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CERGE-EI, Prague

How to become a good academic economist?. CERGE-EI, Prague. April 11, 2003. Vítězslav Babický, Andreas Ortmann. PLAN OF THE PRESENTATION: 1. Motivation 2. Lonely economist 3. Simulation results 4. Scientific cooperator 5. Conclusion, discussion

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CERGE-EI, Prague

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  1. How to become a good academic economist? CERGE-EI, Prague April 11, 2003 Vítězslav Babický, Andreas Ortmann

  2. PLAN OF THE PRESENTATION: 1. Motivation 2. Lonely economist 3. Simulation results 4. Scientific cooperator 5. Conclusion, discussion The goal: discussion and feedback on the model (which is in the proposal stage here)

  3. MOTIVATION Important question that everyone have addressed, obviously interesting for CERGE, particularly for me Human capital formation: Long-run project with many pre-requisites and uncertain outcome

  4. FOUR PILLARS: 1) English - language, communication 2) Mathematics - analytic and logic skills 3) Economics - principles, interest 4) Research activity - creativity, publications (Publish or perish!)

  5. MODEL INGREDIENTS Knowledge: English … L Mathematics … M Economics … E Concave production functions - education is increasingly hard Finite limit of knowledge (1=absolute knowledge; can be never reached) Starting point at zero knowledge

  6. Assumptions: Acquiring knowledge of English and mathematics is independent on other factors Example: fl(t) = 1 – 1/(l*x+1), l=3 fm(t) = 1 – 1/(m*x+1), m=0.5

  7. Studying economics is productive according to the level of English and mathematics reached in previous period; E(t)=M.L.f(t)

  8. Depreciation of knowledge over time - every period, knowledge I {L,M,E} depreciates by factor dI; the learning in new period starts at the point of depreciated knowledge For example, it means that Lk+1 = fl(tl,k + fl-1 (Lk(1 – dl))

  9. Scarce resources - time A) Finite time horizon (limited lifetime of a scientist): n periods B) Time endowment equal to one in every period Every period, an adept allocates her time among studying English (tl), mathematics (tm), economics (te), and the remaining time is spent on the research activities

  10. RESEARCH Random process with Poisson distribution; measured by number of published papers In the expected value, the outcome is proportional to the level of knowledge in economics, in mathematics and in English; it is also proportional to the level of creativity, i.e. c.M.E.L.(1 – tl –tm –te) papers each period

  11. LONELY RESEARCHER - wants to publish single-author pieces Solves the optimization problem maxk cMkEkLk(1 – tl,k –tm,k –te,k) such that M0 =E0 =L0 = 0; tl,k ,tm,k ,te,k are control variables, k=1,2, …, n

  12. RESULTS: Policy functions of the lonely econ, suggestions from 3-period models for various values of parameters:

  13. Empirical observation: in recent days more and more papers are co-authored  SCIENTIFIC COOPERATORS emerge - they specialize on one field of knowledge only (mathematics or economics) - they have to be good in communication - they have to understand the other field up to a reasonable level Model similar to the previous one, with two types of agents:

  14. The model: maxks C.Mk,1Ek,2Lk,1Lk,2 (1 – tl,k,1 –tm,k,1 –te,k,1) such that M0,1 =E0,1 =L0,1 = M0,2 =E0,2 =L0,2 = 0, tl,k,1 +tm,k,1 +te,k,1 = tl,k,2 +tm,k,2 +te,k,2 , and for all ks and i{1,2} Mk,i  M’, Ek,i  E’. All kinds of knowledge follow the same processes as previously.

  15. Suggestions for future: Solve an analogue of such model in continuous time Calibration of the model on real data Example 1: Prof. A M.Sc. in mathematics first (5 yrs.), PhD. in economics then (4 yrs.), 50 papers in top journals Example 2: Dr. BB PhD. in maths (8 yrs.), PhD. in econs (6 yrs.), 4 papers More data  running regressions

  16. CONCLUSION Even though for economists, as follows from our model, mathematics seem to be really important and CERGE does hopefully a good job for us teaching the applied methods

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