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THE IMPACT OF MUNICIPAL MERGERS ON LOCAL PUBLIC SPENDING: EVIDENCE FROM REMOTE-SENSING DATA

Published online by Cambridge University Press:  03 April 2020

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Abstract

How are resources distributed when administrative units merge? We take advantage of recent, large-scale municipal mergers in Japan to systematically study the impact of municipal mergers within merged municipalities and, in particular, what politicians do when their districts and constituencies suddenly change. We argue that when rural and sparsely populated municipalities merge with more urban and densely populated municipalities, residents of the former are likely to see a reduced share of public spending because they lost political leverage through the merger. Our empirical analyses detect changes in public spending before and after the municipal mergers with remote sensing data, which allows for flexible units of analysis and enables us to proxy for spending within merged municipalities. Overall, our results show that politicians tend to reduce benefits allocated to areas where there are a small number of voters, while increasing the allocation to more populous areas. The micro-foundation of our argument is also corroborated by survey data. The finding suggests that, all things being equal, the quantity rather than quality of electorates matters for politicians immediately after political units change.

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Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
Copyright © The Author(s), 2020
Figure 0

Figure 1 Scatterplots Comparing Nighttime Light Data with Spending Proxy

Figure 1

Figure 2 Scatterplots Comparing Nighttime Light Data with Infrastructure Proxy

Figure 2

Figure 3 Number of Municipalities in Japan, 1961–2008

Figure 3

Table 1 Entropy Balancing Analysis

Figure 4

Figure 4 Marginal Effect of Merger on Light Images

Figure 5

Table 2 Main Analysis

Figure 6

Figure 5 Comparison of Light Change before and after Merger: A Case of Toyooka

Figure 7

Figure 6 Ratio of Light for Each Municipality in Toyooka for 2000 and 2010

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