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Demand-Driven Innovation and Spatial Competition Over Time Under Heavy-Tailed Signals

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  • Rustam Ibragimov

Abstract

We study robustness of the model of demand driven innovation and spatial competition over time with log- concavely distributed signals in Jovanovic and Rob (1987) to heavy-tailedness assumptions. We demonstrate that mplications of the model remain valid for not extremely heavy-tailed distributions of consumers' signals. However, ts properties are reversed in the case of signals with extremely thick-tailed distributions if the ¯rms employ the ample mean of the signals to estimate the ideal product. We further show that conclusions of the model continue to hold under the only assumption of symmetry of signals if a more robust estimator of the ideal product, the sample median, is chosen as the product design.

Suggested Citation

  • Rustam Ibragimov, 2005. "Demand-Driven Innovation and Spatial Competition Over Time Under Heavy-Tailed Signals," Harvard Institute of Economic Research Working Papers 2087, Harvard - Institute of Economic Research.
  • Handle: RePEc:fth:harver:2087
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    File URL: http://www.economics.harvard.edu/pub/hier/2005/HIER2087.pdf
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    Cited by:

    1. Ibragimov, Rustam, 2007. "Efficiency of linear estimators under heavy-tailedness: convolutions of [alpha]-symmetric distributions," Scholarly Articles 2623749, Harvard University Department of Economics.

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