Are Trust and Reciprocity Related within Individuals?

Tamas Kovacs; Marc Willinger

doi:10.1515/bejte-2012-0009

Article

Are Trust and Reciprocity Related within Individuals?

Tamas Kovacs and Marc Willinger

Published/Copyright: June 21, 2013

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From the journal The B.E. Journal of Theoretical Economics Volume 13 Issue 1

Abstract

We provide new evidence about a positive correlation between the own amount sent and the own amount returned in the investment game. Our analysis relies on the experimental data collected under the strategy method. While the percentage returned is independent of the amount received for most of our subjects, it is strongly correlated to their amount sent as a trustor. Our analysis is based on a two-way classification of subjects: according to their trusting type and according to their reciprocal type. We show the existence of a strong positive relation between trusting types and reciprocal types within subjects.

Keywords: trust; reciprocity; trustworthiness; experimental economics; social preferences

Appendix

Table 6:

Average sent amounts according to demographic variables.

Gender	#	Mean	St. dev.
Female	45	4.56	2.53
Male	28	5.96	3.02
Total	73	5.10	2.79
Academic major
Economics	2	6.50	4.95
Law	14	6.36	2.65
Engineering	20	4.95	2.86
Human arts	37	4.62	2.67
Total	73	5.10	2.79
Live with par.
No	19	4.89	2.28
Yes	54	5.17	2.97
Total	73	5.10	2.79
Academic year
1	14	3.71	2.33
2	20	4.40	2.54
3	10	5.40	3.03
4	15	5.87	2.59
5	14	6.43	3.06
Total	73	5.10	2.79
Age
–20	23	4.04	2.53
21–22	25	5.40	2.71
23–	25	5.76	2.93
Total	73	5.10	2.79
Pocket money
0–5000	36	4.75	2.47
5,001–10,000	24	5.46	3.09
10,001–	13	5.38	3.18
Total	73	5.10	2.79

Table 7:

ANOVA-tests for demographic variables.

Grouping variable	F-statistics	p
*Gender*	4.605	0.035
Age	2.595	0.112
Academic year	2.461	0.121
Academic major	1.525	0.221
Pocket money	0.540	0.465
Live with parents	0.131	0.718

Table 8:

Regression coefficient of returned percentage according to individual standard error categories.

Individual st. error (%)	#	Constant	Own trust (Ti)	s	R² (%)	p
0–10	16	0.2513	0.029	0.028	88.13	0.000
10.1–20	12	0.2315	0.028	0.063	58.56	0.002
20.1–30	15	0.2088	0.040	0.107	60.09	0.001
30.1–50	10	0.3796	0.006	0.155	0.74	0.788
50.1–	14	0.2420	0.032	0.342	7.88	0.328

Table 9:

Significant regression coefficients of returned percentages in case of all possible received amounts.

Independent variables (€)	Received amounts
	3	6	9	12	15	18	21	24	27	30
Constant	0.287	0.322	0.316	0.279	0.256	0.229	0.221	0.202	0.194	0.188
Own trust (Ti)	0.016	0.019	0.021	0.029	0.030	0.035	0.035	0.038	0.040	0.041
s	0.228	0.196	0.176	0.196	0.198	0.186	0.182	0.176	0.180	0.192
R² (%)	3.4	6.6	9.4	13.6	14.8	21.2	21.9	25.8	26.6	25.7
p	0.137	0.036	0.012	0.002	0.001	0.000	0.000	0.000	0.000	0.000

Figure 6:

Distribution of returned percentages according to the subjects’ trust category and reciprocity profile.

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1
The standard trust question of the General Society Survey (GSS) and European Social Survey (ESS round 4) is phrased as follows: “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?” The percentage of “yes” answers is taken as a crude measure of trustfulness in the studied sample (in more recent versions respondents are asked to provide a rating between 0 and 10). Two additional questions are used to measure social confidence: “Do you think that most people would try to take advantage of you if they got the chance, or would they try to be fair?”, and “Would you say that most of the time people try to be helpful or that they are mostly looking out for themselves?”, and respondents are asked to provide a rating between 0 and 10.
2
See also Naef and Schupp (2009).
3
For instance, Johansson-Stenman, Mahmud, and Martinsson (2005a) showed that increasing the stakes in the investment game reduces significantly the proportion of the endowment sent by the trustor.
4
Barr (2003) found a positive relation between the amount sent (s) by the trustor and the percentage returned by the trustee (r/s): an increase in r/s leads to an increase in s (while r/s is independent of s in the regression of r/s with respect to s).
5
They rely on OLS and force the constant to be zero.
6
The experiment started with 74 participants, who were equally split between room I and II, which means 37 subjects in each room. However, during the experiment one participant stopped reading and filling the questionnaires and left the room. Since at this point there was an odd number of participants, one randomly selected B player was actually matched with two A players in order to determine the final payoff of the remaining A player. The selected player B received his payoff according to the decision of the first player A. This had no influence on our data, although it affected the final payoff of one of the A players.
7
Based on a two-tailed t-test, as we did not have the individual data of BDMc.
8
We provide summary results for the amount sent according to demographic variables in Tables 6 and 7 (see supplementary material). As Table 6 shows the sample was well balanced according to gender, age, academic year, and all other demographic variables, from which only gender appeared as a significant variable determining sent amount.
9
The total number of participants was 73, but six observations had to be excluded from the sample because their second mover profile was incomplete.
10
The relative standard errors in Table 8 are calculated as the relative difference between the average returned percentage of an individual and the returned percentage estimated by regression [1] for the same individual. This way the participants with very similar individual standard errors were classified into the same cluster and we could set up more particular regressions for the five clusters of subjects. However, the coefficients of the significant regressions are in line with the one we found in Table 1.
11
The precondition for these t-tests in case of small samples is equality of variances. The F-statistics reveals no significant differences (5% level) between each pair of the categories.
12
The Cramer measure calculated from Table 5 also shows a medium strength relation between the two variables (C 0.35). We take this as further evidence that trusting behaviour and trustworthiness are correlated within individuals.

Published Online: 2013-6-21

Published in Print: 2013-1-1

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https://doi.org/10.1515/bejte-2012-0009

Keywords for this article

trust; reciprocity; trustworthiness; experimental economics; social preferences