Public finance- cost and benefits i need the spreadsheets with memo

V401 Case 2: An Economic Evaluation of “Safer Choices”

Overview

School programs to reduce unprotected sexual intercourse have been implemented across the United States, to reduce human immunodeficiency virus (HIV) infection, infection by other sexually transmitted diseases (STDs), and unintended pregnancy among US adolescents. Program evaluations have shown that such programs are effective in reducing unprotected sexual intercourse, substantially increasing condom use and other forms of contraceptive use among sexually active young people. Because resources to fund school-based HIV, other STDs, and pregnancy prevention programs are limited, however, program effectiveness is not sufficient to justify program implementation. Issues of practical concern to policy makers are financing (whether prevention programs are affordable) and whether the benefits of such programs exceed their costs.

Few economic studies of school programs have been conducted. Most studies of HIV prevention programs in particular have focused on those targeting intravenous drug users, adult urban women, and adult or adolescent gay and bisexual men. Moreover, few studies have assessed the reduction of STDs other than HIV, or have looked at the benefits and costs of preventing unintended teenage pregnancy. This case tries to get a better sense of the benefits and costs of a program to reduce the amount of unprotected sex, by monetizing the multiple benefits such programs can offer.

This topic is particularly policy relevant since sexually active people between the ages of 15 and 24 accounted for 50% of all new cases of sexually transmitted diseases in the United States. Researchers found about 18.9 million new STD cases occurred in 2000, for example, and 9.1 million of the cases, or roughly 50%, occurred among people between the ages of 15 and 24. This age group also accounts for the majority of unintended pregnancies, and a significant fraction of new HIV infections.

The Data and NPV Computations

Tables 1 and 2 give the basic economic data needed to compute probability distributions for the net present value of the “Safer Choices” program. The question to be answered is whether it is probable that the costs of the program are less than the expected benefits, and thus, whether such a program should be instituted widely by local school districts, assuming the financial resources are available to implement such a program. We will return to financing issues in the next section.

Costs include the usual inputs of time and materials needed to institute this kind of program. The benefits fall into the following categories:

· reduced medical costs for treating STDs

· reduced medical costs for dealing with unintended pregnancies

· increased work productivity from reducing the incidence of HIV infection

· Reduced medical costs associated with reducing the incidence of HIV infection. See Table 2 for the particular details.

Not included on this list is the quality-of-life improvement received by someone who otherwise would have contracted STDs, had an unintended pregnancy, or contracted HIV. Since it is hard to monetize the benefit “quality of life improvement,” we leave it out of the quantitative assessment. However, such a benefit might affect your decision about recommending the program, even though it cannot be explicitly considered in the quantitative analysis.

Similarly, the “value of live” is not monetized in this study, for two reasons. First, the assumption that a person who now contracts HIV will live close to a normal life span, given dramatic improvements in the efficacy of antiretroviral drugs. In this particular case, we assume that life spans are 10 years shorter for the person who contracts HIV. Secondly, monetizing the value of life is a controversial issue in cost benefit analysis. But note that by not monetizing the value of life, the approach taken here, a downward bias is imparted to our estimate of the economic value of the program – that is, our estimate of the program’s benefits will be conservative – because extending lifespans 10 years definitely has value. This issue can also be considered qualitatively in your assessment of the program.

Overall, the question is what is the probability that the net economic value of Safer Choices is positive, given the data in Tables 1 and 2? Given the information you have, can you recommend with reasonable confidence that Safer Choices provides positive net-benefits?

Distributional and Financial Analysis

We now consider how Safer Choices might be financed. One option would be to have the taxpayer finance the program. KHT1 below shows the distributional effects of Safer Choices when taxpayers finance the program. The table reflects the fact that insurance companies receive the fraction “a” of medical cost savings on the assumption that insurance companies would otherwise have paid the fraction “a” of these costs. The student beneficiary of the program receives the fraction (1-a) of the benefits – effectively, the value of the savings in copayments they would otherwise have had to have been paid had the program not benefited the student in one of the possible ways it might. On the assumptions that (a) the cost of the program is completely covered by taxpayers and (b) the employers gain in productivity just equal the wages they would pay out, we can see that Safer Choices benefits two groups: (a) the students who use it and benefit from it: they gain a lifetime stream of co-payment savings, plus additional wages from additional work and (b) insurance companies, who get a lifetime stream of savings in reimbursements for medical expenses. To get a sense of the magnitude of the benefits to these two groups, numerically specify KHT1 based on the mean npv estimates for the stakeholders in question. Choose the means from either the college educated or non college educated npv distributions.

A second KHT should be specified for an alternative financing arrangement whereby insurance companies pay schools to adopt “Safer Choices” (see KHT2). Again choose means from either college educated or non-college educated distributions to specify the KHT

Note that if the financial returns to health insurance companies from avoided future reimbursements are higher than the subsidy they would have to pay to school districts to institute safer choices, it would be in their interest to do so. It is for this reason that many employer-provided insurance program, such as the TIAA-CREF programs which cover IU faculty, reimburse preventive care at 100% in the hopes that people will live healthier lifestyles -- reducing health insurance payouts later down the road. In the same way, it might make sense for insurance companies to pay schools to encourage students to lead healthier lifestyles.

Note: you can assume that “a”= .8, and therefore that “1-a”= .2 In short, students affected by the program (or their parents) would normally make a 20% copay, with health insurance companies covering 80%.

Case Outputs

The basic output is a no longer than a 3 page double-space memorandum (this page length EXCLUDES ANY TABLES YOU MIGHT INCLUDE) that describes the analysis, presents the results, and then makes a recommendation whether or not Safer Choices is a program local school districts should promote, with also a recommendation about the financing mechanism. As with the pervious case, your memo should be broken down explicitly into sections with bolded headers as follows:

Introduction

Analysis Method and Assumptions

Results

Policy Recommendation

See memo for Cincinnati Vehicle Emissions Inspections case as a model for this kind of policy/decision memo. Also, revise the writing style below.

Your assessment should be based on four figures/tables.

Figure 1 shows the NPV distribution of the program for non-college educated students, with the summary statistics @Risk provides (mean, standard deviation, minium, maximum, etc.) Also, do the overlay that shows the kind of distribution generated.

Figure 2 shows the NPV distribution of the program for college-educated students, with the summary statistics @Risk provides (mean, standard deviation, minimum, maximum, etc.) Also, do the overlay that shows the kind of distribution generated.

Table 3 is KHT 1 based on the mean estimated from the distributions in either Table 1 or Table 2.

Table 4 is KHT2 based on the means estimated from the distribution you chose for KHT1. That is, do either non-college educated or college-educated for both the KHTs.

Table 1: Program costs per 1000 students in initial period (period zero)
Cost Category	Cost
Teacher training	59000
Teaching	36153
Peer facilitators	53166
Site coordinator training	48913
Site coordination	12121
Curriculum packages	8000
Implementation manuals	1063
Activity kits	1250
Photocopies for students	58
Photocopies for teachers	64
Videos	600
Total	220388

Table 2: Program Benefits
Cost Category	Value and Time Period	Cases Avoided per 1000 students
Avoided medical cost of STD treatment (a weighted average of bacterial STDs (Chlamydia, Gonorrhea, PID) and viral STDs such as Herpes	Lognormal distribution Mean $75 per case avoided, Sigma=$5 realized every year for 51 years, starting in program year (period 0)	PERT Low=0 Medium=12 High =15
Avoided cost of one unwanted pregnancy (a weighted combination of cost of live birth, prenatal care, or pregnancy termination)	Lognormal distribution Mean=$5,200 per avoided pregnancy, Sigma=$900 realized in the program year, and the following year (Periods 0 and 1)	PERT Low=0, Medium=2 High=6
Value of work productivity gain from avoiding HIV -- non college educated	Normal distribution: Mean=$14.00 per hour Sigma=$2.00 per hour 2000 hours per year over 40 years starting in year after program commences (period 1)	Lognormal Mean=2 Sigma=.4
Value of work productivity gain from avoiding HIV -- college bound	Normal distribution Mean= $18.00/hour Sigma=$3/hour 2000 hours per year over 40 years starting in the 4th year after program commences, for 36 years (starting in period 4)	Lognormal Mean=2 Sigma=.4
Cost estimate of value of medical cost savings from avoiding HIV (savings in antiretroviral drugs and other treatments)	Normal distribution Mean=$15,000 per case avoided per year Sigma=$1000 Realized each year for 40 years	Lognormal Mean=2 Sigma=.4

KHT1-Taxpayer financed	Students	School Administrators	Employers	Tax Payers	Insurance Company	Net
Avoided medical costs of STDs	(1-a) B1				aB1	B1
Avoided medical costs of unintended pregnancy	(1-a) B2				aB2	B2
Avoided Medical costs of HIV	(1-a) B3				aB3	B3
Benefits of improved quality of life/ length of life
Worker Productivity Gain from reduced HIV incidence			B5			B5
Program Cost		-C1				-C1
		T1		-T1		0
	T2		-T2			0
Net	(1-a)[B1+B2+B3] +T2	T1-C1=0	B5-T2=0	-T1	a[B1+B2+B3]	B1+B2+B3+B5-C1

KHT2-Insurance Company Financed	Students	School Administrators	Employers	Insurance Company	Net
Avoided medical costs of STDs	(1-a) B1			aB1	B1
Avoided medical costs of unintended pregnancy	(1-a) B2			aB2	B2
Avoided Medical costs of HIV	(1-a) B3			aB3	B3
Benefits of improved quality of life/ length of life
Worker Productivity Gain from reduced HIV incidence			B5		B5
Program Cost		-C1			-C1
		T1		-T1	0
	T2		-T2		0
Net	(1-a)[B1+B2+B3] +T2	T1-C1=0	B5-T2=0	a[B1+B2+B3]-T1	B1+B2+B3+B5-C1

Case Writing Style

Grades for case write-ups will be based both on the rigor of the analysis and on the clarity of the presentation. Here are some basic writing principles: Avoid redundancy. Select words to precisely describe the meanings and nuances you wish to convey. Develop themes clearly and logically. Use adverbial and adjectival qualifiers judiciously, e.g., “brilliant,” rather than “incredible genius,” “poses a risk,” rather than “threatens all humanity.” Finally, use the active voice most of the time.

FYI, here is a sample of bad writing and why it is bad:

“The government refocused its influence in the agricultural sector by implementing policies such as more rigid production controls, lowering support prices, and more measures intended to increase demand, like school lunch and food welfare programs. Surpluses were lowered, but not significantly. In a related fashion, an exporting program to rid the government of surpluses was implemented. Yet these practices were seen as “dumping” measures to the lesser-developed nations who unavoidably received the surpluses.”

I would give this passage a F grade for the following reasons:

1. It is wordy;

2. It uses the passive voice too much;

3. The language is not precise.

Here is an improved re-write:

“Consequently, the government implemented a battery of policies to reduce growing food surpluses. On the supply side, the government reduced support prices and instituted more rigid production controls. On the demand side, the government started two new programs: school lunch and welfare. Additionally, the government began subsidizing agricultural exports.

Unfortunately, these efforts had little effect. Surpluses dropped, but not significantly. Further, the export promotion program had an obvious side effect: it increased competition for struggling third-world exporters. This consequence undermined other U.S. policies designed to promote economic development in these countries.”