(1)
University of South Australia, Adelaide, Australia
Abstract
In countries such as Australia, the UK and Canada, regulators are required to select a decision threshold that is a signal to firms of a price above which the drug is less likely to be purchased. The maximum willingness to pay (maxWTP) for a health effect was the decision threshold preferred by a number of institutions and academics since 1993. In this chapter, the advantages of using a shadow price rather than a maxWTP are demonstrated. These advantages arise because the former necessarily captures information about the forgone benefit of a purchase whereas the latter might or might not. Furthermore, if the price of a substitute good reduces, only the shadow price will reflect the increased competition, not the maxWTP. But which shadow price? There are at least three different shadow prices used in practice, all of which value an action with reference to its minimum possible loss or maximum possible gain. I show that in contexts where there is economic inefficiency and the market fails for a particular input, the derivation of a shadow price for an input from existing information about the economic context (Cost Benefit Analysis, CBA, style) is a more appropriate approach than using the shadow price of a budget constraint. A general method of deriving a CBA-style shadow price for an input without a market price is illustrated.
5.1 The Reimburser’s Problem
How should the objectively determined therapeutic significance of a new drug, its clinical innovation, be valued for the purpose of a market transaction?
The Reimburser recently read a paper by US pharma-economists who stated that the economic value of new drug innovation was indicated by the Payer’s maxWTP as revealed by the aICER of the least cost-effective of funded programmes, for example, dialysis (Vernon et al. 2009). Rough calculations suggest to the Reimburser that if all new drugs were paid the aICER of programmes such as dialysis there would be a significant expansion of the current drug budget, and health services that are more cost-effective than the new drugs would need to be displaced to finance these additional costs from a fixed health budget.1
The Reimburser then reviews a series of papers that refer to the use of the maxWTP as an appropriate value of the health effect, in the absence of evidence of the shadow price of the budget constraint (Johannesson and Weinstein 1993; Stinnett and Mullahy 1998). She also reads a paper by Weinstein (2008) that links the imperative to find a value for a QALY to the recognition by the US population that resources are limited. He argues that the need for a benchmark dollar value of a QALY is present only when a country recognises that it cannot (or will not) afford to buy all citizens effective health care.2
Five years ago the Reimburser was involved in the decision to award a significant grant to a group of academics who surveyed over 1,000 people to estimate the maxWTP for a QALY.3 At the time she was convinced by the argument that because there was no perfectly competitive market for health effects, health tended to be undervalued by the market and therefore it was necessary to survey society to find a value. The Reimburser provides the result of this study (maxWTP per QALY = $75,000) to her Health Economic Adviser as a guide to the economic value of the health effects of a new drug. The Reimburser is confused when the Health Economic Adviser states that this information is not what he needs. The Health Economic Adviser uses this example to illustrate the issue:
A Consumer asks her Agent to purchase a particular new bicycle on her behalf. Which of the two following pieces of information should she give her Agent? The maximum price she is willing to pay for the bicycle ($5,000) or the lowest price that bicycle is available for, according to the results of an online search ($1,250)? The latter is the shadow price of the bike, the former is the maxWTP.
The Reimburser is inclined to say the shadow price is the price the Consumer should give her Agent. In fact, if the market for this type of bike were perfectly competitive, then it would not matter which of these two prices the Consumer gave her Agent. In this case the price at every shop would be $1,250 and hence the price the Agent pays for a new bike would be $1,250, regardless of the information the Agent is provided with and regardless of the Consumer’s maxWTP. However, if the local market were a monopoly and the online price were from a competitive market, then it would matter which price she gave her Agent; the monopolist could be pricing at average rather than marginal cost and hence the purchase price could be higher than the online price from a competitive market. The potential loss resulting from providing the wrong piece of information to her Agent would be maximised under the following scenario.
The local monopolist bike shop owner does not provide price tags for her new bikes. Instead she asks the Agent, what is the maximum you are willing to pay for a bike? Then, after receiving this information she writes a price tag for that bike and offers it to the Agent. In this case the Agent would pay $5,000 for the bike if the only information that were provided to the Agent was the maxWTP. The loss of surplus to the Consumer would be $3,750 (=$5,000 − $1,250). If the Agent were provided with the information about the shadow price, and the local monopolist bike shop owner knew the Agent could take her business elsewhere (not such a monopoly after all), she would have reduced this price.
This example makes the intended point, but it just does not seem “technical enough” to the Reimburser. There is no “online price” from a competitive market for a new drug against which she can benchmark the new drug price. The Reimburser asks her Health Economic Adviser:
Why is it that the maxWTP is not an economic value?
Which shadow price should she use?
5.2 Why Is the Shadow Price Preferable to the maxWTP?
The key difference between the shadow price and the maxWTP is that the former acts as a conventional price by capturing information about the economic context (albeit imperfectly) whereas the maxWTP captures only one aspect of the economic context, the consumer’s preferences. If there is increased competition in the market for a good and its substitutes, the maxWTP for the item does not change, whereas the shadow price will reduce.
A hypothetical application of shadow prices to a real world problem (the non-excludability and non-rivalry of the outputs of dung beetles) illustrates this issue. The method is an adaption of those described by Mishan and Quah (2007) and McKean (1972).
5.2.1 Dung Beetles, Flies and Outdoor Dining in Canberra
When the number of flies in Australia was reduced by the introduction of dung beetles by the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) in the 1980s, outdoor dining in places such as Canberra became possible, apparently for the first time. There is no dung beetle market in Australia, despite their tangible and significant value to the Australian economy (Commonwealth Scientific and Industrial Research Organisation 2006). The output of a programme to introduce dung beetles is both non-rival in consumption and non-excludable; such a programme is a public good. So how can we derive a price for the main input into this programme; the dung beetle? (While the role of dung beetles in reducing flies in Canberra is true, the following story about the bidding process and competition is completely fictional.)
Assume for the sake of simplicity that the only output of the dung beetle programme is fly-free outdoor dining in Canberra (FFODC). Assume that there are three inputs in this programme, two of which are priced at their marginal cost of production (transport and labour) and one of which does not have a price (the dung beetle). Now assume that there is an alternative method for achieving FFODC and there is a functioning market for this good (outdoor fly screens). The evidence of the value in exchange of FFODC is revealed in the functioning market of outdoor fly screens.
This story is set out in Tables 5.1 to 5.5. The Canberra Council, which will finance this dung beetle programme, wants to know about its costs. CSIRO is the only group in Australia to have a licence to import dung beetles and there is no other way for the Canberra Council to obtain them.
Table 5.1
Cost of dung beetle programme
Part 1 | Part 2 | Scenario | |
|---|---|---|---|
Max WTP output | Shadow price input | Max WTP output (higher costs of production for dung beetle programme) | |
Labour | $100,000 | $100,000 | $2,000,000 |
Transport | $10,000 | $10,000 | $30,000 |
Subtotal | $110,000 | $110,000 | $2,030,000 |
Dung beetles—no market price | |||
1,000 beetles | $19,890,000 | $1,040,000 | $17,970,000 |
Per beetle | $19,890 | $1,040 | $17,970 |
Programme total cost | $20,000,000 | $1,150,000 | $20,000,000 |
Table 5.2
Cost of outdoor fly screen programme
Part 1 | Part 2 | Scenario | |
|---|---|---|---|
Max WTP output | Shadow price input | Max WTP output (higher costs of manufacture for dung beetle programme) | |
Labour | $100,000 | $100,000 | $100,000 |
Transport | $50,000 | $50,000 | $50,000 |
Fly screens | $1,000,000 | $1,000,000 | $1,000,000 |
Programme total cost | $1,150,000 | $1,150,000 | $1,150,000 |
Table 5.3
Maximum willingness to pay for fly free outdoor dining
Part 1 | Part 2 | Scenario | |
|---|---|---|---|
Max WTP output | Shadow price input | Max WTP output (higher costs of manufacture for dung beetle program) | |
Max WTP | $20,000,000 | $20,000,000 | $20,000,000 |
Table 5.4
The social welfare impact of implementing the dung beetle programme*
Part 1 | Part 2 | Scenario | |
|---|---|---|---|
Max WTP output | Shadow price input | Max WTP output (higher costs of manufacture for dung beetle program) | |
Cost of dung beetle programme | $20,000,000 | $1,150,000 | $20,000,000 |
Surplus (MaxWTP less cost) | $19,890,000 | $19,890,000 | $17,970,000 |
Dung beetle patent holder | $19,890,000 | $1,040,000 | $17,970,000 |
Consumer surplus | $0 | $18,850,000 | $0 |
Deadweight loss | $0 | $0 | $880,000 |
Table 5.5
The social welfare impact of implementing the outdoor fly screen programme
Part 1 | Part 2 | Scenario | |
|---|---|---|---|
Max WTP output | Shadow price input | Max WTP output (higher costs of manufacture for dung beetle program) | |
Cost of outdoor fly screen programme | $1,150,000 | $1,150,000 | $1,150,000 |
Surplus (MaxWTP less cost) | $18,850,000 | $18,850,000 | $18,850,000 |
Consumer surplus | $18,850,000 | $18,850,000 | $18,850,000 |
Part 1
From the first column of Table 5.1, we see that the labour and transport costs for the dung beetle programme are $100 thousand and $10 thousand respectively. CSIRO has not told the Canberra Council how much it costs for the 1,000 dung beetles. CSIRO has also financed a rigorous study that estimated the maxWTP by the Canberra population for the state of FFODC and found this was an amount of $20 million. The Council asks the CSIRO the cost of the dung beetles. They reply that it is $19,890 per beetle or $20 million for the overall cost of the program. This is exactly the maxWTP for FFODC. The owners of the Outdoor Fly Screen Company make an urgent submission to Canberra Council. They say they can achieve the same result (FFODC) with a different programme for $1.15 million (Table 5.2). Clearly, even though the cost of the dung beetle programme is the same as the benefits, there is a more cost-effective option. The Canberra Council decides to use outdoor fly screens.
Part 2
CSIRO comes back to the Council and says they have revised their costs. They can now provide dung beetles for $1,040 each (Part 2, Table 5.1). The costs of the dung beetle programme are now the same as the outdoor fly screen programme: $1.15 million.
This simple example illustrates the following point. If there is only one situation in which dung beetles are an input, and there is a failure of a dung beetle market to function, then, provided that there are multiple inputs and methods of production that can be used to achieve the same output (FFODC), a shadow price for dung beetles that takes into account this competition can be calculated. The dung beetle is valued at $19,890 but its shadow price is $1,040.
So why is it that there is an advantage to the Canberra Council in using the shadow price? The first advantage is that if outdoor fly screens are a more cost-effective way to achieve the intended output of outdoor dining, Canberra’s Council will recognise that they can achieve the same result at a much lower cost. The maxWTP considers only the preferences for outdoor dining and not alternative method of achieving this; it values the output rather than the specific input.
The second advantage of this approach is that it maximises consumer welfare. CSIRO knows the maxWTP for the benefits of the programme; it conducted the study to estimate it. If the CSIRO knew that the competition (fly screens) was not recognised, then it would be possible for the CSIRO to appropriate the entire surplus associated with the reduction in flies in Canberra by pricing its input such that the total cost of the programme is the same as the maxWTP. At the shadow price the surplus is appropriated by the consumers. The point is that not only does the shadow price capture information about the economic context—the competition in the outdoor dining market—it also has the potential to reduce the risks associated with other distortions that could arise as a consequence of, for example, market power due to patents.
The third problem this method overcomes is the deadweight loss4 that can arise when the maxWTP for the output is used to derive the price of an input with market power and the competition of the alternative input is neglected. The Scenario columns from Tables 5.1 to 5.5 illustrate an example where the financial costs of labour and transport for the dung beetle programme are higher than the total costs of the outdoor fly screen programme. Even if the benefits outweigh the costs of the dung beetle programme, for example it could be priced at $15 million, there could still be a deadweight loss of $880,000 compared with the best alternative strategy, the outdoor fly screen programme.
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