Dataset Information

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

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.

SUBMITTER: Ustaoglu E

PROVIDER: S-EPMC5587288 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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

Ustaoglu Eda E Lavalle Carlo C

PloS one 20170906 9

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 ...[more]

PMID: 28877204

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Project description:Given the negative environmental impacts of intensive agriculture, there is an urgent need to reduce the impact of food production on biodiversity. Ecological restoration of farmland could potentially contribute to this goal. While the positive impacts of ecological restoration on biodiversity are well established, less evidence is available regarding impacts on economic development and employment. Potentially, prospects for economic development could be enhanced by ecological restoration though increased provision of ecosystem services, on which some economic activity depends. Here we examined this issue through the development of contrasting land use scenarios for the county of Dorset, southern England. Two scenarios of future agricultural expansion were compared with two scenarios of landscape-scale ecological restoration and the current situation. Impacts on provision of multiple ecosystem services (ES) were explored using InVEST models and proxy values for different land cover types. Impacts on economic employment were examined using an economic input-output model, which was adjusted for variation in ES flows using empirically determined ES dependency values for different economic sectors. Using the unadjusted input-output model, the scenarios had only a slight economic impact (≤ 0.3% Gross Value Added, GVA). Conversely, when the input-output model was adjusted to take account of ES flows, GVA increased by up to 5.4% in the restoration scenarios, whereas under the scenario with greatest agricultural expansion, GVA was reduced by -4.5%. Similarly, employment increased by up to 6.7% following restoration, compared to declines of up to -5.6% following maximum agricultural expansion. These results show that the economic contribution of rural land is far greater than that attributable to agricultural production alone. Landscape-scale restoration of agricultural land can potentially increase the contribution of farmland to economic development and employment, by increasing flows of multiple ES to the many economic sectors that depend on them.

Project description:BackgroundInter-regional relationships between landscape factors and biological responses in natural conditions are important but difficult to predict because of the differences in each landscape context and local environment. To examine the inter-regional variability in relation to landscape factors and the biological response of an insect pest of rice, Stenotus rubrovittatus, we extrapolated a damage prediction model (the 'original model' of our previous study) for rice using land-use data. The 'original model' comprised as fixed factors the area of source habitat (i.e. pastures and graminoid-dominated fallow fields), soybean fields, and rice paddies within 300-m radii with research years as the random intercept. We hypothesized that the original model would be applicable to new regions, but the predictive accuracy would be reduced. We predicted that fitting a new extended model, adjusting the parameter coefficients of identical fixed factors of the 'original model,' and adding regional random intercepts would improve model performance (the 'extended model'). A field experiment was conducted in two regions that had a similar landscape context with the original region, each in a different year of four years in total. The proportion of rice damage and surrounding land use within a 300-m radius was investigated, and the data were applied to the models and the applicability and accuracy of the models were examined.ResultsWhen the 'original model' was assigned to the combined data from the original and extrapolated regions, the relationship between the observed and the predicted values was statistically significant, suggesting that there was an inter-regional common relationship. The relationship was not statistically significant if the model was applied only to the new regions. The extended model accuracy improved by 14% compared with the original model and was applicable for unknown data within the examined regions as demonstrated by three-fold cross validation.ConclusionsThese results imply that in this pest-crop system, there is likely to be a common inter-regional biological response of arthropods because of landscape factors, although we need to consider local environmental factors. We should be able to apply such relationships to identify or prevent pest hazards by offering region-wide management options.

Dataset Information

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

Publications

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

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