Third, however, to the extent that demand decisions also reflect physician incen- tives, through indicative drug budgets, prescription monitoring by third party
payers, etc., the full price is the relevant measure, not the consumer’s co-payment. Fourth, to the extent that regulatory systems require price reductions if volume
exceeds target levels, this imposes a spurious inverse relation between quantity
Ž .
and price that would bias up in absolute value the estimated price elasticity in countries with regulation.
32
Sorting out the contribution of these factors to the observed elasticities with respect to manufacturer price is an important topic for
future research.
5. Accounting for price differentials: characteristics vs. parameters
We have shown that the relation between prices and product characteristics differs significantly across countries. In this section, we use the regression results
in Table 2b to examine how far differences in mean values of these characteristics Ž
. and their parameter effects can account for the log mean foreignrUS price ratio.
Ž .
The log mean price relative for country j relative to the US can be written:
ln R s ln P rP s ln P y ln P s ln X b y ln X b q u y u 5
Ž .
Ž .
j u
j u
j j
u u
j u
Ž . Ž .
Comparing Eqs. 4 and 5 : b s b
u
d s b y b
j j
u
or b s b q d
j u
j
Ž . Eq. 5 can thus be rewritten:
ln R s ln X y ln X b q ln X d
Ž .
j u
u j
j
The mean price ratio can thus be decomposed into two components. The first Ž
.
component or characteristics effect ln X y ln X
b reflects the difference in
j u
u
mean characteristics of our sample of drugs in country j, relative to the US, Ž
.
evaluated at US parameter values. The second component, ln X
b y b s ln
j j
u
X d , is the country interaction or implicit price effect, which reflects the
j j
difference in implicit prices for characteristics in country j, compared to the US.
33
Ž .
The country intercept estimates with opposite sign the unexplained country residual effects that are not explained by measured characteristics or their parame-
ter effects. It also subsumes country effects for the omitted cardiovascular
32
France applied a total revenue constraint ‘‘envelope globale’’ to certain products. The UK PPRS Ž
profit constraint implies a portfolio revenue constraint, given the capital base. For Italy the Emilia .
Ž .
Romagna region for 1989–1993, Anessi
1997 estimates own price elasticities for individual
cardiovascular products with respect to out-of-pocket prices to be y0.26 to y0.36.
33
Ž .
For application of a similar decomposition to wage differences, see Oaxaca 1973 , Smith and Ž
. Ž
. Welch 1977 , and Reimers 1983 .
category. Cross-country differences in implicit prices for product characteristics are of interest, although in this pharmaceutical context, the standard interpretation
of hedonic equations under assumptions of competitive equilibrium does not strictly apply. In an industry with significant fixed costs and imperfect competi-
tion, unregulated prices should approximate consumer valuations, rather than marginal costs. However, imperfect information and insurance may undermine this
interpretation for pharmaceuticals and other medical services. In addition, in countries with regulation, monopsony government purchasers may drive prices
towards marginal cost. The implicit characteristic prices presumably reflect the net effect of all these factors. Table 3 shows that differences in implicit prices are
relatively more important than differences in mean product characteristics in accounting for mean price differences, at least for these matching products.
5.1. Quality The main factors that tend to reduce drug prices in most other countries relative
to the US are more negative returns to molecule age and to therapeutic value, as measured by global penetration. Returns to age and global penetration are most
negative in France, Italy and Japan, which have the strictest price regulation Ž
. Table 3, column 7, ‘‘parameter interactions’’ . Smaller but still negative age and
global effects contribute to lower prices in Germany and Canada; only age effects are significant for the UK.
34
Smaller packs due to unit pack dispensing contribute to higher prices in other countries. But the overall effect of the quality variables
Ž .
strength, age, forms, global, and packsize , including characteristics and parame- ter values, is to reduce prices significantly in the strictly regulated markets
compared to the US, and to a lesser extent, the UK, Germany, and Canada. Ž
. Differences in therapeutic mix
ATC1 dummies and their parameter effects
contribute very little to the overall mean price differences for these matching molecules, but this conclusion cannot necessarily be generalized to the full
universe of drugs in each country.
5.2. Competition The price-reducing effects of generic competition partially but not completely
offset the more negative effects of age and global in the regulated countries. All other countries have fewer generic competitors per molecule than the US, and the
price competitive effect of a given number of generic competitors is weaker
34
The higher mean globalization score for foreign countries than for the US is an artifact of the bilaterally matched sample. Each non-US sample includes only drugs that are also available in the US,
whereas the US sample includes all drugs that are available in at least one foreign country, and is Ž
. therefore a larger sample. Other analysis not reported here shows that the fraction of sales that is
attributable to global drugs is higher in the US than in France, Italy, Germany or Japan.
P.M. Danzon,
L.-W. Chao
r Journal
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Economics 19
2000 159
– 195
188
Table 3 Accounting for observed price ratios
Canada vs. US Variable
US mean CA mean
US parameter CA parameter
Characteristic Parameter
Total effects
interactions Strength
y3.1947 y3.2458
0.1242 y0.0217
y0.0064 0.0703
0.0639 Age of molecule
5.1501 5.2481
y0.1835 y0.1496
y0.0180 y0.7851
y0.8031 Forms
0.7942 0.7390
0.2729 y0.0151
y0.0151 Global
1.4675 1.6495
0.4297 y0.2406
0.0782 y0.3969
y0.3187 Packsize
4.2203 4.5254
y0.7052 y0.0877
y0.2151 y0.3967
y0.6118 Quality subtotal
y0.1763 y1.5085
y1.6848 Generic competitors
1.0400 0.5584
y0.5674 0.0965
0.2732 0.0539
0.3271 Therapeutic substitute molecules
1.9829 1.8350
0.0693 y0.0103
y0.0103 Therapeutic substitute molecule entry lag
3.9194 3.7744
y0.0367 0.0053
0.0053 Competition subtotal
0.2683 0.0539
0.3222 Therapeutic categories subtotal
0.0112 y0.2029
y0.1916 Residual subtotal
1.0000 1.0000
3.2600 1.2031
0.0000 1.2031
1.2031 Total: log of observed price ratios
y0.3510 Germany vs. US
Variable US mean
GE mean US parameter
GE parameter Characteristic
Parameter Total
effects interactions
Strength y3.1947
y3.1998 0.1242
0.0891 y0.0006
y0.2851 y0.2857
Age of molecule 5.1501
5.4017 y0.1835
y0.2156 y0.0462
y1.1648 y1.2109
Forms 0.7942
0.8158 0.2729
0.0059 0.0059
Global 1.4675
1.6532 0.4297
y0.3408 0.0798
y0.5634 y0.4836
Packsize 4.2203
3.7189 y0.7052
0.1799 0.3536
0.6691 1.0227
Quality subtotal 0.3925
y1.3441 y0.9516
Generic competitors 1.0400
0.7627 y0.5674
0.2306 0.1573
0.1759 0.3332
Therapeutic substitute molecules 1.9829
2.2971 0.0693
y0.2794 0.0218
y0.6418 y0.6201
Therapeutic substitute molecule entry lag 3.9194
4.4072 y0.0367
0.0738 y0.0179
0.3254 0.3075
Competition subtotal 0.1612
y0.1406 0.0206
Therapeutic categories subtotal 0.0491
y0.0955 y0.0464
Residual subtotal 1.0000
1.0000 3.2600
1.0076 0.0000
1.0076 1.0076
Total: log of observed price ratios 0.0303
P.M. Danzon,
L.-W. Chao
r Journal
of Health
Economics 19
2000 159
– 195
189
France vs. US Variable
US mean FR mean
US parameter FR parameter
Characteristic Parameter
Total effects
interactions Strength
y3.1947 y3.3296
0.1242 y0.0168
y0.0168 Age of molecule
5.1501 5.2840
y0.1835 y0.4429
y0.0246 y2.3402
y2.3648 Forms
0.7942 0.5656
0.2729 y0.1704
y0.0624 y0.0964
y0.1587 Global
1.4675 1.7235
0.4297 y0.6449
0.1100 y1.1115
y1.0015 Packsize
4.2203 3.2359
y0.7052 0.6942
0.6942 Quality subtotal
0.7005 y3.5481
y2.8476 Generic competitors
1.0400 0.4293
y0.5674 0.6450
0.3466 0.2769
0.6234 Therapeutic substitute molecules
1.9829 2.1812
0.0693 y0.2157
0.0137 y0.4706
y0.4568 Therapeutic molecule entry lag
3.9194 4.2098
y0.0367 0.0413
y0.0107 0.1739
0.1632 Competition subtotal
0.3496 y0.0198
0.3298 Therapeutic categories subtotal
0.0352 0.1050
0.1402 Residual subtotal
1.0000 1.0000
3.2600 1.6015
0.0000 1.6015
1.6015 Total: log of observed price ratios
y0.7761 Italy vs. US
Variable US mean
IT mean US parameter
IT parameter Characteristic
Paramter Total
effects interactions
Strength y3.1947
y3.2587 0.1242
0.0520 y0.0079
y0.1694 y0.1774
Age of molecule 5.1501
5.2171 y0.1835
y0.3871 y0.0123
y2.0197 y2.0320
Forms 0.7942
0.6336 0.2729
y0.0438 y0.0438
Global 1.4675
1.7256 0.4297
y0.8203 0.1109
y1.4155 y1.3046
Packsize 4.2203
3.1055 y0.7052
0.7861 0.7861
Quality subtotal 0.8330
y3.6046 y2.7716
Generic competitors 1.0400
0.5657 y0.5674
0.7562 0.2692
0.4277 0.6969
Therapeutic substitute molecules 1.9829
2.2460 0.0693
y0.1876 0.0182
y0.4213 y0.4031
Therapeutic molecule entry lag 3.9194
4.1805 y0.0367
0.0367 y0.0096
0.1536 0.1440
Competition subtotal 0.2778
0.1600 0.4378
Therapeutic categories subtotal 0.0862
0.1814 0.2677
Residual subtotal 1.0000
1.0000 3.2600
1.7429 0.0000
1.7429 1.7429
Total: log of observed price ratios y0.3232
continued on next page
P.M. Danzon,
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r Journal
of Health
Economics 19
2000 159
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190
Ž .
Table 3 continued Japan vs. US
Variable US mean
JA mean US parameter
JA parameter Characteristic
Parameter Total
effects interactions
Strength y3.1947
y3.4937 0.1242
y0.0655 y0.0371
0.2289 0.1917
Age of molecule 5.1501
5.3882 y0.1835
y0.6900 y0.0437
y3.7178 y3.7615
Forms 0.7942
0.8079 0.2729
0.0037 0.0037
Global 1.4675
1.6679 0.4297
y0.6167 0.0861
y1.0286 y0.9425
Packsize 4.2203
5.2774 y0.7052
y0.7454 y0.7454
Quality subtotal y0.7363
y4.5175 y5.2539
Generic competitors 1.0400
0.8107 y0.5674
0.6739 0.1301
0.5463 0.6764
Therapeutic substitute molecules 1.9829
2.3063 0.0693
y0.1444 0.0224
y0.3331 y0.3107
Therapeutic molecule entry lag 3.9194
3.9518 y0.0367
0.0570 y0.0012
0.2251 0.2239
Competition subtotal 0.1513
0.4384 0.5897
Therapeutic categories subtotal 0.0719
y0.0446 0.0272
Residual subtotal 1.0000
1.0000 3.2600
4.1970 0.0000
4.1970 4.1970
Total: log of observed price ratios y0.4400
UK vs. US Variable
US mean UK mean
US parameter UK parameter
Characteristic Parameter
Total effects
interactions Strength
y3.1947 y3.2369
0.1242 y0.0052
y0.0052 Age of molecule
5.1501 5.3195
y0.1835 y0.3535
y0.0311 y1.8805
y1.9116 Forms
0.7942 0.7728
0.2729 y0.1449
y0.0058 y0.1120
y0.1178 Global
1.4675 1.7103
0.4297 0.1043
0.1043 Packsize
4.2203 3.9501
y0.7052 0.1060
0.1906 0.4185
0.6091 Quality subtotal
0.2527 y1.5740
y1.3212 Generic competitors
1.0400 0.3624
y0.5674 0.3220
0.3845 0.1167
0.5012 Therapeutic substitute molecules
1.9829 1.9842
0.0693 y0.2000
0.0001 y0.3969
y0.3968 Therapeutic molecule entry lag
3.9194 3.8916
y0.0367 0.0556
0.0010 0.2163
0.2173 Competition subtotal
0.3856 y0.0639
0.3217 Therapeutic categories subtotal
0.0829 y0.0058
0.0771 Residual subtotal
1.0000 1.0000
3.2600 0.3887
0.0000 0.3887
0.3887 Total: log of observed price ratios
y0.5337
Ž .
except for Canada . However, the overall price-increasing effect of generic Ž
competition i.e., the effect of fewer generics plus the effect of weaker price .
competition among generics in non-US countries ranges from 0.62 in France to 0.70 in Italy, which is much smaller in magnitude than the negative molecule age
Ž .
Ž effect from y2.03 in Italy to y3.76 in Japan or the negative global effect from
. y0.94 in Japan to y1.30 in Italy . Note that these characteristics are related:
incentives for generic entry are weak where demand is not price sensitive and where regulated originator prices decline with molecule age, hence, are very low
by the time of patent expiry. The combined effect of therapeutic substitute molecules and therapeutic substitute entry lag contributes little to explaining the
magnitude of cross-national price differences, although in general the combined
Ž effect is to reduce prices in other countries relative to the US insignificant
. difference for Canada . As discussed earlier, this effect is more plausibly attributed
to regulation than to competition, at least for France, Italy and Japan. 5.3. Unmeasured effects
The country intercepts can be interpreted as conditional estimates of country price differentials, controlling for measured characteristics and their implicit prices
that are themselves influenced by regulation. These country intercepts are positive and significant in all countries except the UK. This implies that predicted values
based solely on measured characteristics are below actual values, but that this is partially offset by positive, country-specific effects due to unmeasured factors,
such as insurance. As an alternative, unconditional measure, Table 2d reports the
Ž . Ž .
country intercepts for a the full specification in Table 2a; b omitting the Ž .
competition variables; and c omitting molecule age and competition variables, which appear to be the characteristics that are most affected by regulation. When
competition alone is omitted, all the country interactions are insignificant except Japan, which is still positive. When molecule age is also omitted, the country
interactions for Germany, France, and the UK, are significantly negative, while Canada, Italy, and Japan are not significantly different from the US.
Thus, the country intercepts from quasi-hedonic regression for drug prices, which in theory, might offer an approach to measuring cross-national price
differences that controls for product differences, are in fact extremely sensitive to specification. For some countries, these measures differ in both magnitude and
sign from the Laspeyres and Paasche indexes in Table 1. This is a further evidence of the sensitivity of drug price comparisons to methods used. Improving these
estimates from hedonic regression is the subject of ongoing research.
6. Conclusions