The Palestinian Economy. Theoretical and Practical Challenges

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Proceedings “The Palestinian Economy: Theoretical and Practical Challenges” 347 the entire population, calling for potential “masking effect”, where the behaviour of some classes of the population would cover that of others; i.e., resulting in aggregate results that might not reflect the reality associated with certain sub-groups. In effect, the decomposition of inequality into its justifiable and unjustifiable parts is interpreted in terms of average behaviour; i.e., the use-need mean relation as observed over the entire sample. The inter-personal variations in use are thus assumed to derive solely from variations in its (non-need) determinants, where the model implicitly presumes, given (non-need) estimates, the amount of care that ought to be allocated on average for that need; provided that average behaviour being regarded as if it was a norm (van Doorslaer, Clarke et al. 2006). An appealing method of decomposition is the one based on microsimulation technique (e.g., Harding 1996; Gupta and Kapur 2000; Dormont, Grignonc et al. 2006; Huber 2006). While it offers a way out to overcome the above shortcomings of the standard methods, such approach proves to provide several conceptual and practical advantages over the commonly used ECuity group methods. First, it allows (the unconditional) use of an appropriate regression model specification of health care utilisation. Therefore, it avoids the linearity restriction or the “inevitable price… for the linear approximations” (O’Donnell, van Doorslaer et al. 2007) that is imposed by the standard decomposition method. In fact, the latter was essentially developed for a singlelinear additive model (Wagstaff, van Doorslaer et al. 2003), which is not directly amenable to an analysis of health care utilisation. However, despite being conceptually unsatisfactory, linear specification based on OLS technique was advocated (van Doorslaer and Masseria 2004), and implemented (e.g., van Doorslaer, Clarke et al. 2006; Lu, Leung et al. 2007) for the measurement of inequality in health care utilisation, on the grounds that these measures are not, particularly, sensitive to linear OLS specifications. Otherwise, linear approximations to the non-linear models, using the “marginal effects evaluated at the means”, was proposed (van Doorslaer, Koolman et al. 2004) as a way to deal with the inherent non-linearity problem in health care utilisation. Though this solution has the advantage of using appropriate specifications (such as TPM combining a logit and a truncated negbin) the proposed decomposition, which remains only an “approximation”, with a bias due to approximation error, was computed separately for each single equation of the model – i.e., by decomposing separately the CI of participation, conditional consumption, and the unconditional consumption. By contrast, the microsimulation technique applied in the present study, while allowing the use of TPM specifications, the relative importance of each explanatory factors as per
348 Abu-Zaineh – Mataria participation and conditional consumption are disentangled within a single-model explaining the total consumption of health care. It, therefore, avoids the limitation to “single-equation” decomposition. Besides convenience, the advantage of this is that it enables to identify the contribution of each explanatory factor to the overall inequality in utilisation, while ensuring that the fraction of inequality due to a certain factor can be partitioned into a part due to participation behaviour and a part due to conditional consumption behaviour. Secondly, the microsimulation-based decomposition allows for estimating separately a model of health care utilisation for each socio-economic status (SES) groups (e.g., income quintile). As result, it enables for a more transparent and convincing decomposition, whereby the relative contributions of heterogeneity in behaviours – as captured by differences in parameters across SES groups – to the observed inequality are revealed. Indeed, differentials in behaviour by income quintiles was early shown (Oaxaca 1973) to be of inherent interest, as they enable to duck the potentially contentious role of genuine individuals’ preferences, which may indeed be related to the rank of individuals in the income distribution. In fact, while the measurement of HI in health care utilisation was essentially examined and statistically tested by comparing the behaviours of SES groups – i.e., differences in the regression coefficients (cf. van Doorslaer, Wagstaff et al. 1993), such a feature was absent in the standard decomposition method where the explanatory model was only estimated for the entire sample population, and thus, individuals’ preferences were neglected. By contrast, the adapted microsimulation-based horizontal inequity (HI) index presented here depends on both the distribution of variables (z k ) by income and the heterogeneity in parameters (β k ) with respect to income (or SES). This method provides, therefore, a way of detecting patients’ preferences as well as providers’ behaviour, which is not possible with the standard decomposition. While microsimulation method has been recently deployed and successfully applied for the decomposition of health expenditure growth (e.g., Dormont, Grignonc et al. 2006), they have hitherto not been used to fully disentangle the sources of inequality in the health care delivery. To our knowledge, only one similar study (Huber 2006) has been done earlier to examine inequalities in the context of French health care system. This essay attempts, therefore, to apply the above methodological advances and to illustrate how these developments can significantly help clarifying debates about health care policies in the context of developing countries, using the particular case of the Occupied Palestinian Territory (OPT). First, we use data from a recent household health use and expenditure survey (the HCEU-2004). The survey, which was carried out by the
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The Palestinian Economy Theoretical
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© Gianni Vaggi - Marco Missaglia -
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VOLUME II
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246 Zagha 1. Introduction The local
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248 Zagha and groups in political d
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250 Zagha drawbacks in the politica
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252 Zagha it is not surprising that
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254 Zagha economy (including expend
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256 Zagha social norms sharply dist
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258 Zagha Bird (1995) puts it, info
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260 Zagha intergovernmental fiscal
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262 Zagha low rate flat tax levied
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264 Zagha need to be given access t
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266 Zagha Such failures are found i
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268 Zagha 4.1.3. The Relationship b
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270 Zagha a final account report of
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272 Zagha 4.1.6. Functions of LGUs
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274 Zagha • Management of LGU ass
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276 Zagha Figure 2: Local Governmen
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278 Zagha In summary, what the data
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280 Zagha on the cash basis. Almost
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282 Zagha Figure 7: Business Opinio
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284 Zagha within the Palestinian na
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286 Zagha Table 5: Number of NGOs i
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288 Zagha Fiscal decentralisation i
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290 Zagha Burki, J., Perry, G., Dil
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292 Zagha Palestinian Legislative C
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Issues, Performance and Trajectorie
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424 Olivera provisions - in particu
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426 Olivera Figure 1: Economic Grow
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428 Olivera 3. Traditional economic
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430 Olivera costs and lower market
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