A Traditional Approach to Agglomeration Economies

Otsuka, Akihiro

doi:10.1007/978-981-10-6490-6_3

Akihiro Otsuka³

Part of the book series: New Frontiers in Regional Science: Asian Perspectives ((NFRSASIPER,volume 20))

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Abstract

This chapter sheds empirical light on the relationship between agglomeration economies and regional economic growth and the impact of that relationship on the convergence of regional disparities in productivity, using a traditional approach to agglomeration economies. Based on Japanese prefectural data, an empirical analysis indicates that agglomeration economies have significant effects on regional economic growth. Furthermore, agglomeration economies contribute to economic convergence in the manufacturing industry, while they contribute to increasing disparities across regions in the non-manufacturing industry. These results suggest that an increase in the proportion of non-manufacturing industries has the potential to create regional disparities.

This chapter is based on Otsuka and Yamano (2008) “Industrial agglomeration effects on regional economic growth: A case of Japanese regions” Discussion Papers 08-T-2, Regional Economics Applications Laboratory, University of Illinois, IL and Otsuka (2008) “Industrial agglomeration and economic convergence: the case of Japanese regions,” published in The Economic Analysis (The Keizai Bunseki) (No. 180, pp. 1–19, in Japanese).

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Notes

1.
Chipman (1970) first formulated internalization of external economies of scale in the production function framework. His formulation shows that the industrial-level production is increasing returns to scale by internalization, while the firm-level production is constant returns to scale. Nakamura (1985) has set out to distinguish the productivity effects of urbanization and localization based on Chipman’s work.
2.
It is expected that variations in the logarithm of the inverse of the capital coefficient, \( \ln \left(\frac{Y}{K}\right) \), have a constant slope over time under a production system employing capital-intense technology over the long term. However, the value fluctuates every year in an observed data set. Hence, this study assumes the fluctuations in \( \ln \left(\frac{Y}{K}\right) \) can be attributed to a change in capital utilization as well as a time trend. Based on that assumption, a proxy of the capital utilization rate can be measured with a residual error term (ε) in the regression ln(Y/K) = α + βT + ε, where T is a time trend and β is a time-invariant slope of \( \ln \left(\frac{Y}{K}\right) \).
3.
According to Harrington and Warf (1995), local demand could be an important driver for the service sector because this sector is, to a large extent, reliant on face-to-face contact, which leads to high transport costs for service delivery.
4.
See Appendix for detailed decomposition results.
5.
Using this method, Fukao and Yue (2000) have clarified the contribution of social overhead capital toward labor productivity disparities for Japanese prefectures.

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Association of International Arts and Science, Yokohama City University, Yokohama, Japan
Akihiro Otsuka

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Appendix: Growth accounts (in %, annual growth rate, 1980–2002)

	Product Growth	Capital Growth	Labor Growth	TFP
	Product Growth	Capital Growth	Labor Growth	Localization Economies	Urbanization Economies	Market Access	Technological Progress	Other
(a) Manufacturing industry
Hokkaido	2.340	1.108	−0.810	0.159	−0.002	0.673	1.356	−0.144
Aomori	3.288	2.571	0.063	0.223	−0.013	0.653	−0.415	0.206
Iwate	4.147	2.408	−0.006	0.281	−0.022	0.646	0.821	0.018
Miyagi	3.533	2.232	−0.255	0.240	0.016	0.628	1.425	−0.752
Akita	3.165	2.159	−0.383	0.215	−0.020	0.706	0.455	0.033
Yamagata	3.916	2.582	−0.270	0.266	−0.012	0.664	0.431	0.256
Fukushima	4.573	2.557	−0.437	0.310	0.008	0.671	1.279	0.184
Ibaraki	3.727	2.283	−0.175	0.253	0.021	0.708	1.048	−0.412
Tochigi	3.362	2.416	−0.327	0.228	0.010	0.686	1.661	−1.312
Gunma	3.422	2.391	−0.264	0.232	0.008	0.674	1.353	−0.971
Saitama	2.072	1.994	−0.496	0.141	0.042	0.683	−0.267	−0.026
Chiba	2.917	1.239	−0.535	0.198	0.040	0.692	0.571	0.712
Tokyo	0.258	1.096	−1.636	0.018	0.006	0.687	1.122	−1.033
Kanagawa	0.530	1.243	−1.125	0.036	0.035	0.707	0.285	−0.651
Niigata	2.693	1.867	−0.672	0.183	−0.001	0.719	−0.108	0.706
Toyama	3.450	1.830	−0.547	0.234	0.006	0.696	1.596	−0.365
Ishikawa	3.725	2.192	−0.745	0.253	0.009	0.650	1.702	−0.334
Fukui	2.388	2.017	−0.860	0.162	0.004	0.652	0.332	0.082
Yamanashi	3.915	3.260	−0.131	0.266	0.016	0.698	0.955	−1.148
Nagano	2.904	2.524	−0.586	0.197	0.006	0.697	0.621	−0.554
Gifu	2.792	2.180	−0.676	0.189	0.009	0.680	−0.113	0.523
Shizuoka	4.108	2.123	−0.258	0.279	0.005	0.682	0.881	0.396
Aichi	3.310	2.018	−0.397	0.225	0.020	0.666	0.855	−0.078
Mie	4.011	1.963	−0.212	0.272	0.010	0.673	0.887	0.419
Shiga	4.370	2.403	0.224	0.297	0.035	0.585	2.885	−2.058
Kyoto	1.850	1.579	−1.202	0.126	0.001	0.632	1.674	−0.959
Osaka	0.545	1.176	−1.287	0.037	0.005	0.653	0.290	−0.330
Hyogo	1.685	1.433	−0.901	0.114	0.011	0.573	0.999	−0.544
Nara	2.723	2.251	−0.442	0.185	0.024	0.562	1.866	−1.724
Wakayama	2.107	1.129	−1.387	0.143	−0.014	0.603	1.645	−0.012
Tottori	3.243	1.900	−0.804	0.220	0.002	0.617	1.957	−0.648
Shimane	2.296	2.123	−0.978	0.156	−0.014	0.605	0.396	0.009
Okayama	2.988	1.243	−0.807	0.203	0.015	0.604	1.625	0.106
Hiroshima	2.266	1.241	−0.908	0.154	0.004	0.632	0.920	0.224
Yamaguchi	4.087	1.375	−0.667	0.277	−0.013	0.645	2.371	0.099
Tokushima	3.764	1.924	−1.084	0.255	−0.004	0.582	2.377	−0.285
Kagawa	2.684	1.348	−0.896	0.182	0.004	0.565	1.839	−0.359
Ehime	2.406	1.359	−0.864	0.163	−0.005	0.590	1.319	−0.156
Kochi	2.824	1.897	−1.062	0.192	−0.008	0.589	1.844	−0.628
Fukuoka	1.502	1.057	−0.882	0.102	0.026	0.647	1.336	−0.784
Saga	3.713	2.470	−0.456	0.252	0.000	0.585	1.983	−1.122
Nagasaki	2.518	1.701	−0.867	0.171	−0.004	0.606	1.112	−0.201
Kumamoto	3.862	2.266	−0.174	0.262	0.017	0.626	1.546	−0.680
Oita	3.904	1.328	−0.443	0.265	−0.001	0.623	3.521	−1.388
Miyazaki	3.157	1.704	−0.387	0.214	0.005	0.638	0.789	0.194
Kagoshima	3.819	2.576	−0.809	0.259	0.001	0.633	1.399	−0.240
Okinawa	3.058	2.002	−0.766	0.208	0.036	0.649	0.783	0.146
(b) Non-manufacturing industry
Hokkaido	1.718	1.433	−0.505	0.138	−0.001	0.551	0.487	−0.384
Aomori	1.567	2.080	−0.415	0.126	−0.008	0.534	−0.015	−0.736
Iwate	2.032	1.616	−0.463	0.163	−0.014	0.529	0.127	0.074
Miyagi	2.478	1.932	0.079	0.199	0.010	0.513	0.381	−0.637
Akita	1.606	1.606	−0.759	0.129	−0.013	0.578	0.164	−0.099
Yamagata	1.640	1.634	−0.659	0.132	−0.008	0.543	0.032	−0.033
Fukushima	1.919	1.717	−0.350	0.154	0.005	0.549	−0.035	−0.121
Ibaraki	2.640	1.609	−0.043	0.212	0.013	0.579	0.348	−0.079
Tochigi	2.518	1.603	0.083	0.202	0.007	0.561	0.146	−0.084
Gunma	2.225	1.558	0.038	0.179	0.005	0.551	−0.085	−0.020
Saitama	3.428	2.073	0.733	0.275	0.027	0.559	0.010	−0.249
Chiba	3.103	2.058	0.558	0.249	0.026	0.566	−0.021	−0.334
Tokyo	3.047	2.338	0.239	0.245	0.004	0.562	0.771	−1.111
Kanagawa	3.221	2.172	0.816	0.259	0.022	0.579	−0.157	−0.469
Niigata	1.943	1.826	−0.483	0.156	−0.001	0.588	0.139	−0.282
Toyama	1.905	1.287	−0.266	0.153	0.004	0.569	1.107	−0.949
Ishikawa	2.070	1.697	−0.089	0.166	0.005	0.532	0.775	−1.016
Fukui	2.456	1.402	−0.206	0.197	0.003	0.533	0.938	−0.410
Yamanashi	2.466	1.934	−0.174	0.198	0.010	0.571	0.010	−0.083
Nagano	2.407	1.819	−0.159	0.193	0.004	0.571	−0.291	0.271
Gifu	2.243	1.892	0.026	0.180	0.006	0.556	0.276	−0.693
Shizuoka	2.367	1.966	0.018	0.190	0.003	0.558	−0.414	0.046
Aichi	2.741	1.872	0.257	0.220	0.013	0.545	0.219	−0.385
Mie	2.424	1.999	−0.231	0.195	0.007	0.550	0.529	−0.625
Shiga	3.087	1.444	0.507	0.248	0.023	0.478	1.494	−1.107
Kyoto	2.017	1.938	−0.173	0.162	0.001	0.517	0.678	−1.105
Osaka	2.370	1.862	0.093	0.190	0.003	0.535	0.690	−1.002
Hyogo	2.138	2.002	−0.065	0.172	0.007	0.469	0.308	−0.754
Nara	3.389	1.990	0.415	0.272	0.015	0.460	1.363	−1.126
Wakayama	1.467	1.396	−0.487	0.118	−0.009	0.494	−0.206	0.162
Tottori	1.800	2.523	−0.474	0.145	0.001	0.505	0.239	−1.138
Shimane	1.996	2.099	−0.656	0.160	−0.009	0.495	0.133	−0.226
Okayama	2.125	1.506	−0.146	0.171	0.009	0.494	0.563	−0.473
Hiroshima	1.964	2.171	−0.009	0.158	0.002	0.517	0.730	−1.605
Yamaguchi	1.412	1.655	−0.582	0.113	−0.008	0.527	0.366	−0.660
Tokushima	1.883	1.795	−0.565	0.151	−0.003	0.476	0.418	−0.389
Kagawa	2.177	1.764	−0.326	0.175	0.003	0.462	0.768	−0.669
Ehime	1.836	1.676	−0.310	0.147	−0.003	0.483	0.242	−0.399
Kochi	1.215	1.857	−0.620	0.098	−0.005	0.482	0.187	−0.783
Fukuoka	2.098	1.798	0.069	0.168	0.017	0.529	0.372	−0.855
Saga	1.685	1.622	−0.319	0.135	0.000	0.479	0.366	−0.599
Nagasaki	1.745	1.910	−0.537	0.140	−0.003	0.496	−0.027	−0.235
Kumamoto	1.831	1.818	−0.590	0.147	0.011	0.512	0.038	−0.105
Oita	1.871	1.694	−0.622	0.150	−0.001	0.510	0.341	−0.201
Miyazaki	1.940	1.702	−0.475	0.156	0.003	0.522	0.035	−0.003
Kagoshima	1.877	1.903	−0.569	0.151	0.000	0.518	−0.035	−0.090
Okinawa	2.640	2.443	0.392	0.212	0.023	0.531	−0.117	−0.845

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Otsuka, A. (2017). A Traditional Approach to Agglomeration Economies. In: A New Perspective on Agglomeration Economies in Japan. New Frontiers in Regional Science: Asian Perspectives, vol 20. Springer, Singapore. https://doi.org/10.1007/978-981-10-6490-6_3

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DOI: https://doi.org/10.1007/978-981-10-6490-6_3
Published: 19 September 2017
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Appendix: Growth accounts (in %, annual growth rate, 1980–2002)

Appendix: Growth accounts (in %, annual growth rate, 1980–2002)

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