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Instrument-free inference under confined regressor endogeneity; derivations and applications

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  • Jan F. Kiviet

    (University of Amsterdam and Stellenbosch University)

Abstract

Instead of exploiting instruments and claiming these to be uncorrelated with the disturbances, in an instrument-free approach one may adopt flexible bounds on the correlation between the endogenous regressors and the disturbances. Such an alternative to Two-Stage Least-Squares (TSLS) inference is developed here for general linear models with endogenous possibly time-dependent regressors. Earlier results enabled this just for rather restrictive mesokurtic i.i.d. cross-section data. In three empirical replication studies their underlying exclusion restrictions are shown to be most doubtful. Next, incredible (weak-instrument robust) TSLS inference is replaced by more reliable remarkably narrow instrument-free asymptotically conservative confidence intervals.

Suggested Citation

  • Jan F. Kiviet, 2020. "Instrument-free inference under confined regressor endogeneity; derivations and applications," Working Papers 09/2020, Stellenbosch University, Department of Economics.
  • Handle: RePEc:sza:wpaper:wpapers344
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    References listed on IDEAS

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    2. Jan F. Kiviet, 2020. "Causes Of Haze And Its Health Effects In Singapore: A Replication Study," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1367-1387, December.
    3. Dovì, Max-Sebastian & Koester, Gerrit & Nickel, Christiane, 2021. "Addressing the endogeneity of slack in Phillips Curves," Working Paper Series 2619, European Central Bank.

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    More about this item

    Keywords

    endogeneity robust least-squares inference; new exclusion restrictions test; replication studies; sensitivity analysis of two-stage least-squares;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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