Equipo de Rayos X Estacionario para Grafía

Find  new  firms  wherever  the  other  firms  are  

If  most  programs  aimed  at  encouraging  entrepreneurship  intend  to  provide   affordable   facilities   proximate   to   supportive   institutions   and   allied   firms,   my   findings   suggest   that   these   programs   should   be   fairly   effective.   As   the   Ordinary   Least  Squares  regression  models  demonstrate,  the  number  of  existing  firms  in  area   proves   the   biggest   predictor   of   new   firm   location   in   area.   Presuming   there   is   a   causal   relationship   between   existing   firms   and   new   firm   generation,   then   any   incubation   facility   located   amongst   a   concentration   of   existing   firms   ought   to   be   successful.   Further,   as   new   firm   locations   appear   somewhat   price   motivated   by   lower  rents,  when  considered  in  isolation,  offering  such  affordable  space  in  existing   firm  rich  areas  ought  to  ensure  further  success  of  the  incubator  approach.  

What  remains  surprising  about  my  findings  is  that  the  degree  of  urbanization   seems  not  to  matter.  So  long  as  firms  locate  in  an  urbanized  area  (>1,000  people  per   square   mile),   my   findings   suggest   that   whether   the   existing   firm   concentration   occurs  in  a  CBD  or  suburban  office  park  fails  to  matter  in  its  ability  to  attract  new   firms.  Despite  compelling  arguments  connecting  urbanization  and  human  capital  to   endogenous  growth,  these  results  seem  to  suggest  that  beyond  a  certain  threshold,   the   degree   of   urbanization   matters   little.   Or,   as   in   the   case   of   Research   Triangle   Park,   new   firms   may   even   sprout   in   the   woods,   so   long   as   there   are   other   firms   around  to  nurture  them.    

Opportunities  for  Further  Study  

Clearly,   the   spatio-­‐economic   factors   driving   firm   location   and   formation   behavior   remains   a   fertile   subject   for   further   analysis.   If   the   presence   of   existing   firms  in  an  area  serves  as  such  a  strong  indicator  of  new  firm  formation  and  location   patterns,  as  determined  in  this  study,  the  mechanisms  by  which  firms  agglomerate   in  the  first  place  remain  uncertain.  

Further   consideration   of   real   estate   market   relationships   and   effects   upon   new  firm  behavior  is  needed.  While  the  data  utilized  in  this  study  provided  a  multi-­‐ year  picture  of  prevailing  commercial  market  dynamics  within  Triangle  ZIP  codes,   this  data  was  nonetheless  limited.  Data  for  years  before  2001  was  unavailable,  and   not  all  ZIP  codes  had  real  estate  market  data  for  all  years.    A  more  comprehensive   time  series  of  real  estate  market  conditions  would  prove  invaluable  to  determining   how  these  dynamics  exert  influence  upon  new  firm  formation.  

Further,  while  the  NETS  is  an  invaluable  tool  for  studying  firm  behavior  over   time,  future  studies  within  this  subject  area  could  do  well  to  compare  this  historic   data  against  self-­‐reported  behavioral  data  for  new  firms  over  the  same  time  horizon.   The  ability  to  compare  how  new  firms  report  their  formation  and  location  decisions   against   the   behavior   documented   within   NETS   would   undoubtedly   provide   rich   insight  into  the  needs,  choices,  and  socio-­‐economic  factors  important  to  new  firms   and  ultimately,  endogenous  economic  growth.  

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