Title: Alternative Tests for the Selection of Model Variables (Classic Reprint)
Publisher: Forgotten Books
Publication Date: 2018
Language: English
ISBN 10: 0331900319
ISBN 13: 9780331900316
Binding: HRD
Condition: New
Weight: 379 grams

About this title

Synopsis

Discover how to choose model variables using whole-model testing rather than single-equation statistics.

The work argues that traditional single-equation tests often fail to identify which variables truly shape model behavior. It contrasts these tests with model-behavior analysis, which examines how removing or constraining a variable changes the overall system. Readers will see why data usefulness, not a variable’s isolated significance, should guide variable selection.

Through practical examples at the firm level and in macroeconomic contexts, the material shows how feedback loops and interconnections matter. It demonstrates that a complete system view can clarify when a variable is essential and when its apparent impact is misleading.

Learn why t-tests and partial correlation coefficients may mislead about a variable’s importance.
Understand the difference between measuring data usefulness and model specification.
Explore how whole-model testing analyzes feedback among variables to assess impact.
See concrete examples at both company and national-economy scales.

Ideal for readers interested in economics, statistics, and the evaluation of social theories through system-wide analysis.

"About this title" may belong to another edition of this title.

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