RICE. an Examination of the Median Voter Hypothesis

University of Utah

Western Political Science Association

An Examination of the Median Voter HypothesisAuthor(s): Tom W. RiceSource: The Western Political Quarterly, Vol. 38, No. 2 (Jun., 1985), pp. 211-223Published by: University of Utah on behalf of the Western Political Science AssociationStable URL: http://www.jstor.org/stable/448625 .

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AN EXAMINATION OF THE MEDIAN VOTER HYPOTHESIS

TOM W. RICE

University of Vermont

VO VER 100 YEARS ago Scottish historian Alexander Tytler wrote that in a democracy, "the majority always votes for the candidate promising the most benefits from the public treasury .. ." (Ty-

tler 1840). His conclusion still captures the interest of many scholars. For instance, in recent years the general theme of Tytler's statement has been advanced as an explanation for such varied phenomena as the collapse of democracies and government growth (Buchanan and Tullock 1962; Musgrave and Musgrave 1969; Brittan 1975).

But perhaps the best known use of the Scotsman's conclusion has been as an explanation for the increased efforts by governments in democracies to redistribute societal resources from the better off to the less advantaged. This explanation, commonly referred to as the "median voter" hypothesis, has evolved in part from the works of Key (1949), Schumpeter (1950), Downs (1957, 1960), and Buchanan (1967). In brief, the argument emerging from these studies runs as follows. In a democracy voters enter coalitions (political parties) "to use the state to confer benefits [usually income] on coalition members and dispense costs generally or to the voters not in the coalition" (Reynolds and Smolensky 1977: 95). More precisely, voters can be expected to vote for the political party which promises the largest increases in their incomes. It follows that in a two- party system, like the United States, the bottom 50 percent plus one of the voters on the income continuum will form the winning party, since this permits a greater redistribution of income than if the top 50 percent plus one formed the majority coalition (Reynolds and Smolensky 1977). The key voter in this case is the one makingjust at or above the median income, for it is he or she who must be enticed into the lower income coalition in order to ensure a majority coalition. Under the hypothesis, this would mean that the minimum income taxed must be set just above this voter's income and he or she must be included in the redistribution of benefits.

To be sure, the median voter argument has not escaped criticism. It does not allow for the possibility of the rich bribing some of the poor out of the majority coalition. It does not provide for more than a single criterion (usually income) to serve as the base for developing political alliances.' And maybe most damaging, "it fails to explain why redistribution [in

This is indeed one of the major criticisms of the median voter hypothesis. Redistribution in modern nations often includes more than just transferring incomes between individuals. For example, affirmative action regulations, job training programs, and student loans allow government to alter the distribution of wealth in society without directly transferring incomes. And, much of the redistributive efforts of charities, which often come in the form of goods rather than money, are not captured by measures of income redistribution.



212 Western Political Quarterly

democracies] has not been greater" (Meltzer and Richards 1977: 116). Still, the argument has a certain appeal. Political parties in most democracies are arranged roughly according to income distribution. And, the parties gaining most of their support from voters below the median income do tend to pursue programs favorable to the incomes of their constituents (Tufte 1978; Bunce 1980). So, although the median voter hypothesis has been criticized as being simple-minded and not applicable to the real world, there is evidence suggesting it does operate.

In this paper I attempt to detect systematically the operation of the median voter hypothesis using United States income data from 1947 to 1982. Initially, the concept underlying the argument is measured for empirical testing. This is followed by a time-trend analysis of this measure designed to indicate whether the hypothesis shows evidence of operating in the United States over the post-World War II years. Finally, a model is put forth to account for the variation in this measure over the 36 year span. It is important to note that this analysis is not meant as the definitive empirical test of the median voter hypothesis. The analysis performed here provides simply a small portion of the much needed empirical evidence testing the validity of the hypothesis.

MEASURING THE MEDIAN VOTER CONCEPT

As stated above, the median voter hypothesis contends that voters with incomes at and below the median income will use their superiority in numbers to elect politicians disposed to taxing individuals making above the median income and redistributing this wealth to those below the median. It is important to realize that all individuals at or below the median income benefit from the redistribution, ensuring continued income inequality. According to the median voter hypothesis, then, the equal distribution of income is not inevitable. Thus, measures of income distribution designed specifically to tap the degree of income equality, such as the Gini Index, are less than ideally suited for empirically testing the hypothesis.2 Instead, some measure better capturing the flow of income from those above the median to those below is needed.

Figure 1 diagrams such a measure. A post-tax income frequency curve, similar to the actual United States curve, is presented, along with indicators of the median and mean income levels. The curve is positively skewed, due to the relatively large incomes of a few individuals. This acts to pull the mean income up beyond the median income, opening a gap between the two. As explained below, changes in the size of this gap over time can be used to test the median voter hypothesis.

At first glance it might appear that under the hypothesis the gap would remain stationary in a society over time. This is indeed the case if we

2For example, suppose that after redistribution income was normally, but not equally distributed. Because income was normally distributed the median and mean would be identical, evidence that the median voter hypothesis operated. But the Gini Index would still register an unequal distribution of income, possibly even more unequal than prior to the redistribution.



An Examination of/ the Median Voter Hypothesis 213

FIGURE 1. A POST-TAX INCOME FREQUENCY CURVE

1

(r median

LL income IIm income

Income Level

assume: (1) every individual is aware of every other individual's location on the income distribution, including his or her own; (2) bribing is out- lawed; (3) the number of individuals in the society and their pre-tax annual income remain the same year to year; (4) the 50 percent plus one lowest income earners benefit equally from redistribution; (5) the top 50 percent minus one of the income earners are taxed equal amounts; and (6) all individuals vote. Under these restrictions, the mean will remain stationary since the number of individuals and total income remain unchanged. The median will also remain the same from year to year as those individuals rising above the median because of redistribution benefits are exactly offset by those falling below the median due to income lost to taxes. This process is illustrated in Figure 2. Frame 1 represents the income distribution in a society in a given year, with individual A making the lowest income and individual Y making the highest. For simplicity we will assume only one individual is located at each income slot (Ii .... Ij). Individual M makes the median income (MED), leading the lower income coalition to set the minimum income taxed (T)just above M but below N, attracting M and thus forming the winning coalition. Frame 2 shows the results of taxing everyone above T one income unit and redistributing to those below T one income unit each. That is, Frame 2 displays the post-tax and post-transfer income distribution given a minimum tax level of T and a tax of one income unit.3 The Frame shows that M, benefiting from redistribution and no taxes, moves above the tax line and joins 0, and N falls below the tax line and joins L. More importantly, the median income remains unchanged. Given the same minimum tax line (T), the median

3 It is true that there will always be one more individual receiving redistribution than paying taxes, so the income units taxed will be one short of what is needed for everyone below T to receive one. However, in a large nation, like the United States, all individuals below T could receive so very nearly a whole income unit in redistribution that we will assume they do for simplicity purposes.




will always remain the same regardless of the tax rate. If, for example, the annual tax rate increases to two income units, the resulting income distribution (post-tax and post-transfer) would be that of Frame 3. Those below T now gain more from redistribution and those above T lose more to taxes, but the median remains unaltered.

FIGURE 2. MEDIAN VOTER MODELS

MED

I k I Im In I o

Frame 1

Frame 2

Frame 3

Frame 2'

Frame 3'

Low High Income Level

The median income would increase, however, if we relax one of the assumptions, actually making our simple model more realistic. In any large society, individuals do not know their exact location in the income distribution, nor anyone else's. If the first assumption is altered to reflect this, it becomes clear that the less affluent will not know exactly where to place the minimum tax line in order to achieve the optimal 50 percent plus one majority coalition. Thus, the minimum tax line will probably be set somewhere substantially above the actual median income, but well below the maximum income. This assures a winning coalition can be formed of those below the tax line, and it assures that hefty redistribution benefits can still be had. Frame 2' shows the redistribution results of placing the



An Examination of the Median Voter Hypothesis 215

minimum tax line (T') well above the median income and taxing one income unit per individual. M now benefits from redistribution along with N, O, and others above the median but below T'. Since M's crossing of the median is not offset by any individual falling below the median, the median increases with M (to MED'). Furthermore, if the tax rate is increased, the median increases as well. Frame 3' shows this for a tax rate of two income units. Thus, as the majority coalition raises taxes over the years, the median will be pushed toward the mean.

The above illustration suggests that a closing of the gap between median and mean income would be strong support for the median voter hypothesis. Obviously, however, the real world is much more complex than our model, with many factors influencing median and mean income levels. The number of individuals in a society changes from year to year, as does total income; tax and redistribution structures are complicated, with most individuals both paying taxes and receiving public benefits; and knowledge is imperfect, not allowing those key individuals with the median income the luxury of knowing they hold the balance of power. In addition, not all individuals vote, complicating the task of constructing a minimum winning coalition; and elites often behave contrary to the wishes of their supporters. Still, the median voter hypothesis should not be rejected out-of-hand. While the hypothesis may seem too simplistic, something like it may operate in democratic societies such as the United States. Research indicates that individuals may not know their exact positions on the income continuum, but they do realize their general location (Campbell et al. 1960; Hamilton 1972; Marwick 1980). Further- more, this perceived general location is related to voting behavior. Lower income individuals are more likely to support the Democratic party as it generally favors greater redistribution than the Republican party (Campbell et al. 1960; Hamilton 1972; Pomper 1977; Jackman and Jackman 1983). Thus, a systematic closing of the gap between median and mean income levels in the United States would lend substantial credibility to the median voter hypothesis. Our attention now turns to examining this gap in the United States.

THE MEDIAN-MEAN INCOME GAP IN THE UNITED STATES

A straightforward method of measuring the size of the gap between median and mean income is to take the median as a percentage of the mean. This ratio, which is employed in this study, has the advantage of being sensitive to movement in both the median and mean, and controlling automatically for the effects of inflation. Figure 3 plots this ratio using United States family income figures from 1947 to 1982 (prior to 1947 the mean income data was not available on an annual basis). The plot reveals a sharp increase in the ratio from 1947 until the mid-1960s, and an equally sharp decline thereafter. In other words, the median voter hypothesis seemed to be operating until the mid-1960s, the period when the Great Society redistributive programs were implemented. From then on the median and mean pulled further apart. This is not consistent with what




would be expected. According to our model developed in the previous section, increases in redistributive programs should act to close the gap between the median and mean, not widen it.

FIGURE 3. RATIO OF UNITED STATES MEDIAN TO MEAN INCOME PLOTTED OVER TIME: 1947-82

91%

0 E

1 87%

u

cr

8.

_ 89%

E

c 87%

85% 1950 1960 1970 1980

Time

This counter-intuitive trend may be due in part to the data. United States median and mean income figures are calculated using pre-tax and post-transfer incomes.4 Ideally, post-tax and post-transfer figures would be used, but they are not available. Relying on pre-tax and post-transfer income figures results in double counting all transfers, or redistributive payments. Transfers are first counted as part of the gross income of all those individuals who will later have to surrender this money to taxes, and they are counted again as part of the gross income of those who receive them. This has the effect of raising the mean income, since the sum of all incomes is increased through the double counting. Thus, when pre-tax and post-transfer income figures are used, increases in redistributive programs may actually result in a widening of the gap between median

4Broadly, the transfers included as income consist of: (1) Social Security payments; (2) unemployment benefits, government employee pensions, and veterans benefits; and (3) public assistance or welfare payments. For a more detailed listing see: Historical Statistics of the United States, U.S. Department of Commerce, Washington, D.C., 1975, pp. 332-33. As mentioned earlier, these are clearly not the only redistribution programs. However, measuring the effects of other less obvious transfer programs is extremely difficult. For the purposes of this paper only the transfers outlined above are used.

@0

0

0 00 0

I ) I 0 0 @0go0

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0 00 00 0

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An Exlaminattion of the Median Voter Hypothesis 217

and mean income levels. The Great Society programs would be particu- larly likely to produce this widening gap, as their major purpose was to assist the poor. With the poor being the principal beneficiaries, the median would likely remain almost stationary, meaning any upwards movement in the mean would not be offset by an increasing median.

The unfortunate effect of using pre-tax and post-transfer income figures should be in part corrected by controlling for increases in transfers. If the gap between the median and mean income levels actually does increase as a result of growth in transfers, then controlling for transfers should leave a set of residuals which are relatively free of the effects of double counting. Equation 1 reports the results of regressing the median-mean ratio on the control variable real total per family social assistance benefits.

Y = 88.9 -.002 (SW) R2 = .03 (Equation 1) (-1.00)

Where Y = the ratio of median to mean income; SW = real total per family social assistance expenditures (from various volumes of Statistical A4bstract (of the United States, Department of Commerce, Washington, D.C.); and the value in parentheses = the t-statistic. The results suggest that changes in per family transfer totals account for little of the variation in the median-mean income gap. This conclusion is reinforced when the residuals from Equation 1 are examined. Although the residual plot is not shown, the disturbing parabola, peaking in the mid-1960s, is still promi- nent. The extent to which the residual pattern resembles Figure 3 is evident from a .98 correlation between the two. Evidently, the widening of the median-mean gap after the 1960s cannot be attributed to the effects of double counting transfers.5 We now turn to exploring other possible explanations for the variations in the gap.

DETERMINANTS OF THE MEDIAN-MEAN GAP

A number of forces could plausibly influence the size of the gap between United States median and mean income levels. Below, six such forces, or explanations, are discussed and operationalized for empirical testing. Following operationalization, multiple regression analysis is employed to assess the relative impact of each of these forces in account- ing for changes in the median-mean gap.

The first two forces to be examined might best be considered political explanations for changes in the gap. The first of these concerns the influence of partisanship on public policy. There exists a growing number of systematic studies indicating that parties supported by lower income

'Other evidence is congruent with this conclusion. United States Commerce Department quintile income distribution figures indicate that even after transfers, the poorest 20 percent of the families received an ever decreasing portion of total income over the 1965-1982 period (falling from a high of 5.6 in 1965 to a low of 4.7 in 1982), while the wealthiest 20 percent increased their percentage of the income (from a low of 40.0 percent in 1965 to a high of 42.6 percent in 1982).




earners more vigorously pursue policies designed to redistribute wealth from the affluent to the less affluent (Kerschen 1974; Winters 1976; Cameron 1978; Tufte 1978; Bunce 1980). For example, Tufte (1978) determines that the degree of income equalization is greatest in those democracies which have experienced extensive leftist control of their governments. This suggests that when the Democratic party controls the reins of government in the United States, redistributive programs should increase more rapidly than when Republicans are in power. In turn, increases in redistributive programs should increase the median income, thus closing the median-mean gap. Two variables are employed to test this explanation; a dummy variable coded 1 for years when Democratic presidents held office and 0 when Republicans were in office, and an annual interval variable averaging the percent of the House and Senate under Democratic control (percent of House Democrat plus percent of Senate Democrat divided by two). Both of these variables were lagged one year. So, for example, 1980 was considered to be the last year of the Carter presidency (coded 1) even though Reagan was elected during the year.

The second political explanation argues that policies benefiting the less affluent stem from increased voter turnout (Jacobs 1981). Since increased turnout usually means a higher turnout among the less advantaged (Erbe 1964; Asher 1980; Wolfinger and Rosenstone 1980), it is argued that redistributive policies favorable to these individuals should follow. Indeed, Stack (1978) demonstrated "that turnout was the strongest predictor of economic equality in the eighteen most indus- trialized democracies" (acobs 1981: 603). Turnout is operationalized as the percent of eligible voters going to the polls in the last presidential election.6 As with the other political variables, turnout is lagged one year.

The next two forces possibly influencing the median-mean income gap will be considered demographic explanations. The first concerns the influence of the trend toward more female headed families. As a percentage of all families, these have increased from 9.0 percent in 1947 to 15.2 percent in 1982, with an increase of 10.8 to 15.2 percent just since 1970. Since females, in general, continue to earn below the median income, the increasing number of female headed families may influence the median-mean gap. Both the median and mean income levels should be pulled down by the increase in female headed families, although perhaps at different rates. To test for this, the percentage of female headed households is entered as an independent variable.

6 It is likely, of course, that the turnout variable will be correlated with the two previous party control variables. Afterall, increased turnout should bring more Democrats into office, resulting in policies favoring the less affluent. High turnout may have the additional effect, however, of persuading those Republicans managing to retain their elective offices to view more favorably redistributive programs benefitting the less advantaged. This suggests there may be an interaction effect between turnout and party control. The influence of increased Democratic control of the government may be accented by Republican officeholders softening their conservative positions as a result of this increased Democratic strength. An interaction variable was added to test for this possibility, but was never significant (the variable was: turnout x percent of the House and Senate Democrat).




A second demographic explanation contends that changes in the age distribution in society may alter the gap size. Young workers are likely to earn less than their elders, in part because they have not achieved the seniority which commands a higher salary. Thus, changes in the age distribution of working-age individuals in United States society may influence median and mean incomes, probably pushing both up as the population ages. To account for any impact age has on the median-mean gap, the annual ratio of young working-age individuals (25-44 year olds) to old workers (45-64 year olds) is calculated (old/young).

The last two possible forces influencing the gap will be labeled economic explanations. The first is the independent variable from Equation 1, real annual per family transfer dollars. This is retained as a control variable. The second economic variable taps the influence of economic conditions on the gap. It is widely agreed that an unhealthy economy has stronger negative effects on middle and lower income groups. In par- ticular, unemployment hits these groups first and hardest. The conse- quences of an unhealthy economy on the gap may be to lower the median income, as middle income individuals suffering economic hardships drop below the median. Of course, the mean would be lowered in this situation as well. To assess the influence of economic conditions on the median- mean gap the annual United States unemployment rate is entered as an independent variable.

Bivariate regression equations revealed all independent variables significant (at the .05 level) except the presidential dummy and the family transfer control.7 The failure of the presidential dummy suggests that the gap size has not changed systematically with respect to which party oc- cupies the oval office. Indeed, Figure 3 shows the gap was both wide and small under presidents of both parties.

A number of multivariate equations were tested. Turnout always proved to be the most significant variable, and when it was in a model the age distribution and female headed families variables always failed to reach significance. Table 1 presents the best model in terms of the number of significant variables and the R-square (real per family social welfare expenditures was retained as a control variable even though it was not significant). Two political variables appear in the model, the percent of Congress under Democratic control and turnout. The coefficient of the former indicates that a 1 percent increase in the Democratic strength in Congress results in the median-mean income gap closing .06 units. The coefficient of the turnout variable says that a 1 percent increase in voter turnout is associated with a closing of the gap of .20 units. Together, these variables account for much of the increased gap size since the mid-1960s. According to the model, the drop in turnout from 61.9 percent in 1964 to

7The bivariate coefficients and t-statistics were: presidential dummy coefficient -.35, t- statistic -.75; Democratic Strength in Congress coefficient .07, t-statistic 1.80; turnout coefficient .23, t-statistic 5.32; female headed households coefficient -.24, t-statistic -1.89; age distribution coefficient -.74, t-statistic -2.71; family transfer control coefficient -.002, t-statistic -1.00; and unemployment coefficient -.31, t-statistic -2.19.




53.2 percent in 1980, combined with the drop in Democratic congres- sional strength of from 68 to 53.5 percent over the same period, should have increased the gap 2.61 units ([.2 x 8.7]) + ([.06 x 14.5]). The gap actually increased 4.00 units. Much of the remaining variance in gap size can be attributed to the deteriorating economic conditions. The coefficient for the unemployment rate variable indicates that a 1 percent increase in unemployment translates into a widening of the gap .28 units. Continuing with the example above, unemployment rose from 5.2 percent in 1964 to 9.7 in 1982, meaning it should have worked to widen the gap another 1.26 units (.28 x 4.5). Thus, the increased gap size since the mid-1960s seems due primarily political and economic conditions unfa- vorable to the operating of the median voter hypothesis.8

TABLE 1 MEAN POLICY SUPPORT AND MEAN MEMBER-LEADER

POLICY AGREEMENT BY GROUP PARTICIPATION

NRTA AARP

Policy Member-Leader Policy Member-Leader Support Agreement Support Agreement

Inactive 14.3 8.5 14.6 8.7 (576) (576) (881) (881)

Active 14.3 8.2 15.2 8.7 (321) (321) (177) (177)

Very Active 14.7 8.2 15.3 7.4 (104) (104) (65) (65)

P >.05 >.05 >.05 .05

The summary statistics suggest the model in Table 1 is well specified. The R-square is .56, indicating that over half the variance in the median-mean income gap is accounted for. Also, the Durbin-Watson statistic of 1.69 is strong evidence that autocorrelation is not biasing these time trend results.9 In short, the four variables combine to account for a substantial portion of the variation in the size of the gap over the past 36 years.

8 A variety of lagged models were also tested (the political variables, of course, were already lagged one year). The bivariate correlations between the lagged independent variables and the dependent variable remained significant for both one and two year lags (except the presidential dummy and the family transfer control which were not significant before they were lagged either). The,variables in Table 1 also remained significant when lagged one and two years (again, except the family transfer control). This suggests the estimates from the independent variables in Table 1 are robust.

9Moreover, when the model is corrected for first-order autocorrelation using the Corchrane-Orcutt technique the coefficients remain significant (Democratic Strength in Congress coefficient .06, t-statistic 1.72; turnout coefficient .18, t-statistic 3.98; family transfer control coefficient -.003, t-statistic -.98; and unemployment coefficient -.32, t-statistic -2.26).



An Examination of the Median Voter IHypothesis 221

DISCUSSION

Through the years, the median voter hypothesis has been advanced as a quite plausible explanation for one of the major social and economic phenomena of our time: the increased redistribution of wealth from the more affluent to the less affluent in democracies. Yet the hypothesis has largely escaped rigorous empirical testing, and not without good reason. The concept underlying the hypothesis has proved difficult to quantify. That is, how do we measure whether lower income majority coalitions, through the power of the vote, successfully elect elites disposed to taxing the better off and sharing this wealth among the majority coalition? This paper, using United States data, represents an effort to both measure the concept implied by the hypothesis and observe changes in the measure over time. In addition, the primary forces which impinge on this measure are isolated, giving us a fuller understanding of what influences the operation of the median voter hypothesis.

More specifically, this paper argues that the ratio of a society's median to mean income serves to capture the concept behind the median voter hypothesis. By way of a simple model, it was shown that increases in this ratio (a tightening of the gap between median and mean income levels) would be evidence in support of the hypothesis. Changes in the gap in post-World War II United States income data suggest that the hypothesis was operating until the mid-1960s, but increases in the gap thereafter indicate a failure of the hypothesis to operate. An effort at isolating the forces which influence gap size, thus perhaps providing clues as to why the median-mean gap widened after the mid-1960s, uncovered three important explanatory variables. First, increases in the Democratic party strength in Congress led to a tightening of the gap. This should be no surprise, since Democrats are usually considered the party of the less affluent, and thus more disposed to redistributing wealth from the rich to the poor. Second, increased voter turnout led to a tightening of the gap as well. Higher turnout usually means more lower income individuals are voting, suggesting Democratic candidates stand to gain. Further, Repub- licans maintaining their public offices may feel pressured to ease their opposition to redistributive programs. Third, increases in unemployment work to widen the gap, probably because middle income families suffering from the unhealthy economic times fall below the median income, pulling it away from the mean.

All this should be encouraging for median voter advocates. After all, they claim that the lower class must exert itself politically by taking control of the reins of government for the hypothesis to operate, and indeed, when lower income individuals turnout at the polls in large numbers contributing to increased Democratic strength in government, the hypothesis shows signs of operating. As turnout and Democratic strength in Congress increased in the 1950s and early 1960s, redistribution programs aimed at the less affluent increased. When turnout and Democratic strength in Congress began to slip after the mid- 1960s so did the emphasis




on redistributive programs aimed primarily at the less affluent."' Instead, programs such as Social Security and Medicare, which tend to extend their benefits "to all that qualify by virtue of age or dependency," were greatly expanded, even being indexed to inflation (Nelson 1982: 79). Also, redistributive programs in the areas of education and housing were increased, with many of the benefits aimed at the population as a whole. In short, redistribution increased, but much of the increase found its way to those above the median income. Finally, the very low voter turnouts of the last few years coupled with increased Republican strength in government have been associated with actual reductions in certain redistributive programs intended for the less affluent. This is almost certainly part of the reason the median-mean income gap has widened sharply since 1980.

REFERENCES

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,and Gordon Tullock. 1962. The Calculus o/ Consent. Ann Arbor: University of Michigan Press.

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Key, V. 0. 1949. Southern Politics in State and Nation. New York: Knopf.

'0Why this is so is not clear given the logic of the median voter hypothesis. Under the hypothesis, lower income voters should be guided only by the desire to redistribute income from the wealthy to themselves, which requires voting for the party favoring such redistribution. Their absention from voting suggests they must be "guided" by other influences as well. This brings to light the need for additional research aimed at incorporating the whole host of known influences on voting (i.e., personal economic conditions, candidate personalities, international events, trust in government) into the framework of the median voter hypothesis.




Kirschen, E.S., et al. 1964. Economic Policy in Our Time. Amsterdam: North- Holland Publishing.

Marwick, Arthur. 1980. Class. New York: Oxford. Meltzer, Allan H., and Scott F. Richard. 1976. "Why Government Grows (and

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Musgrave, Richard A., and Peggy Musgrave. 1973. Public Finance in Theory and Practice. New York: McGraw-Hill.

Nelson, Joel I. 1982. Economic Inequality. New York; Columbia University Press. Pomper, Gerald. 1977. The Election of 1976. New York: McKay. Reynolds, Morgan, and Eugene Smolensky. 1977. Public Expenditures, Taxes, and

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Tufte, Edward R. 1978. Political Control of the Economy. Princeton: Princeton University Press.

Tytler, A. 1840. Universal History, From the Creation of the World to the Eighteenth Century. Boston: Hilliard, Gray and Co.

Winters, Richard. 1976. "Party Control and Policy Change." American Journal of Political Science 20: 597-636.

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RICE. an Examination of the Median Voter Hypothesis