Modeling industrial location decisions in U.S. counties



If we plug the γjs back into the expression for pj/k, we obtain,

_    exp(Yj) exp(β0zjk)

pj/k " PJ=1 exp(β0Zjk + Yj )

_ __________nj__exp(β0Zjt)

PK=1 exp(βzjk + Ik) PJ=1 exP(αj + βzjk)

_     exp(β0Zjk + Ik )

PtT=1 exp(β0zjk + Ik)

and the concentrated log-likelihood is that of a logit model where the choices
are now the sectors with an alternative specific constant added to the model.
This log-likelihood is equivalent to that of a Poisson regression with fixed-
effects (see, for example, Cameron & Trivedi (1998)].

24



More intriguing information

1. Public Debt Management in Brazil
2. The Formation of Wenzhou Footwear Clusters: How Were the Entry Barriers Overcome?
3. A dynamic approach to the tendency of industries to cluster
4. Outsourcing, Complementary Innovations and Growth
5. The name is absent
6. Weak and strong sustainability indicators, and regional environmental resources
7. Cross border cooperation –promoter of tourism development
8. AJAE Appendix: Willingness to Pay Versus Expected Consumption Value in Vickrey Auctions for New Experience Goods
9. The effect of globalisation on industrial districts in Italy: evidence from the footwear sector
10. PROJECTED COSTS FOR SELECTED LOUISIANA VEGETABLE CROPS - 1997 SEASON