Correcting Autocorrletation in a Model with Dummies

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SUMMARY

The discussion focuses on correcting first-level autocorrelation in a model using SPSS, specifically when working with dummy variables for time and state effects. The user has implemented 22 YEAR dummies and 51 STATE dummies and seeks to replicate a method outlined in a previous paper involving the transformation of the dependent variable Yij into Yij - ρ Yij-1. This transformation requires estimating the autocorrelation coefficient ρ from the residuals of a weighted least squares fit. The user emphasizes the need for SPSS to recognize the dataset as a panel to properly execute this autocorrelation correction.

PREREQUISITES
  • Understanding of SPSS for statistical analysis
  • Knowledge of panel data structures
  • Familiarity with dummy variable regression
  • Concept of autocorrelation in time series data
NEXT STEPS
  • Research how to specify panel data in SPSS
  • Learn about estimating autocorrelation coefficients using residuals
  • Explore the application of weighted least squares in regression analysis
  • Study the transformation of variables in regression models
USEFUL FOR

Statisticians, data analysts, and researchers working with panel data in SPSS who need to correct for autocorrelation in their regression models.

coraUK
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How can I get SPSS output that corrects for first-level autocorrelation in the dependent variable and gives me appropriate beta estimates and significance levels? I used dummy variables for time and state effects in a model, I have 22 YEAR dummies and 51 STATE dummies. The method I want to copy is explained in an older paper:



Eij = pEij-1 + Sij



"Where ρ is the autocorrelation between the εijth and εij-1th errors and δij is a normally and independently distributed error with a constant variance across time and counties. The residuals from the weighted least squares fit were used to estimate rho. The dependent variable Yij was then transformed into Yij - ρ Yij-1. The regression analysis was rerun with these transformed independent and dependent variables." Can anyone explain what was done in this example and how I can do the same?
 
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It is standard autocorr. correction, except for the panel structure of the data. SPSS needs to be somehow "told" that the dataset is panel (has a cross-section dimension in addition to a time series dimension).
 

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