Content
Introduction and Lecture Overview
Welcome everybody to Lecture 6, where we’re going to talk about the optimality of pollution. That sounds like a contradiction, right? You thought you were in an environmental economics class, and that’s supposed to regard pollution as a bad thing. But we’re economists, and there are two sides to every debate. In this case we’re going to talk about the efficient level of pollution.
To get specific, this lecture will start with a quick reintroduction that will also elicit some information on mitigation costs. Then we’ll talk about pollution and the costs and benefits associated with abating pollution, or just living with the downsides. In between those two ways of talking about it, we’ll have a prelude on the fairness of distribution when the pie might grow.
Economic Analysis of Pollution
Why did we do this? We’re transitioning from basic micro theory to specific issues, starting with the question: what would an economist say is the optimal amount of pollution? If you hear “what would an economist say,” the answer almost always involves the word marginal. Economists love marginal analysis. This activity shows how marginal analysis and the law of increasing marginal costs apply to reducing climate change.
The Marginal Cost of Abatement
We can talk about the benefit of abating pollution and the cost of doing so. If we want to evade a little bit of pollution, we choose the lowest-cost option first. That might be something like scooters or e-bikes. Carpooling or public transit might be a little higher cost because it takes longer. Lowering the thermostat is effective but makes you cold. Veganism and reforestation are high cost. We can express these options by how much they abate pollution and formalize that into the marginal cost curve. As we rank options from lowest to highest cost, we see that the options get more challenging at the margin.
Historical Success: The Case of Leaded Gasoline
This is important because economists bring tools that allow us to mitigate pollution in a way that is optimal or efficient. We’ve been really successful in the past. One of the highest return-on-investment environmental policies was banning leaded gas. Leaded gas burned slightly better and reduced pre-ignition, but it caused lead poisoning. The optimal amount of lead in gas was set to zero, and the ban has been phenomenally successful. There is evidence of huge health benefits and links to lower rates of violence.
As a Roman history note, one theory of the decline of the Roman Empire is that they got rich, used lead plumbing, and poisoned themselves. Pb comes from plumbum, the Roman word for lead and the root of “plumbing.”
Economic Tools for Analyzing Pollution
When Banning Isn’t Obviously Best
The question for economists is what happens in harder circumstances where banning isn’t obviously best. We’ve got tools such as production functions, but here we’ll be flexible about what goes on the axes. For example, think about emissions of PM2.5 as a function of the number of permits to pollute, like a cap on the total number. Or think in health terms: how emissions translate to exposure, which depends on plant location, smokestack height, and so on. We’ll tie our functions to physical phenomena, even when relationships like exposure to disease incidence are hard to measure.
The Benefits of Pollution Abatement
Total Benefits of Abatement
We’ll talk about the benefits of pollution abatement in two ways. The first is in terms of the benefits of abatement. Put benefits on the vertical axis and abatement on the horizontal axis. The curve comes from science: epidemiological studies can tell us the benefit of reducing pollution from the current level (zero abatement is the current level). We often draw a curve that is steep at first and then flattens out, because marginal benefits are high at first and then diminish. We label that total benefit.
This shape makes sense: if there’s a really stinky water pipe in your neighborhood, removing that one offender has a big benefit. But if you start from an already clean stream, it’s hard to improve it much more. Could you make the Boundary Waters any prettier? Probably not. For any level of abatement, we have some total benefit.
Marginal Benefits of Abatement
You can think of this in a table. Suppose the first unit of abatement gives 10 benefits, the second gives 13, and the third gives 14. The marginal benefits are the increments: 0 to 1 is 10, 10 to 13 is 3, and 13 to 14 is 1. The total benefit and marginal benefit curves come from the same data. When the total benefit curve flattens, the marginal benefit hits zero.
The Costs of Pollution Abatement
Total Costs of Abatement
Now the costs. A motivating example is coal production zones. Different types of coal, like anthracite versus higher-sulfur coal, have different emissions. If you are near lower-emissions coal, you can reduce plant emissions by switching fuel. That’s cheap in some locations and costly in others. Once the cheap options are used up, you need other ways to reduce emissions. We generalize this with a total cost curve for abating pollution.
The Condor Conservation Example
Another example is protecting an endangered species. One study estimates cost per condor saved across options. Cheap options include habitat protection or removing wind turbines from dangerous areas. Other options, like reducing contaminants or banning lead shot for hunters, are effective but more expensive. You could even set up a condor anti-poaching agency, which might be very effective but very costly. The point is that costs rise as you run out of cheap options.
Marginal Costs of Abatement
Just like with marginal benefits, marginal costs come from data. The marginal cost of abatement starts low and rises as cheap options are exhausted. If we plot marginal benefit and marginal cost on a single graph, we can compare them directly.
Finding the Optimal Level of Abatement
Why Economists Prefer Marginal Analysis
Why do economists like the marginal version? Because it makes the optimal level easy to identify. Spoiler alert: it’s where the two lines cross. But let’s build the intuition.
Net Benefits and the Optimal Point
Given total benefits and total costs, net benefit is benefits minus costs at a given abatement level. Graphically, you want the largest gap between the curves. That occurs where the slopes are equal, which is where marginal benefits equal marginal costs.
This should sound familiar from other economics courses: profit maximization and utility maximization often come down to marginal benefits equaling marginal costs (or marginal revenue equaling marginal cost). Benefits rise faster than costs at low abatement levels, but at high abatement levels costs rise faster than benefits. The efficient level of abatement is in the middle where the marginal curves cross.
Addressing the Critique: Is Any Pollution Morally Wrong?
One student in a conservation biology class thought this framework was a capitalist justification for allowing pollution. Their contention was that the optimal level of abatement is all of it, meaning optimal pollution is none. They argued any framework that allows some pollution is morally wrong.
The counterargument is this: if you define the benefits or costs differently—say, the total benefits of abatement are enormous or the costs of pollution are infinite—the same framework yields zero pollution. So the tool can represent their view, depending on the inputs.
The Ethics of Distribution: Fairness When the Pie Grows
The Challenge of Differential Impacts
The challenge is that abatement affects people differently. Some people benefit more, and some firms can abate more cheaply. So a lot of this comes down to fairness. Think of two people, A and B, and different pies representing social net benefits from pollution control. A might live close to a polluting plant, so A benefits more than B.
The Redistribution Argument
People debate whether to choose a smaller, equal pie or a larger, less equal one. Economists add: you could redistribute gains from A to B, keeping the large pie while improving fairness. This is relevant to pollution abatement and to economic growth. A classic argument for growth is that it raises all boats, even if some rise more than others. The ethical debate is between smaller but fairer versus larger but less fair, or largest with effective compensation.
The Second Approach: Marginal Pollution Damages
Shifting from Benefits to Damages
That was the prelude on ethics. Now the second way of expressing optimal pollution. Instead of benefits of abatement, we’ll look at pollution damages. You can use either approach and get the same conclusions, but the damages approach often fits standard tools more naturally.
Defining MPD and MAC
We’ll express damages as MPD, marginal pollution damages. Pollution reduction is not free. It can require expensive controls, like electrostatic scrubbers for coal plants that capture emissions into a slurry for underground storage. That costs money. We’ll optimize using the MAC curve, marginal abatement cost.
Understanding the Emissions Axis
The tricky part is the x-axis. We now put emissions on the horizontal axis. When we looked at benefits of abatement, abatement was on the x-axis. With MPD and MAC, we think in terms of emissions. Abatement is moving in the opposite direction.
The Shape of MPD and MAC Curves
We’ll skip the total curves and go to marginal curves. MPD is upward sloping: a little pollution causes some harm, but more pollution causes much more harm. MAC, in this emissions graph, is downward sloping because the left side represents abating everything. That looks inverted compared to the earlier abatement graph, but it is equivalent.
If you ever get confused, remember the two graphs are the same story with different axes. In the emissions graph, current emissions are on the right, and abatement is measured from that baseline. In the abatement graph, the current state is zero abatement.
Cost-Effective Pollution Control: A Two-Firm Example
Setting Up the Problem
In general, as environmental economists, we use this information to calculate the optimal amount of emissions and abatement. Let’s work through a cost-effective pollution control example.
Consider a table with two firms, Jones and Smith. Each can reduce pollution at a marginal abatement cost. For Jones, going from emissions of 10 to 9 costs $100, and from 9 to 8 costs $200. Marginal abatement costs rise as emissions reductions increase. The question is: what is the least-cost approach to getting 10 total units of abatement?
Finding the Least-Cost Solution
We haven’t abated anything yet. The first choice is the cheapest unit, so we start where cost is lowest. The second unit is then the next cheapest, and so on. As we move up each firm’s cost curve, the ranking can flip. If we track the ten cheapest units across both firms, we end up with Jones abating 3 units (emitting 7) and Smith abating 7 units (emitting 3). This is the cost-efficient outcome.
The Fairness Problem
But what’s the problem? Fairness. One firm has to reduce a lot, and the firm that is more efficient at reducing emissions gets “punished” by doing more. That feels unfair and can create resentment. This tension between efficiency and fairness is a fundamental problem in environmental economics.
A firm in Smith’s position might lobby against regulation, arguing, for example, that the EPA lacks authority or that certain pollutants are not health effects. This kind of tension shows up repeatedly in policy debates.
Conclusion and Upcoming Assessments
One logistical note: there will be a micro-quiz on Friday. With today’s content, you now have everything you need for Assignment 1. Technically it’s due by the end of Friday, but there will be a mini-quiz in class that is almost one-to-one with the assignment questions. The numbers and the context will change, but if you did the assignment you’ll be able to move through the quiz quickly. This is an adaptation in the age of AI: fewer take-home assignments, more proof that you learned it yourself.
Introduction and Overview
Welcome to the continuation of Lecture 6. The previous lecture did not cover all the intended material due to going into too much depth and getting excited about the topics, which commonly happens. This lecture will continue from where we left off and cover several important topics.
The agenda for this lecture includes several items. First, there will be a quick look at the new course website, which has been reorganized to be much easier to navigate. The previous table format was getting out of control, and feedback on the new organization is welcome. Second, there will be Micro Quiz 1, which will be almost identical to a subset of the problem set but shorter, and students will not know which part will be included. After the quiz, the lecture will finish up the aggregate marginal abatement cost curves and think about optimal emissions targets in that context. Finally, there will be a game to transition into the next set of topics on public goods and commons dilemmas.
Course Website Reorganization
From Megatable to Hierarchical Structure
The course website has undergone a significant reorganization. Previously, it was displayed as one big table, which was getting increasingly hard to work with because not everything fit properly. Instead of one big megatable, the website is now hierarchical in structure. The organization now includes Part One, Chapter 1, and then each lecture, which refers to all the content like slides, videos, and links to the actual page. The website is longer now in terms of scrolling, but the navigation should still make it useful.
The new structure is more similar to Canvas and the modules system, which was the intent. The course is being developed as open source and does not rely on expensive, proprietary approaches. This reflects a belief in open education and making course materials accessible.
Course Content Updates
One important update is that Chapter 6 on Optimal Pollution was supposed to be one lecture, but it is now being split into two lectures to allow for more thorough coverage of the material. Feedback is welcome on anything that could make the course or the website easier to use.
Micro Quiz and Assessment Philosophy
Quiz Administration
The micro-quiz was administered to get it out of the way early in the lecture. The quiz should look very familiar to students because it is based directly on the problem set material. Students had until ten minutes after the hour to complete it, though most finished well before then. The quiz consisted of just one question with four parts.
Assessment Philosophy and AI Considerations
The quiz was designed to be similar to the problem set, and this is intentional. The goal is not to make assessments hard. The class should be easy for students because if it is easy, it means the instructor is doing a good job of teaching the material effectively.
There is a need to deal with the current AI situation in education. The concern is that someone might take a screenshot of an assignment and put it into one of the AI tools available. While that might not necessarily work perfectly, if students did that, they would not actually learn the material, and they would fail at the in-class assessments. The in-class quizzes serve as a check on whether students have genuinely learned the concepts.
Course Progress and Teaching Innovations
Recent Assignments and Activities
Students have completed Assignment 1 and also turned in Weekly Questions 2. Several new teaching methods have been showcased recently. Next week, there will be an early semester course evaluation to gather feedback on which of these different approaches work best. This is the first time this class is being taught by this instructor, so many new things are being tried.
Interactive Web Applications
One passion that has been brought into the course is building web apps for educational purposes. Students used a couple of these applications recently. The first one was designed to illustrate the concept of how changes in prices lead to the demand curve, which demonstrates an important economic concept in an interactive way. The second application was the Market Masters game, which attempted to gamify the learning of supply and demand concepts.
Everyone turned in the Market Masters assignment, and there was a lot of feedback with many different strategies observed. The speed slider was an important feature that students discovered, making the game more manageable. While the game is not competitive in nature, it was designed to illustrate two main points.
Supply and Demand Foundations
The first main point of the game is about supply and demand. In introductory economics, supply and demand is learned as a standalone concept, but it actually arrives naturally from underlying curves. On the demand side, the demand curve arises from indifference curves, budget constraints, and utility maximization. On the producer side, the supply curve comes from profit maximization based on marginal costs and prices. Some details were left out of the game, like shutdown rules for firms below average variable cost, but the core concepts were illustrated.
The hope is that this interactive approach builds intuition. For the instructor, it definitely does. Being able to drag sliders around to solve problems hopefully drives the concepts home for students as well. The early semester survey will help determine if this teaching method is effective.
Advanced Market Simulation Game
Three-Dimensional Economic Simulation
For fun, a new game has been added to the website. The original Market Masters game was admittedly not very fun. Over the weekend, a new version was created as a real 3D game with nice graphics. In this simulation, green spheres represent consumers who walk to the market and, based on what is available, bring goods back home to generate utility. Red squares represent producers bringing goods from their factory to the market. Producer profitability depends on how much consumers pay them.
Players can click on a factory to track its profit over time, or watch it solve the marginal cost equals price condition in real time. Consumers in the simulation try to consume up to their indifference point, demonstrating consumer optimization behavior.
The Importance of Spatial Economics
This simulation adds spatial detail, which is fundamentally missing in standard economics. When the course gets to actual research topics, the argument will be made that earth economy modeling is necessary in the macro context of environment and natural resources. A recurrent theme throughout the course is that location and space matter, yet they are almost uniformly ignored in standard economics.
Here is a simple example from the game: did a consumer walk to the market before it ran out of goods? That spatial and temporal consideration matters for how happy each household becomes. This is a detail that traditional economic models typically ignore.
Game Development and Features
The game is still a work in progress. Some features have not worked yet, like houses getting fancier as they earn more utility, or factories getting bigger as they become more profitable. The only indicator currently working is that happiness is shown by how dark green each person is. The game is essentially being turned into something like SimCity for economic education.
Key Economic Insights from the Game
The main economics point from these games is twofold. The first insight is the beauty of how all these economic elements fit together into a coherent system. The second insight is how hard it actually is in practice. It is difficult to track utility and production and hit all those buttons correctly, and this is a super simplified case with just two goods.
An anonymized distribution of scores might be posted to show how good students are at being video game utility maximizers. The point is that optimization is genuinely difficult.
Behavioral Economics Connection
Standard economic theory with rational consumers assumes that individuals can perfectly solve all these optimization problems in real-world complexity with thousands or millions of products. This assumption is challenging to maintain when you consider actual human cognitive limitations.
Behavioral economics has dived into modeling consumer behavior more realistically, acknowledging that people use heuristics, make mistakes, and have bounded rationality. This topic will be covered soon in the course.
Pollution Abatement Economics
Transition to Pollution Content
Now the lecture returns to finishing up the pollution abatement material. On Monday, the next weekly assignment will be assigned along with another assignment on this material.
Emissions on the Horizontal Axis
Where the previous lecture left off was discussing how to express most things in the pollution section in terms of emissions on the horizontal axis. There are two different curves to consider in this framework.
The Marginal Abatement Cost Curve
The first curve is the MAC curve, or marginal abatement cost curve. With emissions on the horizontal axis, the MAC curve is downsloping when moving from right to left, or equivalently, it slopes upward when moving from left to right toward higher emissions. If you have an upward-sloping MAC curve when looking at it from left to right, either it is drawn incorrectly or you have abatement rather than emissions on your horizontal axis. This is an important distinction to keep in mind when working with these graphs.
Marginal Pollution Damages
The other curve represents marginal pollution damages. As emissions go up, the marginal pollution damages also go up. This makes intuitive sense because more pollution causes more harm to society, and often the additional harm from each unit of pollution increases as total pollution increases.
Defining Current Emissions and Business as Usual
Setting up the framework with emissions on the horizontal axis requires defining one more thing: what is the current emissions level? Current emissions is the point where no abatement has been done yet. This is simplified to business as usual, which represents the expected behavior of a profit-maximizing firm with no tax or policy fix in place.
An important acronym that will be used frequently throughout the course is BAU, which stands for business as usual. Almost always in environmental analysis, two steps are needed. First, there is a need to identify what would happen under business as usual. Second, that baseline must be defined so that the counterfactual or the policy being considered can be properly compared. How good any proposed fix is depends on how much improvement over business as usual it achieves.
Optimal Pollution and Efficiency
Ideally, a policy would implement an efficient amount of pollution. The previous lecture showed this interactively by marching down the curves and choosing whoever has the lowest marginal abatement cost at each step. The result was that Jones abates 3 units and Smith abates 7 units, and there was discussion about how that allocation might seem unfair even though it is efficient.
Building a Policy-Relevant Framework
What Lies Behind the Curves
The remainder of the lecture focuses on building a policy-relevant framework for understanding pollution abatement. First, there are some comments on what lies behind the MAC and marginal damage curves. These curves come from total benefit and total cost curves. But why are those curves shaped the way they are?
Abatement Options
In thinking about the MAC curve and abatement options that would move a firm leftward on the emissions plot, there are probably more than three categories, but the focus will be on these main ones.
The first option is producing less output. If a firm produces fewer goods, it will typically emit less pollution. This is the most straightforward but also potentially the most costly approach since it means giving up revenue.
The second option is changing the input mix. An example would be switching from coal to natural gas for electricity generation. Natural gas produces fewer emissions per unit of energy than coal, so changing inputs can reduce emissions while maintaining output levels.
The third option involves broader technology changes. An example would be building a scrubber on a power plant to remove SO2, which is sulfur dioxide, before it leaves the smokestack. This kind of end-of-pipe technology can dramatically reduce emissions without changing production levels or input mixes.
The Shape of the MAC Curve
As more abatement is undertaken, it gets more expensive. This is reflected in the MAC curve being upward sloping when viewed from the current emissions level moving toward lower emissions. This upward slope occurs because of the low-hanging fruit principle.
If you are in an apple orchard picking fruit, it is easy to pick apples at the lowest part of the tree and progressively harder to reach those at the top. This is an example of diminishing marginal returns. The same principle applies to pollution abatement: as more abatement is done, the easy things are completed first.
For example, switching to e-bikes for transportation might even have negative cost because e-bikes can be cheaper to operate than cars. But more ambitious options like becoming vegan or eliminating car usage entirely become more expensive and more difficult to implement. The easy wins get captured first, leaving only increasingly costly options for additional abatement.
Underlying Economic Factors
In terms of underlying economic factors, the shape of the MAC curve comes from several sources. The price of outputs may change as production methods are altered. The price of polluting inputs changes as demand for cleaner alternatives increases. The substitutes that might be used to replace dirty inputs become more expensive as demand for them rises.
A big factor is the price of clean technology solutions. The recent success in decarbonizing economies, such as China reducing emissions last year, comes from clean technology getting cheaper. This is mostly driven by solar energy becoming dramatically cheaper over the past decade. The falling cost of clean technology is a huge driver of the position and shape of the MAC curve.
Aggregate Marginal Abatement Cost Curves
Different Firms, Different Abilities
Now the lecture turns to policy optimality when there are two different firms. In reality, firms have different abilities to abate their emissions due to differences in their production processes, technologies, and circumstances. The MAC curves for different firms will start at the same current emissions point, but they will differ in how effective each firm is at abatement and therefore in their slopes.
Example with Two Firms
Consider an example where Firm A has a MAC of 12 minus 2E, and Firm B has a MAC of 6 minus E. These individual firm curves are not directly useful to the EPA or policymakers because policy decisions typically affect the entire industry or economy.
What is usually desired is to combine these individual curves into an aggregate MAC curve. This aggregate curve shows what it would cost society as a whole to achieve different levels of total abatement across all firms.
Horizontal Summation of MAC Curves
The approach to creating an aggregate MAC curve is horizontal summation of the individual MAC curves. This is similar to what is done with firm supply functions to create market supply. The technique involves identifying price levels where only one firm would abate, then adding the quantities as prices fall and more firms begin abating.
At price 12, the aggregate curve is the exact same as Firm A’s curve because Firm B would not abate at all at that price level. Firm B only starts abating once the price falls to 6. Once both firms are abating, the curves are combined by adding the horizontal distances at each price level to get the total quantity of abatement across both firms.
Why the Aggregate MAC Matters
This aggregate MAC is what the EPA cares about because it shows the total cost to society of achieving different levels of pollution reduction. The aggregate curve can be compared to the total benefits of abatement to determine the socially optimal level of emissions reduction.
Policy Design Considerations
Uniform Standards vs. Firm-Specific Targets
An important policy question arises: Is it more efficient for the EPA to set a standard requiring everyone to abate the same amount, or to have firm-specific targets that account for differences in abatement costs?
Intuitively, if everyone faces the same policy, one shoe does not fit all feet. Firms with low abatement costs end up not abating as much as would be efficient, while firms with high abatement costs are forced to undertake expensive abatement that could have been done more cheaply elsewhere. Custom targets that account for heterogeneity in abatement costs can be more efficient.
Preview of Upcoming Material
This concept of efficiency in policy design will be illustrated in the next class with graphs that show exactly why differentiated policies can achieve the same environmental outcome at lower total cost. Assignment 2 will formalize this concept and give students practice working with aggregate MAC curves and optimal policy design.
Conclusion
This concludes the lecture material for today. The key concepts covered include the organization of the course website and the philosophy behind open education, the assessment approach including how micro-quizzes relate to problem sets, teaching innovations including interactive web applications and economic simulation games, the importance of spatial considerations in economics, the marginal abatement cost curve and its shape, the concept of business as usual as a baseline for policy analysis, the different options firms have for abating pollution, the low-hanging fruit principle and diminishing marginal returns in abatement, how to construct aggregate MAC curves through horizontal summation, and the efficiency considerations in choosing between uniform and differentiated environmental policies.