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Table 6 Causality rules

From: Mining precise cause and effect rules in large time series data of socio-economic indicators

Rules Countries Support Strength
Binary causal rules
(Cereal production, D, 2 %, 2) \(\Rightarrow\) (agricultural raw materials exports, 3 %) India 74 120.8767
Pakistan 76 124.1436
(Air transport, D, 1 %, 2) \(\Rightarrow\) (GDP growth, 0.22 %) India 74 120.8767
Nepal 79 129.0440
(Cereal production, D, 3 %, 1) \(\Rightarrow\) (crop production index, 1 %) Srilanka 76 124.1436
Nepal 81 132.3109
Afganistan 76 124.1436
India 76 124.1436
Transitive causal rules
(Rural population, D, 1 %, 1) \(\Rightarrow\) (population density, D, 0.33 %, 1) \(\Rightarrow\) (population total, 0.68 %) Afghanistan 74 120.8767
India 83 135.5779
Maldives 77 125.7771
Nepal 71 115.9763
(Land under cereal production, D, 3 %, 1) \(\Rightarrow\) (food exports, D, 1 %, 2) \(\Rightarrow\) (GDP growth, 1.5 %) India 71 115.9763
Pakistan 72 117.6097
Bangladesh 71 115.9763
(Arable land, D, 1 %, 1) \(\Rightarrow\) (agricultural land, D, 1 %, 3) \(\Rightarrow\) (CO2 emissions, 1.5 %) India 71 115.9763
Srilanka 71 115.9763
India 70 114.3428
Many to one (combined causal) causal rule
{(Rural population, D, 2.3 %, 1), (urban population D, 0.5 %, 1)} \(\Rightarrow\) (population density, 1 %) India 79 129.0440
Afghanistan 72 117.6097
Pakistan 72 117.6097
{(Forest rents, I, 5 %, 2), (Foreign direct investment, D, 3 %, 1)} \(\Rightarrow\) (crop production index, 7 %) Srilanka 72 117.6097
{(Land under cereal production, D, 0.8 %, 1), (rural population, I, 1 %, 2)} \(\Rightarrow\) (cereal production, 2 %) Afghanistan 73 119.2432
India 72 117.6097
Pakistan 70 114.3428
Cyclic causal rules
(Land under cereal production, D, 2.5 %, 2) (agricultural land, D, 4.5 %, 1) India 72 117.6097
(Gross domestic savings, D, 1 %, 1) (cereal yield, D, 0.5 %, 2) Srilanka 70 114.3428
India 70 114.3428