COU 1: Modeling A Policy Issue
Instructions
Below are three descriptions of policy issues. Pick ONE to work with, then use the one you pick to construct answers to all of the prompts.
Issue 1: Price controls on prescription drugs. The prices of prescription drugs are sometimes shockingly high. For instance, an August, 2023 article quotes the list price in the U.S. of a one-month supply of Ozempic – the brand-name of a relative new antidiabetic medication – as $936. It’s perhaps unsurprising, then, that candidates for office sometimes promise voters that, if elected, they will impose price controls that restrict the amounts pharmaceutical companies can charge for their products. Any government that considers imposing a price control on a drug must in the end decide one major question: How much more than the marginal cost of producing each dose of the drug will the drug manufacturer be allowed to charge per dose? If, say, it costs the manufacturer $10 to produce each dose, will the government set the maximum price of sale at exactly $10? Or will it permit the manufacturer some revenue in excess of marginal cost by, for instance, setting a per-dose maximum of $10-plus-some-percentage? (Setting the per-dose cap at less than the per-dose cost of production amounts to banning production of the drug outright, so we’ll ignore that option!) Behind this decision lurks tradeoff between the health of present-day patients and the health of future patients. The marginal cost a manufacturer pays to produce each dose of a drug does not include the (sometimes quite massive) costs the company paid years prior to discover, test and win regulartory approval for the drug. Thus the closer the government sets the per-dose price cap to the manufacturer’s marginal cost per-dose of production, the less of the already-paid costs of drug discovery the manufacture recoups. If they’re set too low, then, price caps on drugs can deter drug companies from investing in the discovery and development of new drugs that could be safer and more effective than those already on the market. Thus, while price caps lower the prices for current drugs paid by present-day patients, they risk depriving future patients of new, safer, and more effective pharmaceuticals yet-to-be-discovered.
Issue 2: Place-based vs. person-based policies for coping with economic change. Change is hard, especially the economic kind, and especially economic change that is geographically concentrated. For reasons that are too complicated to get into here, most of the firms in a given industry typically cluster closely together in a very small number of cities or regions. In the present-day U.S., for instance, we see this clustering in the software industry (clustered in the SF bay and Seattle Metro areas), the film and T.V. industries (clustered in LA, NYC and Toronto), the finance industry (clustered in the NYC metro area), and in the pharmaceutical and biotech industries (clustered in Central and Northern New Jersey and the Boston metro area). Industrial clustering is great for those who put down roots in a place while the industries clustered in that place thrive. But when changes in technology, consumer tastes and international development cause an industrial cluster to leave a city or region permanently, things can get ugly. Politicians, then, often seek to adopt policies that will address the challenges faced by “left behind” places and their residents. To this end, there are two broad categories of policies governments typically consider: “place-based” policies, on the one hand, and “person-based” policies, on the other. “Place based” policies (as the name suggests), provide benefits that are only accessible to persons living in specific places. For instance, a tax-credit that firms can get if and only if they locate offices or plants in a specific city or region is place-based. “Person-based” policies, on the other, provide portable benefits that persons harmed by industrial re-location can use regardless of where they live or move to. For instance, governments sometimes give educational grants to workers laid off in a plant closure that workers can use for re-training in any industry or trade at any educational institution regardless of the institution’s location or where jobs in that industry or trade are located. Some policies, of course, a have both place-based and person-based aspects. Governments will sometimes, for instance, provide free re-training to workers laid off in a plant closure by directing subsidies to the community college nearest to the closed plant. Such a program is to some extent person-based, since workers who take the training can in theory use it to get a job anywhere in the world. But it’s also place-based, since the only place the free training is accessible is at that one community college.
Issue 3: Skills-based immigration policies. How should wealthy countries, such as the U.S., Canada, Japan, South Korea, and the nations of Northwestern Europe, decide who they permit to settle within their borders as legal immigrants? One aspect of all these nations’ immigration policies is the extent to which their immigration systems are skills-based. At the extreme, a purely skills-based immigration system only admits persons as legal immigrants (along with their immediate family members) who have job skills that are in short supply and high demand within the domestic economy. For instance, imagine a country in which trained primary care physicians are needed but scarce, while dentists are plentiful. If that country had a purely skills-based immigration system, it would admit as immigrants persons trained as primary care physicians but deny legal entry to dentists. In practice, most countries’ immigration laws weigh the domestic demand and supply for a potential immigrant’s skills only to some extent, relative to other considerations. For instance, the U.S.’s immigration system allocates in each year a certain proportion of its fixed number of immigration “slots” to each of a several different immigration programs. Some of these programs allocate their slots on the basis of the domestic demand for the job skills of persons applying to immigrate. Other programs allocate their slots on the basis of other criteria, such as a person’s family relationships to current U.S. permanent residents and citizens. By adjusting the number of slots allocated to the job-skills-based immigration programs, relative to the number of slots allocated to other immigration programs, the U.S. adjusts the extent to which its immigration system is skills-based.
Prompt 1
Write three or four sentences in which you state the policy issue you’ve chosen to work with, and then name two policies that lie at the extremes of that issue. Then, below what you’ve written, draw a policy space and place the two policies you named on that space in positions that represent the fact that they are opposite extremes on the issue.
Prompt 2
Name and describe a policy on your chosen issue that lies between the two extremes you named in response to Prompt 1. Then, below what you’ve written, draw a policy space and:
- Place the two policies you named in Prompt 1 on that space in positions that represent the fact that they are opposite extremes on the issue.
- Place the policy you named in response to this prompt in a position that represents the fact that it lies between the two extremes.
Prompt 3
Name and describe another policy on your chosen issue that lies between the two extremes you named in responses to Prompt 1. Then, below what you’ve written, draw a policy space and:
- Place the two policies you named in Prompt 1 on that space in positions that represent the fact that they are opposite extremes on the issue.
- Place the policy you named in response to Prompt 2 in a position that represents the fact that it lies between the two extremes.
- Place the policy you named in response to this prompt in a position that represent the fact that it lies between the two extremes. Make sure that policy is ordered in the policy space relative to the policy you named in Prompt 2 in a way that makes sense, given the order in which you’ve placed the two extreme policies.
Prompt 4
In two to four sentences, explain why you placed the policies you named in responses to Prompts 2 and 3 in the order along the line that you did. In your explanation, name the criterion by which the four policies you’ve represented in your model are ranked. (For instance, in the example of policies towards abortion in the Lesson, the criterion used in the model is “restrictiveness”.) Then, below what you’ve written, draw a policy space and:
- Place the two policies you named in Prompt 1 on that space in positions that represent the fact that they are opposite extremes on the issue.
- Place the policy you named in response to Prompt 2 in a position that represents the fact that it lies between the two extremes.
- Place the policy you named in response to this prompt in a position that represent the fact that it lies between the two extremes. Make sure that policy is ordered in the policy space relative to the policy you named in Prompt 2 in a way that makes sense, given the order in which you’ve placed the two extreme policies.
- Label the policy space with the criterion you named in response to this prompt and put an arrow next to the label pointing in the direction that represents higher levels according to that criterion. (For instance, in the example of policies toward abortion in the Lesson, more restrictive policies are placed to the right, thus the label reads “restrictiveness” and has an arrow pointing to the right.)
Prompt 5
In about one-half a page of double-spaced text, describe an aspect of the policy issue that you’ve chosen to work with that the spatial model you developed in response to Prompts 1 through 4 fails to depict and state reasons why that aspect is important. As in the Lesson, you must do this by describing a criterion or feature that differentiates policies towards your chosen issue from one another other than the criterion your model represents.
Rubric
You can earn up to 5 points on this COU, one point for each of the 5 prompts. Because evaluating your response to each prompt depends on part on your success in the previous prompts, getting full credit on any one prompt requires performing well on the previous prompts.