方法对比
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| 德宾-沃森自相关检验× | 布雷施-戈弗雷序列相关LM检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1950 | 1978 |
| 提出者≠ | James Durbin & Geoffrey Watson | Trevor Breusch & Leslie Godfrey |
| 类型≠ | Test for first-order residual autocorrelation | Lagrange-multiplier test for serial correlation |
| 开创性文献≠ | Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428. DOI ↗ | Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301. DOI ↗ |
| 别名≠ | DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi | BG test, LM test for autocorrelation, Breusch-Godfrey serial correlation test, Breusch-Godfrey otokorelasyon testi |
| 相关≠ | 4 | 3 |
| 摘要≠ | The Durbin-Watson test, developed by James Durbin and Geoffrey Watson in 1950–1951, detects first-order serial correlation in the residuals of a linear regression. Its statistic ranges from 0 to 4, with a value near 2 indicating no autocorrelation, values toward 0 indicating positive autocorrelation, and values toward 4 indicating negative autocorrelation. It remains one of the most reported regression diagnostics despite well-known limitations. | The Breusch-Godfrey test is a Lagrange-multiplier test for serial correlation in regression residuals, developed independently by Trevor Breusch (1978) and Leslie Godfrey (1978). Unlike the Durbin-Watson test, it detects autocorrelation up to any chosen order p, remains valid when the model includes lagged dependent variables, and produces a definite chi-square p-value rather than an inconclusive region — making it the modern standard for autocorrelation testing. |
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