A Methodical Approach to Design and Valuation of Weather Derivatives in Agriculture

Table 2

The results of the test of various weather indices.

	𝑇2	𝑇3	𝑆𝑖2	𝑆𝑖3	CDD 1	CDD 2	CDD 3
Wheat
Critical month (weight)		4 (0.074)		4 (0.152)
	5 (0.257)	5 (0.213)	5 (0.555)	5 (0.440)
	6 (0.743)	6 (0.713)	6 (0.445)	6 (0.408)
Pearson correlation	−0.69	−0.693	−0.617	−0.632	−0.503	−0.522	−0.569
	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃=0.0009)	(𝑃=0.0005)	(𝑃=0.0001)
𝑅^2	0.477	0.481	0.381	0.399	0.253	0.273	0.323
Barley
Critical month (weight)		4 (0.194)		4 (0.271)
	5 (0.264)	5 (0.149)	5 (0.500)	5 (0.307)
	6 (0.736)	6 (0.657)	6 (0.500)	6 (0.422)
Pearson correlation	−0.666	−0.688	−0.592	−0.645	−0.459	−0.45	−0.497
	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃<0.0001)	(𝑃=0.0029)	(𝑃=0.0036)	(𝑃=0.0011)
𝑅^2	0.443	0.473	0.35	0.416	0.211	0.2027	0.2472

Source: authors.