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Time Aggregation and the Contradictions with Causal Relationships: Can Economic Theory Come to the Rescue?

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  • R Gupta
  • K Komen

Abstract

The literature on causality takes contradictory stands on the direction of causal relationships based on whether one uses temporally aggregated or systematically sampled data. As an example, using the relationship between a nominal target and the instrument used to achieve it, we show that one can fall back upon the data in itself, and analyse it from the perspective of economic theory, not only as a source of second opinion to econometric theories and Monte Carlo simulations, but also to draw proper conclusions regarding the form of the causal relationship that might be actually existing in the data.

Suggested Citation

  • R Gupta & K Komen, 2009. "Time Aggregation and the Contradictions with Causal Relationships: Can Economic Theory Come to the Rescue?," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 33(1), pages 16-27, April.
    • Handle: RePEc:taf:rseexx:v:33:y:2009:i:1:p:16-27
    DOI: 10.1080/10800379.2009.12106460
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    Cited by:

    1. Lumengo Bonga-Bonga, 2017. "Assessing the Effectiveness of the Monetary Policy Instrument during the Inflation Targeting Period in South Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 706-713.
    2. Bonga-Bonga, Lumengo & Kabundi, Alain, 2015. "Monetary Policy Instrument and Inflation in South Africa: Structural Vector Error Correction Model Approach," MPRA Paper 63731, University Library of Munich, Germany.
    3. Temitope L.A Leshoro, 2014. "Does the Repurchase Rate Affect Inflation in South Africa? An Empirical Analysis Using an Impulse Response Function," Journal of Economics and Behavioral Studies, AMH International, vol. 6(7), pages 524-531.

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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