Granger-causality tests

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1. Run a regression of X 2. Determine a statistically significant time lag interval 3. Run multiple regressions 1. Make sure additional regressions are also significant 2. Include regressions that add explanatory power 4. Can be repeated for multiple Ys 5. Hopefully, find a clear relationship, such as Y granger-causes X
Do a series of F-<strong>tests</strong> on lagged values of Y to see if those values provide statistically significant information about future values of X Can involve more variables if vector autoregression is applied to capture interdependencies
Page 1 and 2: Because sometimes it’s more than
Page 3 and 4: What is causality? What do you thin
Page 5 and 6: Sir Clive William John Granger •B
Page 10 and 11: Linear Regression models Used to d
Page 12 and 13: Autoregressive model X t = c + φX
Page 14 and 15: Tools (Continued) F - tests (F dis
Page 16 and 17: F-Tests - on the difficulty of find
Page 18 and 19: Vector Autoregressions Macroeconom
Page 20 and 21: Recursive VARs Each error term i
Page 22 and 23: Continuous VAR Can correct for dis
Page 24 and 25: Performance VARs capture comovem
Page 26 and 27: Ljungwall, C. Wang, Z. Why is capit
Page 28 and 29: McCrorie, R. Chambers, M. Granger c
Page 30 and 31: Tian, G. Wan, G. Interaction among
Page 32 and 33: Applications of Granger Causality W
Page 34 and 35: Microfit software Microfit has impr
Page 36: Granger causality is a statistical

Granger-causality tests

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