Out with the Old, In with the New? Congressional Voting Patterns, Intergenerational Conflict and Demograpic Change

Department of Economics Working Paper Out with the Old, In with the New? Congressional Voting Patterns, Intergenerational Conflict and Demograpic Change Deborah Fletcher Miami University October 2008 Working Paper # - 2008-10

1 Out with the Old, In with the New? Congressional Voting Patterns, Intergenerational Conflict and Demographic Change October 2008 Deborah Fletcher Miami University Department of Economics 208 Laws Hall Oxford, OH 45056 USA fletchd@muohio.edu Running title: Congressional Voting, Intergenerational Conflict, and Demographic Change Abstract: This paper explores how demographic change in the constituency affects Congressional voting on aging issues. Demographic data from the 1990 Census and vote records of individual members of the House of Representatives from 1987 to 1998 are used to examine how demographic changes in the constituencies of Representatives, and particularly changes in the age distribution of the of the constituencies, affected how the Representatives voted on issues specific to aging. Redistricting is used to separate the effects of changes in demographics from the individual inclinations of the various members of Congress. This paper offers evidence that Representatives change their voting behavior on some issues after redistricting, indicating that generations differ in their preferences for some issues and that Representatives respond to those preferences.

2 I. Introduction In 2000, just over 12% of the American population was aged at or above 65. By the year 2030, this proportion is expected to rise to nearly 20%. Because different government services exist for different age groups (e.g. education and nutrition programs for children and Medicare for the elderly) there exists a potential conflict between the generations as they compete for governmental resources. As America continues to age, changes in the demographic composition of the population could have far-reaching effects on the mix of services provided by the public sector. The purpose of this paper is to consider how demographic change within a constituency that occurs as a result of redistricting affects legislators voting behavior on aging issues. After each Decennial Census, each state redraws its Congressional districts in accordance with Federal guidelines and the state s own constitution. For the 1990 Census, redistricting occurred after the 1992 session 1 and caused significant changes in the constituencies of many individual Representatives. In particular, I use demographic data from the 1990 Census and vote records of individual members of the House of Representatives from 1987 to 1998 to examine how demographic changes in the constituencies of Representatives affect how the Representatives vote on issues specific to aging. Of particular interest is how changes in the age distribution of the constituencies affect voting behavior. The 1992 redistricting of the House of Representatives is used to isolate and examine these effects. Redistricting provides multiple observations on demographic variables for individual legislators. We can examine how a Congressperson s voting patterns might change on issues related to demographic characteristics, such as age, when his constituent demographics 1 A small amount of additional redistricting occurred in 1994; this analysis does not consider any effects this might have on voting behavior.

3 change. This allows me to separate the effects of changing demographics from the individual inclinations of the various members of Congress. The extent to which age differences will bring about changes in public policy depends on the interaction of two factors: the extent to which the elderly and those younger differ in their preferences for public services and the extent to which elected officials respond to the preferences of their constituents. If both of these occur, then significant changes in public policy should be expected. While it might seem obvious that both would hold, there has been significant debate about each. As to preference differences, a growing literature has explored education finance issues. The literature on intergenerational conflict and education expenditures gives mixed hypotheses and evidence on the effects of change in the proportion of older people on education expenditures. Altruism may mitigate the tendency of the elderly to demand fewer services for children (see Logan and Spitze (1995) and Fletcher (2003)). It is also possible that increased spending on education may decrease crime, improve services for the elderly such as health care, or increase contributions to Social Security (see Poterba (1998) and Kemnitz (2000)). However, the lags between spending and these kinds of benefits would likely be long. Various empirical studies have found conflicting effects of a larger elderly population on school spending. 2 A second literature on intergenerational conflict has addressed Social Security. This literature has focused on the viability of the system and possible reforms, as well as the extent to which future generations will be negatively impacted by the costs of caring for a growing elderly 2 In a state-level analysis, Poterba (1997) finds that older voters do not support increases in state education expenditures. Ladd and Murray (2001) and Harris, Evans and Schwab (2001) perform similar analyses at the county and district levels, respectively, and find the fraction of elderly to have no effect on education expenditures. Fletcher (2003) finds that education spending is higher when a larger fraction of the population is elderly and has lived in the same county for at least five years, and decreases as the elderly who do move migrate from a greater distance. Fletcher and Kenny (2008) estimate a median voter model and find the elderly to have a small but statistically significant negative impact on school spending.

4 cohort (see Baker and Weisbrot (1999) and Schultz (1995)). Finally, a recent contribution by Borge and Rattso (2008) uses panel data from Denmark to examine both how the elderly population share affects the provision of education and child care, and how the size of the younger cohort affects spending on programs for the elderly. They find that a larger elderly cohort reduces spending on programs for children, but the size of the younger cohort has no effect on spending for the elderly. As to the second factor, an important thread in the political economy literature explores the relation between the actions of political representatives and the preferences of their constituents. In a simple majority-voting scheme bills would be passed that would reflect the demographic makeup of the area. Abstracting from differential voting participation rates between age groups, we would expect to see more elderly-friendly bills, and fewer to provide goods and services to children, in places where more elderly people reside. However, in the United States we elect legislators, governors and Presidents to make most decisions about public expenditures. Do politicians respond to varying demographic characteristics of their constituent bases, or do they vote according to their own preferences? The empirical evidence on the relation between the preferences of the electorate and representative voting behavior is mixed. Most studies have shown that the positions of legislators often differ from the position of the median voter, but it is unclear to what extent this is true. 3 Several recent articles in the political economy literature examine the effects of demographic change on Representatives voting behavior. However, most of these authors use broad measures of demographic change. For example, Gerber and Lewis (2004) measure the extent to which districts 3 Inman (1987) summarizes the models addressing the competition of various groups for resources and resulting representative voting behavior. Among these models, Downs (1957) median voter model is perhaps the best known. Demographic change may not change the position of the median voter, but if it does, the model predicts that changes in voting behavior should result. Other models concentrate on the sizes of the competing groups, positing that shifts in the relative group sizes should translate to changes in voting behavior. For example, Preston (1984) shows that government transfers depend on the political power of the cohort, with a larger cohort getting higher transfers. He suggests that this partially explains the increased welfare of the elderly and decreased welfare of children from 1960 to 1980.

5 are homogeneous and show that the median voter s position has less of an effect on Representatives roll-call voting records when the district is heterogeneous than when it is relatively homogeneous. They explain this by suggesting that a more heterogeneous constituency may allow Representatives to deviate from the median voter s position. Two recent papers use redistricting to analyze the effects of exogenous demographic change. Stratmann (2000) finds that, if more than half of the district changed in the post-1990 redistricting, there was a greater absolute change in the Representative s Americans for Democratic Action (ADA) index. Stratmann s empirical modeling of redistricting is somewhat limited because of his construction of the explanatory variable for redistricting. He visually inspected each district map and recorded redistricting as yes if it appeared that the district boundaries changed by 50% or more, and no otherwise. His measure for the change in constituency preferences due to redistricting is the percentage of electoral vote for Clinton in 1992 less the percentage for Dukakis in 1988. This is problematic because there were likely differing preferences for these two candidates that were not due to redistricting, and possible other changes over time for which Stratmann does not control. Stratmann also finds that as the district s median household income increases, the ADA falls; that is, voting becomes more conservative. However, this again does not control sufficiently for other changes which occurred in the districts over time. Changes in income and voter preferences as measured by the difference in a district s Democratic vote cannot adequately capture the districts changing preferences for specific types of issues, such as those affecting the elderly. Rothenberg and Sanders (2000) find that, if redistricting caused a shift in the liberalness of the district, a greater ideological shift in Representatives voting records resulted. Their measure of

6 liberalness is single-dimensioned: the change in percentage of the two-party vote for Dukakis in the district before and after redistricting. LeVeaux and Garand (2003) also use redistricting to measure how Representatives of different party affiliations react to changes in the racial composition of their districts. They find that Democratic Representatives tended to respond to increases in the African American makeup of their constituencies with a more liberal voting pattern. Interestingly, Republican Representatives whose districts became more heavily African American responded by voting more conservatively. Since my analysis concerns redistribution toward the elderly, it is necessary to consider multiple demographic characteristics, and to specifically measure voting behavior on issues impacting the elderly. The advantage of my approach to redistricting is that it can capture subtle changes due to minor adjustment of the district boundaries. In addition, my explanatory variables address many potential dimensions of preference. My use of only 1990 Census data, divided up by Congressional district before and after the boundary changes, also means that there are no changes in the variables at the aggregate level for which I must adjust. The remainder of the paper will be structured as follows. In Sections II and III, I discuss my data sources, empirical model and results. I conclude in Section IV with a discussion of the implications of my findings and ideas for future avenues of research. II. Data and empirical approach Individual Congressional votes on every major bill are recorded in the Congressional Quarterly Almanac (CQA); the other data used in this analysis are taken from the 1990 Census. The Census data were aggregated from the 1990 Census tract level to the Congressional district

7 level for both the 102 nd and 103 rd Congresses 4. This provides a set of demographic data for each legislator before and after the 1992 redistricting. I created a database of votes on all the bills related to aging issues from 1987 to 1998; that is, six years before and after redistricting changes went into effect. I evaluated the descriptions given by CQA for every bill in the period of my study to determine which votes were relevant. Votes were included if they had a substantial focus on aging issues, but this was a more difficult process than it might seem. Many votes, while they include some provision for the elderly, have a variety of other provisions as well. Most of the votes concerning Medicare, for instance, also include various other budget items. One example is vote 84 from 1990, a substitute amendment to the Fiscal 1991 Budget Resolution, which included Medicare cuts of $3.2 billion, but also froze the budget for defense programs and discretionary domestic programs. Most of the other votes in this session concerning the budget resolution do not mention Medicare cuts, and this vote does in large part concern Medicare. For these reasons, this vote was ultimately included in the database. Sometimes it was even difficult to determine whether a vote was pro-elderly. For example, the 1988 Medicare Catastrophic Coverage Act was largely repealed in 1989. Vote 268 of 1989 was an amendment to repeal all stop-loss coverage of hospital and doctor bills while retaining broad prescription drug coverage and non-medicare provisions. While this was a vote to significantly reduce Medicare benefits, it allowed more coverage for Medicare patients than the previous vote would have. For this reason I was unable to determine whether voting yes on this bill would be pro-elderly, and ultimately excluded it from the index. Similar issues came up in other situations, such as when Medicare cuts were being argued. If a legislator suggested a sizeable Medicare cut that was still smaller than the previous suggestion, I was unable to record a yes vote 4 Special thanks to Alex Hooper for his assistance in constructing the Census dataset.

8 as pro or anti. I also excluded votes where there was less than twenty percent contention; many of these votes would otherwise have been perfect additions to the index. The final list of votes included is in the Appendix. The Appendix shows that there were only two votes on elderly issues in 1991, and none in 1992, 1993 or 1994. In order to have a reasonable number of observations for each Representative, I also excluded those legislators whose first observation was after 1990 or whose last observation was before 1995. 5 The remaining sample consists of 216 legislators who cast at least one vote on elderly issues in each of the two periods (before and after redistricting). For each of these legislators I created two elderly-friendly indices: one for the period from 1987 to 1992 and one for 1993 to 1998. The index is a simple average of the pro-elderly and anti-elderly votes cast by the legislator. Pro votes were assigned a value of one and anti votes a value of zero; thus, an index value of one indicates a legislator always voting pro-elderly. 6 Table 1 contains the summary statistics for the voting index for the entire period of the analysis and for the periods before and after the 1992 redistricting. (Insert Table 1) For my analysis of the effects of demographic change on the voting index, I perform an ordinary least squares, first difference regression. The dependent variable is the difference in the voting index, and the explanatory variables are a vector differences in demographic characteristics that varied in the district because of redistricting, including age (difference in the fraction of the district s population aged 55 and older) 5 There is one legislator in the sample who cast only two votes included in the index in the period before redistricting, while 182 of the remaining 215 cast all 10 votes included in the index in this period. After redistricting, each legislator cast a minimum of 10 votes included in the index, and 169 of the 216 cast all 18 included votes. 6 Note that index values differ across legislators in part because different legislators voted on different bills included in the indices. However, when the sample is restricted to only those 141 legislators who voted on all bills in the index, the signs of the coefficients in the regression are unchanged, and the magnitudes and statistical significance are very close to the values presented here. These results are available on request.

9 income (difference in per capita income) the difference in the interaction of fraction aged 55 and older and per capita income proportion of children (difference in the fraction of the population younger than 18) educational attainment (difference in the fraction with a college degree) Note that using the difference of the voting index over time (the value of the index for each legislator after redistricting less its value before redistricting) and the difference in the district s demographic variables (which will be due to redistricting) means that the effects of ideological differences peculiar to individuals that would cause them to vote in a given way, regardless of the makeup of their districts, will drop out of the analysis. 7 The explanatory variables of interest in this analysis are primarily those related to age and income, as they should capture any conflict between the generations. 8 Older people should prefer spending to benefit the elderly if they are narrowly self-interested. Thus, legislators in a district with a large proportion of older people should have a higher elderly index value. The difference in the proportion of the population aged 55 and older is used as the measure of older residents because people are forward-looking to some extent. While most people do not retire until they reach their 60s, people start to care about aging-related issues somewhat earlier than that. A 55-year-old probably does not have minor children, so should be less concerned with children s issues. Fiftyfive is also the age at which people are eligible to receive certain age-related perks, such as senior citizen bank accounts and the ability to live in adult-only housing communities. Eligibility for membership in the American Association of Retired Persons (AARP) begins at 50. 7 The coefficient estimates for the first difference analysis are equivalent to those from estimation of a two-period panel regression with time and individual fixed effects. Only the intercept and fit statistics will differ, with a lower R squared for the first difference approach. 8 Proportions (e.g. fraction female and fraction children) are used to normalize districts. Although districts tend to be rather uniform in size, there are some differences across states. This is particularly the case in states with small populations, such as Alaska, Vermont and Wyoming, which have only one Congressional district.

10 Intergenerational conflict implies that a high proportion of children in the district should cause Representatives to be less supportive of elderly issues. The difference in the proportion of the population aged 18 or younger is used to measure the proportion of children in a district. Although education programs largely affect children above the age of 4, the parents of infants can be expected to be forward-looking for four years. Other programs for children, such as WIC, begin at birth. Higher income areas will prefer less redistribution because the rich want to keep their money, and there are fewer poor people who would prefer these programs for their own narrow selfinterest. Thus, wealthy areas may oppose programs that redistribute toward the elderly poor. Programs for the elderly that are not viewed as strongly redistributional, however, might be normal goods. 9 In addition, as income increases, the opportunity costs of private (i.e. family) provision of services to the elderly increase, raising the demand for public provision of elderly services. Thus, income has potentially countervailing effects. The difference in each district's per capita income, measured in thousands of dollars, is used as the income variable. If a high per capita income and a high proportion of seniors means the seniors in the district are wealthy, as seems reasonable, 10 these individuals may be less likely to prefer government services for seniors. Thus, I include in my analysis the difference in the interaction between the proportion elderly and income. Educational attainment is a measure of permanent income. This would imply that, as educational attainment in a district increases, voting for elderly services --- particularly those viewed as strictly redistributional in nature --- would fall. On the other hand, the sign may be ambiguous if services for the elderly are normal goods, as discussed above. The 9 Some programs might be viewed as being more redistributional in nature than others. For example, legislation against age discrimination in employment does redistribute money away from younger workers and toward older people; however, this redistribution works through the labor market, so it is more indirect than transfer payments. This might mean that it is viewed as less redistributional than transfer payments. 10 The correlation coefficient for percent 55 and older and per capita income is 0.1308. If seniors tend to have lower incomes on average than people more apt to be in the working population, a high proportion of seniors and a high mean per capita income in a district may imply that the seniors are wealthier than average in this district.

11 difference in the fraction of the district s population with a college degree is included to measure educational attainment. The combination of redistricting and the 1992 elections brought about sweeping changes in the composition of the House of Representatives, leaving only 322 Representatives who were in both the 102 nd and 103 rd Congresses. Of these, 216 were in office by 1990 and until at least 1995, and voted on at least one issue included in the elderly voting index, and so are included in the analysis. The summary statistics of interest for the constituencies of these 216, including the preredistricting levels and mean, standard deviation, minimum and maximum changes in the variables, are shown below. (Insert Table 2) Since the dependent variable is the change in the elderly voting index rather than the individual vote, the sample is made up of 216 observations, one for each of the 216 Representatives. 11 Each of the proportional changes in the key variables has a relatively large standard deviation; in fact, the standard deviation of each is larger than the absolute value of the mean. This suggests there is sufficient variation for identification of the effects of these changes. III. Results The effects of changes in the demographic makeup of the districts are shown in Table 3. (Insert Table 3) The coefficient for the fraction of the population aged 55 and older is statistically significant at the 90% level, while the coefficient for per capita income is not statistically significant. The 11 An alternate index was also constructed that included a larger set of votes. While all the votes contained an elderly component, the additional votes included in the larger set were less focused on elderly issues. The results of the regressions performed on the alternate index were similar to those in the main regression, but were weaker. This is to

12 interaction of these two variables, however, is significant at the 95% confidence level. The fraction of college graduates in the population has a statistically significant effect at the 99% confidence level, but the fraction of children has no statistically significant effect. The full estimated effect of a one standard deviation increase in the proportion aged 55 and older is to increase the voting index value by 0.03. This positive effect is expected if legislators respond to the perceived wishes of their electorates; that is, if politicians respond to increases in the proportion of older people in their districts by voting more often for benefits to the elderly. The effect of an increase in the fraction aged 55 and older diminishes as income increases, becoming negative when per capita income exceeds $21,300. This is substantially above the mean per capita income of $14,250, and is true in only about 7% of the observations. Thus, an increase in the fraction of the population that is at least 55 years old almost always has a positive effect on the index value. Using the mean value of the proportion of seniors (which is 0.3), a one standard deviation increase in per capita income is associated with approximately a 0.1 decrease in the index value. The effect of an increase in income becomes negative when more than 4.5% of the population is in this age group. At least 5% of the population is 55 or older in all districts in the sample, so an increase in per capita income is always associated with a decrease in the index value. This is consistent with the idea that higher income areas prefer less redistribution toward the elderly poor. The fraction of college graduates in the district has a positive and strongly significant effect on the index vote, with a one standard deviation increase in this variable associated with an increase of 0.12 in the index. This suggests that per capita income may not capture all of the effects of permanent income. Given that the sign of this coefficient is different from the overall direction of be expected, as the effects if demographic change on elderly issues would be difficult to separate from other issues included in these additional bills.

13 the effect of per capita income, however, the educational attainment variable may be capturing some other district characteristic relating to preferences for elderly services. Finally, the proportion of children in the district has no statistically significant effect. This may suggest that intergenerational conflict is not an issue in this context. IV. Conclusion This paper uses the redistricting following the 1990 Census to explore the responses of politicians to changes in their constituencies. Demographic data from the 1990 Census is used to determine the change in the composition of districts of members of Congress who served both before and after redistricting. This was related to how they voted on issues related to the elderly between 1987 and 1998. The results offer evidence that politicians did respond to changing demographics when voting on issues related to the elderly. When a larger proportion of the population is made up of elderly people, legislators are more likely to vote to support redistribution toward the elderly. For this to be true, the elderly must have different preferences than those younger on those issues and representatives must respond to these preference differences. On the other hand, when the proportion of children in the district increased, representatives did not seem to reduce their support for elderly issues. Since representatives do seem to respond to constituent preferences, it would seem that younger families with children do not differ in their preferences for redistribution to the elderly. One possible explanation for this is cross-generational altruism. Fletcher (2003) showed that cross-generational altruism can have important effects on the provision of age-specific, publicly provided goods, but her analysis focused on the elderly cohort s altruism toward the young. It is equally possible that younger generations behave altruistically toward the elderly.

14 It should be noted that this analysis does not take several factors into account. More work should be undertaken to determine the effects of differential voting participation rates of competing cohorts, as well as the effects of interest group power (e.g. fraction membership in AARP). Also, if the newness of a Representative to his constituency matters, the chronological distance from the point of redistricting may play a role in voting behavior. Similarly, it would be interesting to see if politicians vote strategically to ensure reelection, voting more in line with the characteristics of their constituencies when an election is approaching. Another key question is the extent to which politicians whose voting records do not reflect the demographic makeup of their electorates are punished by defeat in election. This paper offers a unique and effective identification strategy that can be used in addressing the additional questions raised here. The use of redistricting allows for analysis of how the external shock of a changing constituency affects the many actions of Representatives. This area of inquiry will contribute to a better understanding of voting behavior in a representative democracy as well as issues of intergenerational conflict.

15 References Baker, D. and Weisbrot, M., Social Security: The Phony Crisis, Chicago and London: University of Chicago Press (1999) Borge, L.E. and Rattso, J., Young and Old Competing for Welfare Services, CESifo Working Paper Series No. 2223, 2008 Congressional Quarterly Almanac v42 - v54, Washington, D.C.: Congressional Quarterly Inc. (1986-1998) Dewey, J., Husted, T. A., and Kenny, L. W., The Ineffectiveness of School Inputs: A Product of Misspecification?, Economics of Education Review, v19, n1 (February 1999): 27-45 Fletcher, D. (2003). Intergenerational Conflict and Publicly Provided Goods. Ph. D. diss., Department of Economics, University of Florida, Gainesville, FL Fletcher, D. and Kenny, L.W., The Influence of the Elderly on School Spending in a Median Voter Framework, Education Finance and Policy, v3, n3 (Summer 2008): 283 315 Gerber, E.R. and Lewis, J.B., Beyond the Median: Voter Preferences, District Heterogeneity and Political Representation, Journal of Political Economy, v112 n6 (2004): 1364-1383

16 Harris, A. R., Evans, W.N., and Schwab, R.M., Education Spending in an Aging America, Journal of Public Economics, v81 n2 (September 2001): 449-472 Inman, R. P., Markets, Governments and the New Political Economy, in Alan J. Auerbach and Martin Feldstein (eds.), Handbook of Public Economics, Volume 2, Amsterdam: North Holland (1987) Kemnitz, A., Social Security, Public Education and Growth in a Representative Democracy, Journal of Population Economics, v13 n3 (August 2000): 443-462 Ladd, H. F. and Murray, S. E., Intergenerational Conflict Reconsidered: County Demographic Structure and the Demand for Public Education, Economics of Education Review v20 n4 (August 2001): 343-357 LeVeaux, C. and Garand, J.C., Race-Based Redistricting, Core Constituencies, and Legislative Responsiveness to Constituency Change, Social Science Quarterly, v84, n1 (March 2003): 32-51 Maddala, G.S., Limited-Dependent and Qualitative Variables in Econometrics, Cambridge, New York, Melbourne and Madrid: Cambridge University Press (1983) Poterba, J. M., Demographic Change, Intergenerational Linkages and Public Education, American Economic Review v88, n2 (May 1998): 315-320

17 Poterba, J. M., Demographic Structure and the Political Economy of Public Education, Journal of Policy Analysis and Management v16, n1 (Winter 1997): 48-66 Preston, S., Children and the Elderly in the United States, Demography v 21 (1984): 435-457 Rothenberg, L. S. and Sanders, M. S., Severing the Electoral Connection: Shirking in the Contemporary Congress, American Journal of Political Science v44, n2 (April 2000) Schultz, J. H., The Economics of Aging, 6th Edition, Westport, CT and London: Auburn House (1995) Stratmann, T., Congressional Voting over Legislative Careers: Shifting Positions and Changing Constraints, American Political Science Review v94, n3 (September 2000): 665-676

18 Appendix: Votes on Elderly Issues with 20% or Greater Contention, 1987 to 1998 Vote Bill Bill Pro/ Pro Anti Total Year Number number Name Anti votes Votes votes 1987 152 HR 1451 Older Americans Act/Funding Levels A 297 95 To reduce total authorizations under the bill for fiscal 1988 by $108 million 154 HR 1451 Older Americans Act/Home Care P 273 116 To authorize $4 million to test ways to assist seniors who receive home care 171 HR 4 Housing and Community Development/Elderly Rents P 284 137 To limit rent increases to elderly residents of subsidized housing 279 HR 2470 Catastrophic Health Insurance Bill/Republican Substitute A 242 190 This version would cost an estimated $18.2 billion, vs. $33.9 billion for original bill 281 HR 2470 Catastrophic Health Insurance Bill/Passage P 302 127 Passage of catastrophic coverage and other expansions (estimated cost of $33.9 billion) 407 HR 1212 Polygraph Tests/Nursing Home Employees P 187 237 Amendment to permit nursing home employers to use lie detector tests Number of votes 4 2 6 1988 176 HR 3436 Long-Term Health Care/Rule P 169 243 To increase Medicare coverage of long-term home care services Number of votes 1 0 1 1990 436 H Con Res 310 Fiscal 1991 Budget Resolution/Conference Report P 238 192 Same spending targets as in budget summit agreement, with smaller cuts in Medicare 474 HR 5835 Fiscal 1991 Omnibus Reconciliation Act/Democratic Alternative P 250 164 To provide smaller increases in Medicare premium and deductible, with other tax provisions Number of votes 2 0 2 1991 70 H Con Res 121 Fiscal 1992 Budget Resolution/Spending Caps A 336 89 Decreased domestic outlays, including $25.2 billion in Medicare cuts over 5 years Number of votes 0 1 1

19 Vote Bill Bill Pro/ Pro Anti Total Year Number number Name Anti votes Votes votes 1995 50 H J Res 1 Balanced Budget Amendment/Recommit P 184 247 To place Soc. Sec. trust funds off budget and exempt them from balanced budget calculations 69 HR 5 Unfunded Mandates/Older Americans and Juvenile Justice P 126 296 To exempt mandates related to Older Americans and Juvenile Justice Acts 301 HR 483 Medicare Demonstration Program Expansion/Waxman Substitute P 175 246 To bar age-based premium increases, allow individuals to switch back to fee-for-service plan 355 HR 483 Medicare Select Policies/Motion to Instruct Conferees A 224 197 Reminder of fiscal limitations in extending Medicare Select policies 458 H Con Res 67 Fiscal 1996 Concurrent Budget Resolution/Adoption A 194 239 Budget balance by 2002 via $894 billion spending cuts, including $270 billion from Medicare 729 HR 2425 Medicare Revisions/Democratic Substitute P 149 283 Medicare reductions of $90 billion over 7 years (Republican bill called for $270 billion cuts) 730 HR 2425 Medicare Revisions/Motion to Recommit P 183 249 To remove Medicare Part B premium increases from legislation 731 HR 2425 Medicare Revisions/Passage A 201 231 Medicare reductions of $270 billion over 7 years 742 HR 2491 1995 Budget Reconciliation/Recommit P 180 250 Instructions to protect the health and income security of children and the elderly 743 HR 2491 1995 Budget Reconciliation/Passage A 203 227 Cut spending by $900 billion over 7 years, including $270 billion in Medicare cuts Number of votes 6 4 10 1996 156 HR 2406 Housing Overhaul/Family Rent Cap P 196 221 Rent cap for subsidized housing for elderly and disabled residents 291 HR 3675 Fiscal 1997 Transportation Appropriations/Commercial Pilot Retirement A 159 247 Prohibit money for a study of whether the mandatory retirement age for pilots should be raised Number of votes 1 1 2 1997 102 HR 2 Public Housing System Overhaul/Community Service Exemption P 181 216 Exempt primary caregivers of young children and the elderly from service requirement in subsidized housing 300 HR 2003 Budget Enforcement/Recommit P 148 279 To take Soc. Sec off budget and limit Medicare Part B premium increases Number of votes 2 0 2

20 Vote Bill Bill Pro/ Pro Anti Total Year Number number Name Anti votes Votes votes 1998 115 HR 3546 National Dialogue on Social Security/Recommit P 174 236 Reserve budget surplus until Soc. Sec is solvent for the future 463 HR 4578 Surplus to Social Security/Social Security Trust Fund P 210 216 To transfer all Soc. Sec. Trust Fund surpluses to be held in trust for Soc. Sec. 464 HR 4578 Surplus to Social Security/Passage A 188 240 Set aside 90% of any budget surplus in a special account until Soc. Sec. solvent for the future 468 HR 4579 Tax Cuts/Democratic Substitute P 197 227 Prohibit tax cuts from taking effect until Soc. Sec. solvent for the future Number of votes 3 1 4 Total Votes: 19 9 28

21 Table 1 Summary Statistics: Index of Votes on Elderly Issues, for the Period 1987 1998 and Before and After Redistricting Observations Mean Standard Deviation Minimum Maximum 1987 1998 216 0.5523 0.3335 0 1.0000 1987 1992 216 0.6201 0.3136 0 1.0000 1993 1998 216 0.4844 0.3397 0 0.9412

22 Table 2: Demographic Variables of Representatives Constituencies before and after 1992 Redistricting Variable Mean value before redistricting Mean value after redistricting Changes due to redistricting, in percentage terms: Standard Mean Deviation Minimum Maximum Fraction of the population 0.3009 0.3009 0.12% 7.48% -26.40% 35.40% aged 55 and older Per capita income 14.383 14.545 3.18% 16.53% -57.15% 92.84% (thousands) Fraction of the population 0.2547 0.2535-0.36% 6.19% -37.65% 28.69% aged 18 and younger Fraction of the population 0.1284 0.1312 3.79% 23.67% -68.43% 212.71% with at least some college The sample consists of the 216 Representatives who were in office by 1990 and until at least 1995, and who voted on at least one issue included in the elderly voting index before and after the 1992 redistricting. The changes in redistricting are shown in proportional rather than absolute terms to show the relative magnitudes of the changes.

23 Table 3 Difference in Elderly Voting Index Effect of a one standard Variable Coefficient deviation increase in X Fraction aged 55 and up 2.1126* 0.0341 (1.2808) Per capita income 0.0045-0.1094 (coefficient and SE * 1000) (0.0143) Interaction of income and 55 up -0.0992* (coefficient and SE * 1000) (0.0547) Fraction aged < 18 0.5245 0.0178 (2.1309) Fraction college grads 2.1729*** 0.1198 (0.7077) Constant 0.1347*** (0.0125) Adjusted R-squared 0.0731 Standard errors in parentheses. The sample consists of the 216 Representatives who were in office by 1990 and until at least 1995, and who voted on at least one issue included in the elderly voting index both before and after the 1992 redistricting. Each variable is the difference in its value after and before the 1992 redistricting. The full effects of the differences in the fraction aged 55 and older and income are found using the means of the interacted variables. *** Statistically significant at the 99% confidence level ** Statistically significant at the 95% confidence level * Statistically significant at the 90% confidence level