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Decision making under uncertainty: the relation between economic preferences and psychological personality traits

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Abstract

Both economists and psychologists are interested in understanding decision making under uncertainty. Yet, they rely on different concepts to analyse human behaviour: economists use economic preference parameters rooted in utility theory, while psychologists use personality traits to describe responses to uncertain situations. Using a large sample of university students, this study examines and contrasts five economic preference parameters and six psychological personality traits that are commonly used to study individuals’ attitudes towards uncertainty. A novelty of this paper is including both the economic concept of ambiguity aversion as well as the personality trait of ambiguity intolerance. We find that standard economic preference measures based on incentivized choice tasks seem to capture rather different characteristics than psychological personality traits. In contrast, economic preference measures obtained from self-assessment questions appear more related to personality traits, especially ambiguity intolerance.

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Notes

  1. While Dimmock et al. (2015) are the first to show this in the context of ambiguity preferences, the idea goes back to Smith (1961). It has subsequently been used by Roth and Malouf (1979) and generalized in Berg et al. (1986).

  2. Kirton (1981) is widely used in empirical work in social psychology. For a review, see Furnham and Ribchester (1995). Another important Ambiguity Tolerance scale is by Norton (1975).

  3. Before proceeding to the actual choice lists to measure risk and ambiguity preferences, subjects were asked to find the right answers to some control questions. They are presented in Appendix 1.

  4. Since the sessions lasted for about 60 min, the payoffs are substantial. The lowest payment was GBP 4, the highest payment GBP 21.

  5. The average scores of the two ambiguity questions are also significantly different from each other (t test, p value \(< 0.01\)).

  6. It should be noted, however, that Heath and Tversky (1991) measure perceived competence and ambiguity premia for the very same specific question, whereas our measure of self-esteem is not related to the task measuring ambiguity preferences.

  7. In addition to the correlation analysis, we also use kernel-weighted linear polynomial regressions to explore any non-linear relation between economic preferences and personality traits. A few outliers aside, the results suggest a monotonic relation between economic preferences and personality traits. In most cases the relation is even linear.

  8. Regression tests of the psychological personality traits on the various risk and ambiguity preference measures give similar results as the pairwise Pearson linear correlation statistics of Table 3, panel A.

  9. The economic concept of ambiguity was first introduced by Knight (1921). Ambiguity is therefore sometimes known as ‘Knightian uncertainty’. Knight, however, did not use the term ‘ambiguity’ to describe this type of uncertainty.

  10. An alterative view is that both concepts are based on the same fundamental roots, but have been increasingly overstretched across the two disciplines, leading to the empirical differences documented in this study. The debate whether some concepts become too overstretched across subfields is well known in other disciplines of social sciences; see Sartori (1970).

  11. This is especially important as previous studies are inconclusive on the relationship between ambiguity aversion, ambiguity intolerance and real-life behaviour. The recent survey by Trautmann and van de Kuilen (2016), e.g. finds little evidence for external validity of economic ambiguity preferences (i.e. their predictive power for real-life behaviour.)

  12. The actual decision table presented to the subjects depends on the color chosen. In this appendix, we assume that the selected color is white. If the selected color is black, the word “white” has to be replaced with “black”, and vice versa.

  13. In practice, the ambiguous urn was filled with 10 balls of the winning colour. Of course, this was unknown to participants. While this is deception, this type of deception is not harmful to subjects. Since the computer randomly drew a ball from the chosen urn only at the end of the session, there was no possibility for subjects to update their belief about the composition of the ambiguous urn for subsequent decisions.

  14. The instructions are taken from the psychology literature, see, e.g. Mac Donald Jr (1970).

  15. This single-item measure is highly correlated (0.68) with the selected items of the Extended Life Orientation test by Chang et al. (1997).

  16. Similar to Robins et al. (2001), this item uses a five-point answer scale.

References

  • Allport, G. W., & Odbert, H. S. (1936). Trait-names: A psycho-lexical study. Psychological Monographs, 47, 1–171.

    Google Scholar 

  • Almlund, M., Duckworth, A., Heckman, J., & Kautz, T. (2011). Personality psychology and economics. IZA Discussion Paper 5500.

  • Bagana, E., Raciu, A., & Lupu, L. (2011). Self esteem, optimism and exams’ enxiety among high school students. Procedia—Social and Behavioural Sciences, 30, 1331–1338.

    Google Scholar 

  • Becker, A., Deckers, T., Dohmen, T., Falk, A., & Kosse, F. (2012). The relationship between economic preferences and psychological preference measures. Annual Review of Economics, 4, 453–478.

    Google Scholar 

  • Berg, J. E., Daley, L. A., Dickhaut, J. W., & O’Brien, J. R. (1986). Controlling preferences for lotteries on units of experimental exchange. Quarterly Journal of Economics, 101(2), 281–306.

    Google Scholar 

  • Bilker, W. B., Hansen, J. A., Brensinger, C. M., Richard, J., Gur, R. E., & Gur, R. C. (2012). Development of abbreviated nine-item forms of the raven’s standard progressive matrices test. Assessment, 19(3), 354–396.

    Google Scholar 

  • Bochner, S. (1965). Defining intolerance of ambiguity. The Psychological Record, 15(3), 393–400.

    Google Scholar 

  • Borghans, L., Duckworth, A. L., Heckman, J., & ter Weel, B. (2008). The economics and psychology of personality traits. IZA working paper 3333.

  • Borghans, L., Golsteyn, B. H. H., Heckman, J., & Meijers, H. (2009). Gender differences in risk aversion and ambiguity aversion. Journal of the European Economic Association, 7(2–3), 649–658.

    Google Scholar 

  • Budner, S. (1962). Intolerance for ambiguity as a personal variable. Journal of Personality, 30, 29–50.

    Google Scholar 

  • Burks, S. V., Carpenter, J. P., Götte, L., & Rustichini, A. (2009). Cognitive skills affect econoics preferences, social awareness, and job attachement. Proceedings of the National Academy of Science (USA), 106, 7745–7750.

    Google Scholar 

  • Butler, J. V., Guiso, L., & Jappelli, T. (2014). The role of intuition and reasoning in driving aversion to risk and ambiguity. Theory and Decision, 77, 455–484.

    Google Scholar 

  • Chakravarty, S., & Roy, J. (2009). Recursive expected utility and the separation of attitudes towards risk and ambiguity: An experimental study. Theory and Decision, 66(3), 199–228.

    Google Scholar 

  • Chang, E. C., Maydeu-Olivares, A., & D’Zurilla, T. (1997). Optimism and pessimism as partially independent constructs: Relationship to positive and negative affectivity and psychological well-being. Personality and Individual Differences, 23(3), 433–440.

    Google Scholar 

  • Charness, G., Karni, E., & Levin, Dan. (2013). Ambiguity attitudes and social interactions. Journal of Risk and Uncertainty, 46, 1–25.

    Google Scholar 

  • Chateauneuf, A., Eichberger, J., & Grant, S. (2007). Choice under uncertainty with the best and worst in mind: Neo-additive capacities. Journal of Economic Theory, 137, 538–567.

    Google Scholar 

  • Chemers, M. M., Watson, C. B., & May, S. T. (2000). Disposal affect and leadership effectiveness: A comparison of self-esteem, optimism and efficacy. Personality and Social Psychology Bulletin, 26(3), 267–277.

    Google Scholar 

  • Chow, C. C., & Sarin, R. K. (2002). Known, unknown, and unknowable uncertainties. Theory and Decision, 52, 127–138.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the social sciences. New York: Lawrence Erlbaum Associates.

    Google Scholar 

  • Daly, M., Harmon, C. P., & Delaney, L. (2009). Psychological and biological foundations of time preference. Journal of the European Economic Association, 7(2–3), 659–669.

    Google Scholar 

  • Dimmock, S. G., Kouwenberg, R., Mitchell, O. S., & Peijnenburg, K. (2015). Estimating ambiguity preferences and perceptions in multiple prior models: Evidence from the field. Journal of Risk and Uncertainty, 51(3), 219–244.

    Google Scholar 

  • Dohmen, T., Falk, A., Huffman, D., & Sunde, U. (2010). Are risk aversion and impatience related to cognitive ability? American Economic Review, 100(3), 1238–1260.

    Google Scholar 

  • Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: Measurement, determinants and behavioral consequences. Journal of the European Economic Association, 9(3), 522–550.

    Google Scholar 

  • Du, N., & Budescu, D. V. (2005). The effects of imprecise probabilities and outcomes in evaluating investment options. Management Science, 51(12), 1791–1803.

    Google Scholar 

  • Ellsberg, D. (1961). Risk, ambiguity and the savage axioms. Quarterly Journal of Economics, 75(4), 643–669.

    Google Scholar 

  • Falk, A., Becker, A., Dohmen, T., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time and social preferences. working paper.

  • Fischbacher, U. (2007). z-tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171–178.

    Google Scholar 

  • Frenkel-Brunswik, E. (1949). Intolerance of ambiguity as and emotional and preceptual personality variable. Journal of Personality, 18(1), 108–143.

    Google Scholar 

  • Frey, R., Pedroni, A., Mata, R., Rieskamp, J., & Hertwig, R. (2017). Risk preference shares the psychometric structure of major psychological traits. Science Advances, 3, 1–13.

    Google Scholar 

  • Furnham, A., & Ribchester, T. (1995). Tolerance of ambiguity: A review of the concept, its measurement and applications. Current Psychology, 14(3), 179–199.

    Google Scholar 

  • Gilboa, I., & Schmeidler, D. (1989). Maxmin expected utility with non-unique prior. Journal of Mathematical Economics, 18, 141–153.

    Google Scholar 

  • Heath, C., & Tversky, A. (1991). Preference and belief: Ambiguity and competence in choice under uncertainty. Journal of Risk and Uncertainty, 4(1), 5–28.

    Google Scholar 

  • Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644–1655.

    Google Scholar 

  • Kirton, M. J. (1981). A reanalysis of two scales of tolerance of ambiguity. Journal of Personality Assessment, 45(4), 407–414.

    Google Scholar 

  • Knight, F. H. (1921). Risk, uncertainty, and profit. Boston, MA: Houghton Mifflin Company.

    Google Scholar 

  • Lauriola, M., & Levin, I. P. (2001). Relating individual differences in attitude toward ambiguity to risky choices. Journal of Behavioral Decision Making, 14(2), 107–122.

    Google Scholar 

  • Lönnqvist, J.-E., Verkasalo, M., Walkowitz, G., & Wichard, P. C. (2015). Measuring individual risk attitudes in the lab: Task or ask? An empirical investigation. Journal of Economic Behaviour and Organization, 119, 254–266.

    Google Scholar 

  • Mac Donald, A. P, Jr. (1970). Revised scale for ambiguity tolerance: Reliability and validity. Psychological Reports, 26, 791–798.

    Google Scholar 

  • Mata, R., Frey, R., Richter, D., Schupp, J., & Hertwig, R. (2018). Risk preference: A view from psychology. Journal of Economic Perspectives, 32(2), 155–172.

    Google Scholar 

  • McLain, D. L. (2009). Evidence of the propoerties of an ambiguity tolerance measure: The multiple stimulus types ambiguity tolerance scale-ii (mstat-ii). Psychological Reports, 105(3), 975–988.

    Google Scholar 

  • Norton, R. W. (1975). Measurement of ambiguity tolerance. Journal of Personality Assessment, 39(6), 607–619.

    Google Scholar 

  • Prokosheva, S. (2016). Comparing decisions under compound risk and ambiguity: The importance of cognitive skills. Journal of Behavioural and Experimental Economics, 64, 94–105.

    Google Scholar 

  • Pulford, B. D. (2009). Is luck on my side? Optimism, pessimism and ambiguity aversion. The Quarterly Journal of Experimental Psychology, 62(6), 1079–1087.

    Google Scholar 

  • Roberts, B. W. (2009). Back to the future: Personality and assessment and personality development. Journal of Research in Personality, 43(2), 137–145.

    Google Scholar 

  • Robins, R. W., Hendin, H. M., & Trzesniewski, K. H. (2001). Measuring global self-esteem: Construct validation of a single-item measure and the rosenberg self-esteem scale. Personality and Social Bulletin, 27(2), 151–161.

    Google Scholar 

  • Roth, A. E., & Malouf, M. W. (1979). Game-theoretic models and the role of information in bargaining. Psychological Review, 86(6), 574–594.

    Google Scholar 

  • Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs, 80(1), 1–28.

    Google Scholar 

  • Rubinstein, A. (2007). Instinctive and cognitive reasoning: A study of response times. Economic Journal, 117, 1243–1259.

    Google Scholar 

  • Rustichini, A., DeYoung, C. G., Anderson, J. E., & Burks, S. E. (2016). Toward the integration of personality theory and decision theory in explaining economic behaviour: An experimental investigation. Journal of Behavioural and Experimental Economics, 64, 122–137.

    Google Scholar 

  • Rydell, S. T., & Rosen, E. (1966). Measurement and some correlates of need cognition. Psychological Reports, 19, 139–165.

    Google Scholar 

  • Sartori, G. (1970). Concept misformation in comparative politics. American Political Science Review, 64(4), 1033–1053.

    Google Scholar 

  • Savage, L. J. (1954). The Foundations of Statistics. New York: Wiley.

    Google Scholar 

  • Smith, C. A. B. (1961). Consistency in statistical inference and decision. Journal of the Royal Statistical Society. Series B (Methodological), 23(1), 1–37.

    Google Scholar 

  • Spearman, C. (1904). The proof and measurement of association between two things. American Journal of Psychology, 15, 72–101.

    Google Scholar 

  • Tanaka, Y., Fujino, J., Ideno, T., Okubo, S., Takemura, K., Miyata, J., et al. (2015). Are ambiguity aversion and ambiguity intolerance identical? A neuroeconomics investigation. Frontiers in Psychology, 5(1550), 1–7.

    Google Scholar 

  • Trautmann, S. T., & van de Kuilen, G. (2016). Blackwell handbook of judgment and decision making. Chapter: Ambiguity attitudes. Oxford: Blackwell.

    Google Scholar 

Download references

Acknowledgements

We are grateful to Elisa Cavatorta, Luc Meunier, Daniel Navarro, participants at the FUR 2018 conference in York (UK), the IMEBESS 2019 conference in Utrecht (Netherlands), the research seminar at Birkbeck College (UK) and two anonymous referees for helpful comments and discussions. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Any remaining errors are ours.

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  1. Birkbeck College, University of London, Malet Street, Bloomsbury, London, WC1E 7HX, UK

    David Schröder

  2. IDC Herzliya, Kanfei Nesharim St, 4610101, Herzliya, Israel

    Gail Gilboa Freedman

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Appendices

Appendix 1: Economic preferences

This appendix presents the economic preference measures, the two incentivized decision tasks and the three self-assessment questions.

Before each choice task, subjects were presented examples of the choice tasks to familiarize themselves with the design. In addition, subjects were asked several control questions before the risk task to ensure that they understood the tasks. Only after correctly answering these questions, the actual tasks started. The control questions are presented below the risk task.

Risk task: This task is taken from decision sheet B of Chakravarty and Roy (2009).

In this task you need to fill in the decision table shown below. The decision table consists of 10 different situations, listed 1 to 10. Each situation offers you a choice between drawing a ball from two different urns, urn A or urn B. Both urns contain 10 balls, either white or black.

  • The composition of urn A is identical in all 10 situations. There are 5 white balls and 5 black balls.

  • The composition of urn B changes from one situation to the next. The number of white balls increases incrementally from 0 white balls in situation 1 to 9 white balls in situation 10, while the number of black balls decreases accordingly.

At the end of the session, the computer will randomly select one out of the 10 situations. Then, depending on whether you have chosen urn A or urn B in that situation, the computer will randomly draw one ball from that urn. Depending on the color of the ball, you earn the points indicated in the table. Notice that even though you will make 10 decisions, only one of these will determine the points you earn, but you will not know in advance which situation will be selected (they are equally likely to be selected).

In each situation, from which urn do you prefer to draw a ball, urn A or urn B?

Situation

URN A:

URN B:

Your choices

If a white ball is drawn you earn 6 points

If a white ball is drawn you earn 10 points

 

If a black ball is drawn you earn 4 points

If a black ball is drawn you earn 0 points

 

1

5 white balls, 5 black balls

0 white balls, 10 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

2

5 white balls, 5 black balls

1 white ball, 9 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

3

5 white balls, 5 black balls

2 white balls, 8 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

4

5 white balls, 5 black balls

3 white balls, 7 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

5

5 white balls, 5 black balls

4 white balls, 6 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

6

5 white balls, 5 black balls

5 white balls, 5 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

7

5 white balls, 5 black balls

6 white balls, 4 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

8

5 white balls, 5 black balls

7 white balls, 3 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

9

5 white balls, 5 black balls

8 white balls, 2 black balls

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

10

5 white balls, 5 black balls

9 white balls, 1 black ball

Urn A \(\bigcirc\)\(\bigcirc\) Urn B

Participants had to correctly answer three control questions before starting the risk task:

  1. 1.

    What is the probability of winning six points when drawing a ball from urn A, in each situation (in %)? [Correct answer: 50%]

  2. 2.

    In situation 4, what is the probability of winning ten points when drawing a ball from urn B (in %)? [Correct answer: 30%]

  3. 3.

    In situation 5, which urn should you choose if you prefer a 50% chance to win six points and a 50% chance to win four points over a 40% chance to win ten points? [Correct answer: urn A]

Ambiguity task: The task extends the Ellsberg (1961) thought experiment to different situations, similar to Lauriola and Levin (2001) and Butler et al. (2014).

In this task, we present you a decision table with 11 situations. Each situation offers you a choice between drawing a ball from two different urns, urn 1 or urn 2. Both urns contain 10 balls, either white or black.

  • Urn 1: The composition of urn 1 changes from one situation to the next. While the number of balls in one color (e.g., white) increases incrementally from 0 to 10, the number of balls of the other color (e.g., black) decreases accordingly.

  • Urn 2: The composition of urn 2 is identical in each situation. However, you don’t know how many balls are white and how many balls are black. Any combination is possible. There might be from 0 to 10 white balls, with the remaining balls being black.

One ball will be drawn from the urn you choose. The points you can earn depend on the color of the ball drawn. Only one color yields some points. You can choose whether the color that yields points is white or black. Please choose the color of the ball that provides you points:

  • white

  • black

Please look at the decision table below.Footnote 12In each of the 11 situations, we would like you to indicate from which urn (urn 1 or urn 2) you prefer drawing a ball. As explained before, both urns contain 10 balls, either white or black.

  • Urn 1: The composition of urn 1 changes from one situation to the next. The number of white balls increases incrementally from 0 white balls in situation 0 to 10 white balls in situation 10, while the number of black balls decreases accordingly.

  • Urn 2: The composition of urn 2 is identical in all situations. However, the exact composition of urn 2 is unknown. Any combination of white and black balls is possible: there might be 10 white balls, or 10 black balls, or any other possible combination of white and black balls.

If a white ball is drawn, you earn 10 points. If a black ball is drawn, you earn no points.

At the end of the session, the computer will randomly select one out of the 11 situations. Then, depending on whether you have chosen urn 1 or urn 2 in that situation, the computer will randomly draw one ball from that urn. Depending on the color of the ball, you earn the points indicated in the table.Footnote 13Notice that even though you will make 11 decisions, only one of these will determine the points you earn, but you will not know in advance which situation will be selected (they are equally likely to be selected).

In each situation, from which urn do you prefer to draw a ball, urn 1 or urn 2?

Situation

URN 1:

URN 2:

Your choices

If a white ball is drawn you earn 10 points

If a white ball is drawn you earn 10 points

 

0

0 white balls, 10 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

1

1 white ball, 9 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

2

2 white balls, 8 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

3

3 white balls, 7 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

4

4 white balls, 6 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

5

5 white balls, 5 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

6

6 white balls, 4 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

7

7 white balls, 3 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

8

8 white balls, 2 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

9

9 white balls, 1 black ball

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

10

10 white balls, 0 black balls

Unknown composition

Urn 1 \(\bigcirc\)\(\bigcirc\) Urn 2

In addition to incentivized choice tasks, we also assess risk and ambiguity preferences using non-incentivized self-assessment questionnaires based on Likert scales.

Risk question: The self-assessment question to measure risk preferences is taken from Dohmen et al. (2011).

How do you see yourself? Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks? Please select your answer on the scale, where the value 0 means “not at all willing to take risks” and the value 10 means “very willing to take risks.”

Ambiguity questions: The two self-assessment questions to measure ambiguity preferences are taken from McLain (2009).

Please respond to the following two statements by indicating the extent to which you agree or disagree with them on a scale from 1 (I strongly agree) to 7 (I strongly disagree).

  1. 1.

    I try to avoid situations that are ambiguous.

  2. 2.

    I find it hard to make a choice when the outcome is uncertain.

Appendix 2: Personality traits

This appendix presents the survey or self-assessment questions used to measure the subjects’ personality traits. They are taken from self-reporting scales of the psychology literature.

In this part, we present you a list of statements. Please indicate the extent to which you agree or disagree with them. Please do not spend too much time on each statement. There are no right or wrong answers and therefore your first response is important. Nevertheless, try to be as honest as you can be. Answer according to your own feelings, rather than how you think most people would answer. Don’t worry about being consistent in your responses. Be sure to answer every statement.

Please respond to the following statements by indicating the extent to which you agree or disagree with them on a scale from 1 (I strongly agree) to 7 (I strongly disagree).Footnote 14

Intolerance of Ambiguity Scale by Kirton (1981). Items based on Mac Donald Jr (1970) and Rydell and Rosen (1966):

  1. 1

    There is a right way and a wrong way to do almost everything.

  2. 2

    Practically every problem has a solution.

  3. 3

    I have always felt that there is a clear difference between right and wrong.

  4. 4

    Nothing gets accomplished in this world unless you stick to some basic rules.

  5. 5

    If I were a doctor, I would prefer the uncertainties of a psychiatrist to the clear and definite work of someone like a surgeon or an X-ray specialist.

  6. 6

    Vague and impressionistic pictures really have little appeal for me.

  7. 7

    Before an examination, I feel much less anxious if I know how many questions there will be.

  8. 8

    The best part of a jigsaw puzzle is putting in that last piece.

  9. 9

    I do not like to work on a problem unless there is a possibility of coming out with a clear-cut and unambiguous answer.

  10. 10

    I like to fool around with new ideas, even if they turn out later to be a total waste of time.

  11. 11

    Perfect balance is the essence of all good composition.

Items based on Budner (1962):

  1. 12

    An expert who does not come up with a definite answer probably does not know too much.

  2. 13

    There is really no such thing as a problem that cannot be solved.

  3. 14

    A good job is one where what is to be done and how it is to be done are always clear.

  4. 15

    In the long run it is possible to get more done by tackling small, simple problems rather than lange and complicated ones.

  5. 16

    What we are used to is always preferable to what is unfamiliar.

  6. 17

    A person who leads an even, regular life, in which few surprises or unexpected happenings arise, really has a lot to be grateful for.

  7. 18

    I like parties where I know most of the people more than the ones where all or most of the people are complete strangers.

Optimism/pessimism (own wording)Footnote 15:

  • Do you consider yourself as a pessimist or an optimist?

Single-item measure of self-esteem by Robins et al. (2001)Footnote 16:

  • I have high self-esteem.

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Schröder, D., Gilboa Freedman, G. Decision making under uncertainty: the relation between economic preferences and psychological personality traits. Theory Decis 89, 61–83 (2020). https://doi.org/10.1007/s11238-019-09742-3

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