Homework answers / question archive / Chapter 14 in 4th edition (Chapter 17 in 3rd edition): Greening the Economy How much does the United States currently spend on environmental protection, as a percent of GDP? 2-3% percent of GDP for environmental protection

Chapter 14 in 4th edition (Chapter 17 in 3rd edition): Greening the Economy How much does the United States currently spend on environmental protection, as a percent of GDP? 2-3% percent of GDP for environmental protection

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Chapter 14 in 4th edition (Chapter 17 in 3rd edition): Greening the Economy How much does the United States currently spend on environmental protection, as a percent of GDP? 2-3% percent of GDP for environmental protection. Compare to 6-9% for national defense, 6-9% for medical care, 10-15% for housing, 12-24% for food. Compare to other countries: Are we spending too much or too little on environmental protection? What is a “green economy?” This is how the United Nations defines a green economy (UNEP 2011): UNEP defines a green economy as one that results in improved human well-being and social equity, while significantly reducing environmental risks and ecological scarcities. In its simplest expression, a green economy can be thought of as one which is low carbon, resource efficient and socially inclusive. In a green economy, growth in income and employment should be driven by public and private investments that reduce carbon emissions and pollution, enhance energy and resource efficiency, and prevent the loss of biodiversity and ecosystem services. These investments need to be catalyzed and supported by targeted public expenditure, policy reforms and regulation changes. The development path should maintain, enhance and, where necessary, rebuild natural capital as a critical economic asset and as a source of public benefits, especially for poor people whose livelihoods and security depend on nature. The Relationship between Economic Growth (Economy) and the Environment As a country gets richer over time, what happens to environmental quality? Environmental quality is a normal good = Demand for environmental quality increases as incomes increase. Luxury good = A good that people tend to spend a higher percentage of their income on as their incomes increase. Whether environmental quality is a luxury good is debatable. The Environmental Kuznets curve (EKC) hypothesis: The relationship between income and environmental impacts is characterized by an inverted U-shape: The inverted U-shape suggests that environmental quality deteriorates early in a nation’s development (why?), and then, as it becomes wealthier, environmental quality improves (why?). While there is some evidence that this may be true for SO2 (and perhaps particulate matter and nitrogen oxides) further analysis suggests that it does not apply more broadly to other environmental impacts (Think about CO2 levels and natural habitats). The Porter Hypothesis and the Costs of Environmental Regulations Porter Hypothesis = The idea that firms can enhance their financial performance (and competitiveness) by enhancing their environmental performance (which implies that environmental regulation can be potentially beneficial). How is that possible? What are some key characteristics of environmental regulations that can achieve the “win-win” outcome? 1. “Win-win” environmental regulations prompt firms to innovate. Innovations include, but are not limited to, the use of fewer and/or less polluting inputs (that may also be cheaper), different and/or more efficient production technologies, the recycling of output, etc. 2. “Win-win” environmental regulations allow each firm to decide how to best achieve the desired environmental standard or outcome (i.e., does not expect all firms to adopt the same “prescribed” methods and/or technologies to lower their emissions). That would surely hinder innovation! So the government sets the environmental standard and each firm is free to decide how to best achieve it. 3. Such environmental regulation is often designed in close collaboration with firms within the relevant industry. A single firm may even initiate this collaboration – doing so gives a firm more time to explore its own “best practices” (which often results in lower “compliance” costs), gives the firm the industry head-start in the launch of a novel “green” product,” allows the firm to claim the industry lead. Competing firms are then left to catch up! What is the evidence on the validity of the Porter hypothesis? Some firm-level empirical research supports the Porter Hypothesis. Country-level empirical analyses seem to not support the Porter Hypothesis. But even if the Porter Hypothesis doesn’t hold for all firms in all industries at all times, we know that innovation has, at least, the potential to reduce compliance costs. Several studies have, for example, shown that firms tend to overestimate the compliance costs of environmental regulation—in some cases by about 30%. It is also possible that some industries may be better positioned than others to capitalize on “winwin” environmental regulations. Tourism may be one such industry. Nations, therefore, whose economy depends on such industries may, in fact, become more competitive against others by adopting “Porter-style” strategies. Let’s talk a little about that! Conclusions Does environmental protection result in job losses? Not a single, large-scale, rigorous study has found any evidence that environmental protection results in job losses. These studies show that environmental protection results in job losses in some industries, creates job in other industries, and that the NET EFFECT IS POSITIVE (i.e., more jobs created than lost). See your textbook for specific studies. Does environmental protection reduce economic growth (i.e, reduce GDP growth rates)? The macroeconomic effect of environmental regulations are estimated using computable general equilibrium (CGE) models, and these must predict reduced economic growth due to environmental regulation because pollution control costs are extra expenditures that are necessary to produce the same level of valued output. Further, these CGE models rarely count the non-market benefits of environmental improvements as a result of regulations. So the somewhat reduced growth rates these model find should not be interpreted as the aggregate effect of regulations on the economy. Finally, these CGE models find, anyway, that regulations have a very small effect on GDP growth rate! Does environmental protection really harm international competitiveness? Earlier studies found some weak evidence that there was a minor decrease in exports, but no “large adverse effect on competitiveness.” Studies that followed showed some negative effect on some sectors, but positive effects on other sectors. A 2011 study of US manufacturing found that highly polluting manufacturing plants tend to be associated with lower productivity (e.g., 5% lower productivity associated with failure to meet Clean Air Act standards). A 2012 study of European regulations even finds evidence that certain regulations can have a positive impact on competitiveness! To quote your textbook, “The evidence suggests that the common notion that environmental regulation harms the economy is a myth.” Can you talk about this a little? Suffolk University Department of Economics EC131 – Environmental Economics Professor: Christos Makriyannis Week(s): Date(s): Chapter 6: Valuing the Environment (focus on stated preference discrete choice experiments) Steps to Conducting a Stated Preference Discrete Choice Experiment (as you study these steps, keep in mind that the order is not “set in stone.” This may vary slightly depending on circumstances, valuation goals, whether the “good” being valued is a market or nonmarket good, and the researcher’s preferences). 1. Identify what exactly is to be valued. A policy? A good or service that hasn’t yet been introduced in the market? An animal or plant species? 2. Identify the bundle of attributes that characterize the “object” to be valued. In other words, identify the group of attributes that people value about the good/service/policy/outcome/species to be valued. This may initially be done through focus groups, a literature review, or both. It is critical that attributes are relevant to respondents/residents and that no key relevant attributes are omitted from the choice scenarios. 3. Determine how much people know about the good/service/policy/outcome/species to be valued. This will help determine what and how much information to include prior to the choice questions in the survey instrument. This can also be done through focus groups, a literature review, or a combination of both. 4. Determine how to best define and measure each attribute, and how to best communicate this information in the choice scenarios. It is critical that respondents understand exactly what each attribute means and the units in which it is being measured. 5. Create the statistical design that will appear in the choice scenarios. Having identified the “final” list of attributes and attribute levels, use one of the specialized statistical packages to generate the “numbers” (attribute levels) that will appear in the choice scenarios. The goal is to “mix and match” the attribute levels such that the selected statistical criteria are optimized. Ngene is probably the most popular software for creating discrete choice experiment designs. 6. Focus group testing. Having put together an initial survey draft, test its effectiveness in a focus group setting. It is important to make sure that a) survey language, text, information and graphics are understood by respondents as expected by researchers and b) all key relevant attributes have been included in the survey. 7. Revise the survey based on focus group feedback. 8. Repeat steps 5 and 6 as necessary. 9. Launch the survey within the target population. This can be done either by mail or electronically, using, for example, Qualtrics. Each method has its pros and cons. 10. Collect data and prepare it for analysis. 11. Analyze data. We are dealing here with a binary 0-1 dependent variable, so the data needs to be analyzed using a statistical discrete choice model. Start with the simplest model first (multinomial/conditional logit) and progress to more complex models (e.g., mixed logit, latent class, generalized multinomial logit). The each parameter estimate is the coefficient of an attribute in the (separately additive) utility function we described in class! So each parameter is the slope of the utility function with respect to that attribute. So, very roughly speaking, this implies that dividing the parameter estimate of an attribute by the parameter estimate of the cost or price attribute gives the “willingness-topay” (WTP) for that attribute! Some models are already in WTP space, and the parameter estimates themselves are the WTP estimates! Your notes on BB for this chapter include a stated preference discrete choice experiment. See if you can answer the following questions: 1. 2. 3. 4. What is being valued? What are the attributes that characterize/define this good/policy/service? What are the units of measure of each attribute? What are the WTP values for each attribute? Various Types of Values we Place on the Environment Use Values = Tangible benefits that can be physically observed. In other words, the value due to uses we can actually see. For example, we can observe the shade and cooling effect of a tree; and how wetland and natural beach habitats protect built infrastructure from flooding. Non-Use values = The intangible or psychological benefits we obtain from the environment. How much pleasure/happiness I derive from looking at a forest, how happy it would make me to preserve it for the future, the value to me knowing that it exists. Direct Use Value (one category of use value) = The value one obtains by directly using a natural resource (e.g., visiting a national park or taking a nap under the your tree you were asked to value! Indirect Use Value (another category of use value) = Indirect services (i.e., ecosystem services) not that are not valued by the market (the flood prevention and pollution control services generated by wetlands). Option Value = The value people place on preserving a natural system/resource so that they may have the option to use in the future (e.g., someone’s willingness to pay to preserve the Amazon rainforest). Bequest Value = The value that people place on the knowledge that a resource will be available for future generations to use or enjoy or somehow benefit from (though they themselves may never get to use it in the future!). If you have kids, your bequest value may be higher than someone else’s who does not have kids! Existence Value = The value people place on a resource from knowing that it exists, assuming they or any of their loved ones will never visit or somehow directly or directly use it. TOTAL ECONOMIC VALUE = Direct Use Value + Indirect Use Value + Option Value + Bequest Value + Existence Value.