Federal state differentials in the efficiency of health production in Germany: an artifact of spatial dependence?

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: Due to regional competition and patient migration, the efficiency of health care provision at the regional level is subject to spatial dependence. We address this issue by applying a spatial autoregressive model to longitudinal data from Germany at the district ('Kreis') level. The empirical model is specified to explain efficiency scores, which we derive through non-parametric order-m efficiency analysis of regional health production. The focus is on the role of health policy of federal states ('Bundesländer') for district efficiency. Regression results reveal significant spatial spillover effects. Notably, accounting for spatial dependence does not decrease but increases the estimated effect of federal states on district efficiency. It appears that genuinely more efficient states are less affected by positive efficiency spillovers, so that taking into account spatial dependence clarifies the importance of health policy at the state level. Terms of use: Documents in EconStor may

The Determinants of the Technical Efficiency of Acute Inpatient Care in Canada

“…There are two drawbacks of the DEA. First, DEA scores are serially correlated; that is, the efficiency score for one hospital is not independent from the efficiency scores of other hospitals, which is problematic in the second‐stage regression analysis of the contributions of various factors to inefficiency (Bowlin ; Felder and Tauchmann ). Second, it does not allow for a random component of efficiency.…”

Determinants of Regional Variation in Health Expenditures in Germany

“…The shape files of the counties from the Federal Agency for Cartography and Geodesy (as of 1.1.2012) were used to calculate the distances and transferred into Stata format with the help of the Stata programme shp2dta. We follow Felder & Tauchmann () and normalise the elements with the eigenvalue standardization, in which every element is divided by the largest module of the eigenvalues of M (see (Kelejian & Prucha, ), for a discussion of the normalization procedures). We define the matrix W as a ‘contiguity matrix’.…”

“…We would like to stress that this study does not aim at quantifying inefficiencies. In order to do so, one would have to compare inputs and outputs of health production functions as, for example, done by Felder & Tauchmann (). Moreover, in quantifying inefficiencies, one has to bear in mind that system inefficiency might affect the health system as a whole and therefore not lead to regional variation.…”

Examining the structure of spatial health effects in Germany using Hierarchical Bayes Models

“…Moscone et al (2007) use a similar approach, but analyze cross-municipality variation in mental health expenditures. Felder and Tauchmann (2013) combine a nonparametric efficiency analysis with parametric regressions and model spatial dependence in healthcare provision at the county level in Germany. Bech and Lauridsen (2009) estimate a SUR model relating per capita expenditure for GPs in Denmark to local policies, health care supply as well as regional characteristics.…”

“…Felder and Tauchmann (2013), Augurzky et al (2013), Kopetsch and Schmitz (2013) and Eibich and Ziebarth (2014) study regional variation in health care efficiency and utilization, respectively. Pollack et al (2004), Dragano et al (2007Dragano et al ( , 2009aDragano et al ( , 2009b, Breckenkamp et al (2007), Voigtländer et al (2010), and Diehl and Schneider (2011) use multilevel models to analyze the impact of specific regional factors on health.…”