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PRIVATE AND PUBLIC SECTOR EXPENDITURES ON SOCIAL WELFARE:
AN EMPIRICAL ANALYSIS OF SIMPLE CROWD-OUT
Steven S. CuellarDepartment of EconomicsSonoma State UniversityPhone (707) 664-2305
E-Mail: Steve.Cuellar@Sonoma.eduWeb: http://www.sonoma.edu/users/c/cuellar/home.shtml
Preliminary VersionFebruary 22, 2004
Introduction
This paper examines the interaction between private voluntary contributions to
social welfare and government expenditures on social welfare for the years 1929-1991.
In particular, I examine the extent to which government social welfare expenditures to
the poor affect the level of voluntary private donations to the poor. The present research
has important implications for both the theory of private and public expenditures and the
much debated public policy ramifications of this theory.
For example, if government expenditures affect the level of private charitable
contributions, then increases in government expenditures may either increase or decrease
the total level of funds transferred to the poor. Thus, the extent to which government
contributions affect private contributions becomes a central concern. Consider first the
case in which government involvement in helping the poor is counter productive. This
will occur if a one dollar increase in government contributions reduces private
contributions by more than a dollar. In this instance the total level of contributions to the
poor falls as a result of government involvement. Thus, reducing government
expenditures on social welfare by one dollar will induce the private sector to increase
1 This analysis ignores efficiency issues regarding transfer programs.
2
contributions by more than one dollar thereby increasing the total level of expenditures
on the poor.
Consider next the case in which government expenditures to social welfare
increase the total level of contributions to the poor. This will occur if a one dollar
increase in government contributions to the poor, reduces private contributions by less
than one dollar. In this case the total level of contributions to the poor increases as a
result of government involvement. Conversely, in this case reducing government
contributions by one dollar will induce private contributions to rise by less than a dollar
thereby reducing total expenditures on the poor. Government tax and transfer programs
are thus effective in increasing the well being of the poor.1
Methodology
The paper follow the general methodology of Roberts (1984) who examines the
simple crowd-out hypothesis for the period 1929-1935. I begin first with a presentation
of a more generalized micro-theoretical model of private charitable contributions than
that presented by Roberts. A model of government spending is then introduced which is
eventually combined with the voluntary contributions model to determine the political-
equilibrium level of government spending. A review of the Roberts analysis of
depression era spending is next, followed by a graphical analysis of the present data.
Econometric analysis of the data is then presented. Finally, results of the study are
examined along with the subsequent policy implications.
3
A Model of Private Philanthropy
Consider first an impure public goods model of private philanthropy as examined
by Steinberg (1986) and Andreoni (1989). The economy consists of n consumers, with
well defined inter-dependent utility functions in which the level of consumption by the
poor enters the utility function of the non-poor. That is, it is assumed that consumption
by the poor is seen as a public good by the non-poor. Like the pure public goods model,
the impure public good model initially consists of only two goods, a private consumption
good x and the total level public good G. However, unlike the pure public goods model,
in addition to deriving utility from the two goods x and G, the individual contributors
may also derive utility from the act of contributing to the public good. That is, the act of
contributing essentially becomes a third good. Thus, if gi is individual i�s voluntary
contribution to the public good, then individual i's utility can then be represented by the
following three good well behaved utility function:
(7) . Ui ' Ui (xi , G, gi )
Assume consumers are endowed with an exogenous endowment ωi , which is
allocated, after taxes, between the two goods xi and gi . Endowments are taxed at the
rate t with tax revenues costlessly transferred to the public good. Total government
transfers to the public good are then denoted Tg =Gtωi for all i. The sum of voluntary
contributions by those other than I are denoted by G-I =Ggj for j…i. The total level of the
public good is then G = gi + G-i + Tg . The individual budget constraint can then be
written as:
(8) G ' Pg [ ωi(1 & t) & xi ] % jj…i
Pg[ωj (1 & t) & x] % PT jn
i ' 1ωit
2 For a detailed exposition of the comparative statics, see Chapter I.
3 Note that the model of impure altruism will result in a lower level of crowdingout then the pure public goods model used by Roberts. See Chapter I for a morecomplete discussion of this issue.
4
Where gi = ωi (1-t) - xi , G-I = ωj (1-t) - xj and Tg = 3ωi t . Pg and PT are the cost of
transferring voluntary and government contributions respectively. Set Pg and PT equal to
one (i.e., assume both private and public contributions are made costlessly). Assuming
non-cooperative Nash-Cournot behavior, individual economic agents will maximize the
following inter-dependant utility function:
(9) Maxxi , G , gi
Ui ( Xi , G , gi )
subject to the budget constraint:
(10) G' [ ωi (1 & t) & xi ] % jj…i
[ ωj (1& t) & xj ] % jn
i ' 1ωi
Recall from chapter one that optimization of (9) subject to (10) gives us the conditional
demand for charitable contributions of the form:2
(11) .gi ' gi (ωi (1&t), G& i , TG )
Assume initially that government transfers are zero (i.e., TG =0). In this case,
Nash behavior of economic agents and non-excludability of the public good results in
under provision of the public good.3
A Model of Government Expenditures
Consider now a model of government redistribution. Assume that the
equilibrium amount of government redistribution is determined by a process of
competing political groups. Suppose the government maximizes the following political
function:
4 This model, used by Roberts, was developed by Becker (1983).
5 Inter-dependant utility functions are not a sufficient condition for an upwardsloping utilities possibilities frontier. Charitable contributions will increase the utility ofboth economic agents, only when the marginal benefit of contributing is greater than the
5
Figure 7Political-Economic Equilibrium
(12) P=P(Ui ,Up) where MPMUi
, MPMUP
> 0
The function P depends on the level of utility of its poor and non-poor constituents.
Political competition among the poor and non-poor ensures that P gets maximized. The
function P then produces convex iso-support curves in utility space. The iso-support
curves show a measure of utility among the poor and non-poor that keeps political
support constant.4
We can now combine the model of private philanthropy with the model of
government redistribution. Inter-dependent utility functions create an upward sloping
portion of the utilities possibilities frontier such as that shown in Figure 7.5 A convex
marginal cost. That is, when a one dollar contribution to the poor provides more thanone dollars worth of benefit.
6 Note that if the poor have no political power (i.e. if MG/MUP <_ 0).
6
iso-support curve, such as that indicated by the curve I0 , is also illustrated in Figure 7.
Consider first a Nash-Cournot solution such as that represented by the point E1 in
Figure 7. Point E1 represents an equilibrium point in the absence of government. The
non-poor's most preferred point E*, an efficient allocation, is also shown. Note first that
all points on the increasing portion of the utilities possibilities frontier, that is all points
to the left of E*, are inefficient (i.e., all points to the right Pareto dominate points to the
left). That is both the non-poor and the poor can be made better off by further
contributions increasing the consumption of the poor. Points beyond E* however are
all Pareto-efficient. In order to increase the utility of the poor you must decrease the
utility of the non-poor.
A political equilibrium occurs where the highest attainable iso-support curve is
tangent to the utilities possibilities frontier, at a point such as EP . Note that the political
equilibrium Ep is beyond the non-poor's most preferred point E*. To see why, assume
first that the poor have no political power.6 In this case the iso-support curves will be
horizontal and the non-poor's most preferred point will be E*. Because of the public
good aspect of the poor's consumption, even in the case where the non-poor outnumber
the poor or similarly where the non-poor have more political power than the poor, the
non-poor would still choose a policy of redistribution. If the poor have any political
power, the iso-support curves will be convex to the origin, and will thus be tangent to the
7 The term �over-provision� used by Robert's may be misleading. Recall that allprovisions beyond E* are Pareto optimal. Thus, although points beyond E* are beyondthe non-poor's most preferred point, they are still efficient.
7
utilities possibilities frontier at a point to the right of E*, resulting in �over-provision.�7
Suppose now, however, that the non-poor have no political power (i.e. MG/MUi <_
0). In this case the iso-support curves will be vertical. Because the poor are only
concerned with their own consumption, they would choose to maximize their own
utility. That is the iso-support curves would intersect at a corner point along the
horizontal axis, for example at point E2 in Figure 7, where the utility of the non-poor is
zero.
Political-Economic Equilibrium
In the simple crowd-out model the political economic equilibrium results in a
level of government expenditures beyond the non-poor's most preferred point. What are
the implications of this result for the level of private contributions? In the simple pure
public goods model of Roberts, in which government expenditures crowd-out dollar for
dollar private contributions, private charitable contributions go to zero. That is, in order
to increase the total level of spending on the public good beyond the Nash equilibrium
level, the government must completely crowd-out private sector contributions. These
results, however, are due to the restrictive assumptions used to arrive at dollar for dollar
crowding out.
In the model of impure altruism, government contributions only partially crowd-
out private contributions. Thus, at the margin government transfers will increase the
total level of expenditures to the public good beyond the Nash level. However,
8
depending on the Nash equilibrium level of private contributions, the political
equilibrium may result in a considerable increase in the total level expenditures to the
public good. For example, suppose the political equilibrium results in a total level of
expenditures of EP shown in Figure 7. This would still be significantly beyond the initial
Nash equilibrium level of private contributions of E1 or the non-poor�s most preferred
point of E*. Consequently, although positive private donations may exist at levels of
spending just beyond the Nash equilibrium, for large discrete expenditures by the
government considerably beyond the Nash level, the total level of private contributions
may approach the complete crowding out results obtained by Roberts.
The implications of the political equilibrium arrived by Roberts from the simple
form of the pure public goods model are thus applicable, with some qualifications, to this
analysis using the model of impure altruism. Specifically, Roberts concludes that:
(a) at the political equilibrium, private contributions are [or will be near] zero.
(b) private contributions first became negligible when the government first
intervened in a �significant� way in the charity market.
(c) at the political equilibrium, the government �over-provides� for the poor.
(d) once an efficient allocation is reached, marginal reductions in social welfare
spending will be ineffective in inducing a crowding in of private charitable
contributions.
The Roberts Paper
Roberts (1984) provides an examination of the crowding out of private charitable
giving and public expenditures in 120 urban areas in the United States for the
9
period 1929-1935. This period is especially important in that it presents a picture of the
private sector prior to the significant government intervention of the depression era.
Figure 8 shows a graphical representation of the Roberts data.
Figure 8 provides a clear picture of the crowding out theorem predicted by the
model. Note that initially, private contributions increase as government expenditures
increase. This could be a response by the private sector to the growing despair of the
Great Depression, and as such would be consistent with the assumption of inter-
10
Figure 8Private vs Public Expenditures for 120 Urban Areas 1929-1935
(Thousands of 1920 dollars)Source: Roberts (1984).
dependent utility functions. An alternative explanation may be the so called
�demonstration effect.� The demonstration effect occurs if government expenditures
demonstrate to the private sector a need for giving. The crowding out effect, however,
soon dominates any other effects as government expenditures increase significantly. As
government expenditures increase by nearly 3000% from 1929-1935, private
8 See F. G. Dickinson, The Changing Position of Philanthropy in the AmericanEconomy (1970).
9 Recall that the Roberts data is for 120 urban areas in the U.S.
contributions fall drastically (i.e., are crowded-out). Note, however, that private
contributions do not go completely to zero as the pure public good model predicts.
Roberts argues that this is due to the aggregate nature of the data. Because aggregate
data on private charity does not accurately distinguish between contributions directed to
social welfare uses and those directed toward more amenity oriented uses, it is difficult
to examine how private charitable contributions directed toward strictly social
redistributive purposes react to increases or decreases in government expenditures. The
aggregate nature of the data thus hides the changing structure of private philanthropy
towards more amenity oriented uses and away from redistributive purposes.8
Consequently, Roberts argues that the portion of private charitable contributions actually
reaching the poor is effectively zero. Positive levels of private contributions in the face
of massive government expenditures is also consistent with the impurely altruistic model
of philanthropy: Individuals will continue to give for purely self-interested motives.
Figure 9 provides an alternative view of the Roberts data which further illustrate
the reduction in private contributions. Figure 9 shows private charitable contributions as
a percent of total (private and public) expenditures on social welfare programs for the
Roberts data.9 As can be seen in Figure 9, private contributions as a percentage of total
expenditures initially increase following the onset of the Great Depression. However,
large increases in government expenditure (147.29% and 126.87% in 1931 and 1932
respectively) along with reduced private contributions eventually reduce the relative
10 Note that Roberts' analysis ignores any changes in the tax rate or deductibilityof charitable contributions (i.e. the cost of contributing) and changes in aggregateeconomic variables.
Figure 9Ratio of Private to Total Contributions 1929-1935
Source: Roberts (1984)
share
of private contributions to near zero. Thus, Roberts concludes, the private sector has
been effectively crowded-out of the market for charity.10
This chapter, in addition to using a more generalized model of private charity,
extends the period of analysis from 1929-1991. In doing so, I am able to examine the
period immediately before and after the Great Depression to see how the private sector
11 For a description of how estimates of charitable contributions are made seeGiving USA, or for a more detailed explanation see Nelson (1993).
12 The private data is initially only available in five year intervals for the years1930, 1935,1940,1945,1950 and 1955.
3
reacts to both increases and decreases in government spending. In addition, I examine
two other periods in which large discrete changes in government expenditures occur: The
Kennedy-Johnson �Great Society� programs of the late sixties and early seventies, and
the �Reagan cuts� of the 1980's.
The Data
The data used in this research to analyze the interaction between private
charitable contributions to social welfare and government expenditures on social welfare
comes from two separate sources. The data on private charitable contributions comes
from the American Association of Fund-raising Counsel's annual, Giving USA. The
American Association of Fund-raising Counsel was established in 1935 and has
maintained statistics on private philanthropy starting in 1930 to the present.11 It should
be noted, however, that the data on private philanthropy is incomplete for the period
1929-1955.12 Giving USA classifies data on private charitable contributions into eight
broad categories. These include: religion, education, health, human services, arts &
culture, public/society benefit, environment/wildlife, international affairs and
unclassified. Table 3 shows the human services segment while Table 4 shows the
remaining categories. Along with each category, the corresponding National Taxonomy
of Exempt Entities codes is shown.
The human services segment appears to represent the sort of charitable
13 Roberts uses the human services data from AAFRC in his paper.
14 Note that the Arts and Public/Society begin in 1955 rather than 1930. This iswhen Giving USA began keeping data for these categories. Also, because Giving USAonly began keeping data on the Environment/Wildlife and International categories in1987, both of these categories are aggregated into the category �Other.� Since theseareas are not of concern for this study, this does not pose any problem.
57
contributions that are the most related to the current research .13 That is, the human
services portion provides the best measure of private charitable contributions aimed at
social welfare programs and is thus shown separately in Table 3. As can be seen from
Table 3, human services includes a large number of programs aimed at aiding the poor
including nutrition, housing employment and homeless programs. In its breadth,
however, the human services section also includes charitable contributions to programs
that may benefit the non-poor. Specifically, contributions to human services include
those contributions going to organizations that fall under categories I (public protection),
J (employment/jobs), K (food, nutrition & agriculture), L (housing/shelter), M (public
safety/disaster preparedness & relief), N (recreation, leisure, sports & athletics), O (youth
development) and P (other human services) of the National Taxonomy of Exempt
Entities. If those categories not aimed directly to the poor could be eliminated, a more
accurate measure of charity could be obtained. Unfortunately, contributions to each
subcategory are not readily available, thus precluding any further refinement of the data.
From the data that does exist, a clear picture of the structure of giving in America
can be examined. Figure 10 shows a graph of each category, along with total giving to
all categories in constant 1991 dollars.14 The last panel in Figure 10 shows a graph of
total giving. From Figure 10, it can be seen that total giving has been rising steadily over
58
the entire period 1930-1993. Note also that contributions to the arts, education, health
and religion rose fairly steadily over this period, with religious contributions having the
least variability. The same cannot be said of human services. Although contributions to
human services follow a general upward trend, Figure 10 shows that they tend to vary
more drastically than any of the other categories. Determining why this variation occurs
is the central purpose of this research.
Figure 11 shows each category of charitable contributions as a percent of total
private charitable contributions. Figure 11 shows how the structure of giving has
changed over time. For example, although contributions to the arts consists of less than
ten percent of total contributions, their share of total contributions has been increasing.
Contributions to education which have been steadily increasing over the entire period
have experienced drastic increases and decreases in their share of total contributions.
Contributions to health, while increasing steadily over the entire period, have remained a
relatively constant share of total contributions. Religion, the largest category of
charitable contributions in both dollars and as a percent of total contributions, although
rising relatively constantly over the entire period, exhibits relatively large fluctuations in
its share of total contributions. Human services, while following an upward trend in
giving shown in Figure 10, has been falling as a percent of total giving. In addition,
human services has exhibited large fluctuations in its share of total giving. Contributions
to public/society which have been increasing since 1955, have also been increasing as a
share of total contributions. Figures 10 and 11 provides some insight into how the
structure of private charity has changed over time. The implications of these structural
15 Data in one issue of the Statistical Abstract of the United States did notalways coincide with data recorded in other issues. For example, data for 1960 in the1970 SAUS may be different from data recorded for 1960 in the 1971 issue of theSAUS. The Historical Statistics of the United States provided a partial solution to thisproblem for the years up to 1970. However, for years after 1970, when discrepanciesdid occur, the most recent data was used with the assumption that the most recent data isthe most accurate.
16 This conforms closely to Browning and Browning�s (1994) measure of welfarewhich includes, AFDC, SSI, the earned income tax credit, medicaid, food stamps andhousing assistance.
60
changes for the current research and whether the model of crowding out can explain
some of these changes will be examined more closely below.
The data on public or government expenditures to the poor since 1970 are taken
from various issues of the Statistical Abstract of the United States. Prior to 1970 the
data is taken from the Historical Statistics of the United States.15 The Social Insurance
and Human Services chapter of the Statistical Abstract provides data on Social Welfare
Expenditures. The Public Aid portion of the Social Welfare Expenditures section is the
measure of public expenditures used in this study. The Public Aid section includes many
of those expenditures commonly referred to as �welfare.�16 Table 5 provides a
description of the programs included in the Public Aid section of the social welfare
programs used in this research. These include, Public Assistance including aid to
families with dependant children (AFDC), Medicaid, Social Services, Supplemental
Security Income, the Food Stamps and other public aid expenditures.
This category of public expenditures appears to be the most comparable to the
private contributions data. For the simple crowd out model of Chapter II, the data for
federal, state and local public aid expenditures are aggregated together. In Chapter III,
17 Kingma (1989) provides a discussion of some of the potential problemsassociated with examining crowding out data. This paper also presents a brief descriptionof alternative models of private philanthropy.
61
when the joint crowd out model is introduced, federal expenditures are separated from
state and local expenditures.
Additional data on income, poverty, age, population and education was taken
from various sources of the Statistical Abstract of the United States and the Economic
Report of the President. Data on the distribution of income was taken from various
reports of the Current Population Survey.
Data Limitations
In examining the interaction between private voluntary contributions and public
expenditures to social welfare there are certain problems arising from data limitations.17
To begin with, there is a problem of disaggregating the data. That is, we must first
distinguish between those social welfare contributions/expenditures that are directed
toward increasing the well being of the poor and others that may be more amenity
oriented. For example, charitable contributions to help the homeless are considered as
increasing the well being of the poor while charitable contributions to the local opera are
not. This problem is most evident in the data on private charitable contributions. As
noted above, the Human Services segment includes not only charitable contributions to
the poor, but also contributions that go to programs like disaster prevention and relief,
recreation and athletics, many of which may benefit the non-poor. Consequently, the
data on private charity may not only overstate private charity to the poor, but may also
18 This has been well documented in for example, Dickinson's, The Changing Position of Philanthropy, op. cit.
19 For example the National Survey of Philanthropy, used by Schiff (1985),provides data on reported charitable giving by type for 2,500 households for 1973.
62
dampen the response of charitable giving to changes in government spending.
In addition to finding an appropriate measure of charitable contributions to the
poor, the data on private charity must also be comparable to the data used for public
expenditures. That is, dollars spent on public sector social welfare programs must be
used comparably to dollars used in private sector social welfare programs. Accurately
matching private and public expenditures is perhaps the most difficult problem to
overcome. Compounding the comparability of data at any point in time, matching public
and private expenditures becomes increasingly difficult as the nature of philanthropy
changes over time.18 Inter-temporal comparisons increase the difficulty of comparability
since, as Roberts notes, �A dollar contributed to charity in 1929 bought a very different
bundle of services than it did in 1939.� As a result of the problems associated with the
data, one must be cautious in drawing implications from an analysis using aggregate
data.
The problems of using aggregate data notwithstanding, the benefits of using
aggregate data for the present analysis outweigh the costs. To begin with, dis-aggregated
data covering the present period of analysis 1929-1991 has not yet been found by this
researcher and may not exist. Thus, an analysis with a more comparable data set may not
be feasible. The few studies that use more closely matched data sets do not cover
extended periods of time and are thus not amenable to time series analysis.19 The present
63
Figure 12Private vs Public Expenditures 1929-1955
(Billions of 1991 dollars)
data set, however, provides a unique opportunity to examine critical periods in
government redistribution to the poor and their subsequent affect, if any, on private
charity. Thus, in spite of the limitations of using aggregate data, further economic
analysis may lead to some insight into the inter-dependence between private and public
expenditures towards social welfare.
Graphical Analysis
In this section, I provide a graphical illustration of public expenditures as
measured by the Public Aid segment of governments social welfare expenditures and
private contributions as measured by the Human Services segment of the AAFRC�s
annual Giving USA. Consider first, the period before and after the Great Depression,
20 If we allow for an initial increase in private sector contributions between 1930and 1935, after which private contributions fall to the 1935 level shown in Figure 12then we obtain results similar to Roberts.
64
1929-1955. Examination of this interval allows for a direct comparison with the Roberts
data. As noted earlier, prior to 1955 the private expenditures data is incomplete and thus
precludes any direct replication of Roberts' results. However, since the data does exist in
five year intervals between 1930 and 1955, tracing out the direction of contributions over
this period is easily accomplished. Figure 12 shows private and public social welfare
expenditures for the period 1929-1955 in billions of constant 1991 dollars. The heavy
dots in Figure 12 indicate the actual levels of private contributions while the straight line
connecting the dots represents a linear estimate of contributions between intervals.
At first glance increased government expenditures do not appear to affect the
level of private contributions. However, recall that the private contributions data is in
five year intervals. In the Roberts data, shown in Figure 8, private contributions initially
rise as government expenditures rise. That is, both private and public sector
expenditures rose at the onset of the Great Depression. Thus, the critical period in
examining the initial crowd-out of private expenditures occurs between 1930 and 1935,
for which the data is incomplete.20 Figure 12 does however show a clear picture of
private contributions �crowding back into� the market. Assuming that government
expenditures initially crowded out private contributions, Figure 12 illustrates the private
sectors
response to a significant reduction in public expenditures. That is, beginning in 1941
private charitable contributions increased sharply (i.e., crowded-back-in) as government
65
Figure 13Private vs Public Expenditures 1955-1980
(Billions of 1991 dollars)
spending fell precipitously in 1939.
Figure 13 includes the second period of interest, The Kennedy-Johnson �Great
Society� era of social spending and the �War on Poverty� beginning in 1964. As can be
seen from Figure 13, government spending on the poor remained relatively flat from
1955-1964. Over the same period private charitable contributions remained fairly flat,
albeit less stable than public spending. With the onset of the War on Poverty, however,
government spending on the poor increased drastically. Note again, as occurred in the
Roberts data, private contributions initially follow public spending. As with the onset of
the Great Depression, the initial increase in private charity could be explained by the so-
called demonstration effect. That is, government spending demonstrates to the private
sector a need to give to the poor. As with the Roberts data again, the demonstration
66
Figure 14Private vs Public Expenditures 1980-1991
(Billions of 1991 dollars)
effect is soon overwhelmed by the crowding out effect. Private contributions begin to
fall
in 1970 and continue to fall through to the mid 1970's. From 1970-1976, there is a clear
picture of crowding out. Additionally, as was illustrated in the post depression
reductions in social spending, as the growth rate of government spending significantly
reduced in 1976, private contributions again begin to crowd back in.
The final era of interest is the so called �Reagan cuts� of the 1980's. Figure 14
shows public and private spending for the period 1980-1991. Note first that the �Reagan
cuts� amounted to only a single reduction from 1981-1982. The reduction in 1982
amounted to approximately 13 billion dollars or a reduction of a little over 9% from the
67
Figure 15Private vs Public Expenditures 1929-1991
(Billions of 1991 dollars)
1981 level. Secondly, following the initial cut in 1982, the level of government social
welfare spending remained relatively flat. The average annual growth rate over the
period 1980-1989 was less than one-half of one percent. Over this same period, private
charity grew at an average annual rate of 3.9% per year. Initially, it appears that the data
over this period does not conform to the model very well. However, recall that one of
the conclusions by Roberts of the model of crowding-out is that the private sector will
respond to large discrete changes in public spending.
Although the Reagan cut of 1982 amounted to large dollar amount, they
amounted to only a 9% reduction. Furthermore, the cut of 1982 is considerably smaller
21 Chapter II, page 7, part (d).
68
than the reductions in spending that occurred in 1939 following the Great Depression
and in 1970 following the War on Poverty , both of which induced increases in private
sector giving. Thus, upon further inspection, Figure 14 can be explained by the model of
crowding out. As the model predicts, the marginal cuts of 1982's did not induce a
crowding in of private charity. However, beginning in 1989, as public spending
increased sharply, a clear picture of crowding out is again evident.
Figure 15 shows a graph for the entire period examined, 1929-1991. From the
graph you can easily identify the three periods of concern: The New Deal era following
the Great Depression, the Great Society spending of the late 1960's and early 1970's, and
the Reagan cuts of the 1980's. From Figure 15 and the previous graphs, several
preliminary inferences can be made. First, as Roberts argues, private charity does not
appear to respond to marginal changes in public expenditures.21 The relatively small
Reagan cuts the 1980's did not appear elicit a response from the private sector. Second,
large changes in public spending did appear to elicit changes in private charity. The
sharp reductions in spending following the Great Depression show clear signs of private
charity crowding back in. Similarly, the large increases in spending of the Great Society
and the sharp increase in spending of the late 1980's both show clear signs of crowding
out. As the data becomes available, it will be interesting to see if this most recent pattern
of crowding out continues.
Figure 16 shows private contributions as a percent of total contributions for the
entire period 1930-1991. In 1930, private contributions constituted just under 70% of
69
Figure 16Private Contributions as a Percent of Total Contributions 1930-1991
total contributions. However, as government expenditures increase during the Great
Depression, private contributions fell to just under 4% of total contributions by 1935.
These results are similar to those obtained by Roberts shown in Figure 9. Figure 2.8,
also
shows how private contributions crowded back in to the market for charity as
government expenditures decreased following the Great Depression. Private
contributions rose to 40% of total contributions following the reductions in the New
Deal
social welfare spending. However, the percentage of private contributions begins to fall
again in the mid 1950's and continues until the late 1970's, where the ratio has remained
under 10%. Note that there are two effects working to reduce private contributions share
70
of total contributions. First there is the decrease in private charitable contributions.
Second, there is the increase in government expenditures. The theory hypothesized here
is that increased government expenditures act to reduce private contributions. It should
be noted however, that the magnitude of the government expenditures tends to be of
much greater size than those of the private sector.
Regressions
This section provides an econometric analysis of the theoretical model developed
earlier and shown graphically above. Specifically, in this section, I examine the model
of simple crowd-out using ordinary least squares regressions. In the simple crowd out
model, I examine the interaction between total government expenditures on social
welfare, denoted TG and private voluntary contributions. Recall that TG is defined as the
sum of state, local and federal expenditures. In the next chapter, the model of joint
crowd-out is examined which separates the effects of state and local expenditures TS and
federal expenditures TF on private charitable contributions and the subsequent feed back
effects.
Dependent Variables
The dependent variable in the simple crowd-out model is the aggregate amount of
private charitable contributions directed toward social welfare purposes. This is
measured using the human services segment of charitable contributions from Giving
USA.
Independent Variables
22 Median family income produces both a higher t-statistic and adjusted R2 thanmeasures of aggregate income.
23 The assertion by Bergstrom et. al. that greater income inequality leads to moreprivate charitable contributions will be examined in more detail below.
71
The independent variable of foremost concern in the simple crowd-out model is
public expenditures on social welfare. This is measured by the Public Aid expenditures
by state, local and the federal government. In addition to public expenditures, there are
other factors that are hypothesized to affect the level of charitable contributions.
If charitable contributions to the poor are a normal good, than the greater the
income, the more will be given. Thus, income is expected to have a positive effect on
charitable contributions. The measure of income used in this study is median family
income. Median family income appears to capture the changes in average giving better
than aggregate measures of income.22
Because the simple crowd-out model is a model of inter-dependent utility, it
requires some measure of �need� or well being of the poor. Three measures of well
being are used in the regression equations The first is the percentage of the population
below the poverty level (PBPL). It is expected that the higher the percentage of the
population below the poverty level, the greater the giving. The next two variables used
attempt to capture some measure of wage inequality. Bergstrom, Blume and Varian
(1986) show that greater inequality of wages should lead to more charitable
contributions.23 Thus, to test this hypothesis I use the standard deviation of wages of as
an alternative measure of well being. The standard deviation of wages is used to
measure the spread or inequality of wages. The third measure used, again attempts to
24 A reduction in income will cause a reduction in charitable contributions ifcharitable contributions are viewed as a normal good by contributing agents.
25 See Clotfelter (1985) p.56 for a discussion on the merits of a price variable.
72
capture the inequality of wages. In this case, the difference in weekly earnings between
those at the ninetieth and those at the tenth percentile is used.
The price of giving is also expected to affect the level of giving. Because
charitable contributions are tax deductible, the cost of giving is usually measured using
tax rates. However, there are opposing effects. Higher marginal tax rates reduce the cost
of giving, thereby inducing more giving. But higher marginal tax rates also reduce
disposable income, thereby reducing giving.24 For the study at hand, the aggregate nature
of the data precludes the use of an accurate measure of the cost of giving. Additionally,
Clotfelter (1985) has shown that in previous empirical studies, �[charitable]
contributions are generally insensitive to variations in tax rates� and �that any price
effect of giving was bound to be small.� Thus, the absence of a price variable, is not
expected to create any problems.25
Finally, a vector X of other general population characteristics is also expected to
exert an influence on charitable giving. These include median age, age squared, median
education and the percentage of the population over the age of sixty-five. A population
variable is also included to extract any affects of an upward time trend.
The regression equation for the simple crowd-out model is specified as follows:
(13) PVTt ' β0 % β1PUBt % β2Incomet % β3PBPLt % β4Xt % ut
The regression results for the above model are shown in Table 3.
73
Regression Results (Simple Crowd-Out Model)
Table 6 shows the estimated coefficients resulting from ordinary least squares
regression of equation 13. The equation is estimated using the double log form, thus
allowing the estimated coefficients to be interpreted as elasticities. T-statistics are shown
in parentheses. Three variants of equation 13 are run using the three measures of need
mentioned above. From Table 6, it is clear that most of the variables have the predicted
sign and are generally statistically significant.
Consider first the primary variable of concern, public expenditures on social
welfare. For the first equation, the coefficient on public expenditures is negative and
statistically significant at the .05% level. Converting the estimated elasticity to a dollar
crowd-out parameter allows for a more direct comparison with previous studies. The
estimated elasticity is converted at mean expenditures to yield a crowd-out parameter of
$.045. That is, a one dollar increase in public expenditures reduces or crowds out private
charitable contributions by almost 5 cents. Note however that the two equations using
measures of inequality both produce higher coefficients. Converting these to crowd-out
parameters yields $.093 and $.06 for the equations using the standard deviation of wages
and the 90-10 differential respectively.
Table 6
Simple Crowd-Out Model Regression Coefficients
Constant Public Income Pov/Ineq. Over 65 Pop. Age R2
-299.017(-6.166)
-.426(-4.31)
2.548(3.274)
.865(2.282)
-15.289(-5.526)
15.363(5.605)
3.199(4.348)
.869
26 See Chapter I, Table 2 for a description of the source and type of data used therespective studies.
74
-467.535(-5.94)
-.885(-5.981)
1.288(3.758)
-2.42(-2.479)
-22.652(-5.87)
26.013(6.164)
5.516(4.918)
.85
-299.639(-4.792)
-.566(-5.218)
.837(2.444)
.290(.546)
-15.451(-4.492)
17.062(5.105)
3.216(3.358)
.81
The results shown in Table 6 are similar to those obtained by others using similar
aggregate data, including Reece (1979), Amos (1982), and Lindsey and Steinberg (1990).
For example, both Reece and Amos use measures of public expenditures nearly identical
to those used in this study. While Reece�s measure of private charity is more refined,
Amos uses an aggregate measure similar to that used in this paper. Although the results
obtained here are similar to the studies mentioned above, they are however considerably
less than those obtained by Abrams and Schmitz (1978, 1984), Pacque (1982), and
Schiff (1985, 1990) all of whom obtain results in the 30 cent range. The differences in
the resulting crowd-out parameters may be due to the differences in data sets used
between the two sets of studies. Both pairs of studies by Abrams and Schmitz and Schiff
analyze expenditures to social welfare using more refined measures of private and
public expenditures broken down by state and income.26
Another study of note is Kingma (1984) who obtains a crowd-out measure of
approximately fifteen cents. These results are for contributions to public radio which, it
could be argued, may not be motivated by the same factors that motivate contributions to
social welfare. In addition, Kingma uses a unique data set in which public and private
27 An income elasticity of one generally separates income inelastic necessitiesfrom income elastic luxury goods. The further from one the income elasticities gets, themore a good is considered a luxury good.
75
expenditures are nearly perfect substitutes, with private expenditures measured on an
individual level. Thus, the results of this study would be expected to differ from those of
Kingma.
The next estimated elasticity of concern is income. While all three regression
equations produced positive income elasticities, the equation using the percent of the
population below the poverty level produced the highest elasticity of 2.584, whereas the
equations using the standard deviation and the 90-10 differential produce elasticities of
1.288 and .837 respectively. Recall that a positive income elasticity indicates that
charitable contributions are a normal good, while an income elasticity greater than one
indicates that charitable contributions are fairly sensitive to changes in income
suggesting that they considered are a luxury good.27
The demand or need for charity is examined next. The coefficient of regression
one using the percent of the population below the poverty level produced a positive and
statistically significant coefficient, which is consistent with the inter-dependant utility
model and with most previous empirical studies. The regression using the standard
deviation of wages produced a negative coefficient which is the opposite of what you
would expect with the inter-dependent utility model. While the regression using the 90th
- 10th percentile wage differential produces a positive coefficient which is consistent
with the theory of inter-dependent utility and with the empirical analysis of Hochman
and Rodgers (1973), the estimated coefficient is statistically insignificant.
76
The remaining variables produced the expected coefficients and are all
statistically significant. Charitable contributions are expected to increase with age up to
the critical age of retirement of 65, after which charitable contributions are expected to
decline. As expected, age and age squared produced positive and negative coefficients
respectively. Likewise, the coefficient for the variable measuring the affect of the
percent of the population over the age of 65 was negative. Finally, the estimated
coefficient for total population was effective in extracting the positive time trend.
77
Figure 17Indexed Weekly Wages 1963-1991
(1964=1)
Giving and the Distribution of Income
In this section, I examine an issue concerning charitable contributions and the
distribution of income. Specifically, I examine how giving changed as the distribution of
income has changed. This analysis is a direct extension of Bergstrom, Blume and
Varian�s seminal 1986 paper on public goods. More precisely, I examine Theorem Five
28 Bergstrom, Blume and Varian (1986) pg. 43.
78
Figure 19Charitable Giving and Wage Inequality 1963-1991
of Bergstrom et al which hypothesizes that, �as an economy evolves towards a more
equal distribution of income, we can expect the amount of public goods that would be
provided voluntarily to diminish.�28 The policy implications of this hypothesis are clear.
As voluntary contributions to the poor diminish, government contributions to the poor
becomes more important to increasing the well being of the poor. Conversely, if the
inverse of the above hypothesis is true, then one can conclude �that as an economy
79
moves toward a more unequal distribution of income, public good provision provided
voluntarily should increase.�
I begin first with an examination of income inequality in the U.S. and then
investigate the relationship between income inequality and private sector charitable
giving. Income inequality is examined using Current Population Survey data for the
years 1963-1992. In particular, I examine income for those earning at the ninetieth,
fiftieth (i.e., median) and tenth percentiles. The CPS income data used in this study
consists of men who worked full time (at least thirty five hours a week for at least forty
weeks per year) who were not self employed, in the military or in group quarters.
Figure 17 shows the natural log of weekly wages indexed to one for the years
1963-1964. As can be seen from Figure 17, wages rose for all three groups from 1963
until the early seventies. Wage earners at the 10th percentile began to fall precipitously,
while wages for those at the 90th percentile rose and those earning at the median
remained flat.
The rising inequality of wages has been and remains the subject of a considerable
29 See for example Juhn, Murphy and Pierce (1993) and Finis Welch (1993a,1993b).
30 Herrnstein and Murray provide an interesting albeit controversialinterpretation of the ramifications of rising inequality in their 1994 best seller The BellCurve.
80
Figure 18Measures of Wage Inequality 1963-1991
amount of research.29 In addition, the rising inequality of wages has also provoked a
great deal of concern over the socio-political ramifications of the rising inequality.30
What has not been examined is the effect of wage inequality on private charitable
31 The pattern of giving among different income groups also has significanttheoretical as well as policy implications, but is not examined in the present research.This issue has been examined by among others Boskin and Feldstein (1977), Reece andZieschang (1985), Schiff (1985), Brown (1987), Feenberg (1988), and Choe and Jeong(1993).
81
contributions.
Figure 18 shows two measures of wage inequality in the U.S., the standard
deviation of wages and the difference between the wages at the 90th and 10th percentiles.
Figure 18 clearly shows a rising inequality in weekly wage over the last thirty years.
From Figure 18 you can also see that both these measure of inequality over the period
from 1963-1992 are highly correlated.
Figures 17 and 18 indicate that wages have become more disparate over the last
thirty years. From the proposition in Theorem Five by Bergstrom et al, it follows that
charitable contributions should be increasing as wage inequality increases.31
To examine this proposition, Figure 19 shows private charitable contributions to
social welfare and the standard deviation of weekly wages for the years 1963-1991. As
can be seen, private charitable contributions to social welfare appear to be highly
correlated with the rising inequality of wages. That is, charitable contributions appear to
be increasing and decreasing as inequality has increased and decreased, thus conforming
to Bergstrom Blume and Varian�s Theorem Five.
Table 7 provides a summary of the relationship between wage inequality and
charitable contributions using several different measures of correlation including
32 Pearson�s product moment is the measure most commonly used whencalculating correlation coefficients. Pearson�s product reflects the closeness of fitbetween an ordinary least squares regression line and the data. In the simple twovariable case, the R2 coefficient of determination of OLS regression is the square of thePearson coefficient. The Pearson Product Moment for two variables x and y iscalculated as follows: r' j (xi&x)(yi&y)
j (xi&x)2 j (yi&y)2
33 Spearman�s rank provides a measure of correlation less resistant to outliersthan Pearson�s measure. The Spearman correlation is calculated in the same way as thePearson correlation except that the variables are converted to ranks from lowest tohighest.
34 Kendall�s tau like Spearman�s is a rank correlation used for small samples. For a discussion of the calculations used to derive Kendall�s tau and references see theSTATA reference manual volume Three page 173.
83
Pearson�s Product Moment32, Spearman�s Rank33 and Kendall�s Tau.34
Inspection of Table 7, shows that Pearson�s Product Moment, the most commonly used
measure of correlation, shows the highest degree of correlation, while Kendall�s Tau,
which is used for small samples, produces the lowest correlation coefficient.
Spearman�s rank correlation falls between the Pearson and Kendall measure of
correlation.
Interestingly, although there is a clear positive correlation between wage
inequality and charitable contributions, including the standard deviation of wages in
equation (13), the equation used to estimate charitable contributions, produces a negative
Table 7
The Correlation Between Wage Inequality and Charitable Contributions
Pearson�s Product Moment Spearman�s Rank Kendall�s Tau (τ)
.69 .5488 .4023
35 Recall from the discussion of section XIII showing the regression results andTable 3, that including the standard deviation of wages produced a negative coefficientwhile including the difference between the 90th and 10th percentile of wage earnersproduces a positive, but statistically insignificant, coefficient.
85
p=.0017 p=.009
coefficient, indicating that greater inequality reduces private charitable contributions.35
Testing the Model
Examining the link between private voluntary contributions and public
expenditures to social welfare naturally raises the question of causality. That is, does
government spending �cause� a reduction in private contributions? The theoretical
specification of the public goods model postulates the direction of causality as going
from public expenditures to private expenditures. The regression results (i.e., the
statistical specification of the model) thus far support the negative relationship between
these two variables. Further statistical analysis provides an opportunity to derive
additional measures of causality. These measures, however, are not without their
limitations. To begin with, determining whether one event causes another is difficult
from a theoretical perspective. That is, how does one determine what causes a person to
act in a specific manner (e.g., contributing to the poor). In addition, when testing
causality one must keep in mind the Latin dictum, �post hoc, ergo proctor hoc.� That is,
the fact that X precedes Y does not mean that X causes Y. Statistical analysis of
variables examines the correlation and precedence of one variable relative to another.
36 C.W.J. Granger (1969).
37 G.S. Maddala (1988) and J. Kmenta (1986).
38 G.G. Judge et al.(1985).
88
Thus, what can only be tested and subsequently ascertained is the precedence of X to Y
rather than the actual causality as it is normally understood. Although the term
�causality� is often seen as misleading, it has nevertheless remained a fixture in the
econometric literature and is used throughout this study with the proviso that its more
accurate definition is understood.
The first test for causality used is that developed by Granger.36 Specifically,
given two time series Y and X, Granger examines whether current values of Y can be
better explained by current and past values of X and Y, than by past values of Y alone.
In effect, what Granger attempts to distinguish between is the time trend effect of Y and
the relation between Y and X. Hence, it is maintained the series Xt fails to Granger
Cause Yt if, in a regression of Yt on lagged Y�s and lagged X�s, the coefficients of the
lagged X�s are zero. The length of the lag is not determined according to statistical
doctrine but rather is determined according to the theoretical specification of the model.37
In the context of public and private expenditures to social welfare, the regression
equation is specified as follows:
(14) lnPVTt'jk
i'1αilnPVTt&i%j
k
i'1βilnPUBt&i%Ui
Thus, if past and present public expenditures help to improve the forecast of private
expenditures, then public expenditures are said to cause in, the Granger sense, private
expenditures.38
89
The regression results of the direct Granger causality test are shown in Table 8.
A number of interesting observations can be made from the results in Table 8. To begin
with, the coefficients on the lagged public expenditures are generally very small and
statistically insignificant. More interestingly, although the lagged public expenditures
generally exert little influence, the coefficients on the one period lagged public
expenditures exerts the smallest effect on private expenditures, while the fifth period
lagged public expenditures exert the largest effect. Thus, expectations of future
government expenditures based on past expenditures do not appear to affect the level of
private contributions.
Although lagged public expenditures do not exert a significant effect on private
contributions, lagged private contributions appear to exert an even smaller effect. Again,
the coefficients are generally small and not statistically significant. Thus, past private
contributions do not appear to be a good predictor of present private contributions. The
overall results of the direct Granger causality test indicate that public expenditures fail to
Granger cause private expenditures.
While the public goods model used in this research postulates the direction of
causality as going from public expenditures to private contributions, examining the
causality running in the opposite direction ensures that the model is not mis-specified.
That is, do changes in private contributions �cause� changes in public expenditures?
The Granger equation for the reverse regression equation is specified as follows:
(15) lnPUBt'jk
i'1αilnPUBt&i%j
k
i'1βilnPVTt&i%Ui
The results of the reverse Granger regressions are shown in Table 9. Again, the
39 C.A. Sims (1972).
40 Maddala (1988).
90
regression coefficients are generally not statistically significant. That is, neither past
public expenditures nor past private contributions are accurate predictors current public
expenditures. Thus, the results of the reverse Granger causality indicate that private
expenditures do not �cause� changes in public expenditures in a Granger sense.
An alternative test used to examine causality is that developed by Sims.39 For the
Sims test of causality, you begin by examining the parameter coefficients on a regression
of private contributions on lagged, current and future values of public expenditures.
Based on the regression results, it is said that public expenditures fail to �cause� private
contributions if in a regression of private contributions on lagged, current and future
public expenditures, the latter coefficients are zero.40 What the Sims causality test
attempts to evaluate is whether predictions of private contributions from current and past
values of public contributions would be improved if future values of public expenditures
were included. The direct Sims regression equation is specified as follows:
(16) lnPVT'α0%jn
j'&kβjlnPUBt&j%ut
The results of the direct Sims causality test, shown in Table 10, are significantly more
favorable to the public goods model than the Granger test results. The coefficients on
the third, fourth and fifth period future public expenditures are all negative, and
statistically significant. That is, knowledge of future government expenditures improves
predictions of future private charitable contributions. Additionally, the inclusion of
future public expenditures increased the significance of past public expenditures. The
91
Sims Causality test appear to conform with the theory of rational expectations, which
assumes individuals use all available information in forming expectations. That is,
rational agent will not be solely backward looking in forming expectations, but will also
base expectations on current policies that may affect future government expenditures.
Thus, from the results of the Sims test, one can conclude that public expenditures do not
fail to cause private contributions.
Again, the reverse regression is run to test the direction of causality. The reverse
regression equation is specified as follows:
(17) lnPUB'α0%jn
j'&kβjlnPVTt&j%ut
The results of the reverse Sims causality test are shown in Table 11. As can be seen in
Table 11, the results of the reverse Sims test are generally not statistically significant.
Again, as with the reverse Granger test, we can conclude that private contributions do
not cause public expenditures on social welfare.
The results of the Granger and Sims causality tests are mixed. Although the
Granger test did not indicate a causal link between public expenditures and private
contributions, the Sims test did show that changes in future public expenditures
improved the predictions of private contributions.
Again, however, because of the data limitations the results of the regression
analysis should be taken with caution. The aggregate nature of the data and the
considerable difference in magnitude between the two sources of data create difficulties
in measuring the relationship and the causality between public expenditures and private
voluntary contributions to social welfare.
92
A Comparison of Altruism and Egoism
Recall that in the impure public goods model, there are both altruistic and
egoistic motivates that lead the non-poor toward philanthropy. However, it is altruism
that is generally considered the primary motivating factor in giving to the poor. In this
section I examine the relationship between private charitable contributions and
government expenditures when the benefits are more direct to the benefactor. That is
when egoism dominates altruism. In particular, I examine the relationship between
private charitable contributions to the arts and government expenditures in the form of
expenditures on the National Endowment for the Arts. The source of the data for private
charitable contributions to the arts were obtained from Giving USA, while the data on
public expenditures was obtained from the National Endowment for the Arts. Figure 20
shows a graph of public versus private expenditures on the arts (in billions of 1991
dollars) since funding began for the NEA in 1966.
93
Figure 20Private Contributions vs NEA Expenditures 1966-1993
As can be seen from Figure 20, public and private expenditures rose together
until 1979. In 1979 and 1980 NEA expenditures began a precipitous fall, while private
contributions continued to rise. Subsequently, in what may have been a response by the
private sector to the initial decrease in funding by the NEA , private contributions
increased dramatically in 1982 than fell back to their 1981 level in 1983. From 1984
onward private contributions continued to rise as NEA expenditures continued to fall.
As noted above, the model of impure altruism predicts that the more charitable giving
takes on an element of a private good, the less crowding out will occur. Thus, if
94
charitable contributions to the arts are motivated by egoism, then we should not observe
a significant amount of crowding out.
From Figure 20 you cannot discern any clear relationship between private and
public expenditures to the arts. From 1966 to 1979 public and private expenditures
appear to move complementary, as both increase. Then, from 1980 to 1983, private
contributions fall, while public expenditures continue to rise until 1982, then fall 1983
and
then begin to rise again. From 1983 on, private contributions fall while public
expenditures rise. Private and public expenditures appear to behave as substitutes over
this period. Note however that although private contributions maintained an upward
trend throughout the entire period, the rate of growth increased after 1982.
Private and public expenditures to the arts can be examined closer using the same
regression equation that was used to examine private and public expenditures to social
welfare. Substituting private contributions to the arts into the left hand side of Equation
7 and NEA expenditures on the right hand side produces the following equation:
(18) PVTt ' β0 % β1NEAt % β2Incomet % β3PBPLt % β4Xt % ut
The estimated coefficients for equation 2.9 are shown in Table 12. All equations are run
in log-log form. The results of the regressions shown in Table 12 are shown for three
income levels. Note first that the regression coefficient on NEA expenditures is positive
for all three income levels. In addition, none of the estimated coefficients are
statistically significant. The income coefficient is positive for wage earners at the
ninetieth and fiftieth income percentile, but negative for those at the tenth percentile.
95
Furthermore, only one of the income coefficients is statistically significant. The
coefficient on the percent of the population below the poverty level is positive for wage
earners at the ninetieth and fiftieth income percentile, but negative for those at the tenth
percentile. Again none of the coefficients are statistically significant. In general then,
there does not appear to be a discernable relationship between private contributions to
the arts and NEA expenditures for the period examined.
Table 12
Private vs Public Expenditures to the Arts Regression Coefficients
Constant NEA Income Poverty Over 65 Pop Age R2
-198.613(1.729)
.165(1.456)
1.174(1.279)
.293(.77)
16.341(2.409)
-8.237(-1.214)
-4.451(-2.109)
.96
172.425(1.343)
.098(1.02)
1.126(.721)
.233(.498)
17.01(2.167)
-5.53(-.774)
-4.656(-1.764)
.957
95.735(1.02)
.041(.483)
-.751(-.92)
-.192(-.565)
14.375(2.149)
.691(.142)
-3.604(-1.804)
.958
The preceding analysis demonstrates that giving to the poor is more amenable to
empirical analysis using the public goods model than giving to the arts. This does not
however imply that giving to the arts does not fit the model theoretically, but rather that
the confounding affects of altruism and egoism may be less evident in giving to the poor
than giving to the arts. That is, the egoistic nature of private contributions to the arts
results in contributions to the arts occurring independently of public expenditures.
Consequently, the correlation between private voluntary contributions to the arts and
public expenditures appears to be quite low and not statistically significant.
41 Recall that the dollar for dollar crowding out model of Warr and Roberts is aspecial case of the public goods model.
42 See for example Charles Murray (1984), Herrnstein and Murray (1994) andMarvin Olasky (1992) for a discussion of this point.
96
Conclusion
The simple crowd-out model using aggregate data appears to refute the results of
previous empirical analysis of crowding out. That is, the current research indicates that a
one dollar increase in government social welfare expenditures appear to result in a
reduction of approximately 5¢ in private charitable donations to social welfare rather
than the 30¢ that has been found in other studies. Thus, although the present analysis is
consistent with the partial crowd-out models, including the pure public goods model of
Bergstrom, Blume and Varian, the results of this study also fit impurely altruistic models
of Andreoni and Steinberg. The weak result of the poverty variable is especially
consistent with the impurely altruistic model. Conversely, the results of this study do not
lend support to the dollar for dollar crowd-out model of Warr and Roberts.41
Ignoring the efficiency issues, (i.e., whether the private sector is more efficient
than the public sector in allocating funds to the poor or vice versa) the policy
implications are quite clear. Cuts in government expenditures on social welfare reduce
the total (i.e., private and public) level of expenditures on social welfare programs. The
assumption, by those calling for reduced expenditures on social welfare42, that the
private sector will adequately compensate for government reductions is not borne out by
this research.
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