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A New Variance Component Score Test for Testing Distributed Lag Functions with Applications in Time Series Analysis.

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We introduce a variance component score test (VCST) to evaluate constrained distributed lag models (DLMs). Our simulation study demonstrates VCST offers greater statistical power compared to the traditional likelihood ratio test.

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Area of Science:

  • Econometrics
  • Statistical Modeling

Background:

  • Distributed lag models (DLMs) are crucial for analyzing time-series data.
  • Evaluating constrained DLMs against unconstrained alternatives requires robust statistical tests.

Purpose of the Study:

  • To propose and evaluate a novel variance component score test (VCST) for constrained distributed lag models.
  • To compare the power of VCST against the standard likelihood ratio test.

Main Methods:

  • Development of a variance component score test (VCST).
  • Application of VCST to test a constrained distributed lag model against an unconstrained alternative.
  • Comparative analysis using a simulation study.

Main Results:

  • The variance component score test (VCST) was successfully formulated.
  • Simulation results indicated that VCST is more powerful than the likelihood ratio test for the specified model.
  • The study provides evidence for the superiority of VCST in this context.

Conclusions:

  • VCST is a powerful statistical tool for evaluating constrained distributed lag models.
  • The findings suggest adopting VCST for improved statistical inference in time-series analysis.
  • Further research can explore VCST applications in other econometric models.