Help for xtsel

Description

The package XTSEL includes two commands that help us to rank the best predictors between a number of alternative explanatory variables (xtselvar),
or the best specification between all possible combinations of a set of explanatory variables (xtselmod), according to several in-sample and out-of-sample statistics.
They are specially adapted for a panel data framework, firstly because the out-of-sample prediction performance is measured in the two inherent dimensions of a panel (time-series and cross-individuals),
and secondly because they allow a large number of methodological options that typically are necessary in panel data analysis.

Given a set of n predictors, xtselvar estimates the same specification n times, one for each predictor.
xtselmod estimates (2^n - 1) different specifications, one per each possible combination out of the set of n variables.

Both procedures keep constant the same dependent variable and an optional list of fixed control variables, plus several other methodological options.
For each candidate variable/specification, the procedures estimate a set of parameters and statistical criteria:

1. Adjusted R squared (R2_ad).
2. Akaike Information Criterion (AIC).
3. Bayesian Information Criterion (BIC)
4. U-Theil in time-series dimension: RMSE of variable/specification vs. RMSE from a naïve prediction or an AR1 model (Uth_TS).
5. U-Theil in cross-section dimension: RMSE of variable/specification vs. RMSE from a naïve prediction or an AR1 model (Uth_CS)

Both commands rank each variable/specification according to each criterion and generate one ranking per each one of them.

xtselvar also reports coefficients and t-statistic of each candidate variable. They also compute a composite ranking summarizing all five criteria.
They finally sort all candidate variables/specifications according to the selected ranking, which by default is the composite ranking.

See xtselvar for specific help about xtselvar command.

See xtselmod for specific help about xtselmod command.

Proceedings USA Stata Conference 2020

https://www.stata.com/meeting/us20/slides/us20_Ugarte-Ruiz.pdf

Author

Alfonso Ugarte-Ruiz
alfonso.ugarte@bbva.com

References

. Joseph N. Luchman & Daniel Klein & Nicholas J. Cox, 2006. "TUPLES: Stata module for selecting all possible tuples from a list",
Statistical Software Components S456797, Boston College Department of Economics, revised 17 May 2020.
. Alfonso Ugarte-Ruiz, 2019. "XTOOS: Stata module for evaluating the out-of-sample prediction performance of panel-data models,"
Statistical Software Components S458710, Boston College Department of Economics, revised 09 Jun 2020.