Ecological Economics
ISSN: 0921-8009
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List of references used in the meta-analysis
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The dataset covers the evolution of the governance design of the institutional water regimes in Netherland, France, Belgium, Switzerland, Italy and Spain from 1750 to 2004. It is based on the research project EUWARENESS. We code for extent and integration of these six institutional resource regime.
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  • Text
These files are the two simulation codes for the Human And Resources with MONEY (HARMONEY) model. These codes, programmed in the R language, were used to produce the simulation results in the main paper and supplemental information of "An Integrated Biophysical and Economic Modeling Framework for Long-Term Sustainability Analysis: the HARMONEY Model". The codes also produce several plots in the R plot window. HARMONEY_SetPriceByConstantMarkup: This simulates the results that assume a constant price markup, as defined in the paper. HARMONEY_SetPriceByVariableMarkup: This simulates the results that assume a "variable" price markup, as defined in the paper. When running the code, it might not simulate to the end time for all combinations of parameter choices. This occurs for parameters that lead to system "collapse" when the net power flow from the extraction sector reaches zero. It is best to change the parameter values slightly from those listed as being used in the simulations of the paper. If you have trouble seeing results, reduce the simulation time by reducing the "to" value in this line of code: times <- seq(from = 0, to = 160, by = 0.1); The investment parameters that were changed to explore the "high" and "low" investment cases are the following (for "kappa 0" and "kappa 1"): assign("inv_kappa0.1",1.0) assign("inv_kappa1.1",1.5) Other discussion and simulations in the paper were informed by varying the following parameters, as listed in the code: assign("lambda_h.max1",1.0e2) # Nature carrying capacity before "tcritical.lambda_h" assign("delta_y.1",1.2e-02) # Depletion (production) factor before "tcritical.lambda_h" (1/[Capital * yr]) assign("delta1",0.03) # Depreciation rate of capital (%/yr) assign("v1",1.5) # "Goods capital / gross physical output" ratio assign("a_gg",0.1) # I-O coefficient: goods consumption of goods sector per unit of goods sector output assign("a_ge",0.2) # I-O coefficient: goods consumption of extraction sector per unit of extraction sector output assign("eta.Kextract_max",0.16) # Resources required to operate K.extract (and the maximum value if modeling a decline in K.extract after "tcritical.Inv_Cum_extract") assign("eta.Kgoods_max",eta.Kextract_max) # Resources required to operate K.goods (and the maximum value if modeling a decline in K.goods after "tcritical.Inv_Cum_goods") assign("nature_per_unit_physical_good",0.1) # The quantity of nature needed to become a unit of capital assign("markup.goods",0.07) # fraction to mark up costs to define price, goods sector assign("markup.extract",markup.goods) # fraction to mark up costs to define price, extraction sector assign("S",8e-2); # Subsistence salary per capita (consumption per person when not in famine in nature/(person * yr)) assign("rho.extract",0.010); # Threshold nature consumption per capita (consumption per person below which there is "famine": nature/(person * yr))
Data Types:
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These files are in Esri Shapefile format. They are proposed in 4 categories: 1- Base maps, Such as provinces borders and locations of cities 2_ All cities models are indicated in "Model_Str" field of "City_boundry3.Shp" file. 3- Results of case study, are shown in "GreenAbl", "GreenExs", and "NotGreen" Fields of "Parcells.shp" file. 4- The results of generalization the case study results to whole country, are available in "NotGreen" field of "City_boundry3.Shp" file.
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  • File Set
Data Types:
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  • Dataset
Data for "Ecological Fiscal Transfers for Biodiversity Conservation Policy: A Transaction Costs Analysis of Minas Gerais, Brazil"
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  • File Set
Data used for Irish GS estimates 1990-2016
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  • Tabular Data
  • Dataset
Data Types:
  • Other
  • Dataset
Data analysed in the manuscript.
Data Types:
  • Tabular Data
  • Dataset
These data provide rankings of 6 Beyond GDP indicators (the Human Development Index (HDI), the Social Progress Index (SPI), the Global Well-Being Index (GWBI), Quality of Life (QoL), the Happy Planet Index (HPI), and the recoded Sustainable Society Index (SSI)) and six separate variables, and their correlation with GDP's ranking.
Data Types:
  • Tabular Data
  • Dataset
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