Yokohama National University
Faculty of Business Administration
Working Paper

Political Interventions and Bias in Stem Cell Research

Naoko KISHI*

Abstract
The direction of scientific research could depend on political interventions. To clarify
how they affect science is significant to design science policy appropriately. This study
investigates how political prohibition on human embryonic stem cells affects scientificresearch. The analysis focuses on polices of countries where affiliated organizations offirst authors are located and examines whether they affect scientists’ stem cell choices tostudy cardiac repair and regeneration. The data is constructed from published articles thatare collected using PubMed search. The results demonstrate that countries’ prohibitive
policies partly decreased the number of articles that used embryonic stem cells. The
conclusion is that prohibitive decisions bias the composition of stem cells chosen for
cardiac research.

Keywords: Political interventions; Stem cells; Cardiac regeneration

1. Introduction
The direction of scientific research could depend on political interventions.
Targeted public funding based on science policy provides scientists with incentives tofollow political intention. Although public funding for academic research has gained apositive evaluation from previous research, the effects of politically directed research on*

Professor
Graduate School of International Social Sciences
Yokohama National University
79-4 Tokiwadai Hodogaya-ku Yokohama, Kanagawa, JAPAN, 2408501
kishi-naoko-kn@ynu.ac.jp
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Working Paper

subsequent science have room to be discussed. The contributions of public funding toscience have been explained by market failure rationales and promotion of leading
research (Arrow, 1962; Dasgupta and David, 1994; Edler and Fagerberg, 2017; Packalen
and Bhattacharya, 2020; Nelson, 1959). It financially supports research that isunderinvested by the private sector. Besides, scientists are likely to stick to the previous
research for stable performance and to avoid choosing emerging subjects that are
uncertain to achieve the same level of prior performance (Foster, Rzhetsky, and Evans,2015). Targeted public funding is an effective incentive for scientists to try emerging
research subjects. Meanwhile, how targeted fund allocation affects composition ofscientific knowledge, or whether that biases scientific knowledge, remains unclear.
Scientists would have incentives to choose politically targeted research subjects to gain
public grants and be unlikely to choose subjects that are excluded from the target and are
restricted politically. If the political target for specific technologies’ research causes astrong bias in scientists’ choices, accumulated knowledge would converge on the subject
that is in line with the intention of policy. However, there is uncertainty as to whether
targeting in policy would provide the best path for scientific advance. Thus, the effects ofpolitically driven knowledge accumulation on the evolution of science need to be clarified
for designing science policy appropriately (Fortunato et al., 2018).
To investigate the effects of targeting in policy on the choices of research subjects,
this study focuses on a relationship between prohibitive policy for human embryonic stem
cell (hESC) and scientists’ choices of stem cells to study cardiac repair and regeneration.
Stem cell research has been a significant target of science policy that promotes leading
research. The foci of policies include prohibition and restriction on the use anddevelopment of hESC and promotion of research about other stem cells including induced
pluripotent stem cell (iPSC). Prohibition means that research using human embryo is
prohibited, and restriction means that the development period of hESC for research islimited to 7 or 14 days (Matthews and Morali, 2020). The reason of prohibition andrestriction is that hESC has an ethical issue because it is generated using human blastocyst.
Some countries adopt policy that prohibits the use and derivation of hESC, and others’
policy restricts its development period. Research using embryonic stem cell (ESC) that is
generated from non-human embryo is not the target of prohibition and restriction.
Meanwhile, human induced pluripotent stem cell (hiPSC) is generated by introducing
several factors into somatic cells and could solve hESC’s ethical issues.
Both ESC and iPSC are pluripotent stem cells (PSC) that could be differentiatedto any body cells. They have the potential for prolonging healthy life expectancy andreducing social security costs because cellular therapeutics using them would be able to2

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Working Paper

regenerate damaged and lost adult cells that are the causes of incurable injuries anddiseases by existing therapeutics. Meanwhile, there are uncertainties about their clinicalapplications in the future. While hESC has an ethical issue, hiPSC-derived cells have asafety concern because they risk tumor formation. Therefore, it is difficult to predict
which stem cells have the most potential in the future. Under these uncertain
circumstances, prohibition on hESC for research would become a factor that affects
scientists’ stem cell choices. Thus, this study examines their causal relationship.
The analysis focuses on how prohibitive policy for hESC affected scientists’choices of stem cells to study cardiac repair and regeneration. Clarifying the effects ofpolicy on scientific research is crucial to design science policy that promotes leading
research. The hypothesis of this study is that prohibitive policy for hESC increases thelikelihood that scientists choose other PSC that include iPSC and noncardiac stem cells
that include mesenchymal stem cell (MSC) and bone marrow cell (BMC). The reason to
focus on cardiac research is that cardiac disease is one of the main targets of stem cellresearch. For example, Deinsberger, Reisinger, and Weber (2020) demonstrated that
14.5% of clinical trials that used PSC were concerned with cardiovascular diseases.
Therapies by PSC require a close relationship with basic research because they dependon leading knowledge (Duran, 2018). Thus, political interventions on hESC would havecrucial impacts on stem cell choices for cardiac research and its clinical application.
Biased scientists’ choices caused by targeting policy are assumed to create a researchcluster of specific stem cells, and which stem cell cluster to be formed would depend on
differences in policy on hESC and other research environments. Conclusions indicate thatscientists’ stem cell choices depend partly on prohibitive policy for hESC and that thecomposition of stem cells for cardiac research is peculiar to the respective country. Then,suggestions to correct the different composition of stem cells are to activate international
research collaborations for knowledge exchange (Furman, Murray, and Stern, 2012).
The remainder of this study is structured as follows. The following section
reviews literature about targeting in policy to clarify the position of this study in a streamof policy research. Subsequently, the hypothesis, methodology, and data are explained,
and the results are presented. The final section concludes that the targeted policy could
cause a bias in stem cell choices for research and suggests the significance of international
collaboration to correct the knowledge bias.
2. Literature about Targeting in Policy
In the literature review, this study categorizes previous research about targetingin policy into three groups: targeting industry for economic growth, targeting specific3

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Working Paper

technologies and systems to resolve social/global issues, and preparing environments
before targeting. The first and second groups are categorization based on a developmentof targeting policy. Schot and Steinmueller (2018) described that innovation policy had
developed as business environments changed and demonstrated the three phases of policy
development. The first phase of policy was developed to complement market failure withthe aim of economic growth. The second phase of policy aimed to strengthen international
competitiveness in the face of economic recession caused by the oil crisis in the 1970s.
The third phase of policy had objectives to solve social/global issues such as climatechange and poverty. Policies in the first and second phases targeted specific industries toachieve economic growth and global competitiveness. Policies in the third phases targeted
specific technologies and systems for resolution to social/global issues. Meanwhile, thethird group is based on literature about the horizontal technology policies (HTPs) thatemphasized the preparation of environments for adequate policy design.
Among these three groups, firstly regarding policy that targeted industry,
previous research found out that targeting policies had contributed to economic growthby allocating resources to specific industries like the steel and automobile industries.
Policies targeting an industry for its growth include the provision of business
opportunities through public procurement, to finance publicly research projects in theprivate sector, subsidies such as tax credit, and protections from foreign competition
through tariff and non-tariff measures (Aschhoff and Sofka, 2009; Noland, 1993;
Saxonhouse, 1983). For example, public procurement of new technologies for the public
service is regarded as a tool of innovation policy (Aschhoff and Sofka, 2009).
Additionally, the enhancement of international competitiveness became the reason totarget industry in globalization of economic activities. For example, Edquist and ZabalaIturriagagoitia (2012) analyzed six cases about public procurement in Sweden, Norway,
and the United States (the USA) and found that public support targeted for specificindustry had been effective in strengthening vulnerable technical capabilities andenabling the industry to survive in international competition. Besides, targeting policy inJapan contributed to accumulating and allocating capital and labor to strengthenindustry’s international competitiveness (Noland, 1993; Saxonhouse, 1983).
Meanwhile, political interventions also have negative impacts on industry.
Brahm (1995) found that rivalry competition was intensified by overinvestment due toincumbents’ responses to politically subsidized organizations’ investment in hightechnology industries in the USA. Furthermore, Beason and Weinstein (1996)
demonstrated that targeted policies in 1955–90’s Japan decreased the factor productivities
of industries. They explained that the reason was inappropriately targeting. The targeted4

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industries included low growth sectors like mining. Once the economy has grown to someextent, traditional policies targeting industries could be inefficient because of the
difficulty involved in target selection.
The second group of literature focuses on policy that targeted specifictechnologies and systems to resolve social/global issues. In recent years, studies about
policies that target technologies that promote innovation make a research cluster around
resolution to social/global issues (Schot and Steinmueller, 2018; Weber and Rohracher,2012). Politically targeting specific technologies could increase the number of relevant
research and innovation. Hottenrott and Lopes-Bento (2014) found that policy thattargeted international collaboration and research and development (R&D) at small andmedium-sized enterprises had increased R&D spending and high impacts on increasing
sales from products that were new to market. Examples of target for specific technologies
include the latest technologies of life science to provide a cure for specific diseases.
Sampat (2012) examined how to make a balance between science and health targets at
the National Institutes of Health (NIH). The peer-review system for fund allocation at the
NIH was difficult to concentrate funds on specific technologies. Thus, contractual funding
and research centers for definite purposes like cancer treatment were effective to target
research for specific diseases. As for policies that target systems to find solutions tosocial/global issues, Uyarra, Zabala-Iturriagagoitia, Flanagan, and Magro (2020)
described that public procurement of health innovation platform contributed to setting
institutions that solved social issues brought by reginal aging populations in Galicia.
Regarding the political targeting of social/global issues, Sandén and Azarb (2005)
suggested the significance of setting both short and long-term targets such as carbon
reduction in the manufacturing industry and public support for technological innovationthat enabled to generate eco-friendly products.
The third group is literature that focuses on the preparation of the environment
prior to targeting. Breznitz (2007) and Avnimelech and Teubal (2008) investigated theadequate business environment for targeting policy by analyzing the causes of thesuccessful high-technology industry in Israel. They explored the effectiveness of HTPs
that aimed to promote socially desirable technological activities without targeting specificindustries and technological areas (Teubal, 1997). In Teubal (1997), socially desirable
technological activities mean to conduct innovation-related activities and to build
advanced technological infrastructure in economically developed countries’ context.
Policymakers could develop targeting policy with sufficient preparation by HTPs
(Avnimelech and Teubal, 2008). As examples of adequate environments, Breznitz (2007)
described that the keys to the success of the information technology (IT) industry in Israel
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were public support for R&D that was relevant to IT and business relationships with thefinancial sector in the USA. Additionally, Avnimelech and Teubal (2008) demonstrated
the effectiveness of evolutionary targeting that changed policy targeting dynamically inline with the business environments. Their references to HTPs indicate the significanceof external environments in success of targeting in policy.
In previous studies, the primary questions about targeting in policy have been
whether public investment in industry could offset market failure in R&D investment by
the private sector and whether public support would contribute to improving academic
and business performance for political objects. Because their foci have been to investigate
the effectiveness of targeting, the dynamic effects of targeting policy on science are
difficult to accumulate knowledge (Finkelstein, 2004). Uyarra, Zabala-Iturriagagoitia,
Flanagan, and Magro (2020) described that market failure rationales for policies had little
care about the direction of innovation. Additionally, policies with narrowly defined targets
aim to drive innovation to a definite direction for achieving political objectives. Thus,
policy-driven knowledge accumulation is worth investigation to estimate what effects
targeting policies would have on the progress of science. Therefore, this study would
analyze the effect of prohibitive policy for hESC on subsequent studies and add practicalevidence to the stream of research about targeting in policy.
3. Hypothesis
The objective of this study is to examine effects of political intervention thatprohibits the use and development of hESC on the composition of stem cells for cardiac
research. Political interventions on hESC for research have prohibitive, restrictive, andpromotive patterns to use and develop it. Prohibitive and restrictive polices impose legal
prohibitions or restrictions on the use and development of hESC because of ethical issues.
Promotive policy provides public support for research using specific stem cells. For
example, much public support has been directed for iPSC research in Japan because it
could provide solutions to hESC’s ethical issues and contribute to growing theregenerative medicine industry by providing new treatment for incurable diseases atpresent and new tools for drug discovery (Azuma and Yamanaka, 2016).
The reason to focus on prohibitive policy is to clarify the dynamic effects ofprohibition for hESC on stem cell research. While regulating the use of hESC for researchis necessary from the ethical perspective, the effects on the decrease and increase in
medical and academic performance of neighboring fields by political interventions need
to be investigated. Promotive policy for specific stem cells is simply expected to increase
the number of studies about targeted cells. Meanwhile, prohibition on hESC could reduce6

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relevant research and drive scientists to study the other stem cells. The best stem cell forclinical application in cardiac repair and regeneration remains unclear (Hashimoto, Olson,
and Bassel-Duby, 2018). Prohibitive policy would be the definite reason why scientists
do not choose hESC for research. To investigate the impacts of prohibitive policy on thecomposition of stem cells leads to identify the trend of respective stem cells chosen forresearch. The analysis focuses on the effects of prohibitive policy on scientists’ choicesof stem cells including iPSC and MSC/BMC because it is suspected that prohibitions on
hESC would become a hurdle to use it and induce scientists to use its alternative stem
cells.
Existing research examined the effects of restrictive and prohibitive policies on
hESC by federal and state government in the USA on scientists’ behavior (Alberta et al.,2015; Levine, 2012; Levine, Lacy, and Hearn, 2013). Furman, Murray, and Stern (2012)
found that federal restrictive funding on hESC in 2001 led to decrease the number of
hESC research in the USA. The USA’s share, identified by reprint authors, in citing
articles declined in hESC research after 2001, though this was not the case in RNAi
research. They explained this decreasing share of hESC research to be the result of
restrictive federal funding that targeted hESC. Whereas their research interest was limited
to hESC, this study examines the impact of prohibitive policy for hESC on all species ofstem cell research. The purpose of expanding data from human to all species in this study
is to examine the dynamic effect of targeted prohibitive policy. This study is not the firstto expand data to other species. In previous research, Huang and Jong (2019) found that
restrictive policy on hESC decreased rates of initiation and continuities of cell therapy
projects by firms in the USA. Their data of corporate projects were unlimited to hESC
studies because the number of hESC projects alone was too small to analyze (Huang andJong, 2019). Prohibition on hESC is assumed to drive scientists to choose stem cells otherthan ESC and undermine scientists’ belief in the further development of ESC. The
investigation of the change in stem cell composition would add evidence for the impact
of prohibitive polices on subsequent research.
The causality between prohibitive policy that targeted hESC and stem cellchoices would depend on scientists’ forward-looking decisions of research subjects.
Prohibition on the use and development of hESC increases the difficulty in future clinicalapplications of ESC research. The future uncertainties and difficulties in the developmentof ESC research may be the reason why scientists avoid ESC research and choose otherstem cells. To investigate how political interventions on hESC affect compositions ofaccumulated scientific knowledge, this study hypothesizes that political prohibition on
hESC would drive scientists to choose stem cells other than ESC. In other words, though7

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ESC contains species other than human, scientists would avoid ESC and choose iPSC,
MSC, and BMC because political obstacles for its use would make scientists aware of the
difficulty of clinical application of their ESC research results in the future. Thus, countries’
prohibitive policy would increase the number of studies about iPSC and MSC/BMC.
Additionally, this study investigates whether political interventions on hESC
research cause bias in the compositions of stem cell choices. Bias in the compositions ofstem cell for research could have multiple definitions. This study focuses on ESC, iPSC,
and MSC/BMC research and analyzes the rate of respective stem cell in total number.
Thus, biased stem cell choices in this study mean that the proportion of papers on therespective stem cell is peculiar to the respective country by responding to prohibitive
policy. If prohibitive policy becomes obstacles for scientists to choose ESC and drives
them for the other stem cell research, this study concludes that stem cell choices are biased
by political intervention.
4. Research Method
To examine the influences of prohibitions for hESC on choices of stem cell for
research, this study focuses on studies of cardiac repair and regeneration. To identify
countries that have prohibitions on hESC, it follows the survey by Matthews and Morali(2020). They focused on the top 22 countries based on R&D funding in 2017 andinvestigated their political interventions concerning in vitro culture of human embryo or
embryoids for basic research. Of these countries, Brazil and France have no political
restrictions on its development for research. In the USA, federal funding was not allocatedto research that creates or destroys a human embryo. Austria, Germany, Italy, Russia, andTurkey prohibit scientists from the derivation of hESC. Australia, Belgium, Canada,
China, India, Israel, Japan, South Korea, Spain, Sweden, Taiwan, the Netherlands, andthe United Kingdom have a 14-day limit in the development of hESC on research, andSwitzerland has a 7-day limit. Sample data that is picked up from PubMed is narrowed
down to 22 countries in Matthews and Morali (2020) by the location of the organization
to which first authors belonged. The number of excluded samples and countries is 278
and 26, respectively.
In Matthews and Morali (2020), the policies for hESC in 22 countries are divided
into three groups: prohibition, restriction, and permission without laws and guidelines.
Countries with prohibitive policy include Austria, Germany, Italy, Russia, and Turkey,
and other countries are included in a group of permissive policy, albeit some withrestrictions. Thus, the sample data in this study are split into two groups: prohibiting theuse and development of hESC for research and permissive for that with/without
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Working Paper

restrictions. This study examines whether political approaches to hESC in two groups
explain differences in scientists’ choices of stem cells. It assumes that scientists incountries that have prohibitive policies are likely to avoid choosing ESC for research.
An observation is the choice of stem cell for cardiac repair and regeneration in
an individual article. Because dependent variables are binary data, the analysis uses probit
regression. The dependent variable is whether the chosen stem cell for research is ESC ornot. Furthermore, this study investigates whether scientists choose iPSC and MSC/BMC
to study cardiac research. Specifically, iPSC would be a strong candidate because it is analternative tool for scientists without ethical issues. This study exploits its variation in thelocation of the first authors to identify the impact of political rule for hESC on their stem
cell choices for research. The hypothesis is that political interventions in their locations
are likely to influence the kind of stem cells for research. The analysis would infer that
increased propensity to choose stem cell other than ESC is due to political prohibitions
on hESC. Thus, the key independent variable is whether there were political prohibitions
on hESC in countries where the organizations to which first authors belonged werelocated.
5. Data and Variables
The analysis focuses on PSC and noncardiac stem cells for cardiac repair andregeneration. Duran et al. (2018) categorized the sources of myocardial regeneration into
using cells and others. Cells include ESC, somatic cell, iPSC, and cell sheets. Others
include prefabricated matrices and extracellular matrices. Additionally, stem cells for
cardiac regeneration have three main sources: noncardiac stem cells, cardiac-derived cells,
and PSC (Hashimoto et al., 2018). The ideal cell for cell transplantation remains unclear(Garbern and Lee, 2013; Segers and Lee, 2008). Prohibitive policy on hESC would affectchoices of noncardiac stem cells and PSC among three sources because ESC could betheir alternative tool. Thus, the dataset is composed by articles about them. In the dataset,noncardiac stem cells include MSC and BMC, and PSC includes ESC and iPSC. Th data
include both human and other species’ stem cells.
The dataset was constructed from published articles that were collected using
PubMed search. Sample articles were picked up in January 2021 under the following
conditions about Medical Subject Heading term (MH), publication type, language,
abstract, and publication year. Medical Subject Heading term of sample articles include“induced pluripotent stem cells,” “embryonic stem cells,” “human embryonic stem cells,”“mouse embryonic stem cells,” “mesenchymal stem cells,” “mesenchymal stem celltransplantation,” “bone marrow cells,” or “bone marrow transplantation.” Their
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publication type is journal article, and it is not review, systematic review, retracted
publication, meta-analysis, guideline, comment, and editorial. They are written in English,
are published in 2009–2019, and have an abstract. Subsequently, 4,466 articles wereidentified when using the above criteria. Of these articles, 377 were excluded because
MH did not involve one of the above words. It was turned out that 736 articles were
duplicates; therefore, they were excluded. Then, 22 articles were excluded because yearof publication was 2020. One article was excluded because its language was not English.
Seven articles were excluded because they were conference papers. Additionally, thesample was narrowed down to articles whose first authors’ affiliations were in 22
countries of Matthews and Morali (2020). Because first authors’ affiliations were not in
the 22 countries, 278 articles were excluded. Finally, the number of sample articles was
3,045. Therefore, the number of articles from 22 countries and excluded samples accountfor approximately 90% and 10% of the total, respectively.
To investigate the effect of prohibitive policy on the choice of the respective stem
cell, dependent variables follow three patterns: ESC, iPSC, and MSC/BMC. They equal 1
if scientists choose respective stem cell and 0 otherwise. Because BMC includes MSC,
they are combined into one variable. In the case that multiple stem cells are relevant to a
study, variables of respective stem cell are equal to 1 in the study. The independent
variable is Prohibitive policy. It equals 1 if a location of the first author’s affiliation is inAustria, Germany, Italy, Russia, and Turkey and 0 otherwise. Control variables include
Year 2010–2019 that equal 1 if articles are published in respective year and 0 otherwise
and country dummy that equals 1 if the research institute to which first author belonged
is in respective country and 0 otherwise. Country dummies are set about the top 10
countries in number of articles. Thus, they include Canada, China, France, Germany,
Italy, Japan, South Korea, the Netherlands, the United Kingdom, and the USA. Countries
where scientists conducted research are identified by the location of the first author’s
affiliation in the article. When multiple affiliations about the first author are identified,the affiliation listed first is used to identify a country where research was conducted for
published articles. In the case that scientists changed affiliations, the affiliations where
research was conducted are usually listed first.
6. Countries’ Trends in Stem Cell Choices
The sample data demonstrate that stem cell choices are unique to various
countries. Table 1 shows the number of respective stem cell research by the top 10
countries in descending order of total number of articles. Table 2 shows the ranking ofeach country by respective stem cell. the USA, China, Japan, and Germany occupy the10

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top four countries in all three stem cells’ studies, albeit with different trends by country.
China and Japan have strength in MSC/BMC and iPSC research, respectively. The USA
has published far a greater number of papers on ESC and iPSC research than othercountries.
Figure 1 demonstrates the entire number of respective stem cell studies by year.
The number of MSC/BMC studies remains at a near constant level, and regarding ESC,
the number of studies has been gradually decreasing since 2015. Meanwhile, the numberof iPSC research has increased almost constantly. This study hypothesizes that thedecreasing the number of ESC research would be partly explained by prohibitive policy.
Figure 2 demonstrates the top four countries of respective stem cell research.
Studies in China use MSC the most frequently, and in the USA and Japan, the number ofstudies that use iPSC is the highest, albeit with a different scale. Levine (2011) found thatscientists in the USA faced challenges from the uncertainty of federal policy concerning
hESC because the criteria for allocating federal funds to hESC research had been
modified with the change of administration. Almost half of scientists in the survey
answered that political uncertainty had a substantial impact on their projects. They
explained that the negative impacts were caused by the delay to begin hESC research
projects and the impediment to ongoing projects. Thus, although Chen and Li (2021)
referred that the USA has relaxed conditions on hESC, scientists had faced the difficultyin conducting hESC research, which might affect the likelihood of choosing ESC for
research.
Figure 3 shows a rate of respective stem cell in total in descending order of therate of ESC research. The highest rate of ESC is the Netherlands, and the lowest is Russia.
In the three lowest countries that are Turkey, Brazil, and Russia, the rate of research thatuses MSC is over 80%. McMahon and Thorsteinsdottir (2013) explained the reason ofsmall number of iPSC and ESC research in Brazil by the late start due to public debate
about the legality of hESC research. They suggested that regenerative medicine indeveloping countries was strongly demanded to achieve clinical applications of stem cells.
Additionally, Salter, Zhou, and Datta (2015) referred to the increasing pressures ofmarket-based stem cell innovation from health consumers to a science-based approach.
Thus, pressures from the market may facilitate MSC/BMC research in developing
countries.

<Table 1. The number of stem cell research by total number’s top 10 countries>

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Working Paper<Table 2. Top 10 countries of respective stem cell research><Figure 1. The number of respective stem cell research by year><Figure 2. Top four countries in all three stem cells’ research><Figure 3. The rate of respective stem cell in total>

7. Results
Table 3 provides descriptive statistics and correlations for all variables. Table 4shows the results of probit regression. This study assumes that uniqueness of various
countries in scientists’ stem cell choices is explained by differences in science policy. The
analysis examines whether prohibitive policy on hESC affects the number of cardiac
research that uses ESC, iPSC, and MSC/BMC. The results show that it reduces thenumber of ESC research and increases the number of iPSC and MSC/BMC research,though the extent of the influences on the respective stem cell varies by country.
Models 1–7 show the results of probit regression to investigate the effect ofprohibitive policy on scientists’ choices of stem cells for cardiac research. Dependent
variables of Models 1–2, 3–5, and 6–7 are ESC, iPSC, and MSC/BMC, respectively.
Models 1, 3, and 6 include full independent variables. Models 1 and 2 examine thehypothesis that prohibitive policy decreases the number of ESC research. Negative
coefficients of Prohibitive policy in both models are statistically significant at the 5%
level. Model 2 has the top four countries’ dummies that have a high number of three stem
cells’ studies. Negative coefficients of China and Japan are statistically significant at the
5% and 1% levels, respectively, and positive coefficient of Germany is statisticallysignificant at the 1% level.
Models 3–5 examine whether prohibitive policy affects the number of iPSC
research. Negative coefficient of Prohibitive policy in Model 3 is statistically insignificant,and its positive coefficients in Models 4 and 5 are statistically significant at the 10% and
5% levels, respectively. Thus, scientists in countries with prohibitive policy are likely tochoose iPSC for research. Model 5 has two countries’ dummies, namely, the USA andJapan. They have a higher percentage of iPSC research than ESC and MSC/BMC in the
top four countries in total number of articles. Whereas scientists in the USA have beenleading the latest research areas, the high rate of iPSC research in Japan is a result of the
public support that has targeted iPSC research since its discovery by Japanese scientists.
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Positive coefficients of both countries’ dummy variables are statistically significant at the
1% level. Because the coefficient of Japan is larger than that of the USA, scientists inJapan are more likely to choose iPSC research.
Models 6 and 7 examine the effect of prohibitive policy on scientists’ choices of
MSC/BMC for research. Positive coefficients of Prohibitive policy in both models are
statistically significant at the 1% and 5% levels, respectively. Thus, they support that the
number of MSC/BMC research increases in countries with prohibitive policy. Model 7
has the top four countries’ dummies, namely, China, Germany, Japan, and the USA. The
percentage of MSC/BMC research is high in China and low in the other three countries.
The negative coefficient of China and positive coefficients of the other three countries’
dummies are statistically significant at the 1% level. Compared to those in the other three
countries, scientists in China are more likely to choose MSC/BMC for cardiac research.
Results in Models 1–7 support that prohibitive policy on hESC decreases thenumber of ESC research and directs scientist to choose iPSC and MSC/BMC for research.
However, the impact on MSC/BMC and iPSC research depends on the country. Model 2
shows that scientists in Germany are likely to choose to study ESC, although thegovernment adopts prohibitive policy on hESC. Meanwhile, although China is a country
that adopts policies that permit the use and development of hESC with restrictions, theproportion of ESC research in total is lower than that in Germany. Countries’ dummies inModel 7 indicate that scientists in China differ in their stem cell choices from those inother top countries. They are likely to choose more MSC/BMC than are those in othercountries. Therefore, the extent of the effects of prohibitive policy on scientists’ choices
depends on countries’ different research environments.

<Table 3. Descriptive statistics and correlations><Table 4. Results of probit regression>

8. Discussion
Results show that prohibitive policies on hESC affect scientists’ choices
negatively of ESC and positively of iPSC and MSC/BMC for cardiac research. Thus, theincreasing trend of iPSC research and not the decreasing trend of MSC/BMC research in
Figure 1 are partly explained by prohibitive policy on hESC. This study provides evidence
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that prohibitive policy on hESC leads to decreasing number of ESC research. Although
the impacts on MSC/BMC and iPSC research are different by country, scientists facing
prohibitive policy are likely to choose stem cells other than ESC. Meanwhile, thecausality about how prohibitive policy on hESC affects stem cell choices requires
discussion because dependent variables contain stem cells of all species. If scientists makeforward-looking decisions of research subjects, they choose iPSC and MSC/BMC, not
ESC, because of its difficulty in future development. The applicability of research results
about non-human stem cells to human may attract scientists’ attention to non-ESC cells.
Additionally, the different responses to prohibitive policy on hESC would becaused by research environments in respective countries. Even under prohibitive policy
on hESC, scientists in Germany are likely to choose ESC for research. Germany has alaw that prohibits the derivation of hESC and allows to use hESC that were created before
March 1, 2007, in foreign countries for research (Duran et al., 2018). Nevertheless, thedifference between ESC and iPSC research in Germany is not as large as that in Japan.
Löser et al. (2012) found that the number of hESC research in Germany increased
regarding papers published in 2007–2011. The reason could be a result of their locationthat has neighboring countries with restrictive but permissive policies on hESC. Scientists
in Germany would be able to easily gain the latest information on hESC, and they havean option to move to neighboring countries if they hope to study hESC under permissive
policy. Thus, they could be optimistic about the development of ESC research in the future.
Meanwhile, even in countries where hESC research was permitted, the patternsof stem cell choices vary. For example, compositions of stem cells for research in Brazil
and France that have no restrictions on hESC research might indicate that scientists haveno clear answer for stem cell choices and that exogeneous factors, other thanprohibitive/restrictive policies on hESC, affect their choices. Figure 3 shows that the rateof ESC research in France is less than 40%. This is approximately the same proportion asthat in Germany that has prohibitive policy. In Brazil, over 80% of research is regarding
MSC/BMC. Whereas prohibitive policy reduces the number of ESC research, otherfactors would induce scientists to choose specific stem cells. Future research could
explore what factors other than prohibitive policy affect scientists’ decisions. Additionally,
China and Japan show remarkable differences among the top ten countries. They have a
14-day developmental limit on hESC (Matthews and Morali, 2020). Under the same
conditions, scientists in Japan are likely to choose iPSC, and scientists in China are likely
to be involved in MSC/BMC research. As Figure 3 highlights, their rate of choosing
MSC/BMC is more than 50%. While a high proportion of iPSC research in Japan would
be explained by generous public support for iPSC research, demand-driven pressures for14

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Working Paper

scientists in developing countries might explain China’s high proportion of MSC/BMC
research (McMahon and Thorsteinsdottir, 2013).
9. Conclusions and Limitations
This study examines how prohibitive policy on hESC affects the choices of stem
cells for cardiac research and concludes that it generates bias in their compositions.
Previous research has estimated the effectiveness of science policy by patent count andarticle citations (Furman, Murray, and Stern, 2012; Li, Azoulay, and Sampat, 2017;
Sampat and Williams, 2019 etc.). The core contribution of this study is to add evidence
that prohibitive policy could change scientists’ behaviors and generate bias inaccumulated scientific knowledge. Another contribution is to find variations of stem cellcompositions across countries. Because MSC/BMC and iPSC become alternative tools to
ESC, scientists have options to use them. How scientists respond to the policy on hESC
depends on the availability of stem cells and the amount of funding available for research.
They would affect the compositions of stem cell choices for research.
The first limitation of this study is that the effect of other factors on scientists’stem cell choices remains unclear. The reasons why scientists choose stem cell for
research would include pure scientific interests in the mechanisms, the potential forclinical application, its availability, and the political restrictions and support for it.
Although these direct factors other than prohibitive policy would affect scientists’ choicesof stem cells for research, some of them are not considered in probit regression.
Additionally, indirect factors that include the degree of public and private investment inother stem cells, specialties of local research institutes, market demand, and public
opinion would affect their choices. For example, because public opinion in Japan has
supported investment in iPSC research after the Japanese scientist won the Nobel Prize,
the government has designed science policies that target iPSC to take the lead in theregenerative medicine industry. Figure 3 shows that the targeting policy has significantly
increased the proportion of iPSC research in Japan. Future research is necessary to
identify these other influential factors qualitatively with field study and then toquantitatively clear the degree of effects on scientists’ behaviors.
Another limitation is insufficient support for the causality that prohibition on
hESC leads to decreasing the number of ESC research that includes other species.
Whereas the focus of prohibitive policy is limited to human stem cells, dependent
variables about stem cells contain all species. This study interprets that causality between
prohibitive policy on hESC and decreasing the number of ESC research is explained byscientists that would predict the difficulty of subsequent clinical application with hESC.
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Additionally, field study to ask authors about the reason to choose specific stem cell for
research is necessary to make sure the causality.
Moreover, how locally biased choices of stem cells affect the subsequent
research requires further investigation. The regional specialty of stem cell research would
influence what professional scientists come to study there in the future. This means thatthe locally biased choice of stem cell may decide what stem cell research would be major
in the region. If locally major stem cells could take an important role in future clinicalapplication of cardiac repair and regeneration, politically directed choices would prove
effective. However, predicting appropriate political direction of scientific research isdifficult due to high uncertainty in the future performance of the respective stem cell. In
this respect, the effectiveness of the targeting policy would require a long time to assess.
Azoulay, Zivin, and Manso (2011) find that grants tolerating early failure and rewarding
long-term success contribute to breakthrough performance more than do short-cycle
review grants. Their findings support the idea that the grant system absorbing uncertainty
in the long-term research process is effective for high performance. Therefore, science
policy might need to be designed to absorb unexpected research development by nontargeting.
To correct locally biased knowledge compositions would be another solution ofthis issue. Regarding this aspect, the combination of regionally clustered innovation
processes and collaboration with organizations outside the region are effective tocomplement with each other (Carayannis, Meissner, and Edelkina, 2017). Furman,
Murray, and Stern (2012) found that the decreasing number of hESC research in the USA,
caused by the 2001 policy decisions of the Bush administration, was mitigated byinternational research collaborations. Thus, international collaborations would be also the
key to solving biases caused by politically targeted policy. Finally, because the focus of
this study is limited to research for cardiac repair and regeneration, it is necessary toinvestigate wider applicability of specific conditions in this field to other fields. Future
research should examine effects of targeting policy on scientists’ behaviors in expanded
data, including that outside of heart regeneration.
Despite these limitations, this study contributes to adding evidence about theeffect of political interventions on stem cell choices by scientists for cardiac research andto showing that patterns of bias vary by countries. These contributions would be extended
to future works that examine whether locally different compositions of stem cellknowledge lead to their differences of performance. In other words, because future
research could identify the results of targeting policies, they should verify whether
politically induced knowledge bias would be effective to the subsequent research.
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Acknowledgments
This article was supported by Grants-in-Aid from the Japan Society for the Promotion of
Science (Kiban-C-21K00247).
Declaration of interest
None.
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Table 1. The number of stem cell research by total number’s top 10 countries
Country

ESC

iPSC

MSC/BMC

Total

1
2
3
4
5
6

The USA
China
GermanyJapan
The United Kingdom
Italy

356
159
106
59
47
28

432
94
112
138
34
28

320
365
77
52
32
44

1108
618
295
249
113
100

7
8
9
10

CanadaSouth Korea
The Netherlands
France

37
29
43
22

17
11
19
15

40
49
26
24

94
89
88
61

21

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Working Paper

Table 2. Top 10 countries of respective stem cell research
Country

ESC

Country

iPSC

Country

MSC/BMCThe USA
China
GermanyJapan
The United Kingdom
The Netherlands

356
159
106
59
47
43

The USAJapan
Germany
China
The United Kingdom
Italy

432
138
112
94
34
28

China
The USA
Germany
Japan
South Korea
Italy

365
320
77
52
49
44

CanadaSouth Korea
Italy
France

37
29
28
22

The Netherlands
CanadaFranceSouth Korea

19
17
15
11

CanadaThe United Kingdom
The Netherlands
France

40
32
26
24

22

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Figure 1. The total number of respective stem cell research by year

The total number of respective stem cell research
250
200
150
100
50
0

Year
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
ESC

iPSC

MSC/BMC23

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Faculty of Business Administration
Working Paper

Figure 2. Top four countries in all three stem cell research

The number of respective stem cell research
500
450
400
350
300
250
200
150
100
50
0
The USA

China
ESC

iPSC

GermanyJapan

MSC/BMC24

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Working Paper

Figure 3. The rate of respective stem cell in total

The Netherlands
SwedenThe United Kingdom
CanadaFranceGermany
Switzerland
IsraelSouth Korea
The USA
Australia
India
Italy
China
Japan
Austria
TaiwanBelgium
Spain
TurkeyBrazilRussia
0%

20%
ESC

40%
iPSC

60%

80%

100%

MSC/BMC25

Table 3. Descriptive statistics and correlation
Variables

Mean

S.D.

1

2

3

4

5

6

7

8

9

10

1

ESC

0.32

0.47

-

2

iPSC

0.33

0.47

-0.34

-

3

MSC/BMC

0.40

0.49

-0.52

-0.54

-

4

Prohibitive country

0.14

0.32

0.02

0.02

-0.03

-

5

Canada

0.30

0.17

0.03

-0.06

0.01

-0.07

-

6

China

0.20

0.40

-0.06

-0.18

0.22

-0.20

-0.09

-

7

France

0.02

0.14

0.01

-0.02

0.00

-0.06

-0.03

-0.07

-

8

Germany

0.10

0.29

0.04

0.05

-0.08

0.80

-0.06

-0.16

-0.04

-

9

Italy

0.03

0.17

-0.01

-0.01

0.02

0.45

-0.03

-0.09

-0.03

-0.06

-

10

Japan

0.08

0.27

-0.04

0.16

-0.10

-0.11

-0.05

-0.14

-0.04

-0.09

-0.05

-

11

South Korea

0.03

0.16

0.01

-0.07

0.06

-0.07

-0.03

-0.08

-0.02

-0.05

-0.03

-0.05

12

The Netherlands

0.03

0.16

0.07

-0.04

-0.03

-0.07

-0.03

-0.08

-0.02

-0.05

-0.03

-0.04

13

The United Kingdom

0.04

0.19

0.05

-0.01

-0.04

-0.08

-0.03

-0.10

-0.03

-0.06

-0.03

-0.06

14

The USA

0.36

0.48

0.03

0.13

-0.14

-0.29

-0.13

-0.36

-0.10

-0.23

-0.13

-0.21

16

2010

0.07

0.26

0.09

-0.16

0.07

0.02

-0.01

-0.03

0.01

0.01

-0.02

0.03

17

2011

0.08

0.28

0.09

-0.12

0.03

0.03

0.00

-0.03

0.03

0.02

0.01

-0.01

18

2012

0.08

0.27

0.05

-0.11

0.06

0.00

0.01

-0.02

0.03

-0.00

0.01

0.01

19

2013

0.09

0.29

0.01

-0.05

0.05

-0.00

0.02

0.04

-0.02

-0.02

0.04

-0.04

20

2014

0.08

0.28

0.02

-0.05

0.03

-0.01

0.00

-0.02

-0.02

0.00

-0.01

0.00

21

2015

0.10

0.29

0.03

-0.03

-0.02

-0.04

-0.02

0.02

-0.01

-0.03

-0.02

-0.03

22

2016

0.10

0.30

-0.03

0.09

-0.06

-0.01

-0.02

0.00

0.01

0.00

-0.02

-0.01

23

2017

0.11

0.32

-0.08

0.14

-0.05

-0.00

0.02

0.00

-0.01

0.02

-0.02

0.03

24

2018

0.10

0.31

-0.08

0.15

-0.07

0.01

-0.02

0.01

-0.01

-0.00

0.04

0.03

25

2019

0.12

0.32

-0.11

0.20

-0.10

-0.11

-0.01

0.03

-0.02

-0.00

-0.00

-0.00

26

Variables

11

12

13

14

15

16

17

18

19

20

21

22

23

12

The Netherlands

-0.03

-

13

The United Kingdom

-0.03

-0.03

-

14

The USA

-0.12

-0.12

-0.14

-

15

2010

0.01

0.01

-0.01

-0.00

-

16

2011

0.01

-0.01

-0.00

0.00

-0.01

-

17

2012

0.03

0.02

-0.02

-0.01

-0.08

-0.09

-

18

2013

-0.01

0.02

-0.02

-0.01

-0.09

-0.10

-0.09

-

19

2014

-0.00

0.01

0.04

0.00

-0.08

-0.09

-0.09

-0.10

-

20

2015

-0.03

-0.01

0.00

0.04

-0.09

-0.10

-0.09

-0.10

-0.10

-

21

2016

0.04

-0.01

0.01

0.01

-0.09

-0.10

-0.10

-0.11

-0.10

-0.11

-

22

2017

0.00

-0.00

-0.02

-0.02

-0.10

-0.11

-0.10

-0.11

-0.11

-0.12

-0.12

-

23

2018

-0.03

-0.03

0.02

0.00

-0.10

-0.10

-0.10

-0.10

-0.10

-0.11

-0.12

-0.12

-

24

2019

-0.00

-0.02

0.01

-0.01

-0.10

-0.11

-0.11

-0.12

-0.11

-0.12

-0.12

-0.13

-0.13

27

Table 4. Results of probit regression
Dependent variables
Independent variables

ESC

iPSC

MSC/BMC

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Prohibitive policy-0.64**-0.33**

-0.46

0.14*

0.54***

0.61***

0.28**

Canada0.38**

China

0.08

France0.27

Germany

1.00***

Italy

0.76***

Japan

-0.01

South Korea

0.25-0.67***

0.26*

The Netherlands

0.64***-0.15-0.54***The United Kingdom

0.53***-0.02-0.46***The USA

0.25***-0.01

0.34***

Year 2010

0.12

0.09

0.71**

Year 2011

0.05

0.04

Year 2012-0.13

Year 2013-0.18**
0.43***-0.27***-0.36*-0.19-0.62***

0.38***

-0.08

-0.24

0.81**-1.17***

0.40-0.64**

0.85***

1.18***-0.74***

0.52***-0.70***-0.60***

0.67***-0.47***-0.33***

0.76*

0.72**

-0.12

-0.10

1.27***

1.21***

1.27***-0.32**-0.31**-0.12

1.29***

1.23***

1.28***

-0.18

-0.18

-0.28**-0.27**

1.76***

1.61***

1.73***-0.33***-0.33***

Year 2014-0.26**-0.26**

1.69***

1.63***

1.69***-0.32**-0.31**

Year 2015-0.20*-0.21*

1.84***

1.74***

1.83***-0.58***-0.58***

Year 2016-0.45***-0.45***

2.29***

2.16***

2.27***-0.77***-0.75***

Year 2017-0.67***-0.67***

2.44***

2.31***

2.42***-0.67***-0.66***

Year 2018-0.67***-0.66***

2.48***

2.36***

2.45**-0.76***-0.77***

Year 2019-0.75***-0.77***

2.69***

2.51***

2.65-0.93***-0.92***

Constant-0.34***-0.08***-2.49**-2.31***-2.80**

0.44***-0.30***LR chi-square

201.30***169.26***814.06***

540.70***754.76389.47***

N

3,045

3,045

3,045

3,045

3,045

3,045

356.30***3,045*p<0.1, **p<0.05, ***p<0.1

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