A multilevel analysis on the determinants of regional health care expenditure: a note

Abstract

The interest in the factors involved in rising health care expenditure has created a third generation industry which is exploring data and econometric issues (see Gerdtham and Jönsson, 2000). However a common element missing from research, even in Gerdtham and Jönsson's agenda, is a consideration of the regional composition within the national health expenditure figures. An aggregation fallacy in estimating the income elasticity of health expenditure may therefore result from it.In order to study this, we have applied a multilevel hierarchical model using data for 110 regions in eight OECD countries in 1997: Australia, Canada, France, Germany, Italy, Spain, Sweden and United Kingdom. In doing this we have tried to identify two sources of random variation: within countries and betweencountries. The basic purpose is to find out if the different relationships between health care spending and the explanatory variables are country-specific. Our results show that: 1-Variability between countries amounts to (SD) 0.5433, and just 13% of that can be attributed to income elasticity and the remaining 87% to autonomous health expenditure; 2-Within countries, variability amounts to (SD) 1.0249; and 3-The intra-class correlation is 0.5300. We conclude that we have to take into account the degree of fiscal decentralisation within countries in estimating income elasticity of health expenditure. Two reasons lie behind this: a) where there is decentralisation to the regions, policies aimed at emulating diversity tend to increase national health care expenditure; and b) without fiscal decentralisation, central monitoring of finance tends to reduce regional diversity and therefore decrease national health expenditure. The results do seem to validate both these points.

Cost Containment and Managed Care: Evidence from German Macro Data

“…For example, international level approaches include [13,17] showing that both income levels and the structure of health care financing are relevant health expenditure variables. Similar results have also been discussed at a regional health care expenditure level [8,20,28,30,22,7,11].…”

“…destatis.de/genesis/online/). Similar to [13,12,28,26,8,20, 30], we control for a set of standard factors that determine health care expenditure such as household income (HHI), unemployment (UN), physician density (PHYS), age structure (P65, population share aged 65 and over) and technological progress over time. Note, however, that although our set of control variables mostly agrees with the abovementioned literature we particularly focus on managed care variables, i.e.…”

The determinants of Canadian provincial health expenditures: evidence from a dynamic panel

“…Therefore, if the empirical evidence is consistent with the theory we would expect this effect to be positive. See Casasnovas and Saez (1998), Hitiris (1999) and Roberts (1999) for empirical evidence on the magnitude of this effect.…”

“…Pooling of OECD countries with country specific intercepts yielded an income elasticity close to unity. Casasnovas and Saez (1998) examined the factors involved in rising health care expenditures by developing a model using data for 110 regions in eight OECD countries in 1997. They identified two sources of variation (within countries and between countries) to find out if the relationships between health care spending and the explanatory variables are country-specific.…”

A spatiotemporal analysis of public pharmaceutical expenditure

“…Kitchener et al 2003;Levaggi and Zanola 2003;Lopez-Casasnovas and Saez 2001;Moscone and Knapp 2005;Costa-Font and Moscone 2008). Despite the ample body of evidence of variations in the use of procedures in the literature on small-area variation (Folland et al 2003;Ham 1988;Joines et al 2003;Wennberg and Gittelsohn 1973;Westert et al 2004), few studies have examined the geographical variability in the use of pharmaceuticals (see e.g.…”