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Updated: Oct 22, 2025

Evaluating Primary Blast Effects In Vitro
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Commentary on a method for testing resistance to shocks.

Paresh Kumar Narayan1

  • 1Centre for Financial Econometrics, Faculty of Business and Law, Deakin University, 221 Burwood Highway, Burwood, Victoria 3125, Australia.

Methodsx
|August 26, 2021
PubMed
Summary
This summary is machine-generated.

This study explains Narayan's (2020) method for assessing time-series variable resilience to economic shocks. The approach is demonstrated using crude oil prices, offering a valuable tool for future economic shock analysis.

Keywords:
COVID-19CoronavirusCrude oil pricesExchange ratesNarayan–Popp testPersistencyShock resistanceTime seriesUnit roots

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Area of Science:

  • Economics
  • Econometrics
  • Time Series Analysis

Background:

  • Economic variables face various shocks, such as the COVID-19 pandemic.
  • Assessing the resistance of these variables to shocks is crucial for understanding economic stability.
  • Existing methods may not fully capture the nuances of shock resistance over time.

Purpose of the Study:

  • To provide a detailed walkthrough of the Narayan (2020a) approach for testing shock resistance in time-series data.
  • To illustrate the practical application of this methodology using crude oil prices as a case study.
  • To highlight the utility of the method for future research on economic shock resilience.

Main Methods:

  • The study follows the step-by-step procedure outlined by Narayan (2020a), encompassing steps (1) to (8).
  • The methodology involves analyzing a time-series variable's response to external shocks.
  • Application is demonstrated using the crude oil price dataset.

Main Results:

  • The Narayan (2020a) approach provides a structured framework for shock resistance testing.
  • The application to crude oil prices demonstrates the method's feasibility and relevance.
  • The analysis confirms the applicability of the method beyond the specific context of COVID-19 shocks.

Conclusions:

  • The Narayan (2020a) method offers a robust technique for evaluating time-series shock resistance.
  • This approach is versatile and applicable to various economic variables and historical shocks.
  • Future researchers can effectively employ this method to analyze economic resilience to prolonged or significant events.