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

Table 6

The most significant correlation coefficients between wheat yield per hectare and the average characteristics of weather in regions of the CR (1970–2009).

Region	Air temperature	Rainfall	Drought index 𝑆𝑖
Středočeský	−0.43 (6, 𝑃=0.0059)	0.35 (4, 𝑃=0.0270)	−0.33 (4-5, 𝑃=0.0363)
	−0.42 (5-6, 𝑃=0.0068)	0.33 (4-5, 𝑃=0.0373)	0.43 (10–12, 𝑡−1, 𝑃=0.0063)
	−0.35 (5–7, 𝑃=0.0290)	−0.38 (10–12, 𝑡−1, 𝑃=0.0159)	0.36 (10, 𝑡−1, 𝑃=0.0263)
	−0.32 (5–7, 𝑃=0.0422)		0.36 (12, 𝑡−1, 𝑃=0.0242)
			0.35 (10-11, 𝑡−1, 𝑃=0.0283)
Jihočeský	−0.48 (6, 𝑃=0.0016)	0.40 (2, 𝑃=0.0105)	0.32 (1, 𝑃=0.0473)
	−0.43 (5-6, 𝑃=0.0060)	−0.34 (7, 𝑃=0.0301)	0.32 (10–12, 𝑡−1, 𝑃=0.0449)
	−0.34 (5–7, 𝑃=0.0339)	−0.32 (10–12, 𝑡−1, 𝑃=0.0463)
Vysočina	−0.59 (6, 𝑃<0.0001)	×	−0.42 (6, 𝑃=0.0064)
	−0.53 (5-6, 𝑃=0.0004)		−0.38 (4–6, 𝑃=0.0153)
	−0.47 (5–7, 𝑃=0.0024)		−0.36 (5-6, 𝑃=0.0245)
	−0.45 (4–6, 𝑃=0.0037)
	−0.43 (6-7, 𝑃=0.0057)
Královéhradecký	−0.41 (6, 𝑃=0.0091)	−0.43 (6–8, 𝑃=0.0056)	×
	−0.39 (5-6, 𝑃=0.0122)	−0.41 (7-8, 𝑃=0.0090)
		−0.35 (10–12, 𝑡−1, 𝑃=0.0295)
Jihomoravský	−0.66 (6, 𝑃<0.0001)	0.34 (5, 𝑃=0.0304)	−0.58 (5-6, 𝑃<0.0001)
	−0.66 (5-6, 𝑃<0.0001)	0.33 (4–6, 𝑃=0.0398)	−0.56 (4–6, 𝑃=0.0002)
	−0.60 (4–6, 𝑃<0.0001)	0.32 (4-5, 𝑃=0.0418)	−0.52 (5, 𝑃=0.0005)
	−0.52 (3–6, 𝑃=0.0005)		−0.48 (3–6, 𝑃=0.0019)
	−0.50 (5–7, 𝑃=0.0010)		−0.46 (6, 𝑃=0.0027)
Olomoucký	−0.45 (6, 𝑃=0.0034)	×	×
	−0.42 (5-6, 𝑃=0.0068)
	−0.32 (5–7, 𝑃=0.0418)

The data in front of round brackets are correlation coefficients. The figures in brackets denote critical months for yield formation. The 𝑃 values test the two-tailed statistical significance of the correlation coefficient. The term “×” indicates no statistically significant correlation (Pearson, Spearman) at significance level 0.05. We put a maximum of 5 most statistically significant correlation coefficients.
Source: authors.