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Assets and risk: A neglected dimension of economic voting

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French Politics Aims and scope

Abstract

Economic voting studies have been dominated by the classic reward–punishment paradigm, in which voters vote for the incumbent under good economic performance, but against under bad. This paradigm works well when the economic issue is a valence issue, such as prosperity. However, it leaves out positional economic voting, in which the voter's place in the economic structure influences policy preference, and thus party preference. More precisely, we suggest that the better the economic location of voters in terms of assets, high-risk assets in particular, the more they will vote right, because the right promises a better return on their investments. We demonstrate this effect in French presidential election data, from three national surveys – 1988, 1995 and 2002. This assets effect well exceeds other economic effects tested, and does so under strong statistical controls.

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Notes

  1. Duch and Stevenson (2008), Lewis-Beck and Stegmaier (2007), Lewis-Beck and Stegmaier (2008), Nannestad and Paldam (1994), Norpoth (1996).

  2. Lewis-Beck et al (2008).

  3. The idea of ‘sociotropic economic voting’ was launched by Kinder and Kiewiet (1981).

  4. See especially Clarke et al (2004), and their employment of this perspective in the British case.

  5. See Stokes (1963) and Stokes and Dilulio (1993) on the original distinction between ‘valence’ and ‘position’ issues.

  6. Kiewiet (1983, Chapter 2, p. 13).

  7. A current example comes from the US 2008 presidential election study by Lewis-Beck and Nadeau, who find that voter preferences on progressive tax policy strongly influenced Obama support: Lewis-Beck and Nadeau (2009).

  8. One may argue that pocketbook voting represents a type of positional economic voting. True, good performance from my pocketbook is certainly not a valence issue. But egotropic perceptions measure the evolution of a household economic situation compared to itself across time. As such, they do not form an indicator of a voter's place (compared to others) in the economic structure at one point in time.

  9. Abramson et al (2003, pp. 113–115), Cautrès and Heath (1996), Evans and Norris (1997), Flanagan and Zingale (2006, pp. 115–118), Franklin et al (1992).

  10. Bartels (2008), Stonecash (2000).

  11. Historically, the French National Election Study has been fielded irregularly. However, from 1988, there has reliably been a presidential election survey. Unfortunately, the 2007 survey, although now released for general use, is of relatively little value with respect to the risk-assets economic voting hypothesis, because it has so few relevant items. For a full discussion of this problem, and its explication for the 2007 election, see Foucault et al (forthcoming). There are some asset items in French legislative surveys (1978, 1988, 2002), and these are being explored in Nadeau et al (2010).

  12. Lollivier and Verger (1987).

  13. Piketty (2003), Piketty and Saez (2003).

  14. Rougerie (2002).

  15. Bartels (2008), Stonecash (2000).

  16. Knight (1921).

  17. Bergman (2004), To (1999).

  18. Arrondel (2002).

  19. Arrondel and Pardo (2008).

  20. Benartzi and Thaler (1995), Dahlback (1991), Huang and Litzenberger (1988).

  21. A caveat of the present study is that assets are not measured in terms of the quantitative amount owned by households. One may conjecture that such a measure would have produced even stronger results. In addition, more detailed batteries of asset items could be imagined, which would produce even stronger effects for this kind of variable. For instance, adding a fourth item (only available for the 1988 survey) – owning shares from privatized industries – in the high-risk battery increases the coefficient when estimated on this survey. All these remarks reinforce the importance of paying more attention to the impact of assets on political preferences in future election studies.

  22. See Kennedy (2008).

  23. Arrondel et al (2004), Cordier et al (2006), Lavigne et al (2001).

  24. Alesina and Rosenthal (1995), Boix (2000).

  25. McClosky and Zaller (1984).

  26. Lancelot (1981).

  27. Haegel and Sauger (2007).

  28. Beaudouin (1990).

  29. Denord (2007). See also Denord (2008).

  30. Boy and Mayer (1993), Lewis-Beck (1993, pp. 167–186), Pierce (1995).

  31. Boy and Mayer (1993, p. 174), Cautrès (2004).

  32. Converse and Pierce (1986), Pierce (1995).

  33. Haegel (1993), Fleury and Lewis-Beck (1993).

  34. Lewis-Beck and Chlarson (2002), Evans (2004).

  35. Lewis-Beck (1993), Inglehart (1984).

  36. Mayer and Tiberj (2004), Sauger (2009), Whitten (2004).

  37. The strategy, one of linear transformation, allows the efficient combination of a relatively large number of variables into one index. Our issue Index, I, is built from the following steps, using what amounts to a quasi-instrumental variables approach (see Kennedy, 2008, Chapter 9). Say the vote dependent variable for 1988, V88, is regressed on the seven issues, and a predicted V, call it V88-hat, created. The same is done for V95 and V02, to create predicted V variables for those years. Each of these V-hat variables are centered, by subtracting its mean, for example, V88-hat−mean V88-hat=I88. The same procedure is followed to create I95 and I02. This I score stands as a combined issue index, for assessing the impact of issues in that election year.

  38. Reported vote is used for 1988 and 1995. Vote intention is used in 2002 to account for the Le Pen candidacy and to balance the sample sizes for the three elections (34, 34 and 32 per cent of the total sample, respectively).

  39. It has done so in Britain, for example; see Clarke et al (2004, Table 4.3, p. 98).

  40. It is worth recalling that the notion of total effects (that is, direct effects plus indirect effects) derives from the path analysis approach, and rests on the traditional recursive modeling assumption of one-way causality and uncorrelated errors across equations. For a current assessment of the technique, within the structural equation framework, see Kaplan (2000).

  41. Bélanger and Lewis-Beck (2007).

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Authors and Affiliations

  1. Department of Political Science, University of Montréal, C.P. 6128, succursale Centre-ville, Montréal, H3C 3J7, QC, Canada

    Richard Nadeau & Martial Foucault

  2. Department of Political Science, University of Iowa, Iowa City, 52245, Iowa, USA

    Michael S Lewis-Beck

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  1. Richard Nadeau
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  2. Martial Foucault
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  3. Michael S Lewis-Beck
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Appendix

Appendix

Sources

Data come from three national surveys performed under the supervision of the CEVIPOF (Centre d’études de la vie politique française) in 1988, 1995 and 2002 (see Cautrès, 2004). Data are available at the following website: http://cdsp.sciences-po.fr/.

Variables

Presidential vote=1, if respondent supports a right-wing candidate in the presidential election, 0 otherwise (vote reported for 1988 and 1995, vote intention in 2002 because of the Le Pen candidacy).

Party identification=1, if respondent identifies with a right-wing party, 0 otherwise.

Ideology=1 if respondent locates on points 5, 6 or 7 on a left-right scale, 0 otherwise.

State regulation=1, if respondent thinks that the State should not regulate private firms more tightly in times of economic difficulties, 0 otherwise.

Socialism, nationalizations, stock market, profits, privatizations=1, if respondent expresses negative views about the first two terms and positive views about the last three, 0 otherwise.

Savings account=1, if respondent owns a saving account, 0 otherwise.

House/apartment=1, if respondent owns his or her house/apartment, 0 otherwise.

Country House=1, if respondent owns a country house, 0 otherwise.

A business, farm, or piece of land=1, if respondent owns a business, a farm or a piece of land, 0 otherwise.

Rental properties=1, if respondent owns a rental property, 0 otherwise.

Stocks=1, if respondent owns stocks, 0 otherwise.

Low-risk scale=Average of Saving accounts, House/apartment and Country House.

High-risk scale=Average of Business, farm or piece of land, Rental properties and Stocks.

Age=Age rescaled from 0 to 1.

Gender=1, if male, 0 if female.

Education=Level of education attained, rescaled from 0 to 1.

Income=Household total income, rescaled from 0 to 1.

Professionals=1, if senior manager or professional, 0 otherwise.

White collars=1, if white collar, 0 otherwise.

Blue collars=1, if blue collar, 0 otherwise.

Private sector=1, if working in the private sector, 0 otherwise.

Religion=1, if Catholic and attending church at least once a month, 0.67 if Catholic and attending church less than once a month, 0.33 if other religions, 0 otherwise.

Immigration=1, if the respondents strongly agree ‘there are too many immigrants in France’, 0.67 if somewhat agree, 0.33 if somewhat disagree, 0 if strongly disagree.

Economics=1, if ‘no risk of unemployment’ in 1988, ‘economy better’ in 1995, ‘unemployment not a priority’ in 2002; 0.5 if ‘small risk of unemployment’ in 1988, ‘economy same’ in 1995, ‘unemployment not a second or third priority’ in 2002; 0 if ‘high risk of unemployment’ in 1988, ‘economy worse’ in 1995, ‘unemployment first priority’ in 2002.

Homosexuality=1, if respondents ‘strongly agree’ that homosexuality is morally condemnable, 0.67 if somewhat agree, 0.5 if no opinion, 33 if somewhat disagree, 0 if strongly disagree in 1988; 1 if ‘strongly disagree’ homosexuality is an acceptable way of living one's sexuality, 0.67 if somewhat disagree, 0.5 if no opinion, 0.33 if somewhat agree, 0 if strongly agree, in 1995 and 2002.

French identity=1, if respondents ‘strongly agree’ they are proud of being French, 0.67 if somewhat agree, 0.5 if no opinion, 33 if somewhat disagree, 0 if strongly disagree, in 1988; 1 if respondents feel French only, 0.5 if they feel more French than European, 0 otherwise in 1995 and 2002.

Death penalty=1, if respondents ‘strongly agree’ death penalty should be reinstated, 0.67 if somewhat agree, 5 if no opinion, 33 if somewhat disagree, 0 if strongly disagree.

Environment=1, if respondents are willing to support an association for the defense of environment, 0 otherwise in 1988; 1 if environment is graded 8, 9 or 10/10 on a scale of problem importance in 1995, 0 otherwise; 1 if environment is identified as the most or second most important problem in 2002, 0 otherwise.

School=1, if respondents find ‘very serious’ the abolition of the free choice between public and private school, 0.67 if somewhat serious, 0.5 if no opinion, 33 if not very serious, 0 if not serious at all in 1988; 1 if respondents perceive private school as ‘very positive’, 0.67 if somewhat positive, 0.5 if no response, 33 if somewhat negative, 0 if very negative in 1995 and 2002.

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Nadeau, R., Foucault, M. & Lewis-Beck, M. Assets and risk: A neglected dimension of economic voting. Fr Polit 9, 97–119 (2011). https://doi.org/10.1057/fp.2011.5

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