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Examining lag effects between industrial land development and regional economic changes: The Netherlands experience

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  • Eda Ustaoglu
  • Carlo Lavalle

Abstract

In most empirical applications, forecasting models for the analysis of industrial land focus on the relationship between current values of economic parameters and industrial land use. This paper aims to test this assumption by focusing on the dynamic relationship between current and lagged values of the ‘economic fundamentals’ and industrial land development. Not much effort has yet been attributed to develop land forecasting models to predict the demand for industrial land except those applying static regressions or other statistical measures. In this research, we estimated a dynamic panel data model across 40 regions from 2000 to 2008 for the Netherlands to uncover the relationship between current and lagged values of economic parameters and industrial land development. Land-use regulations such as land zoning policies, and other land-use restrictions like natural protection areas, geographical limitations in the form of water bodies or sludge areas are expected to affect supply of land, which will in turn be reflected in industrial land market outcomes. Our results suggest that gross domestic product (GDP), industrial employment, gross value added (GVA), property price, and other parameters representing demand and supply conditions in the industrial market explain industrial land developments with high significance levels. It is also shown that contrary to the current values, lagged values of the economic parameters have more sound relationships with the industrial developments in the Netherlands. The findings suggest use of lags between selected economic parameters and industrial land use in land forecasting applications.

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  • Eda Ustaoglu & Carlo Lavalle, 2017. "Examining lag effects between industrial land development and regional economic changes: The Netherlands experience," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-34, September.
    • Handle: RePEc:plo:pone00:0183285
    DOI: 10.1371/journal.pone.0183285
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    Cited by:

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    2. Fei Xie & Shuaibing Zhang & Kaixu Zhao & Fengmei Quan, 2022. "Evolution Mode, Influencing Factors, and Socioeconomic Value of Urban Industrial Land Management in China," Land, MDPI, vol. 11(9), pages 1-33, September.
    3. Junheng Qi & Mingxing Hu & Bing Han & Jiemin Zheng & Hui Wang, 2022. "Decoupling Relationship between Industrial Land Expansion and Economic Development in China," Land, MDPI, vol. 11(8), pages 1-21, July.
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    6. Cheng, Jing, 2022. "Analysis of the factors influencing industrial land leasing in Beijing of China based on the district-level data," Land Use Policy, Elsevier, vol. 122(C).
    7. Caroline J. Williams & Rachel A. Davidson & Linda K. Nozick & Meghan Millea & Jamie L. Kruse & Joseph E. Trainor, 2023. "Single-family housing inventory projection method for natural hazard risk modeling applications," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(1), pages 409-434, October.
    8. Eda Ustaoglu & Filipe Batista e Silva & Carlo Lavalle, 2020. "Quantifying and modelling industrial and commercial land-use demand in France," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 519-549, January.

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