of the situation. If we ever have extreme, large-scale natural disasters, geographical locations might matter more than what drives a country's economy, making developed countries as vulnerable as (or even more than) developing countries.As always, models are only as accurate as the data that are fed into them, and are only able to describe reality well if its underlying theoretical assumptions are correct. With so many uncertainties associated with all 28 models, I wonder how good these estimates really are.
Tol’s paper states that some people believe that “abatement costs should be balanced against the avoided costs of climate change”. A variable that can be physically measured has to be observed in order to provide an accurate estimate. There are so many limitations and estimates that the cost of abating carbon would never be truly known. The location and possibility for future adaption are two major factors that have to be analyzed when making the estimate.This paper shows that while it is very difficult to account for all of the variables, it is possible to find a range of the marginal costs. The studies that have sound evidence should be the main focus. The studies that give higher estimates of cost typically have the most uncertainty. The author concludes that a range of $16/tC-$62/tC had a 95% probability of being accurate. This number would allow abatement costs to be set by a tax on carbon emissions. However, this value would have to change over time as innovation/potential disasters occur.
I also found this study pretty confusing. Basically, Tol just presents a bunch of different data and concludes that “climate change impacts may be very uncertain.” He provides a limit of $50/tC but the qualifying statement essentially states that there is no way of telling whether this figure is accurate at all. He seems to be making this conclusion from a laundry list of assumptions that may or may not be true.Tol does mention that research into the economic impacts of climate change is still at an early stage. Maybe it’s too early to conduct a study such as this because of the huge amounts of conflicting data? Since this is one of the early attempts at truly quantifying the impact in terms of monetary value, maybe this will open the door for more conclusive studies.
As many of the previous comments state, this paper was quite confusing, and I agree. I am somewhat unimpressed with the conclusion that there is a marginal damage valuation for CO2 emissions somewhere between $2 and $125, but probably around $5, but possibly as high as $50. It would seem that this paper did little to further the literature, but only made understanding the economics of climate change more confusing. However, there are a few points that I took away from Tol's paper. Firstly, he correctly assesses that "developing countries are more vulnerable to climate change...because their economies rely more heavily on climate-sensitive activities" such as agriculture (and are far more affected by water scarcity). Secondly, Tol recongnizes that some industries will be worse off than others, while some will arguably benefit financially as a result of climate changes and global warming. In the end, we have "best guess" figures. While this is unimpressive to us who would like more exact figures, it is better than no data at all and serves as a good place to start.
As many of the previoous posts mentioned, I really can’t tell whether this was more encouraging or discouraging concerning uncertainty about climate change impact assessments, particularly with regards to estimates of marginal damage costs of CO2 emissions. However, I found some of the insights and ideas the author presented very interesting, for instance the attempt to incorporate ethical parameters - firstly, the aggregation over time (discount rate) and secondly, the aggregation over countries (equity weighting) and the recognition that the latter would draw an idealized picture of rich countries’ concern for their poorer counterparts (which often does not exist in reality). Even though Tol’s analysis still leaves us with a lot of uncertainty, his concerns might provide researchers with new clues to help diminish estimation variations across countries and studies. For example, Tol talks about the different approaches to factor in future catastrophic events and how that decreases the ability to compare varying studies on the impact of climate change, or how those estimation differences are one source of increased uncertainty about the marginal damage cost functions. If researchers could align their studies in this respect and all apply the same hypothetical predictions for future natural disasters or/and climate change scenarios in both case studies for developing countries and developed countries, maybe large estimation variances due to these hypothetical future scenarios could be better disentangled and explained, and in turn reduce the uncertainty associated with impact assessments.
Tol attempts to combine 28 studies that estimated the marginal damage costs of carbon dioxide. I think that the main point of this paper is that there is a lot of uncertainty when estimating how climate change will affect market and non-market systems. While the uncertainties are large, Tol tries to convince readers that they are not large enough to warrant in-action. Tol discusses many of the limitations that make it difficult for scientists to accurately assess the impacts of climate change. These limitations contribute to much of the uncertainty in the current models. The uncertainty of the marginal damage cost of climate change is largely due to the discount rate and equity issues. I think that Tol did a good job of trying to combine the data from 28 different studies, but I am still not convinced that the marginal damage costs of carbon will not exceed $50/tC. This is probably an overly optimistic conclusion. I think that the uncertainties and standard deviations are just too large to safely conclude this number. Tol even admits that most of these studies underestimate the true cost of climate change. I think that I am more uncertain about the true marginal damage cost of CO2 after reading this paper.
I also agree with Katie and Ben that Tol’s analysis, while certainly thought provoking, seems somewhat muddled, particularly his discussion on “discriminating” between the different methods of analyses. In large part, this is probably due to my lack of familiarity with non-market valuation, but I also think that someone more versed in the practice would come to the came conclusion. He essentially aggregated 103 different estimates in order to develop possible range for marginal damage ($/tC). He did clearly show that this range is broad and significantly depends on the discounting method.My overall takeaway is that we need more scientists to continue to run and improve these climate models and estimates. In order for society to make a change, more people need to understand the “tangible” and “pecuniary” damages of climate change.
With a topic like this, with methods as varied as the ones utilized, and with a time frame as far into the future as the one being examined, there is undoubtedly going to be uncertainty within the scientific and economic communities. What I found most interesting about this paper is its conclusion that the aggregate marginal damage of carbon emissions will likely be less than $50/tC, perhaps rather low for what some in the scientific community believe may occur in the environment. The author acknowledges that some effects of climate change are not well understood, and thus may not be perfectly accounted for in these studies, a conclusion that is accounted for with the massive standard deviations in some of the models. However, the studies with better methods and peer review still offer lower estimates than those in grey literature. Can we admit that the future may not look as pessimistic as we may have thought? It's probably too early to tell, but the important thing for researchers and policy makers to understand is that whatever the costs of carbon emission are, there are multiple considerations that have to be taken into account when trying to decide on global solutions, including equity, ethics, sustainability, distribution, etc.
It was interesting Tol brought up the association between adaptation and venerability. Because with the imperfect information about climate changes and the time lags of emission implications, it is difficult to predict what affect the current policy will have in the future, since the result can be different depending on the success of the implementation. As previously mentioned in other responses, the results of climate changes involve so much uncertainty due to the nature of the measurements. But I feel despite the uncertainty involved, it is important to have a ballpark estimate, since from there one can get an idea about where they are at. Like Tal mentioned, from those data they were able to reach numerous conclusions about the climate and the various component of climate change. Although the conclusions were broad, they are nonetheless helpful for future studies or policy creation. It's beneficial that Tal used different calculation methods to arrive at the mean, since that can offset some of the uncertainty with comparison. But the results where the standard deviation is often double or triple the amount of the average, makes it very difficult to use for policy setting. There is too much uncertainty involved to implement a policy regarding pollution reduction when the MAC can vary in the range of the hundreds/tC.
Although Tol tells that the costs of climate change are uncertain and difficult to predict, which is something we already know, I think it is interesting to look at some of his figures. Looking at all of the studies, he says at one point that “the best guess for the marginal damage costs of carbon dioxide emissions is $5t/C, but the mean is $104/tC”, reflecting the uncertainties of climate change. This is quite a gap between 5 to 104, and I think that’s one of the most troubling aspects of his study – costs could be relatively low, or they could be huge. According to Tol, they will unlikely be greater than $50t/C. One of his most important points is that developing countries will share an unequal portion of the cost. But he notes that the rich are not as concerned about the poor as much as the equity weighting used in cost estimates implies.
So, what do we really know about the effects of climate change? The answer, clearly, is that we know too little to truly know the consequences of our actions – or, the lack of actions. It may be that damages are small and manageable, but in reality damages are quite likely fairly large. Even if they are small, who should foot the bill? The truth of the matter is that global climate change is just that – global. We are likely past the point where simply stopping pollution will not bring about a clean environment. It will take generations already, and perhaps it will soon take longer than we have on earth to see the climate return to its natural cycle, whatever that may be in the future. But we can’t wait. In large parts of the world populations face – no matter what the estimated cost is – considerable consequences of climate change. Farmers in the Sahel, farmers in Mexico and pretty much everyone in Bangladesh face dire conditions in the future – and even if their countrymen contributed to pollution, subsistence farmers did so scarcely. Yet, they carry the cost. It is an important part of the puzzle to identify the cost of emissions, but there is only so much we can do with an average, and only so much we can do with making effective pollution markets. There are inevitably some who have not contributed to pollution in any meaningful way, who will face greater costs that the actual polluters ever will. Also, is it fair to charge all populations the same for abatement cost in the future? I don’t know. But from a political stand point it won’t fly with China and India that they can’t pollute because Europe and American already filled the world’s air to the brim with CO2, and now they won’t be allowed to grow their economies because of the simple reason that when we grew ours, we didn’t think to leave enough “space” for them
This paper did not really improve my understanding of the estimation of marginal damage costs. The inconsistency of the findings seem to suggest that the study was inconclusive or not specific enough to have a direct result. I didn't understand a lot of the modeling aspects of the paper as I have only taken econ 101 and in general after reading don't feel like I fully understood what the author was trying to say.
This paper was one of the most impressive pieces we have read about climate change and predicting the MDF for the future. Tol's use of 28 climate studies ranging all across the board of conservative to liberal estimates, allows for him to come up with a pretty solid middle ground estimate. His second section that states the uncertainties associated with climate change makes this paper very different from others in that he acknowledges the weaknesses in the variability of the data. This is a departure from typical studies that just pick and choose what studies to cite based on what will fit their needs. Tol's aggregate of climate change studies provides one of the best estimates of the MDF in my opinion because he doesn't try to make his own climate change study, he just combines all the credible data from studies in the past.
I thought this paper had a very interesting view point on climate change. I appreciate all the empirical data from 28 different studies Toi collected to show that climate change seems connected to anthropogenic causes. However he is upfront about the limitations too solving climate change based on socio-economic trends and adaptations, our knowledge of the climate and difficult policy issues. Non-market goods and indirect effects are areas that are still poorly understood. However, we can be sure that adaptation of unsustainable economic practices will put pressures on natural resources that will speed climate change. Other trends seen from the studies suggest climate effects are felt more in the developing world and non-market impacts will be more severe. Also, vulnerability is different in regions and within regions . Further climate change is frequently measured where effects may be more severe so they total change may be overtold. All of these revelations point the the conclusion that although climate change is a global problem there cannot be a uniform solution. The 28 studies cited in this paper show that there is a great deal of uncertainty in understanding climate change but also shows there is a large amount of work going into understanding and communicating these effects
Tol's paper reflects one of the disadvantages that environmental economists have to face: the lack of controlled experiment designed at a large scale. Even though Tol does have a substantive number of 108 estimates from 28 papers with relatively great credentials, I am rather concerned that this is the best practice to develop the probability density function. As Tol recognized the limitation of his attempt, given the divergent experiment designs, different methods in quantifying the impacts of carbon emission, and different weights in adaptation values/practices, it is almost absurd for Tol to combine these data together to form the probability density function. I also don't understand how he came up with $50 per tC in the Conclusion portion since the probability density function does not center around $50. Nonetheless, this paper is one of a kind since Tol attempts to consolidate existing researches out there in order to flesh out a common message that climate scientists need to deliver to the public, which is that MAC is adequately low and can be addressed without substantial response cost. His attempt is worthy in the inception. The paper could benefit from more selective estimates from experiments of similar designs. In addition, it is very novel that Tol included the equity term to account for the difference in uncertainty estimates between developed and developing countries. I wish he would have explained in more details how he derived the equity term. Last but not least, Tol did not address the big question of what is the most sensitive discount rate to use to assess MAC. Conducting sensitivity analysis is a good practice, but can only be applicable if there is a set range of values that policy makers know they should aim at. Thus, deriving sensitivity analysis without a concrete goal is just circular argument.
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