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Survival
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Survival

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Published in: Technology, Economy & Finance
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Transcript

  • 1.
  • 2. Research Question
    Can we Relate Post-Entry Performance of Individual establishments to establishment specific characteristics?
    Prior Work:
    Audretsch(1991) showed that survival rates of industries happen at industry level and not at business level.
  • 3. Model
    hij – baseline rate of hazard
    Xij – Vector of Covariates containing 3 factors
    Long run average cost function - degree to which new business is burdened by inherent size disadvantage
    Technological regime change
    Industry growth (Price/Cost Margin)
  • 4. Model contd…
    To estimate the β’s the Partial Likelihood function
    Coefficients are estimated by maximizing the PL function..
    In case of Ties a modified PL is used.
  • 5. Model contd..
    S(t) – vector of the sum of covariates for episodes at time t, m – number of exits at time t
  • 6. Data Specification
    Longitudinal data does not have start and end date [5 year interval used]- Annual Survey of Manufacturers
    SIC predicted estimation. – data from D&B file provides virtual census
    12251 new establishments in 1976 studied for 10 years.
    Firm specific characteristics –[ innovation rate=number of innovations/employment]
    Establishment size
    Industry employment growth , price – cost margin
    Macroeconomic employment rate , real interest rate (Economic report of president)
  • 7. Regression Results (Cox Model)
  • 8. Critique
    While Survival Analysis is right, handling of censoring (right/left and interval) is not handled in his model
    Not clear whether the coefficients are significant (Wald test of coefficients)
    Is the model adequate to explain the phenomenon?

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