Discussion Paper No.

522

AN EMPIRICAL RESEARCH
OF SUBSTITUTABILITY
BETWEEN MEDICAL SERVICES AND
OVER-THE-COUNTER MEDICATION.
AN ANALYSIS OF THIRTEENDIFFERENT MINOR AILMENTS
Masako Ii
andYasushi Ohkusa

December 2000

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

8 December 2000

An Empirical Research of Substitutability between
Medical Services and Over-the-Counter
Medication. An Analysis of Thirteen Diﬀerent
Minor Ailments ∗)Masako Ii
Yokohama National University
andYasushi Ohkusa
Osaka University
Abstract
This paper examines the choice of health care for minor ailments in Japan for patients suffering from thirteen diﬀerent minor ailments. Original data were obtained from a survey
conducted by the authors. For the common cold, shoulder/neck pain, backache, constipation/diarrea, asthenopia, various skin diseases, and hameorrhoids, an increase in thecoinsurance rate statistically significantly lowers the demand for medical services. On theother hand, the demand for over-the-counter (OTC) medication is statistically significantly
higher with an increase in the coinsurance rate for the common cold and skin diseases. In
the case of the common cold, the marginal eﬀects for medical services and for the OTC
medication are -0.35 and 0.34 respectively. For shoulder/neck pain, the marginal eﬀect for
medical services is -0.26. For other illnesses, marginal eﬀects for medical services range
from -0.87 to -3.69, while the values of that for OTC are around 1.5.

JEL Classifications: I11,I12, I31, I18
Keywords: minor illnesses, medical service demand, medical insurance system, over-thecounter medication
Correspondence:Yasushi Ohkusa, Institute of Social and Economic Research, Osaka University, 6-1 Mihogaoka Ibaraki Osaka, Japan
Tel:81-6-6879-8566

Fax:81-6-6878-2766e-mail:ohkus iser.osaka-u.ac.jp

1

Introduction

Japanese society is rapidly aging and Japanese national medical costs continue to riseby at least one trillion yen (about 0.1 billion US dollars) every year. There is universal
coverage with unlimited access to all health care facilities to all the residents. Becauseof this generous national medical insurance system, patients have no incentive to prevent
disease and are increasingly turning away from clinics in favour of hospitals because of theirperceived higher quality and standardized price charge across all providers.
Many health care reform plans have been put forward. One of them proposes to increase
the coinsurance rate for relatively minor ailments as well as for their prescribed medications.
Minor ailments are illnesses such as the common cold and diarrea, which are curable bystandard treatments at reasonable costs.
As there are several kinds of treatments for minor illnesses, including medical services
provided by hospitals or clinics, the anticipated eﬀect of an increase in the coinsurance
rate on national medical costs is unclear. If patients are not sensitive to price change, anincrease in the coinsurance rate may not have any appreciable eﬀect on national costs. On
the other hand, if patients are sensitive to a price increase, they may choose other options
and decide to seek medical services less frequently. An increase in the coinsurance rate willthen decrease national medical costs.
In this paper, we assume that when suﬀering from a minor ailment, a patient has three
options: he or she can either consult a doctor, purchase over-the-counter (OTC) medications, or seek no treatment. There is a possibility that patients are highly sensitive to pricechange, but this needs to be tested empirically.
In the United States, where extensive research has been conducted on health economics,
only a few studies have focused on the demand for medical services related to minor ailments, or on the substitutability between prescribed medication and OTC medication(Stuart and James, 1995; Fillenbaum, et. al., 1995). Of these studies, particular attention1

is paid to the research by Newhouse (1993) because of its originality and innovative research design. The research was part of a 10-year study referred to as the Health Insurance
Experiment (HIE) that Newhouse and others at the RAND Institute initiated in 1971. The
HIE is a longitudinal study that experimentally altered the cost-sharing of medical care
faced by families. Between November 1974 and February 1977, the HIE assigned families
to various insurance plans that diﬀered in the amount of cost-sharing. According to thisstudy, the use of emergency units involving minor illnesses is only 47% lower on the costsharing plan than on the free plan. For example, the use of emergency units by patientssuﬀering from influenza declined by 65% on the cost sharing plan compared to the use by
those on the free plan. On the cost sharing plan, for abdominal pain use is 53% lower,
for back/neck pain use is 45% lower, and for headache use is 11% lower. Although priceelasticity are not accounted for in the study, the results suggest that for minor ailments,
the demand for medical services is relatively more sensitive to price than for more urgent
illnesses.
Ii and Ohkusa (1998) were the first to attempt to estimate the demand for medical
services related to minor illnesses. They explicitly modeled the incidence of minor illnesses,
and using micro household data measured the price elasticity of demand for medical care forminor illnesses in Japan. Their data, from the Basic Survey on People’s Life (BSPL), were
not experimentally or extensively collected like that in the HIE. However, the sample sizein the BSPL - approximately 600,000 - is much larger compared to that of the HIE, which
is about 2000. BSPL includes household and individual characteristics such as gender, age,income and assets, as well as detailed health information. Their results show that the priceelasticity for medical services was 0.208, which is comparable to that for the United States,
and that medical services and OTC medications are substitutable.
Ii and Ohkusa (2000a) used patients’ health information from the BSPL to define minor
illnesses, and estimated price elasticities for various minor illnesses. They found that in thecase of minor illnesses, the price elasticities for medical services were between 0.144 and2

0.149. The data set also included detailed information on 43 subjective symptoms. The
authors estimated price elasticities for medical services demanded for the 43 symptoms
separately and found that for almost half of the symptoms, the price elasticities estimatedat less than unity.
In their study using original data from a survey they conducted, Ii and Ohkusa (1999)
examined the choice of health care in Japan for patients suﬀering from the common cold.
Empirical results show that the price elasticity for medical services is between 0.23 and0.36. This estimated price elasticity suggests that if the new medical insurance reform
plan were to increase the coinsurance rate for both the insured and their dependants by
10%, national medical costs may be reduced by, at most, 43 billion yen (358 million US
dollars). Correspondingly, this could increase the demand for OTC medicine by at most
8.8 billion yen (73.3 million US dollars). This result implies that medical services and OTC
medications are substitutable. Moreover, a tenfold increase in the provision of information
on drugs could reduce national medical costs by no more than 60 billion yen (500 million US
dollars) with a corresponding increase in the demand for OTC medications of approximately
6.9 billion yen (57.5 million US dollars).
This paper uses the same research method as that employed by Ii and Ohkusa (2000a)but extends in the following three directions. First, Ii and Ohkusa (2000a) analysed only
the patient’s final decision: either receiving medical services, purchasing OTC or receiving
no treatment. In reality, however, when faced with a cold, some patients would initiallyseek no treatment, later demand OTC, and eventually consult a doctor if they have notrecovered within a period of time. The three options are not mutually exclusive a priori.
This paper takes these dynamics into account1) .
The second point is that Ii and Ohkusa (2000a) only conducted an analysis on thecommon cold, while this paper intends to cover the entire range of minor ailments, interms of both collecting and analyzing the data. The third point is that this article has
better access to information on illnesses such as the treatment the patients received, their3

recovery progress, as well as the symptoms of their illnesses, such as a sore throat or
languidness. This research focuses particularly on the second and third points.2)
Section 2 describes the data. The empirical model is explained in Section 3. The empirical results are given in Section 4. Concluding remarks are then provided at the end of thepaper.

2

Data

The data for this research are obtained from a survey conducted in December, 1999 in the
Kanto area (Tokyo, Kanagawa, Saitama, and Chiba) and the Kansai area (Osaka, Kyoto,
Nara, and Hyogo). Of the total of 1300 questionnaires distributed to 1300 households, 1249
were completed and returned. All households that completed the questionnaire volunteered
to be monitored for the various surveys. Therefore, particular attention should be paid tothe sample bias caused by this type of sampling.
The questionnaire was composed of three parts: household, individual, and illness history.
The household and the illness history sections were completed by housewives, and theindividual section by each household member who are betweenn 20 and 69 years old.
There were some minors (those under 20 years old), the elderly, and other household
members who were not present at the time of the survey and were, therefore, not able tofill in the questionnaires. A total of 4282 respondents completed the household part of thequestionnaire while 2787 people filled in the individual section.
In the household section, the questionnaire asks about age, gender, history of chronic
illness (where applicable), household income, assets, and house ownership. The individual section includes questions related to employment status, labor income, and education level. In the illness history section, respondents were asked to describe their illnesses in detail, that is, date when the first symptom appeared, duration of the illness,
body temperature, symptoms, their ability to continue their daily activities during the ill-

4

ness, whether they were bedridden, the treatments they received, as well as their recovery
progress. Thirteen diﬀerent illnesses were under investigation: common cold, pollinosis,
abdominal pain/indigestion, headache/menorrhalgia, shoulder/neck pain, backache, constipation/diarrea, asthenopia, athlete’s foot/corn, various skin diseases(atopic dermatitis,
insect bites, miliaria, or urtication), injury (cuts, scratches or burns), bruise/sprain andhameorrhoids. The data also include information on nine symptoms: sore throat, cough,rhinitis/running nose, nausea, languidness, itchy eyes/watery eyes, pain/itching, bleeding/internal haemorrhage, and others.
In the following analysis, during the period of a patient’s illness, a day of illness is
considered one sample case. In the case where the patient’s temperature or symptoms
does/do not change, only variation of the time period describes change. In the tables,
length of illness refers to the number of days a patient suﬀers from an illness. Length of
discontinuity refers to the number of consecutive days a patient discontinues daily activities
such as work, study or household chores as a result of poor health. A patient’s bedridden
period is the number of days a patient is confined to bed due to the illness. When a patient
discontinues his or her daily activities or stays in bed for half a day, a value of 0.5 was
assigned.
Tables 1-13 show sample statistics. Among the 18,033 samples who suﬀered from acommon cold, 44% sought medical services from the hospitals, 32% purchased OTC medications, while 24% did not seek medical assistance. On average, patients suﬀered froma common cold for 4.64 days. The average period of time the patients discontinued their
daily activities or remained in bed as a result of their illnesses was half a day. Of thetotal, 65% of the patients were high school graduates, while 14% were college graduates.
The average coinsurance rate was 23%. Patients suﬀering from a common cold or abdominal pain/indigestion were more likely to seek medical services, and those suﬀeringfrom headaches/menorrhalgia, shoulder/neck pain, backache, athlete’s foot or injury weremore likely to demand OTC or take no action to cure their illnesses. This was true espe5

cially among those suﬀering from athlete’s foot or corns, 70% of whom demanded OTC.
The study found that patients suﬀering from pollinosis, shoulder/neck pain, or constipation/diarrea generally had relatively higher education levels compared to those suﬀeringfrom other illnesses. The number of people suﬀering from athlete’s foot, corns or hameorrhoids was higher in Kansai compared to that in the Kanto area. More than half of thepatients suﬀering from hameorrhoids or backache were employed at the time of the survey.
Can this result be interpreted that those working were more likely to suﬀer from backacheeven after the variables age or labor income were controlled? Were those suﬀering frombackache and those with employment more likely to seek medical services or demand OTC?
The answers to these questions will be discussed following the econometric analysis.

3

The Empirical Model

The dependent variable takes three values: Ti,t = 1 if a patient demands medical services,Ti,t = 2 if a patient demands OTC, and Ti,t = 0 in other cases. Independent variables are Xi
patient characteristics Yi,t information on illness and Zi,t variables on length. Individual
characteristics Xi are age, gender (=1 if female, = 0 if male), an education dummy, adummy variable taking the value of one if a person has a history of chronic illnesses, labor
income (in logarithms), per capita household income net of own labor income, household
net financial assets, a dummy variable taking the value of one if a person owns a house, adummy variable taking the value of one if a person owns an apartment, a dummy variabletaking the value of one if a person lives in the Kansai area, and the coinsurance rate.
These variables do not depend on period t. Information on illness Yi,t are temperature,nine symptoms, and a dummy variable taking the value of one if a person has a fever.
Variables on length of time Zi,t are: the number of days a patient suﬀers from an illness,
its squared value, the period of time a patient discontinues his/her daily activities due toillness, and length of a patient’s bedridden period.

6

We have the following empirical specification:j∗Ti,t= α0j + αX Xi + αYj Yi,t (+αjZ Zi,t ) + εji,t (j = 0, 1, 2)

Ti,t



 1

1∗
2∗
1∗
0∗
if Ti,t> Ti,tandTi,t> Ti,t1∗
2∗
2∗
0∗
2 if Ti,t< Ti,tandTi,t> Ti,t=
0 otherwise(1)

The error term, εji (j = 0, 1, 2) is a random variable and follows a three-dimensional normal
distribution. For estimation, the multinomial probit method with random eﬀect on theindividual is used (Keane, 1992). Because the probability of choosing j adds up to 1, we
can estimate the diﬀerences in probability. Here, we set j = 0, the choice of ‘do nothing’,
as the basis for comparison. The variance-covariance matrix should be:
"

4

1 ρ
ρ σ

#

(2)

Estimation Results

Tables 14-39 present the determinants of patients’ demand for medical services and OTC.
The second column shows the marginal eﬀects, and not estimated coeﬃcients. These eﬀects
explain how a unit change in an explanatory variable changes the probabilities of choosing
medical services or OTC.
The coinsurance rates are significantly negative for demand for medical services when
patients suﬀered from a common cold, shoulder/neck pain, backache, constipation/diarrea,
asthenopia, various skin diseases (atopic dermatitis, insect bites, miliaria, or urtication)and hameorrhoids. On the other hand, the coinsurance rates are significantly positive fordemand for OTC in the case of the common cold and various skin diseases. The common
cold and various skin diseases are two illnesses which are statistically significant in bothcases.

7

In the case of a common cold, marginal eﬀects for medical services and for the OTC
medication are -0.35 and 0.34 respectively. For shoulder/neck pain, the marginal eﬀect
for medical services is -0.26. For other illnesses, the marginal eﬀects for medical services
range from -0.87 to -3.69 while the values of that for OTC are approximately 1.5, which
are rather large. This implies that in the case of a cold, a 10% increase in the coinsurance
rate (for example, rising from 20% to 30%) reduces the medical demand by 3.5 percentage
points and increases the OTC demand by 3.4 percentage points. For shoulder/neck pain,
a 10% increase in the coinsurance rate reduces the medical demand by 2.6 percentage
points. For other illnesses, the same percentage increase in the coinsurance rate reduces
the medical demand from 8.7 to 3.7 percentage points while increasing the OTC demandby 15 percentage points.
With some exceptions, the young demanded medical services more and OTC less than
did the elderly. People living in Kansai were more likely to have a higher demand for
OTC than for medical services. Those employed were also more likely to demand OTC
than medical services. While the duration of illnesses was brief, patients demanded more
OTC. However, patients were more likely to consult a doctor if they did not recover fromtheir illnesses within a period of time. For many illnesses, education level did not playa significant role in the level of demand for either medical services or OTC. However, inthe case of asthenopia, skin disease, and haemorrhage, high school and college graduates
had a higher demand for medical services than those still in school. On the other hand,for athlete’s foot/corns, demand for medical services was higher among those in school
compared to graduates.

5

Concluding Remarks

This paper examines the choice of health care for minor ailments in Japan for patientssuﬀering from 13 diﬀerent minor ailments. Original data were obtained from a survey

8conducted by the authors. For the common cold, shoulder/neck pain, backache, constipation/diarrea, asthenopia, various skin diseases, and hameorrhoids, an increase in thecoinsurance rate statistically significantly lowers the demand for medical services. On theother hand, the demand for OTC medication is statistically significantly higher with anincrease in the coinsurance rate for the common cold and skin diseases. In the case of thecommon cold, the marginal eﬀects for medical services and for the OTC medication are-0.35 and 0.34 respectively. For shoulder/neck pain, the marginal eﬀect for medical services
is -0.26. For other illnesses, the marginal eﬀects for medical services range from -0.87 to-3.69 while the values for OTC are around 1.5.
For future research, the dynamics of patients’ choice should be analysed more thoroughly
as the medical options are usually not mutually exclusive. Some illnesses that are prone tooccur during summer time are omitted in this analysis because our survey was conducted in
winter and spring, that is, from the beginning of November until the end of April. Future
research should include these illnesses. Moreover, taking into an account the OTC priceand its accessibility, and the choice among medical institutions such as clinics and hospitals,
this would be interesting to future researchers.

9Footnote*) This study is a part of the research project financed by the Japanese Ministry of Education (1999/2000 Scientific Research Grant). We are grateful to the comments ofthe participants at an associated meeting, particularly Prof.Yoshihiko Seoka (Kanto
Gakuin University), and Prof.Hajime Nakamura and Prof. Keunsik Park (Faculty of
Medicine, Osaka City University). This paper was presented at a meeting on clinicaleconomics. We would also like to acknowledge the comments by Prof.Naoki Ikegami
and Prof.Shunya Ikeda of Medical School of Keio University, and the assistance provided by Mr.Kunio Tsuyuhara.
1) Similar research was done by Gilleskie (1998). Her estimation model is detailed, but
information on illnesses and symptoms were not utilized as in our study.
2) Another paper by Ii and Ohkusa (2000b) focuses more on the first point.

10References[1] Blenkinsopps, A. and C. Bradley (1996), ”Patients, Society, and the Increase in Self
Medication,” British Medical Journal, 312(7031), pp.629-32.
[2] Fillenbaum et. al. (1993), ”Prescription and Nonprescription Drug Use among Blackand White Community Residing Elderly,”American Journal of Public Health, 83,
pp.1577-82.
[3] Gilleskie, D.B. (1998),”A Dynamic Stochastic Model of Medical Care Use and Work
Absence,”Econometrica, 66(1), pp.1-45.
[4] Greenlick, M. and B. Darsky (1968), ”A Comparison of General Drug Utilization in a
Metropolitan Community with Utilization under a Drug Prepayment Plan,” American
Journal of Public Health, 58(11), pp.2121-36.
[5] Johnson, L. (1991), ”The demand for OTC medicines: some Australian evidence,’
Asia-Pacific Journal of Public Health, 5(3), pp.228-35.
[6] Keans, M. (1992), ”A Note on Identification in the Multinomial Probit Model,” Journal of Business and Economic Statistics, 10, pp.193-200.
[7] Leibowitz, A., W. Manning and J. Newhouse (1985), ”The Demand for Prescription
Drugs as a Function of Cost-Sharing,”Social Sciences and Medicine, 21(19), pp.10631069.
[8] Leibowitz, A. (1989), ”Substitution Between Prescribed and Over-the- Counter Medication,”Medical Care, 27, pp.85-94.
[9] McNamee,D.(1994), ”Over-the-counter drugs,”Lancet, 343(4),p.1629.
[10] Newhouse,J(1993),Free For All, Harvard University Press.

11[11] Stuart,B and James,G.(1995), ”Are Prescribed and Over-the-Counter Medicines Economic Substitutes? A Study of the Eﬀect of Health Insurance on Medicine Choicesby the Elderly,”Medical Care, 33, pp.487-501.
[12] Ii, M and Y. Ohkusa (1998), ”Is There Any Substitution Between Medical Services andOver-the-Counter Medications?,” Presented at 1998 Japanese Economic Association,
Ritsumeikan University.
[13] Ii, M and Y. Ohkusa (1999), ”Interchangeability between Medical Services and Overthe-Counter Medication in the Case of Common Cold: Analysis based on an Original
Survey,” (in Japanese) Journal of Health Care and Society, 9(3), pp.69-81.
[14] Ii, M. and Y. Ohkusa (2000a), ”Price Sensitivity of the Demand for Medical Services for Minor Ailments: Econometric Estimates Using Information on Illness andSymptoms,’Japanese Economic Review, forthcoming.
[15] Ii, M and Y. Ohkusa (2000b), ”Dynamic Analysis on Demand for OTC and Medical
Services”, manuscript.
[16] Yamada, T. (1997), ”On the Demand for Medical Service ,”(in Japanese) Journal of
Health Care and Society, 7, pp.99-112.

12

Table1 : Descriptive statistics(Common Cold)
Mean
Medical Service
OTC Medication
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabour income
Coinsurance rate

Standard
deviation.4962063.4667249.4276734
6.60715
1.348751
1.182849.4770181.3499215.4941197.4849196.4700275
2.708611.1064806.4384279.3206169.2409552
4.635856.5711021.5540884.6498823.1428434
1.576534.378081.3294576
1.850485.2297321

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
83
18
12
1
1
1
1
1
7.467942.3

Note: Sample size is 18,033. Education level is relative to those still in school. For insurance
plans, weights are used to adjust a sample distribution to the population distribution. A
day of illness is considered one sample case. For variation of the time (length of illness,length of discontinuity, and patient’s bed ridden period), a period an individual suﬀers
from illness is considered to be one sample.

13

Table2 : Descriptive statistics(Pollinosis)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4775698.4698613.4661862
24.03984.1764092.5935703.499425.3964695.4845141.4649622.4998482
2.836777.0675639.3518444.3289659.3191897
25.08652.0251509.0633803.524491.1953235
1.623571.3160653.4866962
2.652554.263473

Note:Sample size is 8,454.

14

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
89
2
10
1
1
1
1
1
7.467942.3

Table3 : Descriptive statistics (Abdominal pain/indigestion)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4999392.4736056.3548711
12.02703.578988.7674958.4987637.3598436.4760442.4771968.5001004
2.907617.0840217.5129073.3393991.1476936
5.501873.2059925.2509363.536606.1527719
1.653226.350402.5023275
2.846214.2520211

Note:Sample size is 2,253.

15

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
76
4
9.5
1
1
1
1
1
7.467942.3

Table4 : Descriptive statistics (Headache/menorrhalgia)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.3476307.5000974.4833408
3.438218
1.204789.9776256.4957871.3900743.2219031.4796766.4986665
2.496772.0506885.1404651.4883721.3711628
2.276498.2626728.3364055.4334884.1869767
1.948113.3581395.4604651
2.232641.2803015

Note:Sample size is 973.

16

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
30
15
7.5
1
1
1
1
1
6.746412.3

Table5 : Descriptive statistics (Shoulder/neck pain)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.2498033.4917611.4994869
22.48618.3015326.7171513.4898255.4147328.4368158.4866062.4996155
2.778652.0542556.0668579.4093116.5238305
13.29605.0559211.1134868.3993822.2206531
1.74338.3848191.479038
2.541758.2710278

Note:Sample size is 3,975.

17

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
90
3
10.5
1
1
1
1
1
7.467942.3

Table6 : Descriptive statistics (Backache)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.3957111.4858598.4943063
18.9608
1.508759.6776771.4995646.395427.4898069.4600996.4999823
2.992871.1008749.194271.3815645.4241645
10.23684.2587719.1688596.4770474.1939038
1.600884.3040764.5104664
2.972718.2285769

Note:Sample size is 2,380.

18

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
88
20
7
1
1
1
1
1
7.467942.3

Table7 : Descriptive statistics (Constipation/diarrhea)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4876508.4842471.4249967
13.12316.7240769.5676743.4971125.4068017.4853862.4718982.4691238
2.659321.1027542.3888112.3748252.2363636
4.596774.2520161.2096774.4447552.2090909
1.62069.3342657.3265734
1.807746.234442

Note:Sample size is 1,319.

19

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
87
7
4.5
1
1
1
1
1
7.467942.3

Table8 : Descriptive statistics (Asthenopia)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4916528.4161771.4826645
19.18354.4762709.8328345.4868158.3264243.4767204.4256336.5001219
2.850827.0467254.4082969.2227074.3689956
11.40179.0535714.1339286.6146288.121179
1.651201.2374454.5038212.771804.2793613

Note:Sample size is 1,583.

20

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
87
5
7
1
1
1
1
1
7.131699.3

Table9 : Descriptive statistics (Athletes’ foot/corn)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.3346402.4646591.3897059
32.50642.0585206
0.4998555.3736426.500006.5000853.5001461
2.892256.0867652.1283997.6850095.1865908
28.73973.0068493
0.5173941.1676154
1.487666.5085389.4965212
2.766092.2407381

Note:Sample size is 1,949.

21

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
92
.5
0
1
1
1
1
1
7.313887.3

Table10 : Descriptive statistics (Various skin diseases(atopic
dermatitis, insect bites, miliaria, or urticaria))
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4826568.4648682.4646282
23.19915.7152545.3515699.4789457.3509466.5000577.4959947.4305188
2.548173.1016649.3691843.31571.3151057
14.7243.1238318.0560748.6438066.1438066
1.50423.4362538.2456193
1.42729.2359

Note:Sample size is 2,893.

22

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
89
7
3.5
1
1
1
1
1
7.467942.3

Table11 : Descriptive statistics (Injury (cut, scratch or burn))
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.3578777.4982375.4606568
3.039187.5314689.1794729.4769352.3600937.4951415.4901465.4769352
2.652107.1036084.1506849.54414.305175
2.951456.0946602.026699.6506849.152968
1.570878.4003044.3493151
1.884918.2383446

Note:Sample size is 1,095.

23

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
22
6
2
1
1
1
1
1
7.313887.3

Table12 : Descriptive statistics (Bruise/sprain)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4263072.4981472.4609302
12.662211.786773
1.256641.4997415.3869768.4693096.4595866.485171
2.596821.0670628.2385466.4555029.3059505
7.4532967.1950549.5197472.1832543
1.672813.3027909.3786203
1.955575.2633607

Note:Sample size is 1,555.

24

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
79
16
16
1
1
1
1
1
6.746412.3

Table13 : Descriptive statistics (Hemorrhoid)
Mean
Medical Service
OTC Medicaton
Do nothing
Length of illness
Length of discontinuity
Patient’s bed ridden periodHigh sch. grad.
Univ. grad.
FemaleKansai Area
WorkerLabor income
Coinsurance rate

Standard
deviation.4659538.5002423.3889211
16.23975
1.255999
1.268992.4986303.3156879.4606252.5002527.4977011
2.884409.1035098.3180428.4964322.185525
8.175258.3298969.3195876.459735.1121305
1.695058.5015291.5504587
3.08741.2043968

Note:Sample size is 795.

25

Min

Max

0
0
0
1
0
0
0
0
0
0
0
0
0

1
1
1
86
11
11
1
1
1
1
1
7.131699.3

Table14 : Marginal eﬀect for medical services (Common cold)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabour income
Length of discontinuity
Patient’s bedridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0190068.0002153.0248456.0732418.0764142-.0467658-.053413.0054246.0314145-.0071371.007614-.0001331-.3578729

-5.75
4.61
0.78
0.73
0.69
-1.78
-0.37
0.20
3.39
-0.81
2.63
-2.63
-2.22

26

Prob.
value
0.000
0.000
0.435
0.465
0.488
0.076
0.712
0.845
0.001
0.420
0.009
0.009
0.027

Table15 : Marginal eﬀect for OTC medication (Common cold)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabour income
Length of discontinuity
Patient’s bedridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.017197-.0002103-.0451196-.0743143-.0781449.0485596.2495458-.04204-.0268871.0031314-.0070789.0001457.3403793

5.51
-4.81
-1.36
-0.88
-0.91
1.96
1.91
-1.75
-2.76
0.44
-2.53
3.31
1.89

Prob.
value
0.000
0.000
0.175
0.381
0.365
0.051
0.057
0.080
0.006
0.660
0.011
0.001
0.059

Note: Log likelihood is -20831. A correlation coeﬃcient between the diﬀerence of the
disturbance terms for medical services and OTC, and the diﬀerence of the disturbanceterms for OTC and do nothing is -0.4465778. Its probability value is 0.000.

27

Table16 : Marginal eﬀect for medical secvices (Pollinosis)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0217162.0002491-.0831281-.1196931-.0194976-.0856596.1342944-.0277885.1975711-.3465963.0000821-8.64e-06.461461

-2.54
2.17
-0.93
-0.51
-0.08
-1.27
0.52
-0.54
3.34
-2.92
0.04
-0.29
0.73

28

Prob.
value
0.011
0.030
0.350
0.607
0.932
0.205
0.600
0.592
0.001
0.003
0.970
0.771
0.468

Table17 : Marginal eﬀect for OTC medication (Pollinosis)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0042849.0000528.1252463.3243953.1382388.0611221-.1578635.0404836-.1232465.2604591-.0006049.0000123-.7624772

-0.54
0.50
1.53
1.91
0.72
1.06
-0.73
0.97
-3.23
3.62
-0.27
0.42
-1.60

Prob.
value
0.592
0.619
0.126
0.056
0.470
0.291
0.466
0.334
0.001
0.000
0.788
0.676
0.109

Note: Log likelihodd is -296766. A correlation coeﬃcient between the diﬀerence of the
disturbance terms for medical services and OTC, and the diﬀerence of the disturbanceterms for OTC and do nothing is -0.4676118. Its probability value is 0.000.

29

Table18 : Marginal eﬀect for medical services (Abdominal
pain/indigestion)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0379059.0005251.1252175-.0058971-.0978897.2587631-.1411687.0268732.1003026-.0265878.0244221-.0003043.0792102

-3.31
3.38
0.95
-0.02
-0.32
2.75
-0.36
0.37
1.48
-1.04
4.66
-5.08
0.10

30

Prob.
value
0.001
0.001
0.341
0.985
0.753
0.006
0.722
0.710
0.140
0.300
0.000
0.000
0.921

Table19 : Marginal eﬀect for OTC medication (Abdominal
pain/indigestion)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0400448-.0005077-.3216069.0605047.0365491-.0748168.5586636-.1261616-.0361844-.0590296-.0161238.0001973-.3632696

3.74
-3.64
-2.81
0.25
0.14
-1.17
2.27
-2.44
-0.65
-1.11
-4.63
4.95
-0.63

Prob.
value
0.000
0.000
0.005
0.806
0.887
0.242
0.023
0.015
0.516
0.265
0.000
0.000
0.531

Note:Log likelihodd is -1429. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.3614994. Its probability value is 0.000.

31

Table20 : Marginal eﬀect for medical services(Headache/menorrhalgia)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0087293.0001192-.0060813.0073742.0036701.0569773-.1901717.0202852.0074461-.0145837-.0004446.0000288.4995299

-3.82
3.82
-0.28
0.11
0.05
2.95
-1.68
1.99
1.61
-1.65
-0.29
0.58
1.53

32

Prob.
value
0.000
0.000
0.783
0.913
0.960
0.003
0.094
0.047
0.108
0.099
0.770
0.562
0.106

Table21 : Marginal eﬀect for OTC medication(Headache/menorrhalgia)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0005913.0000341.3729852-.9525601-.6909075-.1773043.7455934-.1730022-.0524014.1699684-.1246088.0039213-.2476926

-0.03
0.12
1.52
-2.83
-2.14
-1.79
2.23
-2.15
-1.49
2.83
-5.15
4.08
-0.24

Prob.
value
0.979
0.908
0.129
0.005
0.032
0.073
0.026
0.032
0.135
0.005
0.000
0.000
0.811

Note:Log likelihodd is -366. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -.4927063. Its probability value is 0.000.

33

Table22 : Marginal eﬀect for medical services (Shoulder/neck pain)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0014839-.0000211.0105781.9744353.9795201-.0219652.044843-.0055971.0128259-.0040868-.0002704
8.60e-08-.2612172

0.71
-0.94
0.96
12.35
10.11
-3.32
1.22
-0.93
0.78
-1.25
-0.83
0.02
-2.05

34

Prob.
value
0.475
0.350
0.339
0.000
0.000
0.001
0.222
0.355
0.437
0.212
0.409
0.981
0.040

Table23 : Marginal eﬀect for OTC medication (Shoulder/neck pain)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0030846.0000556.2463723.5337669.552625.274819.7041422-.1559615-.153621.0363429-.0005379-5.00e-06-2.973727

0.13
0.21
1.82
1.27
1.34
2.98
1.87
-1.79
-0.97
1.11
-0.15
-0.12
-1.27

Prob.
value
0.895
0.837
0.069
0.204
0.180
0.003
0.062
0.074
0.331
0.267
0.880
0.901
0.123

Note:Log likelihodd is -1160. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.2493771. Its probability value is 0.000.

35

Table24 : Marginal eﬀect for medical services (Backache)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0256784.0002527.0758801.2300355.5118543-.0859991.3169298-.0775366-.019307-.012238.0077638-.0000807-.8732081

-2.13
1.92
0.87
1.10
1.50
-1.25
1.18
-1.57
-1.62
-0.55
3.08
-2.36
-1.64

36

Prob.
value
0.033
0.054
0.386
0.271
0.135
0.212
0.239
0.117
0.105
0.582
0.002
0.018
0.098

Table25 : Marginal eﬀect for OTC medication (Backache)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0002556-2.71e-06-.0009574-.011382-.0016009.0008393-.0010171.0000886-.0001122-.0000667-.0000102
1.52e-07.0020851

2.11
-2.00
-1.31
-1.80
-1.43
1.05
-0.37
0.21
-0.89
-0.57
-0.42
0.49
0.43

Prob.
value
0.035
0.045
0.192
0.072
0.154
0.294
0.713
0.837
0.374
0.566
0.677
0.622
0.666

Note:Log likelihodd is -1488. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.1522507. Its probability value is 0.000.

37

Table26 : Marginal eﬀect for medical services (Constipation/diarrhea)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0297777.0004167-.2166871.2224986.3575566-.2022586-.3619617.0412234.2125956.1517018.0123883-.0001376-1.807227

-2.43
2.25
-1.59
0.68
1.09
-1.66
-0.72
0.40
2.83
1.65
2.65
-2.93
-2.64

38

Prob.
value
0.015
0.024
0.113
0.495
0.277
0.098
0.471
0.693
0.005
0.098
0.008
0.003
0.008

Table27 : Marginal eﬀect for OTC medication (Constipation/diarrhea)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0030526.0000181.2077292.6463835.7166471.2442321-.424015.1166378-.2536099.1556212.0039275
3.38e-06.3845725

0.30
0.13
2.04
2.18
2.07
3.03
-1.37
1.60
-1.96
1.18
1.04
0.10
0.82

Prob.
value
0.766
0.900
0.041
0.029
0.039
0.002
0.170
0.109
0.050
0.236
0.300
0.922
0.412

Note:Log likelihodd is -894. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.3598876. Its probability value is 0.000.

39

Table28 : Marginal eﬀect for medical services (Asthenopia)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0567773.0007863.1376578.6147256.5788484-.3800073.9965247-.4812977.1751689.0021729-.000032-3.697796

-1.87
2.02
0.65
2.31
1.84
-1.93
3.66
-4.06
1.21
0.53
-0.71
-2.54

40

Prob.
value
0.061
0.043
0.513
0.021
0.065
0.053
0.000
0.000
0.227
0.599
0.477
0.011

Table29 : Marginal eﬀect for OTC medication (Asthenopia)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0328533-.0003826-.2578228-.4738471-.1672668.0160782-.9188349.1589838.8782329-.0367425-.0020196.0000143.6992843

3.43
-3.22
-2.49
-2.68
-2.77
0.22
-2.66
2.38
3.24
-1.00
-0.74
0.46
0.96

Prob.
value
0.001
0.001
0.013
0.007
0.006
0.824
0.008
0.017
0.001
0.319
0.461
0.647
0.337

Note:Log likelihodd is -821. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.2623444. Its probability value is 0.0000.

41

Table30 : Marginal eﬀect for medical services (Athletes’ foot/corn)
Age
Age squared
FemaleHigh sch. grad.
Kansai Area
WorkerLabor income
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0083934-.0001239-.0020502-.9525492.0361695.4792995-.0364885-.0011745.0000121.3290009

2.45
-2.35
-0.11
-2.27
1.03
1.09
-2.15
-2.38
2.78
1.20

42

Prob.
value
0.014
0.019
0.915
0.023
0.301
0.277
0.031
0.017
0.005
0.227

Table31 : Marginal eﬀect for OTC medication (Athletes’ foot/corn)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0203553.0004324-.1745325.8888703.3435814-.2422668-.8986.1640201.0013252-.0000144-1.123085

-1.45
2.10
-1.21
3.49
3.64
-2.57
-2.36
2.30
0.47
-0.57
-1.58

Prob.
value
0.148
0.036
0.225
0.000
0.000
0.010
0.018
0.022
0.641
0.572
0.114

Note: Log likelihodd is -291. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.2960467. Its probability value is 0.000.

43

Table32 : Marginal eﬀect for medical services (Various skindiseases(atopic dermatitis, insect bites, miliaria, or urticaria)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.036201.0006611-.2045767.8096419.8973977-.0820115-.257197.1271258.0800188-.0527944-.0110596.000116-.9167819

-3.23
4.18
-2.37
4.29
4.14
-1.04
-0.51
1.17
0.97
-0.36
-3.01
2.64
-2.35

44

Prob.
value
0.001
0.000
0.018
0.000
0.000
0.300
0.608
0.241
0.333
0.722
0.003
0.008
0.019

Table33 : Marginal eﬀect for OTC medication (Various skindiseases(atopic dermatitis, insect bites, miliaria, or urticaria)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.018164-.0002656.0638806-.8485309-.3922729.0444187-.062161-.0370979.1183589-.1182407.0061915-.0000643
1.623608

1.88
-2.00
0.89
-2.97
-2.86
0.42
-0.14
-0.41
1.69
-0.80
2.18
-2.00
3.34

Prob.
value
0.060
0.046
0.372
0.003
0.004
0.675
0.891
0.682
0.092
0.423
0.029
0.045
0.001

Note:Log likelihodd is -2274. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.2960467. Its probability value is 0.000.

45

Table34 : Marginal eﬀect for medical services (Injury(cut, scratch orburn))
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.011535.0001852-.0409943.0602717.116934.0318216-.1509132.0387758.0139092.0546375-.0118258.0005734.0659511

-3.02
3.47
-1.40
0.78
0.78
1.20
-1.31
1.58
1.17
0.89
-2.81
3.30
0.39

46

Prob.
value
0.003
0.001
0.162
0.433
0.435
0.229
0.191
0.114
0.243
0.372
0.005
0.001
0.696

Table35 : Marginal eﬀect for OTC medication (Injury(cut, scratch orburn))
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0089839-.0001596.0345442.1517395.247799-.0640607-.8134573.1905276-.0132369-.0573224-.0182548.0002182-.0494607

0.71
-0.90
0.30
0.45
0.73
-0.61
-1.99
1.89
-0.41
-0.37
-1.29
0.40
-0.07

Prob.
value
0.477
0.368
0.764
0.652
0.464
0.541
0.047
0.059
0.681
0.709
0.197
0.693
0.945

Note:Log likelihodd is -914. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.2960467. Its probability value is 0.000.

47

Table36 : Marginal eﬀect for medical services (Bruise/sprain)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.005851.0000698-.0750209-.3634502-.1811872.0418156.0019355.0232369.0123036.029024.0131927-.0002441.3450865

-0.88
0.81
-1.54
-1.92
-1.56
0.79
0.01
0.61
1.75
1.11
3.97
-5.18
0.97

48

Prob.
value
0.377
0.418
0.124
0.054
0.120
0.428
0.992
0.545
0.080
0.269
0.000
0.000
0.333

Table37 : Marginal eﬀect for OTC medication (Bruise/sprain)
Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
WorkerLabor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0287334.0004025.1969428.2635165.3595715-.097164.4758668-.0974992-.1061113.0478824-.0129608.0001842
1.541766

-1.48
1.51
1.24
0.46
0.59
-0.76
0.92
-0.89
-2.07
0.51
-2.08
2.23
1.22

Prob.
value
0.140
0.131
0.215
0.649
0.554
0.445
0.357
0.375
0.038
0.609
0.038
0.026
0.222

Note:Log likelihodd is -1121. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.5372352. Its probability value is 0.000.

49

Table38 : Marinal eﬀect for medical services (Hemorrhoid)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
Labor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value-.0208538.0002486-.6133911.9999974.9980987.1768965-.6632161.3184902-.1635912.0183334-.000209-3.562828

-1.66
1.43
-3.31
4.02
4.36
1.36
-4.56
4.06
-1.95
4.53
-4.24
-3.70

50

Prob.
value
0.097
0.152
0.001
0.000
0.000
0.173
0.000
0.000
0.051
0.000
0.000
0.000

Table39 : Marinal eﬀect for OTC medication (Hemorrhoid)Age
Age squared
FemaleHigh sch. grad.
Univ. grad.
Kansai Area
Labor income
Length of discontinuity
Patient’s bed ridden period
Length of illness
Length of illness squared
Coinsurance rate

Marginal eﬀect

t-value.0412808-.0004858
1.356532-.9999997-.831394.1487035.7246168-1.678381
1.253143-.0173603.0001141
1.442343

1.72
-1.84
4.94
-3.95
-4.17
1.33
5.10
-3.62
3.26
-3.99
3.21
1.19

Prob.
value
0.085
0.065
0.000
0.000
0.000
0.183
0.000
0.000
0.001
0.000
0.001
0.233

Note:Log likelihodd is -247. A correlation coeﬃcient between the diﬀerence of the disturbance terms for medical services and OTC, and the diﬀerence of the disturbance terms for
OTC and do nothing is -0.3042642. Its probability value is 0.000.

51