Measuring Spatial Effects in Presence of Institutional Constraints: The Case of Italian Local Health Authority Expenditure
Measuring Spatial Effects in Presence of Institutional Constraints: The Case of Italian Local Health Authority Expenditure
复制标题
衡量存在制度限制的空间效应：意大利地方卫生当局支出案例
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Andrea Piano Mortari
中科院分区：
文献类型：
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作者：
V. Atella;F. Belotti;D. Depalo;Andrea Piano Mortari
在过去的几十年里，空间计量经济学模型是衡量不同地理实体（县、省、地区或国家）溢出效应的常用工具。不幸的是，没有人考虑到，当这些实体有共同的边界，但服从不同的制度设置，忽略这一特征可能会导致误导性的结论。事实上，在这种情况下，如果制度确实发挥了作用，我们希望发现空间效应主要是在”属于同一制度环境的实体“内部，而不同制度环境之间的“之间”效应应该减弱或完全不存在，即使实体共享一个共同的边界。在这种情况下，由于两种不同的效应的组合，仅依靠地理上的接近将产生有偏差的估计。为了避免这些问题，我们得出了一种方法，分区内和相邻矩阵之间的标准邻接矩阵，允许单独估计这些空间相关系数，并很容易地测试存在的制度约束。在我们的实证分析中，我们采用这种方法来意大利地方卫生局的支出，使用空间面板技术。结果显示，仅对于内部效应，空间系数很强且显着，从而证实了我们方法的重要性和有效性。
Over the last decades spatial econometrics models have represented a common tool for measuring spillover effects across different geographical entities (counties, provinces, regions or nations). Unfortunately, no one has considered that when these entities share common borders but obey to different institutional settings, ignoring this feature may induce misleading conclusions. In fact, under these circumstances, and if institutions do play a role, we expect to find spatial effects mainly within" entities belonging to the same institutional setting, while the "between" effect across different institutional settings should be attenuated or totally absent, even if the entities share a common border. In this case, relying only on geographical proximity will then produce biased estimates, due to the composition of two distinct effects. To avoid these problems, we derive a methodology that partitions the standard contiguity matrix into within and between contiguity matrices, allowing to separately estimate these spatial correlation coefficients and to easily test for the existence of institutional constraints. In our empirical analysis we apply this methodology to Italian Local Health Authority expenditures, using spatial panel techniques. Results show a strong and significant spatial coefficient only for the within effect, thus confirming the importance and validity of our approach.
DOI：
10.2139/ssrn.2093394
发表时间：
2012-06
期刊：
ERN: Panel Data Models (Multiple) (Topic)
影响因子：
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作者：
Piergiorgio Alessandri;B. Nelson
通讯作者：
Piergiorgio Alessandri;B. Nelson