Trenton’s median income is in the bottom 9% of communities in New Jersey. Our schools are in the bottom 2% and our crime is in the bottom 1%. Real median income (adjusted for inflation) in Trenton actually declined 6.7% during the ‘90s while New Jersey’s median income rose 4%.

Because our income level and resulting tax base is so low we receive subsidies from the rest of the state most notably Abbott funding. To be a sustainable community we need to pay our own way which means our income must be in the 50^th percentile, roughly that of Hamilton.

One can argue though that an urban city in New Jersey with “average” income would be a great place to live.

Making revitalization decisions isn’t easy

Trenton has been trying to revitalize for many years but with little success, therefore its time to realize that if revitalization were easy everybody could do it.

Trenton is impacted by many city, state and federal policies such as subsidized housing, job training, Abbot funding and public park development. Other policies on policing, sanitation and marketing are built into the city budget. Some policy decisions have greater impact than others and some may even have negative impacts. Understanding these effects and how they interact is hard to do and it isn’t enough to be satisfied with a one or even a 5 year time horizon.

Equally important is the need to be clear on exactly how to measure positive and negative impact. Four measurable statistics come to mind in considering Trenton’s health: median income, school success, crime index and mortality rate. Of the four, median income is the most important as it is a strong predictor of the other three.

Public housing is an example of the need for modeling

Many Trentonians have read my paper on subsidized housing and have looked at the visual representation of a city model I’ve provided. Previous urban dynamics models have shown spending on subsidized housing to be one of the main culprits in a city’s continued downward spiral to a low level of equilibrium (as defined by mean income).

I believe that public housing is an important example of how modeling could have improved policy making. When urban dynamics models were first developed in the late ‘60s they predicted the failure of public housing. Public housing sounded like a good idea at the time but the long term effects were never understood.

Trenton can become more confident in its revitalization efforts

We can start by understanding which public policy measures will actually have a positive long term effect on Trenton’s revitalization. We can carefully prove the effectiveness of a policy before taking the drastic step of implementation.

A more scientific method of thinking is needed

A model that links policies, including city budgets, to measurable outcomes can help the administration and city council make better policy decisions. Even the representation of the potential impact of policy decisions shown in a dynamic model can help clarify thinking on our issues.

Sample Urban Dynamics model

Urban Dynamics models have been built before

The science of understanding complex systems is called “system dynamics” and when applied to cities is called “urban dynamics“. Businesses use system dynamics to guide their strategies. The models include feedback loops that show systems to reach an equilibrium over time.

System dynamics was originally developed by Dr. Jay Forrester at MIT and later improved by Dr. Alan Graham also from MIT and a former colleague of mine.

Urban Dynamics describes cities as complex systems of causes and effects whose relationships are represented by mathematical models. Using a dynamic model, policy makers investigate which variables to affect (e.g. spending on housing, crime, marketing) and how the effects will ripple over time?

We can use systems thinking to guide us

An urban dynamics model forces the policy maker to mathematically express the relation between city programs and outcomes. For instance how many new businesses will be attracted by a 50% increase in the city’s marketing budget? How many new jobs will those businesses create? How many of them will go to existing Trentonians and how many people will relocate to Trenton? How much in taxes will those businesses pay? How much in city services will they require? What effect will an abatement have on all of the above? Will any of this actually have an impact on median income 10 years out?

As you might imagine, knowing the answers to such questions would be helpful.

Every policy we implement has direct and indirect effects. In addition these effects occur with some time delay. Also, impacts can be compounded and can sometimes counteract each other. Modeling to uncover these effects goes a long way towards highlighting the unintended consequences of a policy.

Such a model provides a good way of testing policies before they are implemented. Auto engineers don’t build new cars without modeling them in a computer first. Drug companies don’t put new drugs on the market without clinical trials. Even cereal companies spend hundreds of thousands of dollars testing new brands. Shouldn’t governments test new ideas before trying them out of live humans.

Building a real urban dynamics model requires real work and insight

How much money has been spent in Trenton over the years and on what broad categories? What are the important things to measure: Housing? Number of businesses? Population? Income distribution? The city’s attractiveness to businesses and residents? The timing delay between policy and impact? The interrelationships between these things?

After collecting this information one could create model using either Excel or one of the various dynamic modeling software packages on the market. Finally we will find a way to introduce this concept into the city politic. It is important that key stakeholders go on this journey with us in order to build trust in the process.

A Trenton dynamics model can be a guide for all American Cities

In all fairness to our politicians and press, it is difficult to consider long term effects especially when they have short term negative consequences like a shortage of housing. But part of breaking the cycle is upgrading our knowledge of how the city behaves. Only through a better understanding of the system can we make informed policy decisions. Wouldn’t a debate over policy be much more constructive when the arguments focused on numbers and facts.