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* Add Statistics Menu * Add Granger Causality test * Apply Black formatting * Add Cointegration Tests * Adjust plotting for Cointegration test * Add Significant parameter to Cointegration tests * Move regression functions to seperate .py files * Progress on Panel Data * A lot of progress for Panel Data * Make functions robust and improve documentation * Re-enable Breusch-Godfrey * Add modify functionality * Improve modify functionality * Add Breusch-Pagan heteroscedasticity test * Capitalize a word * Include documentatin for the Statistics Menu * Update _index.md * Update _index.md * Update _index.md * Fix export statements and add Example datasets * Update example with Longley's dataset * Update documentation with a legit source * Compare the results from each regression models based on the wage_panel dataset * Updated with all relevant types of regression tables * Update with all relevant regression types for Panel data * Update _index.md * Add change column type, improve OLS, add time and entity effects for FE * Update documentation and fix a small bug * Add in Statistics menu, replacing Custom menu * Remove custom menu * Add in documentation * Add in gst files * Cointegration can be used on any amount of columns * Add Tests * Make tests time invariant * Update Poetry and Requirements * Change name of Statistics menu to Econometrics menu * Rename scripts * Add type in Documentation * Change names from Statistics to Econometrics * Add graph * Update tests with rounding and naming * Make minor adjustments to fix the tests * Updating tests : allow extra args for capture * Apply recorder formatting * Adding some minor formatting * Fix error with MyPy * Attempt to fix MyPy annoyance * super small style things * Fix small bugs and add plot command to dwat * Small description mistake * Update documentation with missing argument * Update styling * Add error handling and add improve show functionality * Fix merge issue * Allow import from custom_imports Co-authored-by: Jeroen Bouma <jeroenbouma@MacBook-Pro-van-Jeroen.local> Co-authored-by: jmaslek <jmaslek11@gmail.com> Co-authored-by: Chavithra PARANA <chavithra@gmail.com>
3.2 KiB
Vendored
usage: granger [ts {OPTIONS}] [-l LAGS] [-cl CONFIDENCE] [-h] [--export {csv,json,xlsx,png,jpg,pdf,svg}]
Show Granger causality between two timeseries
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another, first proposed in 1969. Ordinarily, regressions reflect "mere" correlations, but Clive Granger argued that causality in economics could be tested for by measuring the ability to predict the future values of a time series using prior values of another time series. Since the question of "true causality" is deeply philosophical, and because of the post hoc ergo propter hoc fallacy of assuming that one thing preceding another can be used as a proof of causation, econometricians assert that the Granger test finds only "predictive causality". Using the term "causality" alone is a misnomer, as Granger-causality is better described as "precedence", or, as Granger himself later claimed in 1977, "temporally related". Rather than testing whether X causes Y, the Granger causality tests whether X forecasts Y. [Source: Wikipedia]
optional arguments:ols
-ts {OPTIONS}, --timeseries {OPTIONS}
Requires two time series, the first time series is assumed to be Granger-caused by the second time series. (default: None)
-l LAGS, --lags LAGS How many lags should be included (default: 3)
-cl CONFIDENCE, --confidence CONFIDENCE
Set the confidence level (default: 0.05)
-h, --help show this help message (default: False)
--export {csv,json,xlsx,png,jpg,pdf,svg}
Export raw data into csv, json, xlsx and figure into png, jpg, pdf, svg (default: )
Example:
2022 Feb 24, 05:54 (✨) /econometrics/ $ granger adj_close-msft adj_close-aapl
Granger Causality Test [Y: adj_close | X: adj_close | Lags: 3]
┏━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┳━━━━━━┓
┃ ┃ F-test ┃ P-value ┃ Count ┃ Lags ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━╇━━━━━━━━╇━━━━━━┩
│ ssr_ftest │ 2.13 │ 0.09 │ 749.00 │ 3.00 │
├──────────────┼────────┼─────────┼────────┼──────┤
│ ssr_chi2test │ 6.46 │ 0.09 │ - │ 3 │
├──────────────┼────────┼─────────┼────────┼──────┤
│ lrtest │ 6.43 │ 0.09 │ - │ 3 │
├──────────────┼────────┼─────────┼────────┼──────┤
│ params_ftest │ 2.13 │ 0.09 │ 749.00 │ 3.00 │
└──────────────┴────────┴─────────┴────────┴──────┘
As the p-value of the F-test is 0.095, we can not reject the null hypothesis at the 0.05 confidence level.