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Integrating endogeneity in survey sampling using instrumental-variable calibration estimator.

Muhammad Nadeem Intizar1, Muhammad Ahmed Shehzad1, Haris Khurram2,3

  • 1Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan.

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|July 29, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces instrumental-variable calibrated estimators to address endogeneity in survey sampling. These new methods improve estimation efficiency when auxiliary variables are endogenous, outperforming traditional calibration techniques.

Keywords:
Auxiliary variablesCalibration estimatorEndogeneityInstrumental variablesSurvey sampling

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Area of Science:

  • Survey Sampling Methodology
  • Econometrics
  • Statistical Inference

Background:

  • Endogeneity, where auxiliary variables correlate with error terms, poses challenges in statistical estimation.
  • Calibration is a key method for population total estimation in survey sampling but struggles with endogeneity.
  • Endogenous auxiliary variables in calibration can lead to biasedness and increased variance.

Purpose of the Study:

  • To propose novel instrumental-variable calibrated estimators to overcome endogeneity issues in survey sampling.
  • To enhance the efficiency of population total estimation when auxiliary variables are endogenous.
  • To provide a robust methodological tool for situations with correlated auxiliary and error terms.

Main Methods:

  • Utilizing the classical instrumental-variables approach for the case of exact identification.
  • Developing new calibrated estimators that incorporate instrumental variables.
  • Evaluating estimator properties through theoretical analysis.

Main Results:

  • The proposed instrumental-variable calibrated estimators demonstrate greater efficiency compared to conventional calibration estimators.
  • The study confirms the effectiveness of the new estimators in the presence of endogenous auxiliary variables.
  • Theoretical properties of the proposed estimators are rigorously presented.

Conclusions:

  • Instrumental-variable calibration offers a more efficient estimation strategy when dealing with endogeneity in survey sampling.
  • The proposed estimators provide a valuable advancement for survey methodology.
  • Empirical validation through simulation and real data supports the practical utility of the new methods.