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Quantitative Marketing and Economics
Erschienen in: Quantitative Marketing and Economics 4/2022

08.10.2022

Price dynamics of Swedish pharmaceuticals

verfasst von: Aljoscha Janssen

Erschienen in: Quantitative Marketing and Economics | Ausgabe 4/2022

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Abstract

This paper investigates price patterns of off-patent pharmaceuticals in Sweden. I show that price dynamics are dependent on the number of competitors in the market. The price patterns follow predictions from a model of dynamic price competition in which the demand for pharmaceuticals incorporates the known biases of consumers: habit persistence and brand preferences. Using the regulated market of Swedish pharmaceuticals, I show that price dynamics may help in identifying possible tacit collusion by manufacturers in markets where consumers experience behavioral frictions.
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1
Regulation of substitution to generics is dependent on the federal state, and prices are based on a free-market mechanism. In 2014 and 2015, the prices of several generic products increased in the US, although there were many producers of a single homogeneous product (Los Angeles Times, 2016), attracting the attention of antitrust regulators. The puzzle of many producers and increasing prices has been featured on Reinhardt’s health care blog (Reinhardt, 2016). The suspected price increases by all competitors led to an investigation by antitrust authorities in November 2016 (Bloomberg, 2016).
 
2
The existence of switching costs has been documented in various empirical studies, including (Calem & Mester, 1995; Dubé et al., 2010; Keane, 1997; Shcherbakov, 2016; Shum, 2004; Shy, 2002), and (Viard, 2007). Relevance in the pharmaceutical market is documented in Crawford and Shum (2005) and Hollis (2002), and (Feng, 2017).
 
3
Note also the existence of similar models in monopolistic competition, i.e., Conlisk et al. (1984) and Sobel (1984), or Villas-Boas (2006). The literature shows that price cycles are even possible for monopolists under some conditions (i.e., durable goods). Another stream of literature considers similar models where consumers are forward looking, e.g., Dutta et al. (2007).
 
4
The exact co-payment functions before and after a reform in 2012 are described in Online Appendix ??. Costs for pharmaceuticals that are not in the benefit scheme are not covered, and their prices are therefore less regulated. Prescription-free (i.e., over-the-counter) medicines that are not solely sold in pharmacies and other traded pharmacy goods are generally not subsidized. Pharmaceuticals prescribed for children under 18 years old, insulin, pharmaceuticals that combat communicable diseases, and pharmaceuticals for persons who lack an understanding of their own illness are fully subsidized, and those patients do not have any expenses.
 
5
In case the original prescription drug is chosen, the out-of-pocket expense equals the price difference between the cheapest product and the prescribed product. If a patient wants to purchase a third pharmaceutical that is neither prescribed nor the product of the month, the patient pays the entire price out of pocket. Note that empirically only out-of-pocket expenses equal to the price differences are observable.
 
6
A price ceiling exists if a branded drug is under generic competition for at least four months and the price of a drug has decreased by 70% of the original branded product’s price 12 months prior to patent expiration. If no price ceiling exists, the most expensive product of the month will serve as the price ceiling. If an original product has insufficient generic competition, prices may also be reduced by 7.5% if marketing approval was received at least 15 years before (TLV, 2016c).
 
7
The exact function from purchasing to retail prices is described in Online Appendix ??. The function had a slight change in 2016 (TLV, 2016a). Pharmacies were privatized in 2009. Two thirds of the pharmacies were privatized, and the remaining third remain under public control.
 
8
Additionally, a pharmacy can sell the remainder of the previous product of the month during the first two weeks of a new month. After these two weeks, pharmacies can sell the products for the pharmacy-purchasing price without profit. Therefore, the pharmacy has no incentive to overstock a product of the month.
 
9
Most prominent are examples in the gasoline market (see for example (Byrne et al., 2015; Byrne and De Roos, 2019; Castanias & Johnson, 1993; Lewis, 2012; Noel, 2007a; 2007b; 2008; Wang, 2009; Zimmerman et al., 2013)).
 
10
Note that pharmacies are a passive actor in the market. They receive a fixed retail margin. Therefore I do not model pharmacies as agents but instead model manufacturers as facing consumers directly.
 
11
Let − j = N ∖{j}.
 
12
The assumption is in line with empirical observations within the data. Note first that the difference between the cheapest and most expensive product is often not high due to the tight setting of the upper bound R. The average maximal price difference between the cheapest product and most expensive product across all substitution groups is 112.2 SEK (approx. 11.2 USD). After controlling for whether a product is the cheapest product within a substitution group, a price decrease of 100 SEK (approx. 10 USD) is associated with a market share increase of only 1 percentage point; see the empirical part of this paper in Section 6.
 
13
Proof in Lemma 2; see Online Appendix C.
 
14
See Online Appendix A for details.
 
15
Note that pharmacies are allowed to sell the remaining stock of previously purchased products in the first two weeks of the next month for the same price as the last month. I exclude those observations as they may lead to an overestimation of habit persistence. The presented estimate can be interpreted as a lower bound of habit persistence.
 
16
One potential explanation is that users of antiepileptics are used to switch drugs within a substitution group frequently. Thus they are likely to switch a product if a new, cheaper product becomes available.
 
17
Note that the same price setting is defined as the situation in which at least two firms set the same price over three subsequent months.
 
18
Note that \(\hat {\beta }_{1c}\) is also negative. I therefore transform the variable by adding the absolute minimum of \(\hat {\beta }_{1c}\) across substances and 0.001 to \(\hat {\beta }_{1c}\) before taking the logarithm.
 
19
The ATC code is ordered according to five levels. The first level describes the main anatomical group, the second level the main therapeutic group, the third level the pharmacological subgroup, the fourth level the chemical subgroup, and the fifth level the exact chemical substance. For this analysis, I use up the ATC code up to the fifth level.
 
20
Using prices to detect collusion is common in procurement auctions (Chassang et al., 2022; Ishii, 2014; Kawai & Nakabayashi, 2022; Kawai et al., 2022). Recent related research focuses on algorithmic pricing and collusion (Calvano et al., 2020).
 
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Metadaten
Titel
Price dynamics of Swedish pharmaceuticals
verfasst von
Aljoscha Janssen
Publikationsdatum
08.10.2022
Verlag
Springer US
Erschienen in
Quantitative Marketing and Economics / Ausgabe 4/2022
Print ISSN: 1570-7156
Elektronische ISSN: 1573-711X
DOI
https://doi.org/10.1007/s11129-022-09257-2