Agricultural economics · Thünen Institute of Farm Economics / University Bonn
Published
Edited
Jun 16, 2021
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Importers
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cleaned = cleanIQR(full_dataset, [`${crop}_yield`, `${crop}_${indicator}`])
yield_soilQuality_smi_plot = pairplot(cleaned, {
vars: [`${crop}_yield`, `${crop}_${indicator}`, "smi"],
width: 800,
height: 600,
hue: "year",
hueVarType: "nominal",
markers: true
})
summary(linearModel)
summary(interactionModel)
summary(detailedModel)
coefficients_detailedModel = coefficientPlot(detailedModel)
stargazer([linearModel, interactionModel])
Object.keys(pricesYieldsDirectCosts).map((c) => c.split(/::/g)[1])
table(cropData)
summary(lm("Yield ~ SQR", yields, { weights: weights }))
weights = {
const dataPerRegions = [...d3.group(yields, (r) => r.Region)];
const weightsPerRegion = dataPerRegions.reduce((obj, reg) => {
obj[reg[0]] = 1 / d3.variance(reg[1].map((r) => r.Yield));
return obj;
}, {});
const weights = yields.map((r) => weightsPerRegion[r.Region]);
return weights;
}
Object.keys(pricesYieldsDirectCosts).map((c) => c)
stargazer(regData, {
modelNames: cropData.map((c) => c.Crop)
})
stargazer(regData.slice(5), {
modelNames: cropData.slice(5).map((c) => c.Crop)
})
stargazer(regData.slice(0, 5), {
modelNames: cropData.slice(0, 5).map((c) => c.Crop)
})
regData = Object.keys(pricesYieldsDirectCosts).reduce((obj, curCrop) => {
const minYear = 2010;
const curCropYields = pricesYieldsDirectCosts[curCrop]
.filter((r) => r.year > minYear)
.map((r) => ({
Yield: r.yield,
Region: r.region,
NUTS2: nuts2_sqrs.find((f) => f.NUTS_NAME === r.region)
? nuts2_sqrs.find((f) => f.NUTS_NAME === r.region).NUTS_CODE
: 0,
SQR: nuts2_sqrs.find((f) => f.NUTS_NAME === r.region)
? nuts2_sqrs.find((f) => f.NUTS_NAME === r.region)._mean
: 0
}))
.filter((r) => r.SQR);
const dataPerRegions = [...d3.group(curCropYields, (r) => r.Region)];
const weightsPerRegion = dataPerRegions.reduce((obj, reg) => {
obj[reg[0]] = 1 / d3.variance(reg[1].map((r) => r.Yield));
return obj;
}, {});
const weights = curCropYields.map((r) => weightsPerRegion[r.Region]);
const model = lm(`Yield ~ SQR`, curCropYields, { weights: weights });
obj.push(model);
return obj;
}, [])
lm = (await import(await FileAttachment("linear-models.esm@59.js").url()))
.default
import { table } from "@tmcw/tables/2"
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