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ABSTRACT
This paper uses the case of Ukraine to explore the association between attitudes and saving behavior. We hypothesize that individuals’ preferences and beliefs, which we proxy with support for left-wing populist economic policies, have an adverse effect on strategic, forward-looking behavior. Using the data from a nationally representative survey conducted in 2019, we find that support for populist economic policies has a negative association with a likelihood to have bank savings. The results hold in the presence of socio-economic and behavioral factors and when we remove the variation attributed to the cultural and socio-economic factors from our measure of economic populism.
Acknowledgments
We thank for the feedback from research seminar participants at TalTech University, especially Matti Keloharju, Triinu Tapver, Orsolya Soosaar, and Tairi Rõõm. We also thank participants of the Conference for Students and Young Researchers organized by the Central Bank of Ukraine, especially Mihnea Constantinescu, for their detailed comments. We are especially grateful to Karsten Staehr for the support, fruitful discussions, and exceptionally useful suggestions and to the editor and anonymous reviewers whose comments helped us to improve the quality of the present paper considerably. This work is partially supported by the Doctoral School in Economics and Innovation, ASTRA project TalTech development plan for 2014–2022 code 2014-2020.4.01.16-0032 (European Union, European Regional Development Fund), as well as by TalTech University under grants B57 “Efficiency in Financial Sector in Light of Changing Regulatory Environment”. This project also has received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No 952574. The survey data used in this study was collected by the Centre of Economic Strategy with the support of the Think Tank Development Initiative implemented by the International Renaissance Foundation in partnership with the Think Tank Fund with the financial support of the Embassy of Sweden in Kyiv. We thank the Centre for Economic Strategy for sharing the data. The funding provider had no role in the research process from study design to submission.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/00128775.2023.2198513.
Notes
1. Here, we understand political populism as the distrust toward the elites and the belief that there is an inherent conflict between the ordinary people and the elites (Mudde 2004). The majority of studies with a similar view on populism tend to measure it either as voting for parties that exhibit certain populist characteristics (Inglehart and Norris 2016; Hernández and Kriesi 2016; Van Hauwaert and Van Kessel 2018) or a set of survey questions about the belief in the existence of the inherent conflict between people and elites, disillusionment with elites and politics, and a preference for inexperienced over the career politicians. See Akkerman, Mudde, and Zaslove (2014), Spruyt, Keppens, and Van Droogenbroeck (2016) for more details.
2. On the other side of the spectrum, literature in economic development and financial inclusion is focused predominantly on the financial decision of households living at the level of the international poverty line.
3. Tax incentives are a standard remedy that aims at increasing savings by addressing financial constraints.
4. Due to the data limitations, we focus specifically on bank savings. However, the hypothesis should in the same way apply to broader measures of financial savings. We use such a measure in the robustness analysis.
5. See a brief discussion of Ukraine’s economic performance in Section AO. 5 in the accompanying Online Appendix.
6. GfK (2017) relies on a sample of adults older than 16 years. In contrast, most surveys, including the source of our data, survey the population above 18 years. Since, the population of 16–17 years of age is less likely to have bank savings, the share of the population with bank savings in GfK (2017) is at least 1–2% points lower than it could be in a sample of adults older than 18 years. Therefore, data in GfK (2017) is quite close to 11.7% in our data.
7. The database, including documentation and microdata, is available here: https://globalfindex.worldbank.org/.
8. The data includes only working Ukrainians. Therefore, it is likely to overestimate the fraction of savers.
9. As the interviews were mainly started in Russian and the question about the language of the interview was also mainly asked in Russian, it is likely that only those people who have a strong preference for Ukrainian chose to switch the language rather than continue in the default Russian.
10. We are aware that terms risk preferences and risk attitudes depict slightly different constructs. The term risk preferences are usually used within the revealed preferences approach, while the term risk attitudes are usually used to describe self-reported preferences. In the present paper, risk preferences are self-reported. Nevertheless, we use both terms interchangeably.
11. As an alternative way to deal with unreasonable present bias and longterm discount, we trimmed the outliers at the 95th percentile. That method produced similar results, which are not reported.
12. Our approach follows CES (2019), a report based on the same original survey data as the present study. However, in contrast to the present study, the economic populism index in CES (2019) increases by 1 if a person shows any support for a populist policy and is not normalized to the scale from 1 to 100.
13. Due to a large number of missing values in the variables indicating time preferences we run the populism proxies on two of the main specifications: excluding and then including variables present bias and longterm discount.
14. In Section 4.3 we also use broad savings rather than bank savings as a dependent variable. In those regressions, the effect of education becomes somewhat smaller, which provides suggestive evidence to this interpretation.
15. See more detailed discussion in Section 4.3, where we use savings rather than bank savings as a dependent variable.
16. And in the last model it approaches the threshold of statistical significance with the p-value of 0.108.
17. 3 out of 4 models in which the effect of populism is insignificant include controls for longterm discount and present bias. The results in these models may be different due to a significantly smaller, non-representative sample.
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Notes on contributors
Illiashenko Pavlo
Illiashenko Pavlo is a PhD student in the Faculty of Economics and Finance at School of Business and Governance, Tallinn University of Technology (TalTech). In his research, he focuses on various aspects of behavioral and household finance. His recent publications include papers in Research in International Business and Finance and Journal of Behavioral and Experimental Finance.
Mykhailyshyna Dariia
Mykhailyshyna Dariia is a PhD student in the Faculty of Economics at University of Bologna. In her research, she concentrates on applied microeconomics and empirical political economy.