Background: An important methodological issue in economic evaluations of healthcare is how to include productivity costs (the costs related to reduced productivity due to illness, disability and premature death). Traditionally, they were included in the numerator of a cost-effectiveness analysis, through either the human-capital or the friction-cost method. It has been argued, however, that productivity costs are already included in the denominator (i.e. in the QALY measure) because respondents consider the effect a given health state will have on their income when valuing health states. If that is the case, many previous economic evaluations might have double counted productivity costs by including them in both the numerator and the denominator. Aim: The aim of this study was to determine whether respondents valuing EQ-5D health states using the time trade-off (TTO) method spontaneously consider income effects, whether this consideration influences subsequent valuations and whether explicit ex post instructions influence valuations. Methods: Through an online survey, we asked 321 members of the Dutch general population to value four EQ-5D health states through three different TTO exercises. The first exercise was a standard TTO question. Respondents were then asked whether they had included income effects. Depending on their answer, the second TTO exercise instructed them to either include or exclude income effects. The third TTO exercise provided explicit information regarding the income loss associated with the health state. Results: Datawere available from 321 members of the Dutch general public. Of these respondents, 49% stated they had spontaneously included income effects. Twenty-five percent of the sample did not trade any time in any of the TTO exercises and these respondents were excluded from the analysis. Results of t-tests showed there were only weakly significant differences in valuations for one health state between those who spontaneously included income effects and those who did not. Explicit instruction led to some significant differences at the aggregate level, but the effect was inconsistent at the individual level. When explicit information on the amount of income loss was provided, all states were valued lower when associated with a larger income loss. Conclusions: This study offers further evidence indicating that income losses do not significantly affect health state valuations.