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101 lines
4.4 KiB
Markdown
Vendored
101 lines
4.4 KiB
Markdown
Vendored
---
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title: bgod
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description: This page provides the usage, parameters, and examples of the Breusch-Godfrey
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autocorrelation test in Python. It's useful for individuals working with OLS Regression
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Results and other econometrics. The BGOD page increases understanding of this functionality
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within Python.
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keywords:
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- Breusch-Godfrey
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- Autocorrelation Test
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- OLS Regression Results
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- Econometrics
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- BGOD
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- Metadata
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- Least Squares Method
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- Durbin-Watson
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="econometrics /bgod - Reference | OpenBB Terminal Docs" />
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Show Breusch-Godfrey autocorrelation test results.Needs OLS to be run in advance with independent and dependent variables
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### Usage
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```python
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bgod [-l LAGS]
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```
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---
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## Parameters
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| Name | Description | Default | Optional | Choices |
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| ---- | ----------- | ------- | -------- | ------- |
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| lags | The lags for the Breusch-Godfrey test | 3 | True | None |
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---
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## Examples
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```python
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2022 Jun 01, 06:29 (🦋) /econometrics/ $ load longley -a ll
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2022 Jun 01, 06:29 (🦋) /econometrics/ $ ols -d ll.totemp -i ll.gnpdefl,ll.gnp,ll.unemp,ll.armed,ll.pop,ll.year
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OLS Regression Results
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=======================================================================================
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Dep. Variable: ll.totemp R-squared (uncentered): 1.000
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Model: OLS Adj. R-squared (uncentered): 1.000
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Method: Least Squares F-statistic: 5.052e+04
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Date: Wed, 01 Jun 2022 Prob (F-statistic): 8.20e-22
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Time: 12:29:44 Log-Likelihood: -117.56
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No. Observations: 16 AIC: 247.1
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Df Residuals: 10 BIC: 251.8
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Df Model: 6
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Covariance Type: nonrobust
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==============================================================================
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coef std err t P|t| [0.025 0.975]
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------------------------------------------------------------------------------
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ll.gnpdefl -52.9936 129.545 -0.409 0.691 -341.638 235.650
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ll.gnp 0.0711 0.030 2.356 0.040 0.004 0.138
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ll.unemp -0.4235 0.418 -1.014 0.335 -1.354 0.507
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ll.armed -0.5726 0.279 -2.052 0.067 -1.194 0.049
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ll.pop -0.4142 0.321 -1.289 0.226 -1.130 0.302
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ll.year 48.4179 17.689 2.737 0.021 9.003 87.832
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==============================================================================
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Omnibus: 1.443 Durbin-Watson: 1.277
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Prob(Omnibus): 0.486 Jarque-Bera (JB): 0.605
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Skew: 0.476 Prob(JB): 0.739
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Kurtosis: 3.031 Cond. No. 4.56e+05
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==============================================================================
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Notes:
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[1] R² is computed without centering (uncentered) since the model does not contain a constant.
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[2] Standard Errors assume that the covariance matrix of the errors is correctly specified.
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[3] The condition number is large, 4.56e+05. This might indicate that there are
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strong multicollinearity or other numerical problems.
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Warnings:
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kurtosistest only valid for n=20 ... continuing anyway, n=16
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2022 Jun 01, 06:29 (🦋) /econometrics/ $ bgod
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Breusch-Godfrey autocorrelation test [Lags: 3]
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┏━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
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┃ ┃ Breusch-Godfrey ┃
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┡━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
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│ LM-stat │ 10.35 │
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├──────────┼─────────────────┤
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│ p-value │ 0.02 │
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├──────────┼─────────────────┤
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│ f-stat │ 0.10 │
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├──────────┼─────────────────┤
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│ fp-value │ 0.96 │
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└──────────┴─────────────────┘
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The result 0.02 indicates no existence of autocorrelation.
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```
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---
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