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Economic Insecurity and Voter Attitudes about Currency Crises

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Abstract

Currency crises are the most common type of financial crisis in recent decades, but little is known about how the public views these events. This paper argues that voters’ perceptions of their economic self-interests in general, and their employment prospects in particular, influence their attitudes about currency crises and preferred policy responses. We hypothesize that individuals with high degrees of job insecurity will be more concerned about currency depreciation, more opposed to orthodox policy responses such as raising the interest rate, and more supportive of unorthodox policy responses, such as intensifying capital controls. Data from nationally representative surveys in two countries experiencing currency crises recently—Argentina and Turkey—support our argument. A follow-up survey experiment in Turkey, which randomly primed some respondents about deteriorating labor market conditions, provides further evidence. Overall, the results show that concerns about the labor market have a strong and systematic influence on how voters respond to currency crises.

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Notes

  1. https://www.valordolarblue.com.ar/

  2. Calculations based on data from the World Development Indicators

  3. These studies draw on surveys conducted in the USA (Bearce and Tuxhorn 2017), Serbia, and the UK (Aklin et al. 2022), and China (Gueorguiev et al. 2020). Aklin et al. (2022) also conducted a survey in Argentina, a country with a much less stable exchange rate, but that survey did not ask questions about exchange rate depreciation.

  4. Some studies show that currency crises impact voters’ support for incumbent governments (Ahlquist et al. 2020; Steinberg 2022), but these studies do not ask citizens about their opinions about exchange rate depreciation.

  5. Some prior scholarship examines how individuals’ concerns about unemployment shape their preferences for domestic macroeconomic policies, drawing on a “Phillips curve”-type trade-off between inflation and unemployment (e.g., Scheve 2004; Jayadev 2008). While domestic macroeconomic policies often force a choice between reducing unemployment versus lowering inflation, currency crashes typically worsen both inflation and unemployment in the short term. For this reason, the logic of the Phillips curve is less applicable to the contexts we are studying here. Put differently, individuals’ concerns about job loss and their concerns about inflation (e.g., Aklin et al. 2022) are both likely to shape attitudes about depreciation, but these two considerations are unlikely to be closely linked to one another in this issue area.

  6. On the other hand, the maintenance of a stable and competitive real exchange rate has the potential to reduce unemployment (Frenkel and Ros 2006). This suggests that the short-term impact of nominal exchange rate changes differs from the longer-term impact of real exchange rate levels.

  7. This difference is statistically significant (p < 0.01). Our analysis is based on all countries with available data from the World Bank from 1960 to 2018, where we defined a currency crash as depreciations greater than 25% compared to the previous year.

  8. A third policy option is to sell foreign reserves, but this is often not a sustainable solution since reserves will eventually run out in severe currency crises.

  9. Over the long run, capital controls can reduce the efficient allocation of capital (e.g., Forbes 2007), which could dampen growth rates and therefore eventually create problems for the labor market. Our argument instead focuses on the short-term stabilizing effects of capital controls on the job market because we expect voters to pay more attention to these more immediate impacts. Moreover, empirical studies fail to find any clear or consistent relationship between capital controls and growth over the long run (e.g., Kose et al. 2009; Rodrik and Subramanian 2009).

  10. Marx and Picot (2020, 359) note that experimental studies are a “[p]romising way to tackle” the endogeneity problems that may afflict observational studies of this topic.

  11. However, in early 2022, in an effort to combat ongoing pressure on the lira, Turkey imposed a form of “soft capital controls” (Reuters 2022).

  12. Data come from the World Bank’s World Development Indicators database.

  13. Details on the designs of the three surveys fielded are presented in Appendix.

  14. When the lira depreciates, many Turkish households respond by transferring their savings out of lira and into dollars (Malsin and Hirtenstein 2021). By the end of 2018 (the year of the survey), foreign currency accounts constituted about 11% of all savings accounts (The Banks Association of Turkey 2019), and by volume, 49% of bank deposits in the country were held in foreign currency (Fitch 2022).

  15. These differences (insecure workers vis-à-vis other workers, the unemployed, and those not in labor force) are all statistically significant at p < 0.01 except for the insecure worker vs. other worker difference for the outcome variable “Support Capital Controls,” which is statistically significant at p < 0.10.

  16. Unfortunately, this survey did not ask about employment status. The question about job insecurity was asked to everyone. The baseline group in the regression is those that did not answer the question about job insecurity. While we cannot be certain that respondents in the “do not know/did not answer” categories (the left-out group in the regression) are not employed, this appears to be the most likely explanation. Consistent with this interpretation, only 20% of those of working age (20–69 years old) did not answer the question, compared to 34% for respondents aged 16–19, and 57% of respondents aged 70 or above.

  17. During the period of fieldwork of this survey (June–August 2019), unemployment had increased to around 14% from around 12.5% in spring of the same year (Turkish Statistical Institute). The increase in youth unemployment (aged 15–24) was particularly steep from around 23 to 27%. Unemployment levels continued to remain high for the rest of the year.

  18. There were two additional response categories to this question: “no one in the household has a job” and a no-response category. The total percentages of these responses are 11% and 12% in the treatment and control groups, respectively. Our experimental results are robust to the exclusion of these respondents from the analysis.

  19. We do not include controls because the treatment is randomly assigned. A likelihood ratio test from the logistic regression of treatment on respondents’ socio-demographics characteristics, reported in Table 8 of Appendix, is statistically insignificant, suggesting that randomization was successful.

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Acknowledgements

The research in this article was reviewed and approved by Koç University Committee on Human Research (protocol no. 2017.127.IRB3.069).

Funding

This research was supported by the Scientific and Technological Research Council of Turkey (TUBITAK, Project No. 217K178).

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Authors and Affiliations

  1. Department of International Relations, Koç University, Rumelifeneri Yolu Sarıyer, 34450, Istanbul, Turkey

    Selim Erdem Aytaç

  2. School of Advanced International Studies, Johns Hopkins University, 1717 Massachusetts Ave NW, Washington, DC, 20015, USA

    David Steinberg

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Appendix

Appendix

Turkey and Argentina in Comparative Perspective

Table 2 lists all countries whose currencies depreciated more than 20% against the US Dollar between 2017 and 2019. Figure 5 shows the trend in annual unemployment rates in Turkey and Argentina. Figure 6 presents the monthly lira/dollar exchange rate from the start of the Erdoğan era (March 2003) until the end of 2019. The dashed vertical lines show the months of the July 2018 and July 2019 Turkey surveys. As can be seen, the first survey coincides with the intensification of the currency crisis. Figure 7 presents the monthly peso/dollar exchange rate during the era of Mauricio Macri’s government. The vertical dashed line is the month of the 2019 Argentina survey. One of the sharpest depreciations of the peso (more than 20%) during this period happened in August 2019, when the incumbent government performed poorly in the first stage of the presidential elections. The market responded negatively to this outcome due to increased political uncertainty and the anticipation of a leftward shift in government. The survey was fielded just 2 months after, in October 2019.

Table 2 Countries with large exchange rate depreciations, 2017–2019
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Fig. 5
figure 5

Unemployment rates in Argentina and Turkey, 2000–2021. Source: World Bank World Development Indicators

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Fig. 6
figure 6

Monthly lira/dollar exchange rate 2003–2019 with the timing of the Turkey surveys

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Fig. 7
figure 7

Monthly peso/dollar exchange rate during Mauricio Macri’s government with the timing of the Argentina survey

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Information About the Surveys

The 2018 Turkey survey was fielded shortly after the 2018 general election, between July 2 and July 7. The survey is a nationally representative sample of 2021 voting-age individuals. The sampling procedure, implemented by the reputable firm Frekans Research (http://www.frekans.com.tr), first randomly selected clusters within each of the country’s ten main geographic regions and then randomly sampled individuals within those clusters. The interviews were conducted face-to-face. Descriptive statistics of the variables used in the analyses are presented in Table 3.

Table 3 Descriptive statistics for the 2018 Turkey survey
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The 2019 Turkey survey was fielded between June 24 and August 2, 2019. The survey is a nationally representative sample of 2021 voting-age individuals. The sampling procedure for the survey starts with the use of Turkish Statistical Institute’s (TUIK) NUTS-2 regions. The target sample was distributed according to each region’s share of urban and rural population in accordance with current records of the Address Based Population Registration System (ADNKS). Household addressed was randomly selected and provided by TUIK. Selection of individuals in households is done on the basis of reported target population of 18 years or older in each household according to a lottery method. If for any reason that individual could not respond to our questions in our first visit, then the same household is visited up to three times until a successful interview is conducted. All interviews were conducted face-to-face by Frekans Research (http://www.frekans.com.tr) in respondents’ households. Descriptive statistics of the variables used in the analyses are in Table 4.

Table 4 Descriptive statistics for the 2019 Turkey survey
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The Argentina survey was administered by an Argentine polling company (Isonomía Consultores) to 1851 Argentine adults between October 14 and 22, 2019, and was designed to be representative of Argentina’s urban population. Data was collected using a combination of face-to-face interviews and telephone surveys based on random-digit dialing. The sample was stratified by the country’s major economic regions and by city sizes. Quotas were set by gender, age group, and the level of educational attainment for the head of household. Table 5 presents descriptive statistics from this survey.

Table 5 Descriptive statistics for the 2019 Argentina survey
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Supplementary Empirical Results

Table 6 presents the full regression results for the 2018 Turkey survey while Table 7 presents complete regression results for the Argentina survey. Using the 2019 Turkish survey experimental data, Table 8 shows that treatment assignment, which is the dependent variable in this model, is not correlated with demographic attributes. Figure 8 displays histograms of the dependent variable, for control group respondents, in the 2019 Turkish survey.

Table 6 Drivers of attitudes about currency crises in Turkey
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Table 7 Drivers of attitudes about currency crises in Argentina
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Table 8 Logistic regression of treatment assignment on respondents’ socio-demographic characteristics in the 2019 Turkey survey experiment
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Fig. 8
figure 8

The distributions of the outcome questions in the Turkey 2019 survey experiment for the control group respondents

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Aytaç, .E., Steinberg, D. Economic Insecurity and Voter Attitudes about Currency Crises. St Comp Int Dev (2023). https://doi.org/10.1007/s12116-023-09399-8

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