Development and Validation of Firm Demography Model Case Study Analysis in Phoenix and Tucson Megaregion 16th TRB National Transportation Planning Applications Conference Arun Kuppam, Cambridge Systematics Srinath Ravulaparthy, Citilabs Brent Selby, Cambridge Systematics, Inc. Kyunghwi Jeon, Maricopa Association of Governments Sreevatsa Nippani, Maricopa Association of Governments Vladimir Livshits, Maricopa Association of Governments May 18, 2017

Firm Synthesis Population Evolution Model Firm Evolution Model Emigration / Immigration Aging / Mortality / Fertility Household formation / dissolution / child leaving Education / Occupation / Wages Firm Evolution Model Firm conception Firm migration Firm death Firm growth – Change in employment Technology – Productivity

Evolution of Firm Population Accurately describes evolution of firm population in space and time [Ft+1 = Ft + Bt – Dt + It – Ot] Firm population at time t Firm population at time t+1 Within migration In-migration (I) Formation or births (B) Out-migration (O) Dissolution or deaths (D) Ft Ft+1 Bt Dt It Ot

Drivers of Firm Evolution Firm internal Employment size Sales Age Standalone/headquarters Market Area Population Average household income Student enrollment by school and university Agglomeration economies Localization – number of employees within same industry Urbanization – number of employees from other types Regional indicators and transport access Miles of roadway by facility type Major hubs in the region

Evolution of Firm Population National Establishment Time Series (NETS) Database 1991 to 2012 F = S + B - D + I - O

Firm Evolution 1991 to 2012 Formation and Dissolution Rates

Model Components Firm Birth Firm Death In-migrate Out-migrate Negative binomial distribution is fitted to the data, for sampling new born Attributes of employment size and type are sampled at random from population Firm Death Binary choice model – firm is the unit of analysis determining the probability of death. One model specified by controlling for industry type Within-migration Binary choice – firm is the unit that determines probability of relocation. In-migrate Determine a fixed rate of in-migration from data Out-migrate Determine a fixed rate of out-migration from data Growth / Decline Log-linear specification of employment size Control for previous year employment to determine future Location choice MNL specification with universal utility function Control for industry type in model specification Applied to – birth, within-migration and in-migration firms

Model Validation Population Aggregates County level totals NAICS 2-digit Industry types Data sources - 2015 InfoGroup and Maricopa County Employer Database (ED) Simulation of 20% validation sample from NETS Firm evolution simulation from 2012 to 2015 Zonal employment validation Spatial distribution with simulated and observed Scatter plots by zone by sector types

Firm Synthesizer Model vs. Observed

Conclusions Firmography approach is better than assuming constant shares for forecast years (as it accounts for formation, relocation, dissolution) Simulation & validation results also confirm predictability and reliability of the Firmography framework Micro-level and zonal predictions closely resemble observed trend