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

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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

Processus 2nd International Colloquium on the Behavioral Foundation of Integrated Land use and Transportation Models: Frameworks, Models and Applications

University of Toronto, ON, June 12 – 15h, 2005


Outline
Outline the City of Hamilton

  • Introduction

  • The Demography of Firms

  • Modeling Framework

  • Study Area and Firm Micro-Data

  • Modeling Methods

  • Overview of Results

  • Future Research

  • Acknowledgments


Introduction
Introduction the City of Hamilton

  • Assess the sustainable of cities via Integrated Land use and Transportation Models

  • The agent-based Approach

  • The change in firm location is an important aspect when developing IUMS

  • Concepts from firm demography to model the evolution of business establishment population


The demography of firms
The Demography of Firms the City of Hamilton

  • 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 the City of Hamilton

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 the City of Hamilton

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 the City of Hamilton

  • 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: the City of HamiltonStatistics 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 the City of Hamilton

  • 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


Modeling Methods the City of Hamilton

  • 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 the City of Hamilton

  • 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 the City of Hamilton

  • 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 the City of Hamilton

  • 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 the City of Hamilton

  • 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 the City of Hamilton

  • 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 the City of Hamilton

  • Model implementation: Creating a synthetic list of business establishments (BE) to use as a base year population for any simulation

  • 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

  • Simulate the inter-play between the local economy and urban form in Hamilton


Acknowledgments
Acknowledgments the City of Hamilton

  • We would like to thank Statistics Canada for supporting this research through their (2003 – 2004) Statistics Canada PhD Research Stipend program.

  • We would like to John Baldwin, Mark Brown and Desmond Beckstead for providing office space and access to the BR data. Also I am thankful to them for their useful discussions, input and assistance.

  • We are grateful to SSHRC for financial support through a Standard Research Grant and a SSHRC doctoral fellowship


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