Abstract
In economic hard-times, do Americans call for increases in governmental assistance, or do they clamor for declines in government assistance? We address this question by identifying the impact of state-level macroeconomic conditions on public support for social welfare spending. We analyze individual-level data from the 1984–2000 National Election Studies, combined with state-level macroeconomic indicators of inflation, unemployment, and productivity. We find that state-level inflation, not state-level unemployment nor state-level productivity, consistently and consequentially shapes citizens’ support for social welfare. With rising inflation, Americans become more supportive of means-tested social welfare spending. Our analyses generally reaffirm the value Americans place on the social welfare safety net, especially during times of economic duress. When the going gets tough, Americans reach out, rather than pull back.
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Notes
Social Security Administration. 2007. Statistical supplement to the Social Security bulletin, 2006. http://www.ssa.gov/policy/docs/statcomps/supplement/2006/supplement06.pdf
US Bureau of the Census. http://www.census.gov/compendia/statab/tables/07s0462.xls
Such a focus is not unique. While some scholars who study attitudes towards the social welfare state take a more general view, analyzing attitudes towards government spending on services generally or in the government’s role in guaranteeing jobs and a good standard of living (e.g., Berinsky 2002; Feldman and Zaller 1992; Jacoby 2000), many others focus primarily on programs for the poor (e.g., Feldman and Steenbergen 2001; Gilens 1999; Jacoby 1994; Schneider and Jacoby 2005; Smith 1987). Further, some research has identified clear differences in the underpinnings of Americans’ views on programs representing these various categories (e.g., Cook and Barrett 1992; Kam and Kinder 1999; Winter 2006).
This would not necessarily be the case for programs that include an explicit cost-of-living adjustment mechanism. Such a mechanism is in place for Social Security but not for several other social welfare assistance programs such as AFDC/TANF and Food Stamps.
An extension of this argument would suggest that citizens would respond to inflationary pressures generally: they would call for increased spending across the board, not just on social welfare policies. We address this possibility below.
The NES, at various points in time, has included other specific mentions that are relevant to social welfare policy, including assistance to the poor, unemployment assistance, and assistance to the homeless. We have not used these measures because they were included in limited years or were asked with inconsistent wording. The Welfare Programs item is available in the 1992, 1994, 1996, and 2000 and the Food Stamps item is available biennially from 1984–1996 and in 2000.
This statement uses average opinion on Food Stamps and on Welfare Programs. Spending on reducing crime, public schools, Social Security, AIDS research, child care, protecting the environment, financial aid for students, space exploration, and even spending on blacks all garnered more support than Food Stamps and Welfare Programs.
Jacoby (1994) combines spending on “assisting blacks,” “food stamps,” “Medicaid,” “unemployment compensation,” and “Social Security” into a social welfare scale. These specific program attitudes are used to predict general attitudes towards government spending (the services and spending item). Jacoby (2000) uses seven of the federal spending items (homeless, poor people, child care, unemployed, assisting blacks, food stamps, and welfare programs) to form a scale of social welfare spending preferences (note that social security is not included in this analysis); these social welfare preferences are contrasted with the more general services and spending item, which, Jacoby characterizes as “a general and nonspecific presentation of the [government] spending issue” (p. 753, FN 3). Feldman and Zaller (1992) analyze the services and spending item and the guaranteed jobs item, noting that these items have been “the primary NES social welfare issue items for the last decade” (p. 276, FN 5). Furthermore, they argue that these items relate well to other questions on “domestic spending priorities” and “general attitudes toward economic equality and redistribution” (p. 276, FN 5). Finally, the items have the virtue of containing the open-ended probes that form the core of the contribution of the article.
The correlations between the four items appear in the Appendix.
Family budget data “tally the cost of food, housing, transportation, clothing, personal items, medical care, and taxes for an urban family of four” (Berry et al. 2000, p. 552). We use Berry, Fording and Hanson’s data instead of the Bureau of Labor Statistics’ Consumer Price Index (CPI) because the BLS CPI provides only regional, rather than state-level, information.
In a departure from previous work, we also included inflation in both its raw and its quadratic form. The two theoretical arguments we address suggest either a positive relationship between good macroeconomic conditions and public support for social welfare (the procyclical pattern) or a negative relationship between good macroeconomic conditions and public support for social welfare (the countercyclical pattern). We added a layer of complexity to these statements in arguing that the relationship between macroeconomic conditions and public support for social welfare might be better modeled using a quadratic, because the marginal effect of changes in macroeconomic conditions might depend upon the level of macroeconomic conditions. Inclusion of a quadratic allows us to identify whether the effect of inflation on social welfare policy is monotonically increasing or monotonically decreasing, or whether it is nonmonotonic (that is, if the effect is positive up to some point and negative thereafter). This specification also allows us to examine whether the effect of inflation on support for social welfare spending varies with the level of inflation itself. This quadratic specification is especially appropriate for the indicator of inflation, as target levels of inflation (e.g., in countries such as the United Kingdom, Canada, and New Zealand (Bernanke and Mishkin 1997) and endorsed by U.S. Federal Reserve Board Chairman Ben Bernanke (Geewax 2005)) suggest that interpretation of inflation levels with respect to “good” or “bad” macroeconomic conditions is not unidirectional. Instead, too low or too high levels of inflation may be undesirable, as low inflation rates may destabilize the economy (Delong 2000; Reifschneider and Williams 2000; Saunders 2000). A one-unit shift in inflation, say from 1% to 2%, may have a different effect on support for social welfare policy compared with a one-unit shift in inflation from 4% to 5%. Inclusion of the quadratic permits the size and direction of the effect of inflation on support for social welfare policy to vary with the level of inflation. The estimated coefficient for the quadratic term was not significantly different from zero in either model; hence we include a linear specification.
We also examined the effects of unemployment at its lagged level, as a raw change between the current and previous year, and as a percentage change between the current and previous year. The effect of unemployment was indistinguishable from zero in each of these specifications. On the same idea that the effect of changes in unemployment may be conditional upon the level of unemployment, we included a quadratic here as well. In all models, the quadratic term on unemployment never obtained statistical significance and was substantively tiny.
We also examined the effects of GSP at its current level, its lagged level, and as a raw change between the current and previous year. The effect of GSP was indistinguishable from zero in each of these specifications.
Within the time frame analyzed, the correlation between state-level inflation and state-level unemployment was −0.32, the correlation between state-level inflation and change in per capita GSP was 0.043, and the correlation between state-level unemployment and change in per capita GSP was −0.009.
Support for social welfare ranges from 0 (conservative) to 1 (liberal). The datapoints refer to the year-state averages across both indicators (i.e., the average opinion on Welfare Programs, within a state for a given year, combined with the average opinion on Food Stamps within the same year and state). When only one indicator is available, the dot represents the year-state average for the one indicator.
The reader may notice a few outlying observations in our state-level data. Results run without the outlying observations on inflation (California respondents in 1990) are nearly identical. Results run without the outlying observations on unemployment (West Virginia in 1984, 1986, and 1992; Louisiana in 1986; Alabama in 1984; and Michigan in 1984) were substantively similar.
We conceptualize economic interests as falling into the following 2 × 2 matrix:
Objective indicators
Subjective indicators
Self/Household (Pocketbook)
Income, work status, program receipt
Evaluations of how the respondent or respondent’s household has been or will be doing
Beyond the Self/Contextual (Sociotropic)
Inflation, unemployment, productivity
Evaluations of how the state/nation/group has been or will be doing
A considerable literature has examined pocketbook versus sociotropic determinants of electoral behavior (e.g., Kinder and Kiewiet 1979, 1981), using both objective and subjective indicators (see Lewis-Beck and Stegmaier 2000 for a review).
The disabled (3% of the sample) often receive Supplemental Security Income (SSI) and benefits from the Social Security Disability Insurance; they are excluded from analysis.
Note that the use of sociotropic information does not mean that individuals are altruistic: “The distinction between pocketbook and sociotropic politics is not equivalent to the distinction between a self-interested and an altruistic politics” (Kinder and Kiewiet 1981, p. 132). It simply means that contextual information about the state of the economy shapes political judgments.
We estimate each of our models with ordered probit, since the dependent variables are ordered categorical indicators. We include yearly fixed effects to allow for intercept differences across years, attributable to factors that we do not explicitly control in our model (such as political discourse, i.e., in the Welfare Reform era). We include regional dummies to capture time-invariant regional differences in the political culture surrounding social welfare policy. We are not able to include state-fixed effects due to the paucity of respondents from some states. These relationships could be modeled using hierarchical modeling or random effects models that attribute shared variance to individuals nested within states. We deal with this shared variance using robust standard error adjustments, clustering by year-state, which produce results that are quite similar to those produced using hierarchical techniques (Kam and Franzese 2007).
The predicted probabilities, based on the combined model, are graphed setting values to their means (or modes for categorical variables).
Note that this sociotropic measure is suboptimal, since we believe that most of the action occurs at the state-level. The NES only included a state-level economic assessments item in the 1992 survey.
Tables 3 and 4 provide results from ordered probit models, where respondents who reported “Don’t Know” or “Haven’t Thought About It” are set to the midpoint. We also estimated the models with selection equations, following Berinsky (2002). Our estimates of the (null) effect of state-level economic conditions remained unchanged. We also extended the time-period of our analysis. For the Guaranteed Jobs item, this meant that we went back to 1976; for the Services and Spending item, this meant that we went back to 1982. In so doing, we had to omit egalitarianism from the models (but since egalitarianism and the state-level economic indicators are not correlated, this should not have biased the estimated coefficients on the state-level economic conditions). The results were similar: null results for each of the state-level economic indicators.
These statistically insignificant coefficients could be attributable to collinearity between the multiple interaction terms. So, we estimated models with an interaction between black affect and only one of the macroeconomic indicators. The results were similar to those reported in Tables 5 and 6: a negative (but insignificant) interaction between feelings towards blacks and inflation appears when it comes to spending on Welfare and a positive but significant interaction between feelings towards blacks and inflation when it comes to spending on Food Stamps. The other interactions were insignificant. Finally, as a more direct test of whether changes in the composition of welfare recipients was responsible for more supportive views of welfare spending, we included several measures directly relating to the race of welfare recipients (e.g., the raw percentage of welfare recipients who were black; changes in the percentage of welfare recipients who were black). None of these were significantly related to support for Welfare Programs or Food Stamps.
In these models, Income is a trichotomous variable indicating low, middle, and high, corresponding to thirds in the income distribution.
Gilens’ analysis consists of an autoregressive (AR(1)) model, with a dummy included for the period between 1983 and 1988, in which there was an anomalous period of GDP growth. GDP is not analyzed alongside other macroeconomic indicators (unemployment or inflation) and no explicit justification is given for analyzing GDP instead of the other indicators.
Aggregate public opinion measures result from combining General Social Surveys, Roper polls, and two Consumer Attitudes and Behavior surveys. Like Gilens, Kluegel uses an AR(1) model to estimate the relationship.
We also analyzed the effects of national economic conditions—inflation, unemployment, and change in per capita gross domestic product. These analyses are a bit perilous, given the relatively few years that are available for analysis, and given the high degree of collinearity between the indicators. One of the symptoms of high collinearity is unstable coefficient estimates—especially estimates that change signs across models. We found that to be the case in our estimates. Hence, here are the estimates from the models where each economic indicator appears on its own. Notice that inflation is the only one that has a consistently positive effect, consistent with our state-level story. Unemployment rates have a negative relationship to Welfare Programs and a positive relationship for Food Stamps. The effect of productivity is significant but shifts direction: greater productivity is associated with less support for Welfare Programs (that is, the worse things are, the more support there is), but greater productivity is also associated with more support of Food Stamps.
Welfare Programs
Food Stamps
Inflation only
0.278**
0.038*
0.076
0.017
Unemployment only
−0.002
0.067**
0.021
0.014
Per capita change in
−0.171**
0.033**
GDP only
0.060
0.008
References
Alesina, A., & Ferraraz, E. L. (2001) Preferences for redistribution in the land of opportunities. National Bureau of Economic Research Working Paper 8267, Cambridge, MA
Axinn, J., & Stern, M. J. (2005) Social welfare: A history of the American response to need (6th ed). Boston: Allyn & Bacon.
Berinsky, A. J. (2002). Silent voices: Social welfare policy opinions and political equality in America. American Journal of Political Science, 46, 276–287.
Bernanke, B. S., & Mishkin, F. S. (1997). Inflation targeting: A new framework for monetary policy? Journal of Economic Perspectives, 11, 97–116.
Berry, W. D., Fording, R. C., & Hanson, R. L. (2000) An annual cost of living index for the American states, 1960–1995. Journal of Politics, 62, 550–567.
Berry, W. D., Fording, R. C., & Hanson, R. L. (2005). Cost of living index for the American states, 1960–2003 [Computer file] (Study #1275). ICPSR version. Ann Arbor: Inter-university Consortium for Political and Social Research [distributor].
Burtless, G. (1994). Public spending on the poor: Historical trends and economic limits. In: S. H. Danziger, G. D. Sandefur, & D. H. Weinberg (Eds.), Confronting poverty: Prescriptions for change. Cambridge: Harvard University Press.
Conover, P. J., Feldman, S., & Knight, K. (1986). Judging inflation and unemployment: The origins of retrospective evaluations. Journal of Politics, 48, 565–588.
Cook, F. L., & Barrett, E. J. (1992). Support for the American welfare state. New York: Columbia.
Delong, J. B. (2000). America’s historical experience with low inflation. Journal of Money, Credit, and Banking, 32, 979–993.
Durr, R. H. (1993). What moves policy sentiment? American Political Science Review, 87, 158–170.
Ellwood, D. (1988). Poor support: Poverty in the American family. New York: Basic Books.
Erikson, R. S., MacKuen, M. B., & Stimson, J. A. (2002). The macro polity. Cambridge: Cambridge University Press.
Feldman, S. (1988). Structure and consistency in public opinion: The role of core beliefs and values. American Journal of Political Science, 32, 416–440.
Feldman, S., & Steenbergen, M. (2001). The humanitarian foundation of public support for social welfare. American Journal of Political Science, 45, 658–677.
Feldman, S., & Zaller, J. R. (1992). The political culture of ambivalence. American Journal of Political Science, 36, 268–307.
Fong, C. (2001). Social preferences, self-interest, and the demand for redistribution. Journal of Public Economics, 82, 225–246.
Gabel, M., & Whitten, G. D. (1997). Economic conditions, economic perceptions, and public support for European integration. Political Behavior, 19, 81–96.
Gamson, W. A., & Lasch, K. E. (1983). The political culture of social welfare policy. In: S. E. Spiro & S. Yuchtman-Yaar (Eds.), Evaluating the welfare state: Social and political perspectives (pp 397–415). New York: Academic Press.
Geewax, M. (2005). Bernanke confirmation hearing: Inflation ‘target’ interests nominee. Atlanta Journal-Constitution 16 November 2005 Business.
Gilens, M. (1999). Why Americans hate welfare. Chicago: University of Chicago.
Gilens, M. (2001). Political ignorance and collective policy preferences. American Political Science Review, 95, 379–396.
Gramlich, E. M. (1974). The distributional effects of higher unemployment. Brookings Papers on Economic Activity 1974, 293–336.
Heclo, H. (1986). General welfare and two American political traditions. Political Science Quarterly, 101, 179–196.
Hibbs, D. A., Jr. (1987). The American political economy: Macroeconomics and electoral politics. Cambridge: Harvard University Press.
Iyengar, S. (1990). Framing responsibility for political issues: The case of poverty. Political Behavior, 12, 19–40.
Iyengar, S. (1994). Is anyone responsible? How television frames political issues. Chicago: University of Chicago Press.
Iyengar, S., & Kinder, D. R. (1987). News that matters: Television and American opinion. Chicago: University of Chicago Press.
Jacoby, W. G. (1994). Public attitudes toward government spending. American Journal of Political Science, 38, 336–361.
Jacoby, W. G. (2000). Issue framing and public opinion on government spending. American Journal of Political Science, 44, 750–767.
Kam, C. D., & Franzese, R. J., Jr. (2007). Modeling and interpreting interaction hypotheses in regression analysis. Ann Arbor: University of Michigan.
Kam, C. D., & Kinder, D. R. (1999). Ethnocentrism revisited: Public opinion and the American welfare state. Presented at the 1999 Annual Meeting of the American Political Science Association, Atlanta.
Katz, M. B. (1989). The undeserving poor: From the war on poverty to the war on welfare. New York: Pantheon Books.
Keane, M. P., & Prasad, E. S. (1991). The relation between skill levels and the cyclical variability of employment, hours, and wages. Minneapolis: Discussion Paper No. 41. Institute for Empirical Macroeconomics, Federal Reserve Bank of Minneapolis
Kinder, D. R., & Kiewiet, D. R. (1979). Economic discontent and political behavior: The role of personal grievances and collective economic judgments in congressional voting. American Journal of Political Science, 23, 495–527.
Kinder, D. R., & Kiewiet, D. R. (1981). Sociotropic politics: The American case. British Journal of Political Science, 11, 129–161.
Kluegel, J. R. (1987). Macro-economic problems, beliefs about the poor, and attitudes toward welfare spending. Social Problems, 34, 82–99.
Lewis-Beck, M. S., & Stegmaier, M. (2000). Economic determinants of electoral outcomes. Annual Reviews of Political Science, 3, 183–219.
Orr, L. L. (1976). Income transfers as a public good: An application to AFDC. The American Economic Review, 66, 359–371.
Reifschneider, D., & Williams, J. C. (2000). Three lessons for monetary policy in a low-inflation era. Journal of Money, Credit, and Banking, 32, 936–966.
Saunders, A. (2000). Low information: The behavior of financial markets and institutions. Journal of Money, Credit, and Banking, 32, 1058–1087.
Schneider, A., & Ingram, H. (1993). Social construction of target populations: Implications for politics and policy. American Political Science Review, 87, 334–347.
Schneider, S. K., & Jacoby, W. G. (2005). Elite discourse and American public opinion: The case of welfare spending. Political Research Quarterly, 58, 367–379.
Smith, T. W. (1987). That which we call welfare by any other name would smell sweeter. Public Opinion Quarterly, 51, 75–83.
Stevenson, R. T. (2001). The economy and policy mood: A fundamental dynamic of democratic politics? American Journal of Political Science, 45, 620–633.
Winter, N. J. G. (2006). Beyond welfare: Framing and the racialization of white opinion on social security. American Journal of Political Science, 50, 400–420.
Acknowledgments
We are grateful to Rebecca Blank, Sheldon Danziger, Paul Goren, Vincent Hutchings, John Scott, and attendees at the National Poverty Center Conference for Small Grant Recipients for valuable advice. We thank Emerald Nguyen, Carl Palmer, and Jeremy Poryes for research assistance. This work has been supported in part by a Small Research Grant from the National Poverty Center at the University of Michigan. Any opinions expressed are those of the authors.
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Appendix
Appendix
Raw correlations between dependent variables
| Welfare | Food Stamps | Guaranteed Jobs | Services and Spending |
|---|---|---|---|---|
Welfare | 1.0000 | |||
Food Stamps | 0.5848 | 1.0000 | ||
Guaranteed Jobs | 0.2912 | 0.2815 | 1.0000 | |
Services and Spending | 0.3195 | 0.2979 | 0.3042 | 1.0000 |
Variable coding
| Original Variable & Question Text | Coding |
|---|---|---|
Dependent variables | ||
Spending on Welfare Programs | Vcf0894: “Should federal spending on Welfare Programs be increased, decreased, or kept about the same?” | 0 (decreased); .5 (kept the same); 1 (increased) |
Spending on Food Stamps | Vcf9046: “Should federal spending on Food Stamps be increased, decreased, or kept about the same?” | 0 (decreased); .5 (kept the same); 1 (increased) |
Guaranteed Jobs | Vcf0809: “Some people feel that the government in Washington should see to it that every person has a job and a good standard of living. Others think the government should just let each person get ahead on his/their own. Where would you place yourself on this scale, or haven’t you thought much about this?” | 0 (let each get ahead) to 1 (government see to it). Don’t Know & Haven’t Thought About It are set to the midpoint. (see Note 23 for results from selection models) |
Services and Spending | Vcf0839: “Some people think the government should provide fewer services, even in areas such as health and education, in order to reduce spending. Other people feel that it is important for the government to provide many more services even if it means an increase in spending. Where would you place yourself on this scale, or haven’t you thought much about this?” | 0 (reduce spending) to 1 (increase spending). Don’t Know & Haven’t Thought About It are set to the midpoint. (see Note 23 for results from selection models) |
Individual-level Independent variables | ||
Income | Vcf0114: “Please look at this card/page (2000 FTF: the booklet) and tell me the letter of the income group that includes the income of all members of your family living here in [previous year] before taxes. This figure should include salaries, wages, pensions, dividends, interest, and all other income. (If uncertain: What would be your best guess?”) We measure income using six categories: 0–16.9%; 17–33.9%; 34–67.9%; 68–94.9%; top 5%; refused. Since the meaning of raw income levels changes over time, these categories allow us to place individuals within their contemporary income distribution. | Categorical dummies ( < 17%; 17–33%; 34–67%; 68–95%; 96% and up; refused) |
Retrospective household economic assessments | Vcf0880a: “We are interested in how people are getting along financially these days. Would you say that you [and your family living here] are better off or worse off financially than you were a year ago. In 2000: “Would you say that you (and your family) (FTF only: living here) are better off, worse off, or just about the same financially as you were a year ago? Is that much better/worse off or somewhat better/worse off?” | 5-point scale: 0 (much worse in past year) to 1 (much better in past year) |
Retrospective national economic assessments | Vcf0871: “Would you say that over the past year the nation’s economy has gotten better, stayed (all yrs. exc 1984: about) the same or gotten worse? Would you say much better/worse or somewhat better/worse?” | 5-point scale: 0 (much worse in past year) to 1 (much better in past year) |
Ideological identification | Vcf0803: “We hear a lot of talk these days about liberals and conservatives. Here is a 7-point scale on which the political views that people might hold are arranged from extremely liberal to extremely conservative. Where would you place yourself on this scale, or haven’t you thought much about this? (2000 telephone: When it comes to politics, do you usually think of yourself as extremely liberal, liberal, slightly liberal, moderate or middle of the road, slightly conservative, extremely conservative, or haven’t you thought much about this?) | 7-point scale: 0 (Extremely Conservative) to 1 (Extremely Liberal) Those who elect “Haven’t thought about this” are set to the midpoint of the scale. |
Party identification | Vcf0301: “Generally speaking, do you usually think of yourself as a Republican, a Democrat, an Independent, or what? (If Republican or Democrat) Would you call yourself a strong (REP/DEM) or a not very strong (REP/DEM)? (If Independent, other, or no preference:) Do you think of yourself as closer to the Republican or Democratic party?” | 7-point scale: 0 (Strong Republican) to 1 (Strong Democrat) |
Egalitarianism | Vcf9013–Vcf9018: Additive six item scale comprised of 5-point Likert responses to the following statements: Our society should do whatever is necessary to make sure that everyone has an equal opportunity to succeed. We have gone too far in pushing equal rights in this country. One of the big problems in this country is that we don’t give everyone an equal chance. This country would be better off if we worried less about how equal people are. It is not really that big a problem if some people have more of a chance in life than others. If people were treated more equally in this country we would have many fewer problems. | Continuous: 0 (inegalitarian) to 1 (egalitarian) |
Feelings toward Blacks | Vcf0206: “Still using the feeling thermometer, how would you rate Blacks?” | Continuous: 0 (cold) to 1 (warm) |
Age | Vcf0101: “What is the month, day and year of your birth?” | Continuous: 0 (17 years) to 1 (99 years) |
Gender | Vcf0104: Interviewer observation | Dummy: 0 if male; 1 if female |
Race | Vcf0106a and Vcf0108: 1972-LATER: In addition to being American, what do you consider your main ethnic group or nationality group? 2000: “What racial or ethnic group or groups best describes you?” To 1998: Interviewer observation of race; 1988 and later: “Are you of Spanish or Hispanic origin or descent?” | Dummies: Black: 0 if white or Hispanic; 1 if black Hispanic: 0 if white or black; 1 if Hispanic |
Education | Vcf0140a: Exact question text not available | 0 ( < 8 years) to 1 (post-graduate) |
Region | Vcf0901a: State of interview New England (ME, NH, VT, MA, CT, RI) Mid-Atlantic (NY, NJ, DE, PA) Midwest (IL, IN, MI, OH, WI, IA, KS, MN, MO, NE, ND, SD) Deep South (AL, GA, LA, MS, SC) Peripheral South (AR, FL, NC, TN, TX, VA) Border State (KY, MD, OK, DC, WV) Mountain (AZ, CO, ID, MT, NV, NM, UT, WY) Pacific (CA, WA, OR) | Dummies: New England; Mid-Atlantic; Midwest; Deep South; Peripheral South; Border State; Mountain; Pacific |
State-level Indicators | Source & Original Variable | Coding |
|---|---|---|
State Inflation Rate | Berry et al. (2005) For each year-state period, the dataset contains a cost of living index. We calculated the inflation rate for that year-state observation: Inflation j,t = (CPI j,t − CPI j,t-1)/CPI j,t-1 ICPSR Datafile #1275 | Inflation rate (0.75–9.95%) |
State Unemployment Rate | Bureau of Labor Statistics, seasonally adjusted unemployment rate Averaged across months to produce year-state unemployment rate http://www.bls.gov/lau/home.htm | Raw rate (2.2–15%) |
Per Capita Gross State Product Rate of Change | U.S. Department of Commerce Bureau of Economic Analysis http://www.bea.gov/regional/gsp | Per Capita % Change ( −31 to +25) |
U.S Department of Commerce Bureau of Economic Analysis (population values, to generate per capita figure) http://www.bea.gov/regional/spi/SA1-3fn.cfm | ||
U.S. Bureau of Labor Statistics (national CPI deflator used for constant dollar values) ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt |
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Kam, C.D., Nam, Y. Reaching Out or Pulling Back: Macroeconomic Conditions and Public Support for Social Welfare Spending. Polit Behav 30, 223–258 (2008). https://doi.org/10.1007/s11109-007-9048-3
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DOI: https://doi.org/10.1007/s11109-007-9048-3