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Agent-Based Firmographic Models: A Simulation Framework for the City of Hamilton. By Hanna Maoh and Pavlos Kanaroglou Center for Spatial Analysis (CSpA) School of Geography and Geology McMaster University Workshop on agent-based microsimulation firmographic models

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agent based firmographic models a simulation framework for the city of hamilton

Agent-Based Firmographic Models: A Simulation Framework for the City of Hamilton

By

Hanna Maoh and Pavlos Kanaroglou

Center for Spatial Analysis (CSpA)

School of Geography and Geology

McMaster University

Workshop on agent-based microsimulation firmographic models

University College London (UCL), London, July 2nd, 2005

outline
Outline
  • Introduction
  • The Demography of Firms
  • Modeling Framework
  • Study Area and Firm Micro-Data
  • Modeling Methods
  • Overview of Results
  • Future Research
research objectives
Research Objectives
  • Objective: Simulate the evolution of business establishment population between t and t +1
  • Improve upon existing methods used to model firms and jobs in conventional Land use and transportation models
  • Adopt the agent-based approach to develop an agent-based microsimulation model
  • Apply concepts from firm demography to model the evolutionary process
the demography of firms
The Demography of Firms
  • Firm demography is dedicated to the study of processes that relates to:
    • Formation of new firms (birth or entry)
    • Failure of existing firms (death or exit)
    • Migration of existing firms (local and regional)
    • Growth and decline of firms
  • It is concerned with identifying and quantifying the causes associated with firmographic processes
evolutionary process of business establishment population
Intra-urban

mobile

establishments*

In-migrated

establishments

Newly formed

establishments

+

+

Establishment

population at

time t

Establishment

population at

time t + 1

Out-migrated

establishments

Failed

establishments

Evolutionary Process of Business Establishment Population
modeling framework
Establishment population

t

Establishment population

t

Failure

submodule

Survivals

Firmographic Processes Processes Output

Newly formed & in-migrating establishments

t+1

Newly formed & in-migrating establishments

t+1

Mobility

submodule

Migrants

Location

choice

submodule

Assign a business to a site

Growth

submodule

Size of business t+1

Establishment population

t+1

Establishment population

t+1

Modeling Framework
real estate market
Real Estate Market
  • A market for industrial and commercial floor space at the parcel level drives the framework
  • This market is influenced by:
    • The firmographic events:
      • Demand for floor-space is generated by the newly formed, relocating and in-migrating establishments
      • Failure, departing current location (out-migration or intra-urban migration) free up floor space
      • Growth, decline, merging and splitting also contributes to change in floor space
    • Development and redevelopment practices influence the available floor-space
firm micro data statistics canada business register br
Firm Micro-Data: Statistics Canada Business Register (BR)
  • Maintain annual information about business establishments in Canada since 1990
  • Confidential and can only be used to conduct statistical analysis
  • Attributes: Establishment size, location (postal code and SGC), SIC code and Establishment Number (EN)
  • BR provides the life trajectory of business establishments over space and time
  • BR can be used to measure firmographic events such as: the formation, migration, location choice, failure, growth and decline of business establishments
small and medium sme size establishments
Small and Medium (SME) Size establishments
  • SME with less than 200 employees is the target of our analysis
  • Account for more than 94% of establishments in 1990, 1996 and 2002
  • Extracted population was constrained to self-owned single establishments
  • Establishments that are part of a chain were not included in the model!
  • However, the extracted sample is deemed appropriate
  • Around 80% of SME are with less than 10 employees, 93% of which are single owned establishments
slide13
Modeling Methods
  • Use discrete–time hazard duration models to explain the failure process
  • Use multinomial logit models to explain the mobility (stay, relocate or out-migrate) of business establishments
  • Use multinomial logit models to explain the location choice behavior of intra-urban mobile, newly formed and in-migrating establishments (maximum utility and Bid-rent concepts)
  • Use multivariate regression models to explain the growth/decline process of business establishments
failure of business establishments
Failure of Business Establishments
  • We follow the life trajectory of 1996 small and medium size establishments till 2002
  • We determine the duration of survival and time of failure
  • We model the process via a discrete time hazard duration model
  • Probability of failure is a function of establishment, industry, location and maco-economic factors
mobility of business establishments
Mobility of Business Establishments
  • Model the mobility status of surviving establishments between 1996 and 1997
  • We assume that each establishment is faced with the choice of either staying (S), relocating (m) or leaving the city (l)
  • The establishment is assumed to choose the alternative with the highest utility; we can exploit the random utility maximization approach to model the process
  • Utility Vnm of the MNL is a function of establishment, industry and location factors
location choice of business establishments
Location Choice of Business Establishments
  • We model the location choice of relocating, newly formed and in-migrating establishments (1996 – 1997) and (2001 – 2002)
  • Establishments are profit maximizers and will choose a location that will maximize their profit.
  • Establishments search the metropolitan area for an optimal location and will out-bid each other for that location
  • The process is modeled via a Multinomial Logit Model
  • Utility of the MNL is a function of establishment characteristics and location attributes
representation of space
Representation of Space
  • Use boundaries of developed land parcels; but postal code addresses has a one-to-many relationship with parcel

Alternatively

  • Divide the city into grid cells of 200 x 200 meters; extract grid cells that correspond to developed commercial and industrial land uses to create the set of alternative locations
general pattern of results
General Pattern of Results
  • Establishment age, size, growth, relocation history, local competition, agglomeration economies, type of industry, size of industry, economic downturn and demand for services and goods can influence the propensity of establishment failure
  • Establishment age, growth rate, size, industry type along with agglomeration economies and level of local competition can influence the mobility behaviour
  • CBD, highway and mall proximity, population density, new residential development, agglomeration economies and land use specialization as well as type of industry influence the location choice decision of establishments
future research
Future Research
  • Model implementation: Creating a synthetic list of business establishments (BE) to use as a base year population for any simulation (in the works)
  • Develop a dynamic Geodatabase data model to store, maintain and update the BE list during simulations. Utilize Unified Modeling Language (UML) as the basis for the development
  • Implement a real estate development model to predict the change in industrial and commercial floor-space (short term plan)
  • Simulate the inter-play between the local economy and urban form in Hamilton
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