Many factors point to the underlying instability of preferences in choice behavior. In particular, discounting reveals some effects not consistent with stable preferences. In discounting, the subjective value of a reward reduces as the uncertainty of or delay to obtaining it increases. The function relating subjective value to delay or probability must be exponential with a constant discount rate to respect transitivity over time, i.e., if A > B and B > C, then A > C (“ > ” = is preferred to). If the discount rate varies with value or time, then it is possible for transitivity to be violated, i.e., for preferences to be unstable. And people do show unstable, preference reversals over time in intertemporal choice more consistent with a hyperbolic discounting function (e.g., Myerson and Green, 1995). Thus, while someone may prefer £100 for certain now rather than £110 tomorrow, they will prefer £110 in a year and a day over £100 in a year’s time. People discount rate is very high initially, more rapid than the exponential, but over time it decreases leading to a flatter function than the exponential. Consequently, the £10 difference is almost totally discounted in the short term, but in a year’s time the extra day barely reduces the subjective value we attach to gaining an extra £10

Jones, S.

Oaksford, Mike

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Stephen Jones

Mike Oaksford

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Frontiers in Psychology

Preferences Show Greater Stability for Transactions than for Gambles in Cost Discounting

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Transactions, Preferences, and Cost Discounting

Preferences show greater stability for transactions than for 
gambles in cost discounting
Stephen Jones and Mike Oaksford*
Department of Psychological Sciences, Birkbeck College, University of London, London, UK
*Correspondence: mike.oaksford@bbk.ac.uk
Many factors point to the underlying insta-
bility of preferences in choice behavior. In 
particular, discounting reveals some effects 
not consistent with stable preferences. In 
discounting, the subjective value of a reward 
reduces as the uncertainty of or delay to 
obtaining it increases. The function relating 
subjective value to delay or probability must 
be exponential with a constant discount rate 
to respect transitivity over time, i.e., if A > B 
and B > C, then A > C (“ > ” = is preferred 
to). If the discount rate varies with value or 
time, then it is possible for transitivity to be 
violated, i.e., for preferences to be unsta-
ble. And people do show unstable, prefer-
ence reversals over time in intertemporal 
choice more consistent with a hyperbolic 
discounting function (e.g., Myerson and 
Green, 1995). Thus, while someone may 
prefer £100 for certain now rather than 
£110 tomorrow, they will prefer £110 in a 
year and a day over £100 in a year’s time. 
People discount rate is very high initially, 
more rapid than the exponential, but over 
time it decreases leading to a flatter function 
than the exponential. Consequently, the £10 
difference is almost totally discounted in the 
short term, but in a year’s time the extra day 
barely reduces the subjective value we attach 
to gaining an extra £10.
Further effects are inconsistent with the 
reasonable assumption that delay works 
by increasing uncertainty. For example, 
the magnitude of a reward seems to have 
opposite effects for uncertainty and delay. 
Amount has opposite effects on the dis-
counting of delayed and probabilistic 
rewards (Green et al., 1999). So, in temporal 
discounting people seem to discount small 
amounts more than large amounts, e.g., 
they prefer £10 now to £20 in a year but 
prefer £200 in a year to £100 now. However, 
in probabilistic discounting people seem to 
discount large amounts more than small 
amounts, e.g., they prefer £20 with a 50% 
chance to £10 for certain but prefer £100 
for certain rather than £200 with a 50% 
chance. This picture is further complicated 
by the fact that for discounting losses, there 
seems to be no effect of amount for tem-
poral discounting and inconsistent effects 
for probabilistic discounting (e.g., Mitchell 
and Wilson, 2010). These effects of amount 
not only violate the axioms of expected util-
ity theory but are also not consistent with 
descriptive decision theories such as pros-
pect theory.
Jones and Oaksford (2011) observed that 
most of these results were obtained using 
gambles, whereas most people rarely receive 
a gain or incur a loss outside the context of 
a transaction, e.g., a choice of paying £10 
now to own a commodity now or of paying 
£20 in 6 months time to own the commodity 
now. Kusev et al. (2009) showed that pre-
cautionary decision content, as in insurance 
situations, altered people’s choice behavior 
consistent with an increase in the probabil-
ity weighting function for low probability 
events in prospect theory. Similarly, Jones 
and Oaksford (2011) argued that using 
transactional problem content rather than 
gambles may alter people’s decision-mak-
ing. In particular, they suggested that this 
content may reveal more consistent effects 
of amount across temporal and probabilis-
tic discounting.
Transactions – but not gambles – will 
bring to mind previous instances of pur-
chasing different commodities for different 
amounts. In particular, people would also 
be expected to have access to a commodity’s 
rate of depreciation or appreciation and 
they would know that the more expensive 
a commodity, the lower its depreciation is 
expected to be. Indeed, for some of their 
most costly purchases, people have the 
reasonable expectation of long-run appre-
ciation. This information implies that in 
a transaction, people may discount small 
costs more than larger costs. So they will 
prefer to pay £100 now for the weekly shop 
rather than £200 in a week because its sub-
jective value in a week’s time will be far less 
than £100 if not zero. In contrast, they may 
well be happy to pay £200K for a new flat 
in 10 years rather than £100K now. The flat 
is likely to be worth more than £100K in 
10 years, and so, over time, its subjective 
value is not likely to decrease much. Jones 
and Oaksford (2011) also made the same 
prediction, more discounting for small costs 
than larger costs, for probabilistic discount-
ing with transactional content.
They report four experiments test-
ing the predicted effects of transactional 
content on cost discounting. All these 
experiments used the standard adaptive 
staircase method to zero in on people’s cer-
tainty equivalent values for three amounts 
given different delays and probabilities. 
Temporal and probabilistic discounting 
curves were generated by plotting the 
certainty equivalent value normalized by 
cost amount against delay or odds against 
loss respectively for each amount. The area 
under the discounting curves (AUC) was 
used as the dependent variable indicating 
the degree of discounting: the lower the 
area under the curve the higher the rate of 
discounting. Figure 1, Panel A shows the 
mean AUC values using transactional con-
tent for both delay and probabilistic dis-
counting in Jones and Oaksford’s (2011) 
Experiment 3, which was a replication 
of their Experiment 1. Both experiments 
showed the same pattern of discounting 
small costs more than large costs, i.e., lower 
mean AUC values for lower amounts. The 
trends were significant in all cases and 
in the same direction for both temporal 
(delay) and probabilistic discounting. 
Figure 1, Panel B shows the mean AUC 
values for their Experiment 4, which 
used gambles rather than transactions. 
For delay discounting, this experiment 
replicated previous findings of no effect 
for discounting losses. For probabilistic 
discounting of losses, a similar effect of 
more discounting for smaller amounts was 
observed. Moreover, for both the temporal 
www.frontiersin.org November 2011 | Volume 2 | Article 293 | 1
OpiniOn Article
published: 15 November 2011
doi: 10.3389/fpsyg.2011.00293
Nonetheless, Jones and Oaksford’s 
(2011) results show that transactions make 
transparent a factor, the differential depre-
ciation of high and low value items, that 
reveals a more stable pattern of preferences 
in people’s discounting behavior at least 
with respect to variation in cost amount. 
Consistent with standard discounted util-
ity models, these results are consistent 
with the view that time or delay affects 
decision-making by increasing uncertainty. 
Moreover, it is arguable that people’s behav-
ior with transactional problem content is 
the general case and consequently how 
they behave with this kind of content more 
indicative of the rationality, or not, of their 
behavior in the real world. A similar trend 
to seeing more of people’s decision-making 
behavior as rational or least conforming 
to the dictates of standard expected util-
ity theory emerges in Regenwetter et al. 
(2011). They point out that it is actually 
quite difficult to establish inconsistency of 
variable choice behavior with deterministic 
axioms like transitivity in expected utility 
theory. They use the example of a student 
observing their supervisor’s behavior when 
choosing between three on campus loca-
tions to meet. Choice proportions seem to 
reveal underlying intransitivity of choice 
until Regenwetter et al. (2011) reveal that 
the supervisor’s choice of location to meet 
is based on how close it is to where she 
is teaching that day. That is, there is an 
underlying consistent basis for the choice 
although the revealed preferences seem 
gain amount increases. By parity of reason-
ing, one could argue that losses implicitly 
involve corresponding gains (i.e., the possi-
bility of losing nothing). This line of reason-
ing suggests that the positive value attached 
to the possible gain increases faster than 
the negative value associated with the loss 
as the loss amount increases. In both cases, 
the implicit gain or loss associated with the 
possibility of no change in one’s financial 
position increases in subjective value, posi-
tive or negative, faster with amount than the 
subjective values attached to the possibility 
corresponding to an actual loss or gain. Such 
an account could explain the peanuts effect 
for probabilistic gains (overall subjective 
value will decrease with amount) and a mag-
nitude effect for probabilistic losses (overall 
subjective value will increase with amount).
Such an account is not consistent with 
prospect theory, in which losses loom 
larger than gains. So, such an explanation 
works for probabilistic gains, but explain-
ing the reverse effect for losses would seem 
to require gains to loom larger than losses. 
Of course, how implicit losses and gains 
behave when the focus of attention is on 
the corresponding gains and losses has not 
been explored. Consequently, much further 
work needs to be done before a complete 
account of the effects of amount on inter-
temporal choice, using transactions or gam-
bles is forthcoming. How consistent such an 
account is with current descriptive decision 
theory or with standard discounted utility 
models remains uncertain.
and probabilistic case, people discounted 
more (lower AUC values) for transactions 
than for gambles.
Like precautionary decisions (Kusev 
et al., 2009), transactions cannot be treated 
like pure gambles. A cost is not a pure loss 
because in a transaction there is always a 
linked gain associated with the purchased 
commodity. For delay discounting these 
differences result in a magnitude effect for 
transactions (Panel A) not observed for 
gambles (Panel B). Moreover, for transac-
tions this effect is paralleled for probabil-
istic discounting of costs (Panel A). This 
is the first time that such parallel effects 
of amount have been observed for proba-
bilistic and delay discounting. However, 
for probabilistic discounting, this effect 
was also observed for gambles (Panel B). 
A possible explanation is that gambles are 
described by prospects, which, like transac-
tions, emphasize an implicit linked gain.
There are some outstanding problems. 
For example, for probabilistic discounting 
with gambles, why are smaller losses dis-
counted more than larger losses but larger 
gains discounted more than smaller gains? 
Jones and Oaksford (2011) proposed the 
following possible explanation. Green et al. 
(1999) and Prelec and Loewenstein (1991) 
argued that in probabilistic discounting, 
gains implicitly involve corresponding losses 
(i.e., the possibility of wining nothing). They 
argued that the negative value attached to 
the possible loss increases faster than the 
positive value associated with the gain as the 
Figure 1 | Mean AuC values at different levels of cost amount using transactions (A) and gambles (B) taken from Jones and Oaksford’s (2011) 
experiments 3 and 4 respectively. Error bars represent SE. AUC, area under the curve; Prob, probability.
Jones and Oaksford Stable preferences for transactions
Frontiers in Psychology | Cognition  November 2011 | Volume 2 | Article 293 | 2
Prelec, D., and Loewenstein, G. (1991). Decision mak-
ing over time and under uncertainty: a common 
approach. Manage. Sci. 37, 770–786.
Regenwetter, M., Dana, J., and Davis-Stober, C. P. (2011). 
Transitivity of preferences. Psychol. Rev. 118, 42–56.
Received: 30 June 2011; accepted: 11 October 2011; pub-
lished online: 15 November 2011.
Citation: Jones S and Oaksford M (2011) Preferences 
show greater stability for transactions than for gambles in 
cost discounting. Front. Psychology 2:293. doi: 10.3389/
fpsyg.2011.00293
This article was submitted to Frontiers in Cognition, a 
specialty of Frontiers in Psychology.
Copyright © 2011 Jones and Oaksford. This is an open-
access article subject to a non-exclusive license between 
the authors and Frontiers Media SA, which permits use, 
distribution and reproduction in other forums, provided the 
original authors and source are credited and other Frontiers 
conditions are complied with.
RefeRences
Green, L., Myerson, J., and Ostaszewski, P. (1999). Amount 
of reward has opposite effects on the discounting of 
delayed and probabilistic outcomes. J. Exp. Psychol. 
Learn. Mem. Cogn. 25, 418–427.
Jones, S., and Oaksford, M. (2011). Transactional prob-
lem content in cost discounting: parallel effects for 
probability and delay. J. Exp. Psychol. Learn. Mem. 
Cogn. 37, 739–747.
Kusev, P., van Schaik, P., Ayton, P., Dent, J., and Chater, N. 
(2009). Exaggerated risk: prospect theory and prob-
ability weighting in risky choice. J. Exp. Psychol. Learn. 
Mem. Cogn. 35, 1487–1505.
Mitchell, S. H., and Wilson, V. B. (2010). The subjective 
value of delayed and probabilistic outcomes: out-
come size matters for gains but not for losses. Behav. 
Process. 83, 36–40.
Myerson, J., and Green, L. (1995). Discounting of delayed 
rewards: models of individual choice. J. Exp. Anal. 
Behav. 64, 263–276.
intransitive. That is, the revealed prefer-
ences seem unstable although the latent 
preferences are stable.
In sum, there is emerging evidence that 
people’s choice behavior may be less irra-
tional or inconsistent with expected util-
ity theory and discounted utility models 
than first thought. People’s preferences are 
more stable for transactions than for gam-
bles. Our research on transactions in cost 
discounting makes a small contribution to 
this literature that suggests exploring more 
fully the effects of transactions on discount-
ing behavior when participants are asked 
to act as sellers as well as buyers, and when, 
as in real world transactions, payment and 
receipt of goods can vary more widely.
Jones and Oaksford Stable preferences for transactions
www.frontiersin.org November 2011 | Volume 2 | Article 293 | 3


Birkbeck Institutional Research Online

   BIROn - Birkbeck Institutional Research Online  Enabling open access to Birkbeck’s published research output    Preferences show greater stability for transactions than for gambles in cost discounting  Journal Article   http://eprints.bbk.ac.uk/4559    Version: Published (Refereed)  Citation:          © 2011 The Authors   Publisher version    ______________________________________________________________  All articles available through Birkbeck ePrints are protected by intellectual property law, including copyright law. Any use made of the contents should comply with the relevant law. ______________________________________________________________  Deposit Guide  Contact: lib-eprints@bbk.ac.uk Birkbeck ePrints Jones, S.; Oaksford, M. (2011) Preferences show greater stability for transactions than for gambles in cost discounting Frontiers in Psychology  2, Article 293 Preferences show greater stability for transactions than for gambles in cost discountingStephen Jones and Mike Oaksford*Department of Psychological Sciences, Birkbeck College, University of London, London, UK*Correspondence: mike.oaksford@bbk.ac.ukMany factors point to the underlying insta-bility of preferences in choice behavior. In particular, discounting reveals some effects not consistent with stable preferences. In discounting, the subjective value of a reward reduces as the uncertainty of or delay to obtaining it increases. The function relating subjective value to delay or probability must be exponential with a constant discount rate to respect transitivity over time, i.e., if A > B and B > C, then A > C (“ > ” = is preferred to). If the discount rate varies with value or time, then it is possible for transitivity to be violated, i.e., for preferences to be unsta-ble. And people do show unstable, prefer-ence reversals over time in intertemporal choice more consistent with a hyperbolic discounting function (e.g., Myerson and Green, 1995). Thus, while someone may prefer £100 for certain now rather than £110 tomorrow, they will prefer £110 in a year and a day over £100 in a year’s time. People discount rate is very high initially, more rapid than the exponential, but over time it decreases leading to a flatter function than the exponential. Consequently, the £10 difference is almost totally discounted in the short term, but in a year’s time the extra day barely reduces the subjective value we attach to gaining an extra £10.Further effects are inconsistent with the reasonable assumption that delay works by increasing uncertainty. For example, the magnitude of a reward seems to have opposite effects for uncertainty and delay. Amount has opposite effects on the dis-counting of delayed and probabilistic rewards (Green et al., 1999). So, in temporal discounting people seem to discount small amounts more than large amounts, e.g., they prefer £10 now to £20 in a year but prefer £200 in a year to £100 now. However, in probabilistic discounting people seem to discount large amounts more than small amounts, e.g., they prefer £20 with a 50% chance to £10 for certain but prefer £100 for certain rather than £200 with a 50% chance. This picture is further complicated by the fact that for discounting losses, there seems to be no effect of amount for tem-poral discounting and inconsistent effects for probabilistic discounting (e.g., Mitchell and Wilson, 2010). These effects of amount not only violate the axioms of expected util-ity theory but are also not consistent with descriptive decision theories such as pros-pect theory.Jones and Oaksford (2011) observed that most of these results were obtained using gambles, whereas most people rarely receive a gain or incur a loss outside the context of a transaction, e.g., a choice of paying £10 now to own a commodity now or of paying £20 in 6 months time to own the commodity now. Kusev et al. (2009) showed that pre-cautionary decision content, as in insurance situations, altered people’s choice behavior consistent with an increase in the probabil-ity weighting function for low probability events in prospect theory. Similarly, Jones and Oaksford (2011) argued that using transactional problem content rather than gambles may alter people’s decision-mak-ing. In particular, they suggested that this content may reveal more consistent effects of amount across temporal and probabilis-tic discounting.Transactions – but not gambles – will bring to mind previous instances of pur-chasing different commodities for different amounts. In particular, people would also be expected to have access to a commodity’s rate of depreciation or appreciation and they would know that the more expensive a commodity, the lower its depreciation is expected to be. Indeed, for some of their most costly purchases, people have the reasonable expectation of long-run appre-ciation. This information implies that in a transaction, people may discount small costs more than larger costs. So they will prefer to pay £100 now for the weekly shop rather than £200 in a week because its sub-jective value in a week’s time will be far less than £100 if not zero. In contrast, they may well be happy to pay £200K for a new flat in 10 years rather than £100K now. The flat is likely to be worth more than £100K in 10 years, and so, over time, its subjective value is not likely to decrease much. Jones and Oaksford (2011) also made the same prediction, more discounting for small costs than larger costs, for probabilistic discount-ing with transactional content.They report four experiments test-ing the predicted effects of transactional content on cost discounting. All these experiments used the standard adaptive staircase method to zero in on people’s cer-tainty equivalent values for three amounts given different delays and probabilities. Temporal and probabilistic discounting curves were generated by plotting the certainty equivalent value normalized by cost amount against delay or odds against loss respectively for each amount. The area under the discounting curves (AUC) was used as the dependent variable indicating the degree of discounting: the lower the area under the curve the higher the rate of discounting. Figure 1, Panel A shows the mean AUC values using transactional con-tent for both delay and probabilistic dis-counting in Jones and Oaksford’s (2011) Experiment 3, which was a replication of their Experiment 1. Both experiments showed the same pattern of discounting small costs more than large costs, i.e., lower mean AUC values for lower amounts. The trends were significant in all cases and in the same direction for both temporal (delay) and probabilistic discounting. Figure 1, Panel B shows the mean AUC values for their Experiment 4, which used gambles rather than transactions. For delay discounting, this experiment replicated previous findings of no effect for discounting losses. For probabilistic discounting of losses, a similar effect of more discounting for smaller amounts was observed. Moreover, for both the temporal www.frontiersin.org November 2011 | Volume 2 | Article 293 | 1OpiniOn Articlepublished: 15 November 2011doi: 10.3389/fpsyg.2011.00293Nonetheless, Jones and Oaksford’s (2011) results show that transactions make transparent a factor, the differential depre-ciation of high and low value items, that reveals a more stable pattern of preferences in people’s discounting behavior at least with respect to variation in cost amount. Consistent with standard discounted util-ity models, these results are consistent with the view that time or delay affects decision-making by increasing uncertainty. Moreover, it is arguable that people’s behav-ior with transactional problem content is the general case and consequently how they behave with this kind of content more indicative of the rationality, or not, of their behavior in the real world. A similar trend to seeing more of people’s decision-making behavior as rational or least conforming to the dictates of standard expected util-ity theory emerges in Regenwetter et al. (2011). They point out that it is actually quite difficult to establish inconsistency of variable choice behavior with deterministic axioms like transitivity in expected utility theory. They use the example of a student observing their supervisor’s behavior when choosing between three on campus loca-tions to meet. Choice proportions seem to reveal underlying intransitivity of choice until Regenwetter et al. (2011) reveal that the supervisor’s choice of location to meet is based on how close it is to where she is teaching that day. That is, there is an underlying consistent basis for the choice although the revealed preferences seem gain amount increases. By parity of reason-ing, one could argue that losses implicitly involve corresponding gains (i.e., the possi-bility of losing nothing). This line of reason-ing suggests that the positive value attached to the possible gain increases faster than the negative value associated with the loss as the loss amount increases. In both cases, the implicit gain or loss associated with the possibility of no change in one’s financial position increases in subjective value, posi-tive or negative, faster with amount than the subjective values attached to the possibility corresponding to an actual loss or gain. Such an account could explain the peanuts effect for probabilistic gains (overall subjective value will decrease with amount) and a mag-nitude effect for probabilistic losses (overall subjective value will increase with amount).Such an account is not consistent with prospect theory, in which losses loom larger than gains. So, such an explanation works for probabilistic gains, but explain-ing the reverse effect for losses would seem to require gains to loom larger than losses. Of course, how implicit losses and gains behave when the focus of attention is on the corresponding gains and losses has not been explored. Consequently, much further work needs to be done before a complete account of the effects of amount on inter-temporal choice, using transactions or gam-bles is forthcoming. How consistent such an account is with current descriptive decision theory or with standard discounted utility models remains uncertain.and probabilistic case, people discounted more (lower AUC values) for transactions than for gambles.Like precautionary decisions (Kusev et al., 2009), transactions cannot be treated like pure gambles. A cost is not a pure loss because in a transaction there is always a linked gain associated with the purchased commodity. For delay discounting these differences result in a magnitude effect for transactions (Panel A) not observed for gambles (Panel B). Moreover, for transac-tions this effect is paralleled for probabil-istic discounting of costs (Panel A). This is the first time that such parallel effects of amount have been observed for proba-bilistic and delay discounting. However, for probabilistic discounting, this effect was also observed for gambles (Panel B). A possible explanation is that gambles are described by prospects, which, like transac-tions, emphasize an implicit linked gain.There are some outstanding problems. For example, for probabilistic discounting with gambles, why are smaller losses dis-counted more than larger losses but larger gains discounted more than smaller gains? Jones and Oaksford (2011) proposed the following possible explanation. Green et al. (1999) and Prelec and Loewenstein (1991) argued that in probabilistic discounting, gains implicitly involve corresponding losses (i.e., the possibility of wining nothing). They argued that the negative value attached to the possible loss increases faster than the positive value associated with the gain as the Figure 1 | Mean AuC values at different levels of cost amount using transactions (A) and gambles (B) taken from Jones and Oaksford’s (2011) experiments 3 and 4 respectively. Error bars represent SE. AUC, area under the curve; Prob, probability.Jones and Oaksford Stable preferences for transactionsFrontiers in Psychology | Cognition  November 2011 | Volume 2 | Article 293 | 2Prelec, D., and Loewenstein, G. (1991). Decision mak-ing over time and under uncertainty: a common approach. Manage. Sci. 37, 770–786.Regenwetter, M., Dana, J., and Davis-Stober, C. P. (2011). Transitivity of preferences. Psychol. Rev. 118, 42–56.Received: 30 June 2011; accepted: 11 October 2011; pub-lished online: 15 November 2011.Citation: Jones S and Oaksford M (2011) Preferences show greater stability for transactions than for gambles in cost discounting. Front. Psychology 2:293. doi: 10.3389/fpsyg.2011.00293This article was submitted to Frontiers in Cognition, a specialty of Frontiers in Psychology.Copyright © 2011 Jones and Oaksford. This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.RefeRencesGreen, L., Myerson, J., and Ostaszewski, P. (1999). Amount of reward has opposite effects on the discounting of delayed and probabilistic outcomes. J. Exp. Psychol. Learn. Mem. Cogn. 25, 418–427.Jones, S., and Oaksford, M. (2011). Transactional prob-lem content in cost discounting: parallel effects for probability and delay. J. Exp. Psychol. Learn. Mem. Cogn. 37, 739–747.Kusev, P., van Schaik, P., Ayton, P., Dent, J., and Chater, N. (2009). Exaggerated risk: prospect theory and prob-ability weighting in risky choice. J. Exp. Psychol. Learn. Mem. Cogn. 35, 1487–1505.Mitchell, S. H., and Wilson, V. B. (2010). The subjective value of delayed and probabilistic outcomes: out-come size matters for gains but not for losses. Behav. Process. 83, 36–40.Myerson, J., and Green, L. (1995). Discounting of delayed rewards: models of individual choice. J. Exp. Anal. Behav. 64, 263–276.intransitive. That is, the revealed prefer-ences seem unstable although the latent preferences are stable.In sum, there is emerging evidence that people’s choice behavior may be less irra-tional or inconsistent with expected util-ity theory and discounted utility models than first thought. People’s preferences are more stable for transactions than for gam-bles. Our research on transactions in cost discounting makes a small contribution to this literature that suggests exploring more fully the effects of transactions on discount-ing behavior when participants are asked to act as sellers as well as buyers, and when, as in real world transactions, payment and receipt of goods can vary more widely.Jones and Oaksford Stable preferences for transactionswww.frontiersin.org November 2011 | Volume 2 | Article 293 | 3

Preferences show greater stability for transactions than for gambles in cost discounting

Oaksford, Michael

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Preferences show greater stability for transactions than for gambles in cost discounting

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