Browsing by Author "Haaga, Tapio"

I study whether modest copayment increases affect the general practitioner (GP) use in Finland, a country with relatively low copayments, low inequality, and an extensive welfare state. I also examine whether the estimates are driven by certain low–income groups considered to be economically vulnerable. The Finnish Government allowed municipalities to increase copayments in 2015 and 2016 by 9.5% and 27.5% respectively. At maximum, this meant that the copayment for a GP visit was 20.90 euros at the beginning of 2016, approximately 40% higher than at the end of 2014. Almost all municipalities made the 9.5% increase at the start of 2015, but some of them decided not to make the 27.5% increase at all or made smaller increases. I exploit this variation by estimating two–way fixed effects regression models, and I use population–wide administrative data containing all primary healthcare visits in 2013–2018 and socioeconomic information on patients. In the models, copayment increases are negatively associated with both GP use and median waiting times. Based on the means of estimates from several specifications, the 27.5% increase alone is associated with a 2% decrease in visits per resident in the first four quarters after the change and a 6% decrease thereafter. The estimates are not statistically significant. The median waiting times decrease by two days in the first year after the change and five days thereafter, and these results are significant. When I estimate the effects of both increases, the means of estimates are now a 5% decrease in visits per resident in the first four quarters after the last increase and an 8% decrease thereafter. Some of the estimates are statistically significant. I find no evidence to support the hypothesis that the low–income groups were more sensitive to the increases. However, the confidence intervals are wide across the study, suggesting that the design may be underpowered to detect small effects from zero. Moreover, the point estimates are surprisingly far from zero, which is especially surprising when upper income quintiles are concerned. Therefore, more evidence is needed to be able to make firm conclusions about the causal effects of policy changes.