Abstract
The paper employs surveys among Austrian households to study ownership and purchase intentions of crypto-assets. About 1.6% of Austrians own crypto-assets and about 5% can be viewed as potential adopters. Owners, on average, have higher financial knowledge and are more risk-tolerant than non-owners. Distrust in banks or in conventional currencies is not found to be an important driver of ownership. Intentions to adopt are strongly affected by profit expectations and by beliefs that crypto-assets offer advantages for payments—most adopters or potential adopters hold both beliefs. Perceptions of high volatility or the risk of fraud and online theft dampen the demand for crypto-assets.
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Notes
We use the term crypto-asset instead of crypto-currency or virtual-currency because crypto-assets lack the characteristics of conventional currencies (i.e. with respect to their usability for daily transactions or to provide a stable unit of account).
See for example “Bitcoin Is the New Gold - Invest in it, perhaps. But don't try to shop with it”, Bloomberg Opinion by Noah Smith (31 January 2018, accessed from https://www.bloomberg.com/opinion/articles/2018-01-31/bitcoin-is-the-new-gold on 19. December 2018) or “Bitcoin is the New Gold, a Better Safe Haven Asset: Goldman Sachs” (13 January 2018, accessed from https://www.ccn.com/bitcoin-new-gold-better-safe-haven-asset-goldman-sachs/ on 19. December 2018). For empirical analyses that qualify such claims, see e.g. Klein et al. (2018) and Baur, Dimpfl and Kuck (2018).
Henceforth the terms “resident of Austria” and “Austrians” will be used synonymously. This is somewhat imprecise, as the sample comprises of persons who have an address in Austria, regardless of their citizenship.
Parino et al. (2018) use a somewhat different approach. This paper employs country level proxies for Bitcoin adoption, derived from various internet sources such as the number of Bitcoin client software downloads per country, to infer the role of country-level economic and institutional characteristics.
With regard to illicit activities, surveys about crypto-assets share this problem with survey about cash holdings. A similar observation holds for mining activities.
This implies that 0.5% hold both Bitcoin and other crypto-assets.
The fact that we do not find a significant increase in past ownership in the second survey wave points towards a pure statistical effect.
To overcome the low number of observations, Henry et al. (2018) propose that future surveys could be based on sampling methods which generate a higher number of observations on owners (e.g. respondent-driven sampling).
Respondents were provided with a list of five potential reasons and were asked to choose one or several reasons that apply.
These figures refer only to the first and second wave of the survey.
Sample of about 1000 persons aged 14 or older (https://www.bitkom.org/Presse/Presseinformation/Inzwischen-kennen-zwei-Drittel-der-Bundesbuerger-Bitcoin.html). Further details on the sampling are not available.
For the interested reader, Table 8 summarizes ownership by socio-economic characteristics.
We prefer to use the dummy variables for net wealth—although these variables are based on a rough proxy measure of wealth. If we used household income, we would lose a sizeable share of observations due to item non-response. Given the already low number of observations for owners of crypto-assets this is critical.
Financial assets comprise investment funds, single company stocks, government bonds, government bills or other assets as antiques, paintings, etc.
Specifically, this can be shown by employing a different survey wave which contains both information on financial literacy and on newspaper/magazine reading habits.
Despite these relative differences, it is noteworthy that the majority of owners does not express concerns regarding the stability of the euro and has trust in banks.
The unconditional means of Owns crypto-assets are as follows. Bank savings, no assets: 0.9%, Bank savings, assets: 2.9%, No bank savings, assets: 13.3%.
In specification 3, the point estimate of Tech interest high more than doubles compared to specification 1 which raises concerns about multicollinearity. To check for this possibility, we have excluded Tech interest high and find that the point estimate of Euro unstable in 5 yrs remains significant and has roughly the same size (2.48).
On average, people without distrust in the stability of the euro expect an inflation rate (over the next year) of 2% and persons with distrust in the euro expect an inflation rate 2.8%. This difference is statistically significant.
The respective results are available upon request. Two examples: Among persons who are not concerned about the medium-term stability of the euro 5% perceived the euro unstable on international financial markets. The respective share is 59% for those with distrust in the medium-term price stability of the euro. Among persons who are not concerned about the medium-term stability of the euro 7% think that domestic banks and the Austrian financial market are unstable. The respective share is 56% for those with distrust in the medium-term price stability of the euro.
See Christelis et al. (2016) for a discussion of how trust in the ECB affects inflation expectations.
The question on attitudes was not asked for persons who are unaware (line 6 of Table 1) or who are aware but say that they are not interested (line 5 of Table 1). Therefore, the balance statistics are based on a smaller sample size. Moreover, item nonresponse was considerable for some statements. To inquire into the statistical significance of the balance statistics of Fig. 6, Table 9 presents all values along with their confidence intervals and with pairwise tests of equal coefficients. The general finding from these tests is that most differences are statistically significant.
Note that the underlying question does not ask about a time frame, e.g. adoption within the next year. As the time frame is left to the respondent Purchase intention can be seen as an upper limit of potential adoption.
At the same time, the descriptive evidence shows that trust in the European Central Bank is higher among owners than among non-owners of crypto-assets.
Kahn (2018) discusses the important role of privacy for (internet) transactions. We conjecture that privacy is an important reason why survey respondents believe that crypto-assets offer advantages for payments.
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Acknowledgements
We thank the anonymous referees, Elisabeth Beckmann and conference participants at the Bank of Canada, the Joint ECB –Banque Nationale de Belgique retail payments conference and the Noeg Annual Meeting for valuable comments. The paper extends a descriptive article about Fintechs in Austria that was coauthored with Doris-Ritzberger-Grünwald. I am grateful to her for valuable discussions which also affected this paper. We thank Christopher S. Henry, Gradon Nicholls and Kim Huynh at the Bank of Canada for sharing their survey questionnaire and for very helpful suggestions. We thank Elisabeth Ulbrich for her collaboration in the design of the questionnaire and the implementation of the survey. We acknowledge helpful comments on the questionnaire by Gabriella Chefalo, Christiane Dorfmeister, Pirmin Fessler, Ronald Neumann, Paul Pichler, Maria Silgoner, Martin Taborsky, Andreas Timel and Beat Weber (all Oesterreichische Nationalbank). The views expressed in this paper are those of the author. No responsibility for them should be attributed to the Oesterreichische Nationalbank or the Eurosystem. All remaining errors are the responsibility of the author.
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Appendix
Appendix
1.1 Definition of variables
Dependent variables
Owns crypto-assets | Ownership of crypto-assets is derived from two survey questions. The first question asks whether respondents have heard of “Bitcoin or of other so-called crypto-currencies”. For those respondents that have heard of crypto-assets, another question elicits whether respondents (i) currently own Bitcoin, (ii) currently own other “crypto-currencies”, (ii) owned them in the past, (iii) never owned but have interest, (iv) know of and (v) know of but have absolutely no interest. Dummy variable = 1 for answers (i) and (ii), = 0 for answers (iii), (iv) and (v) |
Interest crypto-assets broad | See above for a description of survey instruments. Dummy variable = 1 for answers (i), (ii) and (iv), = 0 for answers (iv) and (v) |
Purchase intention | Derived from the following statement: “If you think about Bitcoin or other crypto-currencies. Which of the following two statements best applies?” “It is very likely that I will acquire Bitcoin some time” strongly agree . agree . neutral . agree “It is very likely that I will not acquire Bitcoin” strongly agree Dummy variable = 1 if respondents agree or strongly agree to the first statement, = 0 if respondents answered neutrally or agreed or strongly agreed to the second statement |
Socio-economic variables
Level of education | Edu low = 1 if the highest level of education of the respondent is the completion of mandatory schooling (“Pflichschule mit/ohne Abschluss”), 0 otherwise. Edu medium = 1 if the respondent has completed some form of medium secondary education, e.g. an apprenticeship (“Pflichschule mit Lehre”) or a three-year technical school (“Fachschule, Handelsschule”), 0 otherwise. Edu high = 1 if the respondent has completed higher secondary or tertiary education (“Matura”, university degree), 0 otherwise |
In education, Employed, Unemployed, Retired | Dummy variables = 1 if respondent’s current labor force status corresponds to the respective characteristics (e.g. if a person is in education), 0 otherwise |
Financial wealth | High net wealth = 1 if respondents own their main residence and own a business, 0 otherwise. Medium net wealth = 1 if respondents own their main residence but do not own a business, 0 otherwise. Low net wealth = 1 if respondents rent their main residence (regardless of whether they own a business), 0 otherwise. This classification should provide for a rough proxy of financial wealth and builds upon a classification developed in Fessler and Schürz (2018) who demonstrate that information on tenure status, ownership of real estate that is rented out and ownership of business wealth provide a good classification for net wealth. Their definition was adapted due to data availability (no information is available on whether real estate is rented out) |
Asset holdings, holdings of bank savings | Respondents were asked whether they (i) own bank savings (dummy variable Bank savings) or (ii) investment funds, single company stocks, government bonds, government bills or other assets as antiques, paintings, etc. (summarized in the dummy variable Financial assets). We define four dummy variables. No bank savings, no assets = 1 if respondents do not have bank savings or financial assets, 0 otherwise. Bank savings, assets = 1 if respondents have both bank savings and financial assets, 0 otherwise. No bank savings, assets = 1 if respondents have no bank savings but own financial assets, 0 otherwise. Bank savings, no assets = 1 if respondents have bank savings but do not own financial assets, 0 otherwise |
Homeowner | Dummy variables = 1 if respondents are owners of an apartment or a house, 0 otherwise |
High financial risk | Based on the question: “If there are financial decisions in your household: which of the following statement best describes your attitude toward risk: a) if I can expect a substantial profit, I am willing to take substantial financial risks; b) if I can expect an above-average profit, I am willing to take above-average risks; c) if I can expect average profits, I am willing to take average financial risks; d) I do not want to take any risk. High financial risk = 1 if respondents choose a) or b), 0 otherwise. No financial risk = 1 if respondents choose d), 0 otherwise |
Tech interest high | Based on the following question: “How would you assess yourself in relation to technological developments, e.g. new devices or applications? Which of the following statement best applies to you?” Answers comprise “A) Highly interested, I would like to try new devices or applications immediately”, “B) I am interested, but would not want to buy or try new devices or applications immediately”, “C) I buy new devices or applications only if I see a benefit”, “D) I am not interested in technological developments and only buy new devices when I need them”. Tech interest high = 1 if respondents choose A) or B), 0 otherwise |
Media consumption | Respondents were provided with a list of Austrian newspapers and magazines and asked whether they read them on a regular basis (the full list is provided upon request). Answers to this question were used to separate respondents into three media types: Quality news = 1 if respondents read at least one quality newspaper or magazine. Only boulevard news = 1 if respondents either only read boulevard news or no newspapers at all, 0 otherwise. Intermediate news = 1 if respondents read any intermediate newspaper (e.g. regional newspapers) but no quality newspaper. Additionally, Number news sources refers to the number of newspapers/magazines that are read by respondents |
Trust variables
Discontent with the euro | Based on “Overall, how content are you with the euro as a currency?”. Dummy variable = 1 if respondents answer very discontent and rather discontent, 0 if answer is rather content, very content |
Expected inflation (12 months) | Derived from a sequence of questions on respondent’s expectations regarding the general level of prices in 12 months. First a question was asked about whether the change in prices will increase, decrease or stay the same. Then, respondents were asked by what percent prices will increase, decrease or stay the same (in categories). From these questions, a percentage value of expected inflation is computed |
Euro unstable in 5 yrs | Based on “And if you think about the coming 5 years—how certain are you that Austria will still have a stable currency (in terms of price stability)?”. Dummy variable = 1 if respondents answer very uncertain and rather uncertain, 0 if answer is rather certain, very certain |
No trust ECB | Based on “How much trust do you have in the European Central Bank?”. Dummy variable = 1 if answer is very high, rather high, 0 if is answer is rather low, very low |
No trust domestic banks | Based on “How much trust do you have in domestic banks?”. Dummy variable = 1 if answer is very high, rather high, 0 if is answer is rather low, very low |
Bank savings unsafe | Based on “How much trust do you have in the safety of bank savings?”. Dummy variable = 1 if answer is very high, rather high, 0 if is answer is rather low, very low |
No trust bank’s financial advice | Based on “How much trust do you have in the financial advice provided by your main bank?”. Dummy variable = 1 if answer is very high, rather high, 0 if is answer is rather low, very low |
No trust public TV | Based on “How much trust do you have in the public TV/radio?”. Dummy variable = 1 if answer is very high, rather high, 0 if is answer is rather low, very low |
Attitudes
All variables concerning attitudes are defined similarly. After the introductory statement “If you think about Bitcoin or other crypto-currencies. Which of the following two statements best applies?”, respondents were confronted with a list of statements and counterstatements and they were asked to indicate their consents with either a statement or the counterstatement, allowing for a neutral answer (no clear choice) In the following, only the statement and the corresponding opposing statement are shown and all variables are defined similarly as follows: Dummy variable = 1 if respondents agree or strongly agree to the first statement, = 0 if respondents answered neutrally or agreed or strongly agreed to the second statement | |
Offers advantages for payments | “Offers advantages over conventional payment methods” versus “Offers no advantages” |
Positive returns very likely | “Positive returns are very likely” versus “Losses are very likely” |
Great danger of fraud and online thefts | “Great danger of fraud and online theft” versus “No danger” |
High volatility in euro | “High volatility” versus “Low volatility” |
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Stix, H. Ownership and purchase intention of crypto-assets: survey results. Empirica 48, 65–99 (2021). https://doi.org/10.1007/s10663-020-09499-x
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DOI: https://doi.org/10.1007/s10663-020-09499-x