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Full-Text Articles in Applied Statistics
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans
Lonnie K. Stevans
The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …
Investigating Omitted Variable Bias In Regression Parameter Estimation: A Genetic Algorithm Approach, Lonnie K. Stevans, David N. Sessions
Investigating Omitted Variable Bias In Regression Parameter Estimation: A Genetic Algorithm Approach, Lonnie K. Stevans, David N. Sessions
Lonnie K. Stevans
Bias in regression estimates resulting from the omission of a correlated relevant variable is a well known phenomenon. In this study, we apply a genetic algorithm to estimate the missing variable and, using that estimated variable, demonstrate that significant bias in regression estimates can be substantially corrected with relatively high confidence in effective models. Our interest is restricted to the case of a missing binary indicator variable and the analytical properties of bias and MSE dominance of the resulting dependent error generated vector process. These findings are compared to prior results for the independent error proxy process. Simulations are run …