IDEAS home Printed from https://ideas.repec.org/a/spr/apjors/v4y2020i1d10.1007_s41685-019-00126-7.html
   My bibliography  Save this article

How do population agglomeration and interregional networks improve energy efficiency?

Author

Listed:
  • Akihiro Otsuka

    (Yokohama City University)

Abstract

This study investigates the impact of population agglomeration and interregional networks on the energy efficiency of the Japanese industrial and commercial sector. The empirical analysis employs a stochastic frontier model and reveals a nonlinear relation between population agglomeration and energy efficiency. External diseconomies prevail until reaching a threshold level of agglomeration; when the threshold is exceeded, external economies come into play. Enhanced accessibility is found to significantly increase energy efficiency. These results suggest that policies aimed at strengthening regional agglomeration and interregional networks can greatly contribute to improving energy efficiency.

Suggested Citation

  • Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    • Handle: RePEc:spr:apjors:v:4:y:2020:i:1:d:10.1007_s41685-019-00126-7
    DOI: 10.1007/s41685-019-00126-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41685-019-00126-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s41685-019-00126-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chang, Tzu-Pu & Hu, Jin-Li, 2010. "Total-factor energy productivity growth, technical progress, and efficiency change: An empirical study of China," Applied Energy, Elsevier, vol. 87(10), pages 3262-3270, October.
    2. Li, Jianglong & Liu, Hongxun & Du, Kerui, 2019. "Does market-oriented reform increase energy rebound effect? Evidence from China's regional development," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    3. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    4. Shanzi Ke & Yufeng Yu, 2014. "The pathways from industrial agglomeration to TFP growth – the experience of Chinese cities for 2001–2010," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 19(2), pages 310-332, April.
    5. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    6. Combes, Pierre-Philippe & Gobillon, Laurent, 2015. "The Empirics of Agglomeration Economies," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 247-348, Elsevier.
    7. Karl Aiginger & Stephen W. Davies, 2004. "Industrial specialisation and geographic concentration: Two sides of the same coin? Not for the European Union," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 231-248, November.
    8. Roberta Capello, 2000. "The City Network Paradigm: Measuring Urban Network Externalities," Urban Studies, Urban Studies Journal Limited, vol. 37(11), pages 1925-1945, October.
    9. Daniel Montolio & Albert Solé‐Ollé, 2009. "Road investment and regional productivity growth: the effects of vehicle intensity and congestion," Papers in Regional Science, Wiley Blackwell, vol. 88(1), pages 99-118, March.
    10. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    11. Mika Goto & Amani Mohammed Atris & Akihiro Otsuka, 2018. "Productivity change and decomposition analysis of Japanese regional economies," Regional Studies, Taylor & Francis Journals, vol. 52(11), pages 1537-1547, November.
    12. Akihiro Otsuka & Mika Goto, 2015. "Estimation and determinants of energy efficiency in Japanese regional economies," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(2), pages 89-101, June.
    13. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    14. Rice, Patricia & Venables, Anthony J. & Patacchini, Eleonora, 2006. "Spatial determinants of productivity: Analysis for the regions of Great Britain," Regional Science and Urban Economics, Elsevier, vol. 36(6), pages 727-752, November.
    15. Gilbert E. Metcalf & Kevin A. Hassett, 1999. "Measuring The Energy Savings From Home Improvement Investments: Evidence From Monthly Billing Data," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 516-528, August.
    16. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    17. Rafael Boix & Joan Trullén, 2007. "Knowledge, networks of cities and growth in regional urban systems," Papers in Regional Science, Wiley Blackwell, vol. 86(4), pages 551-574, November.
    18. Hirano, Y. & Fujita, T., 2012. "Evaluation of the impact of the urban heat island on residential and commercial energy consumption in Tokyo," Energy, Elsevier, vol. 37(1), pages 371-383.
    19. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    20. Boyd, Gale A. & Pang, Joseph X., 2000. "Estimating the linkage between energy efficiency and productivity," Energy Policy, Elsevier, vol. 28(5), pages 289-296, May.
    21. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    22. Su, Qing, 2011. "The effect of population density, road network density, and congestion on household gasoline consumption in U.S. urban areas," Energy Economics, Elsevier, vol. 33(3), pages 445-452, May.
    23. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    24. Thompson, Peter & Taylor, Timothy G, 1995. "The Capital-Energy Substitutability Debate: A New Look," The Review of Economics and Statistics, MIT Press, vol. 77(3), pages 565-569, August.
    25. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    26. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    27. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    28. Akihiro Otsuka & Mika Goto, 2018. "Regional determinants of energy intensity in Japan: the impact of population density," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 257-278, August.
    29. Gilles Duranton & J. V. Henderson & William C. Strange (ed.), 2015. "Handbook of Regional and Urban Economics," Handbook of Regional and Urban Economics, Elsevier, edition 1, volume 5, number 5.
    30. Adelheid Holl, 2012. "Market potential and firm-level productivity in Spain," Journal of Economic Geography, Oxford University Press, vol. 12(6), pages 1191-1215, November.
    31. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    32. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171, Elsevier.
    33. Karathodorou, Niovi & Graham, Daniel J. & Noland, Robert B., 2010. "Estimating the effect of urban density on fuel demand," Energy Economics, Elsevier, vol. 32(1), pages 86-92, January.
    34. Brownstone, David & Golob, Thomas F., 2009. "The impact of residential density on vehicle usage and energy consumption," Journal of Urban Economics, Elsevier, vol. 65(1), pages 91-98, January.
    35. Michael Fritsch & Viktor Slavtchev, 2011. "Determinants of the Efficiency of Regional Innovation Systems," Regional Studies, Taylor & Francis Journals, vol. 45(7), pages 905-918.
    36. Kim McCoy & Ronald L. Moomaw, 1995. "Determinants Of Manufacturing Efficiency In Canadian Cities: A Stochastic Frontier Approach," The Review of Regional Studies, Southern Regional Science Association, vol. 25(3), pages 317-330, Winter.
    37. Lall, Somik V. & Shalizi, Zmarak & Deichmann, Uwe, 2004. "Agglomeration economies and productivity in Indian industry," Journal of Development Economics, Elsevier, vol. 73(2), pages 643-673, April.
    38. Buck, J. & Young, D., 2007. "The potential for energy efficiency gains in the Canadian commercial building sector: A stochastic frontier study," Energy, Elsevier, vol. 32(9), pages 1769-1780.
    39. Morikawa, Masayuki, 2012. "Population density and efficiency in energy consumption: An empirical analysis of service establishments," Energy Economics, Elsevier, vol. 34(5), pages 1617-1622.
    40. Antonio M. Bento & Maureen L. Cropper & Ahmed Mushfiq Mobarak & Katja Vinha, 2005. "The Effects of Urban Spatial Structure on Travel Demand in the United States," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 466-478, August.
    41. Aranda-Usón, Alfonso & Ferreira, Germán & Mainar-Toledo, M.D. & Scarpellini, Sabina & Llera Sastresa, Eva, 2012. "Energy consumption analysis of Spanish food and drink, textile, chemical and non-metallic mineral products sectors," Energy, Elsevier, vol. 42(1), pages 477-485.
    42. Filippini, Massimo & Hunt, Lester C. & Zorić, Jelena, 2014. "Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector," Energy Policy, Elsevier, vol. 69(C), pages 73-81.
    43. Theodore Tsekeris & Sotiris Papaioannou, 2018. "Regional determinants of technical efficiency: evidence from the Greek economy," Regional Studies, Taylor & Francis Journals, vol. 52(10), pages 1398-1409, October.
    44. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    45. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    46. Akihiro Otsuka & Mika Goto & Toshiyuki Sueyoshi, 2010. "Industrial agglomeration effects in Japan: Productive efficiency, market access, and public fiscal transfer," Papers in Regional Science, Wiley Blackwell, vol. 89(4), pages 819-840, November.
    47. Peter C. Reiss & Matthew W. White, 2008. "What changes energy consumption? Prices and public pressures," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 636-663, September.
    48. Feijoo, Maria L. & Franco, Juan F. & Hernandez, Jose M., 2002. "Global warming and the energy efficiency of Spanish industry," Energy Economics, Elsevier, vol. 24(4), pages 405-423, July.
    49. Ihara, Tomohiko & Kikegawa, Yukihiro & Asahi, Kazutake & Genchi, Yutaka & Kondo, Hiroaki, 2008. "Changes in year-round air temperature and annual energy consumption in office building areas by urban heat-island countermeasures and energy-saving measures," Applied Energy, Elsevier, vol. 85(1), pages 12-25, January.
    50. Dirk Stelder, 2016. "Regional Accessibility Trends in Europe: Road Infrastructure, 1957-2012," Regional Studies, Taylor & Francis Journals, vol. 50(6), pages 983-995, June.
    51. Du, Kerui & Lin, Boqiang, 2017. "International comparison of total-factor energy productivity growth: A parametric Malmquist index approach," Energy, Elsevier, vol. 118(C), pages 481-488.
    52. Akihiro Otsuka & Mika Goto & Toshiyuki Sueyoshi, 2014. "Energy efficiency and agglomeration economies: the case of Japanese manufacturing industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 6(2), pages 195-212, June.
    53. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    54. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    55. Lin, Boqiang & Yang, Lisha, 2013. "The potential estimation and factor analysis of China′s energy conservation on thermal power industry," Energy Policy, Elsevier, vol. 62(C), pages 354-362.
    56. Mitra, Arup, 1999. "Agglomeration Economies as Manifested in Technical Efficiency at the Firm Level," Journal of Urban Economics, Elsevier, vol. 45(3), pages 490-500, May.
    57. Karl Aiginger & Stephen W. Davies, 2004. "Industrial Specialisation and Geographic Concentration: Two Sides of the Same Coin? Not for the European Union," Journal of Applied Economics, Taylor & Francis Journals, vol. 7(2), pages 231-248, November.
    58. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    59. Wei, Yi-Ming & Liao, Hua & Fan, Ying, 2007. "An empirical analysis of energy efficiency in China's iron and steel sector," Energy, Elsevier, vol. 32(12), pages 2262-2270.
    60. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    61. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    62. Arup Mitra, 2000. "Total Factor Productivity Growth and Urbanization Economies: A Case of Indian Industries," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 12(2), pages 97-108, July.
    63. Nigel Driffield & Max Munday, 2001. "Foreign Manufacturing, Regional Agglomeration and Technical Efficiency in UK Industries: A Stochastic Production Frontier Approach," Regional Studies, Taylor & Francis Journals, vol. 35(5), pages 391-399.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Honma, Satoshi & Ushifusa, Yoshiaki & Okamura, Soyoka & Vandercamme, Lilu, 2023. "Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction," Resources Policy, Elsevier, vol. 82(C).
    2. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    3. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    2. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    3. Akihiro Otsuka & Mika Goto, 2015. "Estimation and determinants of energy efficiency in Japanese regional economies," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(2), pages 89-101, June.
    4. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    5. Akihiro Otsuka, 2023. "Stochastic demand frontier analysis of residential electricity demands in Japan," Asia-Pacific Journal of Regional Science, Springer, vol. 7(1), pages 179-195, March.
    6. Du, Kerui & Lin, Boqiang, 2017. "International comparison of total-factor energy productivity growth: A parametric Malmquist index approach," Energy, Elsevier, vol. 118(C), pages 481-488.
    7. Lester C. Hunt & Paraskevas Kipouros, 2023. "Energy Demand and Energy Efficiency in Developing Countries," Energies, MDPI, vol. 16(3), pages 1-26, January.
    8. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    9. Mark A. Andor & David H. Bernstein & Stephan Sommer, 2021. "Determining the efficiency of residential electricity consumption," Empirical Economics, Springer, vol. 60(6), pages 2897-2923, June.
    10. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    11. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    12. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    13. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    14. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    15. Akihiro Otsuka & Mika Goto, 2018. "Regional determinants of energy intensity in Japan: the impact of population density," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 257-278, August.
    16. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    17. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.
    18. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    19. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    20. Zhang, Shanshan & Lundgren, Tommy & Zhou, Wenchao, 2016. "Energy efficiency in Swedish industry," Energy Economics, Elsevier, vol. 55(C), pages 42-51.

    More about this item

    Keywords

    Population agglomeration; Interregional networks; Accessibility; Energy efficiency; Japan;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:apjors:v:4:y:2020:i:1:d:10.1007_s41685-019-00126-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.