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<p>The purpose of the study is to estimate the average petrol price in Pakistan, as an accurate average is crucial for economic analysis, market monitoring, and policy formulation. There is a strong correlation between petrol and dollar prices, so a study incorporating the international dollar price as an auxiliary variable to improve estimation accuracy. To achieve our goal, we have proposed some predictive estimators by using a systematic sampling scheme. The bias and mean squared error (MSE) of the suggested estimator are expressed, and its efficiency is theoretically compared with that of corresponding existing predictive estimators in simple random sampling. An empirical study based on real petrol price data, supported by simulation results, demonstrates that the proposed predictive estimators outperform the existing estimators in simple random sampling in terms of lower MSE and higher efficiency. The findings confirm that integrating relevant auxiliary information with systematic sampling offers efficient estimators for accurate and cost-effective petrol price estimation.</p>

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Petrol Price Estimation in Pakistan Under Predictive Approach: A Comparative Framework in Systematic and Simple Random Sampling

  • 期刊论文

  • 发表日期：

    2026年5月13日

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  • Muhammad Rafaqat,
  • Hina Khan

摘要

The purpose of the study is to estimate the average petrol price in Pakistan, as an accurate average is crucial for economic analysis, market monitoring, and policy formulation. There is a strong correlation between petrol and dollar prices, so a study incorporating the international dollar price as an auxiliary variable to improve estimation accuracy. To achieve our goal, we have proposed some predictive estimators by using a systematic sampling scheme. The bias and mean squared error (MSE) of the suggested estimator are expressed, and its efficiency is theoretically compared with that of corresponding existing predictive estimators in simple random sampling. An empirical study based on real petrol price data, supported by simulation results, demonstrates that the proposed predictive estimators outperform the existing estimators in simple random sampling in terms of lower MSE and higher efficiency. The findings confirm that integrating relevant auxiliary information with systematic sampling offers efficient estimators for accurate and cost-effective petrol price estimation.