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Guilt by Association?
Exploring the Effects of Business Association
Activity on Economic Growth
Gabriel Mattera
Faculty Advisor: Professor Sami Alpanda
Submitted to the Department of Economics at Amherst College in
partial fulfillment of the requirements for the degree of Bachelor of Arts
with Distinction
April 22, 2005
Acknowledgments
First and foremost among those to whom I owe a great debt is my advisor, Professor
Sami Alpanda. As fellow neophytes, he to the process of thesis advising, I to the process
of thesis writing, I like to think that we both had something to teach the other.
Unfortunately, I know that this is simply not true. The theoretical insights, econometric
understanding and general guidance he bestowed upon me vastly outweigh anything I
could hope to offer in return. I wish to thank him especially for his patience across many
weekly meetings, and for his tolerance of my proclivity towards independent action. The
greatest teachers, I like to think, are those that lead their students to discover things on
their own.
I would also like to sincerely thank Ashfaq Qadri for his honest and straightforward
comments on early drafts of the manuscript. It is truly a noble friend who willingly
offers to take time out of his busy day to read tens of pages of dry undergraduate
economics.
Zeina Nasr deserves special mention. Without her anxious reminders of the impending
April deadline, I would never have become nervous enough to do the intense work
necessary to finish this project in a timely manner.
Thanks goes also to Ngoc Trang, whose conversation and joking in the Economics
Computer Laboratory was a burst of fresh air during the writing process.
Finally, I must acknowledge both of my parents. Throughout my life they have
constantly stressed the value of a full education and the pleasures of a curious mind.
Without their influence and support I would not be at Amherst College.
ii
INTRODUCTION
Business associations are a natural phenomenon in modern, democratic states. In
so far as firms and individuals can benefit from sharing professional experience with each
other, or from uniting to pursue a common economic aim, it stands to reason that
businesses will always have an interest in joining together. The issue, though, is how this
activity affects overall social welfare.
Many other private interest organizations pose a similar question. What partly
distinguishes business associations from these others is that they are a fluid and varied
category, representing a range of groups including, but not limited to, local professional
clubs, national business federations, and on a grander scale the lobbying wings of
multinational corporations. In part because of this, while interest groups as a whole have
been examined at length, there have been few attempts to isolate the effects of business
associations from the greater aggregation of private organizations. The goal of this paper
is precisely to do that. More specifically, it seeks to find whether or not business
associations can have a positive influence on social welfare.
A key hypothesis tested in the study is what is here termed the “information
effect”, the idea that business associations channel information to government about
industry and economic trends that it does not otherwise have access to. This information
should in turn improve the efficacy of government economic policymaking and so lead to
higher growth.
Building on the analysis of Stephen Knack (2003), the current study uses an
econometric model to test the relationship between associations and economic growth.
Membership in professional organizations forms the key explanatory variable. Also
1
incorporated, however, are interaction terms that highlight the relationship between this
variable and gross, public and private investment rates. The idea is to see whether
business associations affect different types of investment. Of specific interest is public
investment. Government capital expenditures are key component of economic policy. If
the information effect is true, then business associations should have a positive effect on
public investment.
Regression results prove somewhat surprising. Membership alone appears to
have a negative effect on economic growth. Turning to the interaction terms,
membership has a positive and significant influence on the efficacy of total and private
investment, and does not seem to be significantly correlated with public investment.
These findings suggest a new perspective on the role of business associations in
economic affairs.
The layout of the paper is as follows. The first section is a brief survey of the
ongoing academic debate about interest groups on social welfare. It focuses in particular
on the activity of business associations. Section two describes the principle data set used
in the empirical analysis. The third section outlines the statistical model used here to
examine the relationship between association activity and economic growth. Section four
gives the regression results and their interpretation. The fifth section is a case study of
Japan. The idea of incorporating such a study is to provide a concrete instance of a
country considered to have a high degree of interaction between business associations
and government. A major point of this section is to draw connections between the
Japanese example and the results of the empirical analysis.
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2
BACKGROUND
Before discussing business associations directly it is critical to consider their
position against the greater backdrop of existing private organizations. Political scientists
have offered differing judgments on private interest groups. Mancur Olson (1982) argues
that interest group activity creates inefficiencies because of collective action problems.
Small groups find it relatively easy to organize and achieve their aims—benefits are
focused in few hands, and it is easier to impose constraints to keep members in line.
Bigger groups, on the other hand, have many members, and as such each individual
obtains little reward from any effort he or she alone puts forth in advancing the group’s
cause.
Observed in a social context, the problem becomes clear. Consider the example
of a small manufacturing industry that succeeds in lobbying the government for tariff
protection. Managers and laborers in the industry would see a great reduction in wages
or even layoffs if they had to face foreign competition. On the other hand, the loss each
domestic consumer faces as a result of the tariff is a relatively minor price increase. As
such, private individuals do not have a strong impetus to counter the lobbying industry.
This holds true even though such a price increase, when multiplied across the entire
consumer population, translates into a major loss bigger than that faced by those in
industry. Thus, total social welfare is reduced because of the collective action problem
inherent in trying to unite all consumers together.
Heckleman’s (2000) study is one of few empirical investigations to use data
associated with business activity to test Olson’s predictions. He bases his data on
information gathered from Murrell (1984) on the concentration of trade associations in a
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sample of OECD and non-OECD countries. In his study the number of these associations
in each country serves as a proxy of overall interest group strength. Regressing a tenyear average of per capita income growth against this variable and a host of control
indicators, his results reveal moderate evidence to support Olson’s idea that interest
groups are a drag on economic growth.
There are opposing views to Olson, however. Robert Putnam (1993) believes that
private associations with horizontal, non-hierarchical structures can actually work to
increase social productivity by instilling a spirit of trust and cooperation between
members within a group. Such groups may also have a hand in overcoming collective
action issues by bringing together diverse individuals who might not meet under ordinary
circumstances because of differences in language, culture, or socio-economic status.
Local neighborhood crime-awareness associations may be seen as an instance of
this type of activity. They serve to unite people of all backgrounds in a given community
who may not normally have much significant interaction with each other. Through the
association, the community achieves a common good, namely crime prevention, that
would not have been realized otherwise.
Literature looking at the Putnam hypothesis in the context of business
associations has been largely theoretical, using mathematical modeling to represent
association behavior on a macroeconomic level. Most of this work, though sharing
Putnam’s premise that interest groups have a positive influence on welfare, incorporates a
different logic from that used by him to explain why this might be the case. For instance,
one argument made is that lobbying on the part of associations can have positive
“spillover effects”. These effects may arise when gains are incurred not only by the
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lobbying parties but by outside individuals as well (Mohtadi and Roe, 1998). An instance
of this phenomenon is found in the example of construction firms that lobby for increased
government expenditure on road works. Though the firms themselves are directly
rewarded through contracts for new roads, in fact all automobile users gain because they
can use these new roads for their own transportation needs.
Other models posit that business associations may have a role to play in
augmenting government economic policymaking. This idea might be termed the
“information effect”. Associations are a channel of communication between private and
public sectors, and can help state officials learn about, among other things, certain market
failures that are impeding private investment in productive sectors. Banning business
associations or their affiliated lobbies would deprive government of what might be a
decision-enhancing dialogue (Ball, 1995).
Interest in the role of information in economic development has been
strengthened by a spate of recent literature on the topic of industrial policy. A key
reference in much of this writing is Peter Evans (1995). His concept of “embedded
autonomy” describes a situation in which policymakers “are embedded in a concrete set
of social ties that binds the state to society and provides institutionalized channels for the
continual negotiation and renegotiation of goals and policies” (Evans, 1995, p.12). In
other words, the state is closely connected to, though not co-opted by, the private sphere.
A major case study for Evans is Japan, where he argues that it was just this sort of strong
relationship between government and industry that led to that country’s spectacular
growth following the Second World War. The example of Japan is discussed at length in
section five.
5
According to Rodrik (2004) and Rodrik and Hausmann (2003), business
associations and other organizations that bridge the gap between government and the
private sector can do more than just help existing industries. They may also serve to
promote growth in new industries that were previously locked out because of the kind of
collective action problems highlighted earlier. This activity might be seen as a different
form of the information effect.
Without state support of some kind, entrepreneurs active in the process of
investing in new business ideas would have to bear the full brunt of the costs of discovery.
Discovery is a hit or miss process, and investors must often spend a great deal of capital
on unproductive projects before hitting upon a viable business idea. Without external
regulation, competitors could simply wait around for entrepreneurs to find a productive
opportunity and then co-opt this opportunity for themselves, thereby eliminating the
lucrative profits entrepreneurs had hoped to achieve as the result of their investments.
Patent and copyright laws are one method of curbing the problems arising from
this information externality. Business associations may be another, allowing
entrepreneurs to “tip off” public officials to productive opportunities, which government
can then support through subsidies, licenses, and other policies that reward capital outlays
and research aimed at the discovery process.
The information effect lies at the core of the current paper. As noted above, much
of the economic literature on the topic of interest groups has displayed mixed results.
Quantitative studies have looked very broadly at the subject as a whole, and those authors
who have honed in on business have done so largely from a theoretical perspective.
6
This study is an empirical analysis that looks directly at the correlation between
business associations, investment and growth. Data and methodology follow Knack
(2003). Using cross-country data from the World Values Surveys (WVS), Knack
examines a broad range of social organizations, separating these into what he calls
“Olson” and “Putnam” groups. “Professional Associations” are placed into the Olson
group. Thirty-eight countries are sampled, and levels of participation in each of the two
groups form the core explanatory variable. Eighteen-year averages of per-capita income
growth and domestic investment serve as the dependent variables. Ultimately, Knack is
unable to support either the Olson or Putnam hypothesis conclusively, as he finds neither
category of group to be significantly correlated with his measures of economic
performance.
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2
DATA
Like Knack (2003), the World Values Surveys (WVS) serve as the source of the
most critical data here. Coordinated by Professor Ronald Inglehart of the University of
Michigan and a host of other social researchers, the WVS were designed with the intent
to be “a worldwide investigation of socio-cultural and political change” (WVS website).
The WVS are public opinion polls with queries on a number of topics ranging
from religion to politics and economics. Participating populations represent a variety of
communities across the globe, including those defined by clear country boundaries
(“Japan”), as well as some defined by regional affiliation (“Basque”). Though the
surveys are centrally coordinated, in each case the actual polling is managed at a local
level, with researchers in each population funding and conducting their own studies.
Standardization is maintained as much as possible, though in some countries costs and
geographical obstacles prohibit a perfect random-sampling. Questionnaires are extremely
similar across each population, differing only on a few topics that speak to social
particularities (for example, questions regarding affiliation with ethnic identities found in
the “home” society but not anywhere else). Country sample sizes range from 500 to 4000
individuals, though most are approximately 1000.
Of the four total surveys that have taken place, three are currently available to the
wider public. These are for 1981, 1990, and 1995-1998. All three are used in the present
study. Moreover all populations found are included, with the single exception of those
that are not defined by country borders. The reason for omitting these is that standard
data on economic indicators such as life expectancy and education exist only for
internationally recognized states.
8
The portion of the WVS used here is the subsection relating to membership in
voluntary organizations. This study is concerned with gauging the effect of business
association activity on the economy. As a result, unlike Knack, only the item on
“professional associations” within the greater set of voluntary organizations is used.
Although Knack incorporates this one in his own study, he does so in aggregation with a
host of other organizations that includes labor unions, recreational associations and
environmental groups. Rather than testing the effect of each of these group types
individually, he clusters them together in a single membership index. As a result of this it
is impossible to separate out the unique effect of professional associations.
In the WVS participants are asked to give a response about the degree of their
membership in professional associations. This membership is defined differently
between survey waves. In the 1990 questionnaire participants were asked to list whether
or not they belonged to professional associations, and additionally whether or not they
did voluntary work for these groups. In contrast, in the 1995-1998 questionnaire
participants had to list whether they were active members, inactive members, or not
members of professional associations. Active membership refers to individuals who take
an active role in the association, and inactive membership to individuals who belong but
do not actively participate. Though no questionnaire is available for the 1981 survey, it
seems that the format of the subsection of this survey on voluntary organizations was
very similar to that of the 1990 survey. Copies of the voluntary organizations subsection
of both available questionnaires appear in Appendix 2.A at the end of this paper.
Interestingly, there is a disjunction between the way the membership categories
are listed in the questionnaires and the way that they appear in the online WVS database
9
found at the University of Michigan’s university library website. In that database,
membership data for all three surveys appears under “active”, “inactive” and “not
member” categories. In effect, it is as if the 1981 and 1990 surveys had been subsumed
under the format of the 1995-1998 survey. Here again, brief communication with
Professor Inglehart served to clarify the issue (personal communication, April 2005). It
appears that the 1981 and 1990 data was transferred into the WVS database as follows;
participants who merely belonged to professional associations were placed in the
“inactive” category, and those who belonged and did voluntary work were placed into the
“active” category. All others went into the “not member” category. Thus, though the
database seems inconsistent at face level its measurements are in fact reliable and can be
used in analysis.
The membership categories are modified slightly for use in the current study.
Two measurements are used here. One is simply “active” membership as it appears in
the WVS database. The other measurement used is “total” membership, defined here as
the sum of active and inactive individuals. The idea is to see whether these have different
effects on economic growth. Each country was assigned two membership scores for each
survey, one corresponding to the total percent of respondents in the sample population
who said they were “active” members, and the other to the combined total percent of
“active” and “inactive” respondents.
Admittedly, it would be improper to tacitly equate “membership in ‘professional
associations’” with the strength of business association activity in a given country.
Because such activity cannot be translated into any sort of direct units, however, a
membership measurement has to suffice.
10
Membership in professional associations functions here as the explanatory
variable of interest in a pair of cross-country growth regressions. These utilize data from
the three individual of the WVS currently available to the public. The dependent
variables in the regressions are decade averages of year-over-year growth in GDP per
capita, roughly matching the survey years of the WVS. The three decades so observed
are 1975-1985 (for the 1981 survey), 1985-1995 (for the 1990 survey) and 1995-2003
(for the 1995-1998 survey). Growth data comes from the World Bank. 2003 is the last
date for which growth data are available, and so forms a cut-off date in the final decade.
A simple illustration of the data is given in Figure 2.1 on the following page. It
displays simple plots of membership against decade growth averages. China is removed
from the 1985-1995 plot and Nigeria and Bosnia from the 1995-2003 plot because of
extreme growth and membership that distort the clarity of the plots. It is apparent from
this figure that that there is no clear-cut relationship between membership and growth.
The little correlation that is in fact visible is in the third graph, and seems to be negative,
a result that at face value contradicts the Putnam hypothesis that business association
activity has a positive effect on growth.
If there is conclusive story to be built from the WVS data, it will come only from
a more detailed analysis. Indeed, though there is no conclusive absolute correlation
between membership and growth, there may be a conditional relationship that will only
be visible once other factors that play a role in growth are controlled for. Going further,
it is possible that business associations exhibit a more pronounced effect on growth only
through their influence on domestic investment. These ideas are expounded upon in the
next section, which deals with the specifics of the econometric model.
11
Figure 2.1 - Total and active membership in professional associations against GDP per
capita growth in the three sample periods (1975-1985, 1985-1995a, 1995-2003b).
1975-1985
7
6
5
Growth (%)
4
3
2
1
0
-1 0
5
-2
10
15
Membership (% of sample population)
Total Membership
Active Membership
1985-1995
10
Growth (%)
5
0
0
5
10
15
-5
-10
-15
Membership (% of sample population)
Total Membership
Active Membership
1995-2003
10
8
Growth (%)
6
4
2
0
-2
0
5
10
15
20
25
-4
-6
Membership (% of sample population)
Total Membership
a
b
China has been removed.
Bosnia and Nigeria have been removed.
12
Active Membership
30
35
3
MODEL
Along with the membership data described above, a host of control variables are
also incorporated in the analysis here. The idea of adding controls is to account for
factors other than membership in professional organization that may affect growth.
Without them, estimates of the effect of membership are likely to be biased.
The control variables included follow the guidelines of Robert Barro and Xavier
Sala-i-Martin (1995) on growth regressions. Decade averages (following the periods
listed above) of life expectancy, annual population growth rates and annual domestic
investment rates are used. Also incorporated are single-year measures of initial GDP-per
capita and male secondary schooling attainment, captured at the beginning of each
respective period in the years 1975, 1985, and 1995.
Schooling attainment data for each country come from Barro and Lee (2000).
Attainment is defined as the average number of years of secondary education completed
by an individual in a sample of the male population age 25 and over. According to theory
and empirical research, higher rates of attainment signify a greater presence of human
capital in the domestic economy and should be positively correlated with economic
growth.
The other controls all come from the World Bank’s World Development
Indicators (WDI) database. Initial GDP-per capita is given in 1995 international dollars
scaled to account for purchasing power parity. The idea of convergence states that poorer
countries will grow faster than richer ones, controlling for other variables. Economies
demonstrating high per-capita income, the reasoning goes, are already quite saturated
13
with physical capital and so face diminished rates of return on that factor. Initial GDPper capita should be negatively correlated with growth.
Life expectancy is given in years, and represents the expected life-span of the
average infant born in the year of measurement. As an indicator of mortality, life
expectancy is positively correlated with a range of health-related variables, and so a
major benchmark for economic development. Countries with a higher life expectancy
should experience greater economic growth.
Population growth rates are measured annually. Greater population growth is
usually indicative of higher domestic birth rates. Since children are net consumers,
higher population growth should be negatively correlated with growth. Though Barro
and Sala-i-Martin (1995) do not find a significant effect, population growth is a standard
feature of many growth models and so is incorporated here as well.
Investment is represented in a number of different forms in the regressions that
follow. One of these is as total domestic investment, defined as gross fixed capital
formation as a percentage of GDP. Alternatively, it is broken down into “public” and
“private” investment variables, to test the separate effects that each might have. “Public”
investment is simply government capital expenditure (also as a percentage of GDP), and
“private” investment is set as gross fixed capital formation less government capital
expenditure.
In Barro and Sala-i-Martin (1995), international differences in investment rates
are not found to be significantly related to growth when other factors are controlled for.
Despite this finding, investment is included in this study. It is a crucial vector, one that
allows for specific testing of the “information effect” hypothesis. According to this
14
theory, business associations improve government economic policymaking by channeling
information about industry that public officials do not have access to. A simple measure
of public investment is used here to account for government economic policy. If the
information effect is true, then higher levels of business association activity should
squeeze more growth out of each average, additional unit expenditure by the government
on physical capital.
Interaction terms are used here to test this effect. The first of these terms pairs
membership with gross investment in an attempt to determine whether or not association
activity has a net effect on investment. The second two terms pair membership with
private and public investment, respectively. Interaction between membership and public
investment directly tests the information effect. The other interaction terms are included
partly to balance out the model and partly to determine whether membership might have
separate effects on gross and private investment.
The complete generalized model is presented below:
Growth = β0 + β1 Membership + β2 Initial per-capita GDP + β3 Secondary Education
+ β4 Life Expectancy + β5 Population Growth + β6 Investment
+ β7 Membership*Investment + ε
Four versions of this model are estimated. For two of these, investment is defined
as “gross investment”, and for the other two it is split up into its “private” and “public”
components. Within each of these groups of two, “active” membership is used in one
regression and “total” membership is used in the other.
Data from the sample decades (again, 1975-1985, 1985-1995 and 1995-2003)
under observation make up three separate equations for each version, for a total of twelve
15
equations. Each set of three is pooled together to form a single system of equations
corresponding to one of the versions. Each version of the model is estimated in two ways.
In the first, the system is completely restricted. The constant term and all coefficients are
fixed between the equations such that the regression provides one coefficient estimate for
each explanatory variable across all periods. In the second estimation, all coefficients are
fixed but not the constant terms. The individual estimation of constant terms is to allow
for fixed effects between the different time periods. Estimations are made using the
Ordinary Least Squares (OLS) technique.
Pooling the data has two major advantages. One is that it allows for a greater
sample size and thus greater degrees of freedom, enhancing the reliability of the results.
The other is that it controls for business cycle effects between decades. Though ten years
is a significant interval of time, it may still be subject to many macroeconomic
fluctuations. The obvious response is to run estimates over longer periods of time. The
nature of the membership data from the WVS, however, makes this difficult. The survey
waves are spread out unevenly in time (occurring in 1981, 1990 and 1995-1998).
Moreover the number of countries varies from one survey to the next. Averaging the data
from the three to construct a single data set may give inaccurate results. As a
consequence, using each of the surveys individually in decade data sets and pooling these
together seems the most appropriate way to mitigate business cycle distortions.
16
4
RESULTS
Table 4.1 presents estimates for the first two versions of the model, which use
gross investment. Estimations using “complete restriction” of the constant and all
variable coefficients and estimations allowing for “fixed effects” are both shown. Results
for the controls roughly correspond to expectation in both total and active membership
versions using both estimation methods. Initial GDP-per capita is negative and
significant, secondary education positive and significant, population growth negative and
insignificant, and gross investment positive but insignificant. Life expectancy is positive
but insignificant.
Surprisingly, the test variables show a mixture of effects. In the total membership
version total membership alone is negative and significant using the “complete
Table 4.1 - Membership in professional associations and economic growth, with
gross investment.
Complete Restriction
Fixed Effects
Initial GDP
per capita
-0.000126**
(-2.387137)
-0.000111**
(-2.179256)
-0.000156**
(-2.618758)
-0.000127**
(-2.221636)
Secondary
Education
0.473061**
(2.047595)
0.497064**
(2.244661)
0.520501**
(2.170988)
0.527959**
(2.234159)
Life Expectancy
0.040728
(0.789169)
0.037769
(0.744689)
0.044352
(0.854522)
0.040976
(0.787960)
Population Growth
-0.477395
(-1.411758)
-0.355925
(-1.089347)
-0.481079
(-1.435498)
-0.362071
(-1.106738)
Gross Investment
0.067071
(0.780475)
0.078448
(1.224211)
0.105482
(1.192222)
0.104138
(1.546363)
Total Membership
-0.283467*
(-1.758448)
Active Membership
Total Membership *
Gross Investment
Active Membership *
Gross Investment
-0.175955
(-1.022700)
-0.626865**
(-2.615578)
0.014356**
(2.018198)
-0.487535*
(-1.821115)
0.010418
(1.409252)
0.029715***
(2.839901)
0.024340**
(2.147692)
Notes: N = 40. *, ** and *** indicates significance at .10, .05 and .01 respectively.
17
restriction” method and negative but not significant using the “fixed effects” method.
The interaction between total membership and gross membership is positive and
significant using the “complete restriction” method and positive but not significant using
the “fixed effects” method. In the active membership version active membership alone is
negative and significant using both estimation methods. The interaction between active
membership and gross membership is positive and significant using both estimation
methods.
Table 4.2 provides estimates for the second two versions of the model, which split
total investment into private and public components. The behavior of the control
Table 4.2 - Membership in professional associations and economic growth, with
private and public investment.
Complete Restriction
Fixed Effects
Initial GDP
per capita
-0.000131**
(-2.393517)
-0.000114**
(-2.169944)
-0.000163***
(-2.659965)
-0.000128**
(-2.195264)
Secondary
Education
0.463860*
(1.919043)
0.501179**
(2.148688)
0.511630**
(2.068897)
0.527912**
(2.157013)
Life Expectancy
0.045976
(0.865482)
0.041360
(0.790610)
0.050943
(0.952792)
0.042845
(0.801702)
Population Growth
-0.480204
(-1.397317)
-0.341329
(-1.018443)
-0.485441
(-1.425431)
-0.352486
(-1.047408)
Private Investment
0.075886
(0.858072)
0.081638
(1.246675)
0.116374
(1.277598)
0.106044
(1.541650)
Public Investment
0.159470
(0.554945)
0.121484
(0.556780)
0.210951
(0.729065)
0.131689
(0.582834)
Total Membership
-0.244425
(-1.374061)
Active Membership
Total Membership *
Private Investment
-0.594452**
(-2.314817)
0.013423*
(1.817215)
Active Membership *
Private Investment
Total Membership *
Public Investment
Active Membership *
Public Investment
-0.126811
(-0.670963)
-0.471116*
(-1.685575)
0.009209
(1.197739)
0.028799**
(2.649387)
0.004607
(0.234978)
0.023903**
(2.051126)
-0.001158
(-0.058881)
0.019862
(0.700485)
0.018299
(0.641956)
Notes: N = 40. *, ** and *** indicates significance at .10, .05 and .01 respectively.
18
variables here is similar to that of the first two versions, and though investment is now
defined as two variables both of these again prove positive but insignificant for each
membership type.
Test variables are again mixed. In the total membership version total membership
alone is negative and not significant using both estimation methods. The interaction
between total membership and private investment is positive and significant using the
“complete restriction” method and positive but not significant using the “fixed effects”
method. The interaction between total membership and public investment is positive and
not significant using the “complete restriction” method and negative and not significant
using the “fixed effects” method. In the active membership version active membership
alone is negative and significant using both estimation methods. The interaction between
active membership and private investment is positive and significant using both
estimation methods. The interaction between active membership and public investment
is positive but not significant using both estimation methods.
The results reveal a surprising story. Active membership, a more defining
measure of business association activity, is negative and significant in all four versions of
the model. Thus business association activity in and of itself appears to have a negative
influence on growth. This result is somewhat in line with the Olson theory.
The investment interaction terms provide somewhat of an opposing effect to the
stand-alone membership variables. As mentioned above, the interaction between active
membership and gross investment is positive and significant under both estimation
methods. Even total membership reacts positively and significantly with gross
investment under the “complete restriction” method. So though gross investment by
19
itself is not related to growth, when combined with business associations it is. This result
would seem to support Putnam’s theory that interest groups are a positive force.
Going further, business associations seem to have different effects on public and
private investment. The interaction between membership and public investment is highly
insignificant for both membership types. Private investment, however, reacts positively
and significantly with active membership, and with total membership in using the
“complete restriction” estimation method. In summary, membership appears to increase
the efficacy of private investment, and to have no effect on public investment. This result
would seem to contradict the “information effect” hypothesis outlined earlier. At the
same time, it may be possible the thinking of this hypothesis in a new light. Specifically,
it may not be government that benefits from business association information, but the
private sector.
There are a number of potential ways to explain the disparity between the
interaction of membership and the interaction of public investment and membership and
private investment. Focusing on the relationship between business associations and
government, it might be that the typical criticisms of industry lobbies are correct.
Lobbies invariably represent both productive industries and unproductive industries. The
latter, in particular, divert government subsidies and funding away from beneficial
projects and are thus a drain on government investment. This effect may cancel out any
positive influence that business associations bestow by providing economic information
to government. That would explain the lack of significant interaction between
membership and public investment in the regression. Note that lobbying behavior may
also explain the negative and significant effect that membership alone had on growth.
20
A reworking of the information effect provides some interesting reasons to
explain the positive correlation between membership and private investment. Business
associations are formed not only as a mechanism for transmitting needs to government
but as a forum for discussion, both between companies within an industry and between
industries in the economy. These entities meet to share information about the business
climate, to establish joint business ventures, and to set industry-wide standards on issues
such as hiring practices or distribution of resources. These are all forms of informational
exchange. By encouraging cooperation between different business and reducing
economic uncertainty, then, business associations can enhance the success rate of
investments made by firms.
Another way in which a business association might have a positive effect on
private investment is as a signaling mechanism. Many business associations have
particular standards which companies must meet if they wish to gain membership.
Conditions may include achieving a certain level of market capitalization, or using
certain production techniques (growing crops organically, for instance). Once in,
however, these conditions might become a sign of distinction for a given firm, putting it
in a recognizable category and indicating its legitimacy to potential investors. Private
investors looking to invest in companies that meet specific qualifications are thus
provided with a means of comparing and classifying different businesses, information
which they can then use to make more informed investment decisions.
21
5
JAPAN
Up to now the current paper has concerned itself with a broader empirical analysis.
This section is meant to provide a specific instance of business association activity.
Japan is a good candidate for study, representing an economy that many political
scientists and economists argue is highly influenced by business associations. Here
particular emphasis is paid to the “information effect”, the role that these associations
play in transmitting information about industry to government.
In order to place this discussion firmly in the context of the paper, discussion of
Japan will parallel the framework of the empirical analysis. First a traditional argument
for Japan’s economic success will presented. The central reasoning behind it is
essentially a form of the information effect, positing that business associations and
government in Japan engaged in prolonged institutionalized dialogue with one another,
and that this dialogue led to the formulation of highly effective economic policy by
government. Afterwards this same argument will be criticized. Just as the empirical
analysis earlier called into question a typical understanding of the information effect, so
too will traditional ideas about Japanese industrial policy be examined anew. Finally, it
will be seen whether Japan’s development success can be explained in an alternative light
consistent with the findings of the empirical analysis on the relationship between business
associations and private investment.
In the last paragraph an explicit assumption was made about Japan being a model
of economic success. Before heading straight into a discussion about what caused this
success, this assumption deserves some comment. This is especially true considering that
in the last decade or so Japan has been a byword for economic “bust”. A rigid
22
bureaucracy, corrupt financial sector, and isolation from foreign markets have all been
cited as reasons for the country’s decline in recent times. These criticisms are most
certainly valid in their present context. Nevertheless they should not discredit the
country’s past triumphs. Indeed, from the end of the Second World War to the beginning
of the 1990’s, Japan was an exemplar of development. GNP per capita rose at an average
rate of 6.9 percent per year between 1946 and 1985. As the first of the East Asian
“miracle” economies, Japan would become a model for its neighbors and a global leader
in high-end industry. The period of post-war growth in Japan, then, is a highly
reasonable instance of economic success.
The source of this success has long been debated by economic and political
theorists alike. Despite differences in opinion, however, many have attributed some if
not most of the credit to industrial policy. Japan has long been touted as an archetype of
the “developmental state”. In the initial post-war years the country was an economically
ravaged place, with much of its physical capital destroyed and many of its people in
poverty. Rather than bolstering agriculture, textiles or small crafts, sectors that could
benefit from the low-wage production in which Japan had a comparative advantage,
policymakers instead turned to heavy manufacturing. Ultimately, some of the sectors that
succeeded most were initially “infant industries” benefiting from the sort of “greenhouse”
trade controls and subsidies anathema to classical economists. Japan’s automobile
industry, today the world’s largest, was one of those.
Yet industrial policy is not a form of economic management limited to Japan.
Indeed, many other countries attempted similar projects and failed at the same time that
Japan was seeing its greatest growth rates. The import-substituting industrialization (ISI)
23
policies undertaken by the governments of many Latin American countries spring to
mind. If industrial policy truly was the foundation of Japan’s triumph, than it was a
version of it tempered by a unique organizational style or set of practices.
Of those who have studied the Japanese economy, many argue that the secret was
in the close relationship and strong communication between state officials and industry
leaders. One half of this relationship was government, the body that actually formulated
policy. Speaking to this aspect, Chalmers Johnson (1982) posits that it was the existence
of a centralized and prestigious bureaucracy, with sweeping control over economic
resources, that promoted rapid development. The Ministry of International Trade and
Industry (MITI) was the “pilot agency” of this bureaucracy. As one of the two most
competitive ministries (the other was the Ministry of Finance) for college graduate
recruits, MITI naturally cultivated an abundance of brain-power within its ranks.
Evidence of this, Johnson argues, can be seen in its judicious support of particular exportled industries such as shipbuilding and consumer electronics.
Johnson is not the only one to give significant credit to MITI. Daniel Okimoto
(1989) too affirms the organization’s central place in Japan’s rise. Like Johnson, he also
puts an emphasis on MITI’s bureaucratic pedigree. His description of the elements that
made the organization successful, however, goes further. In addition to its elite
bureaucracy was MITI’s sweeping administrative control over most areas of Japanese
industry. This power was especially relevant in the early post-war period, when physical
capital was scarce. MITI oversaw allocation of foreign exchange and government
development loans, and was responsible for the imposition of trade controls and approval
of most subsidies to the private sector. This breadth of responsibility allowed the
24
organization to formulate a cohesive industrial policy. It was able to “[weigh] the
interests of one sector against those of others and [aggregate] the welter of diverse,
sometimes conflicting, demands into a comparatively coherent whole” (Okimoto, 1989, p.
114).
Most interesting for the purposes of this case study, though, is another major
element that Okimoto believes was crucial to MITI’s success. This element was the
Japan’s network of business associations, the other half of the close relationship between
business and government spheres. Though MITI was the primary channel for dialogue, it
was Japan’s business community, bound together in its web of associations, which
provided the points of access between both parties.
Okimoto describes three distinct group types through which MITI, and indeed
other government ministries, accessed industry leaders. These are keiretsu (company
aggregates), industrial associations and business federations. The term keiretsu translates
into something like “system” or “succession”. Keiretsu themselves can be further divided
into two major subgroups, kin’yuu keiretsu (financial keiretsu) and kigyou keiretsu
(enterprise keiretsu). Financial keiretsu are a “loosely knit, permeable set of industrial
networks, connected through cross-cutting cleavages” (Okimoto, 1989, p. 133). There
are few such keiretsu, and all involve a grouping of major companies centered around a
large city bank and a trading company. Companies in a financial keiretsu network obtain
relatively easy long-term credit access from their group bank. The unique practice of
cross-shareholding is also important to the structure of financial keiretsu. In 1981, the
average amount of stock in a given financial keiretsu company held by the other members
of the group in total was 25.5%. To a large extent, the group structure offers a manner of
25
financial risk protection from negative business cycle swings. Other benefits include a
high degree of informational exchange between companies.
In contrast to the financial keiretsu are the enterprise keiretsu. These groups are
based on linkages between a large manufacturing company or group of such companies
and the range of subcontractors, distributors, and other firms that operate both “upstream”
and “downstream” to close the supply loop. For instance, an automobile manufacturer
such as Honda is connected on one end to a chain of smaller businesses that supply parts,
and on the other to the distributors pushing its product on the retail market.
Another type of private business group is the industrial association, which
represents the interests of a particular sector. Examples include the Electronics Industries
Association of Japan and the Japan Chemical Industry Association. Industrial
associations work to promote intra-industry cooperation and project the needs of their
member companies.
The third major group is the business federation. These are groups such as Nihon
Keidanren (Japan Federation of Economic Organizations) and Nisshou (Japan Chamber
of Commerce) that unite a wide swath of firms from various industries under common
leadership. The Keidanren is by far the largest of these, representing over one thousand
major companies and industrial associations. It is organized into numerous
subcommittees that tackle different problems in the economy. The results of the
deliberations of these groups, in turn, are taken up by Keidanren leaders and
communicated to appropriate ministries within the government.
Each of these groups, Okimoto argues, was crucial for the success of MITI’s
industrial policy. All were forums through which firms could communicate their needs
26
and relay information about how macroeconomic trends were affecting industry. After
government formulated its policy response, these groups also acted as a vehicle of
dissemination, communicating public decisions back to the private sector.
This idealized picture of government-business dialogue has come under heavy
criticism in recent years. On one level, it is now evident that the back and forth between
business and government did not go on without its share of clashes of interest. Industry
leaders, especially in later years, often went against the wishes of state officials to pursue
avenues of business they felt had more potential, even if such moves cost them certain
policy benefits. During the 1960’s MITI encouraged a series of mergers between
automobile manufactures, supposedly to reduce competition and allow fewer firms to
produce more cars, taking advantage of greater economies of scale. Few firms complied
with this policy recommendation.
On a more general level, many academics have questioned the idea that a
centrally directed industrial policy was the source of Japan’s economic success. Most
criticism has been leveled at MITI, the very same monolithic institution that had been
praised by so many Western writers in the 1980’s. David Flath (2000), for example,
gives evidence to support the notion that MITI’s industrial targeting was misguided.
Citing a study by the economist Paul Krugman, he posits that the tax breaks and subsidies
granted to primary goods industries such as steel actually slowed development by
propping up sectors in which domestic producers could no longer profitably compete
after the mid-1960’s.
Some of MITI’s poorest decisions were invariably political ones. Like political
leadership in any other democratic state, the Liberal Democratic Party, governing
27
Japanese politics without interruption from 1955 to 1993, naturally developed entrenched
voter bases that it sought to retain through patronage. Ministry bureaucrats, in turn, were
often forced to construct policies benefiting industries with concentrations of political
constituents irregardless of the potential of these industries for future success. MITI
subsidies to the Japanese coal and textile industries are two examples of this phenomenon.
Yet political favoritism was not the only instance of support for unproductive
industries. Indeed, many of MITI’s policy failures were made with the full intent of
bolstering economic productivity. Okimoto (1989) himself points to a variety of
industries, including commercial aircraft, aerospace and petrochemicals, that failed
despite sustained aid from the public sector. Moreover MITI sometimes proved unable to
see potential in firms that would turn out to be the greatest engines of economic growth.
Its attempt to cartelize the automobile industry, highlighted earlier, was a specific
reflection of this. It is thus evident that MITI and government policy were not infallible
and did not always “pick winners”.
The results of the empirical study in this paper would also seem to provide some
support in favor of rethinking Japanese industrial policy. In the results section it was
shown that business associations do not have a significant influence on public investment.
This calls into questions typical ideas about the information effect, and suggests that it
might not have been the close interaction between government and business that was at
the heart of Japan’s economic success.
As discussed at the end of the empirical study, one way to redeem the information
effect may be to look at the influence that business associations have on private
investment. Indeed, perhaps somewhat coincidentally, Japan has seen continuously high
28
domestic savings rates since the end of the Second World War. Over the past four
decades these rates have hovered at an approximate average of 33 percent of GDP. Most
of this has been spent in private investment in the form of fixed capital expenditures.
It does not seem farfetched to hypothesize that business associations might have
played a strong role in bolstering the efficacy of private investment during Japan’s
development. For example, the financial keiretsu, it will be recalled, provide a network
of financial and logistical support through cross-shareholding, informational meetings
and other means of inter-firm exchange. They are also unified around a central city bank
that acts as the greatest source of lending for member companies. These characteristics
may have contributed to the success rate of investment in the long-run, as members
facing financial strain were supported through emergency loans, preferential trading and
other measures in the event of credit problems. At worst they would be restructured or
reorganized in some other format within the keiretsu group. The point is that ailing firms
were saved from total failure, a situation that would result in a total waste of invested
resources.
Even in the case of keiretsu, , however, counter-arguments exist. Indeed, some
have argued that keiretsu, rather than simply “tiding over” good companies experiencing
short-term financial problems, actually kept afloat companies that could not conceivably
be productive. If this is true then it becomes more difficult to identify a “uniqueness” in
Japanese business associations that might explain at least part of that country’s miracle
growth in the post-war period.
More generally, it may be that some of the reasoning given in the last section to
explain the interaction between business associations and private investment also applies
29
in the case of Japan. The ability of associations to act as forums of discussion between
companies and industries, or as signal mechanisms to private investors is something that
has not been significantly explored in economic literature, much less in the economic
literature on Japan. When juxtaposed against the findings presented in the empirical
study here, these ideas present interesting avenues for future research.
30
CONCLUSION
This paper began with the general goal of clarifying the role of business
associations in economic activity. As with many studies, it seems that even as certain
questions are answered new ones arise. The overall effect of business associations
remains unclear. Nonetheless, novel insights have appeared to challenge old assumptions.
In particular, though lobbies do not seem to have a significant influence on public
investment, they do appear to have a positive and significant effect on private investment.
This finding poses a direct challenge to typical conceptions of the “information effect”,
which argue that business associations bolster government policymaking through the
transfer of crucial economic knowledge to public officials. In place of this interaction
between business and government, a new kind of information effect was hypothesized in
the results section. This hypothesis is based on the idea that business associations may
serve as a forum within which dialogue between companies and industries can occur,
and/or as a sort of ranking mechanism providing points of distinction or comparison
between different companies.
Business associations are found in many forms and take on many roles. They are
a complex form of organization. This paper tested some generalized ideas about business
association activity and in turn produced generalized but surprising results. The case
study of Japan was an attempt to provide a concrete example to complement the more
general findings of the empirical analysis.
Future studies would do well to narrow the frame of reference and explore certain
facets of the debate laid out here. Of particular interest is the influence of business
association on private investment, a relationship observed in the empirical results.
31
Though some potential explanations for this influence were provided, it remains to be
seen whether these explanations are in fact robust. Moreover, there may be other lines of
reasoning to support the interaction between business associations and private investment
that have not yet been proposed.
Regardless of which hypotheses are ultimately tested, a crucial imperative for
research on this topic remains to acquire more detailed information about the extent of
business association activity. Obtaining figures for the number of major associations in
each industry and/or the average size of associations in a given country would be a good
starting point. Other highly useful information for each country would include the
average yearly expenditure of business associations in each industry and across the whole
economy, and the average number of times per year that associations call meetings of
their members.
Any data along these lines would be of tremendous aid to future research on
business associations. Indeed, without it, it will be extremely difficult to learn more
about a phenomenon that seems to have such a real and important effect on economic life.
32
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34
Appendix 2.A – The WVS survey questionnaires for 1990 and 1995-1998
Copy of the 1990 World Values Survey questionnaire, subsection on membership in voluntary
organizations.
Please look carefully at the following list of voluntary organizations and activities and say…
a) which, if any, do you belong to?
(CODE ALL ‘YES’ ANSWERS UNDER (a))
b) which, if any, are you currently doing unpaid voluntary work for?
(CODE ALL ‘YES’ ANSWERS UNDER (b))
Belong to
(a)
V19 Social welfare services for elderly, handicapped
or deprived people
V20 Religious or church organizations
V21 Education, arts, music or cultural activities
V22 Trade unions
V23 Political parties or groups
V24 Local community action on issues like poverty,
employment, housing, racial inequality
V25 Third world development or human rights
V26 Conservation, the environment, ecology
*V27 Professional associations
V28 Youth work (e.g. scouts, guides, youth clubs, etc.)
V29 Sports or recreation
V30 Women’s groups
V31 Peace movement
V32 Animal rights
V33 Voluntary organizations concerned with health
V34 Other groups
35
Do unpaid
Work for
(b)
0.010418
V35 None
V 36 Don’t Know
*Variable used in the current paper
Copy of the 1995-1998 World Values Survey questionnaire, subsection on membership in
voluntary organizations.
Now I am going to read off a list of voluntary organizations; for each one, could you tell me
whether you are an active member, an inactive member or not a member of that type of
organization?
Active
Member
Inactive
Member
Don’t
Belong
V28 Church or religious organization
1
2
3
V29 Sport or recreation organization
1
2
3
V30 Art, music or educational organization
1
2
3
V31 Labor union
1
2
3
V32 Political party
1
2
3
V33 Environmental organization
1
2
3
*V34 Professional association
1
2
3
V35 Charitable organization
1
2
3
V36 Any other voluntary organization
1
2
3
*Variable used in the current paper
36