Economic Scenarios and Development Patterns in the Baltimore‐Washington Region
Authors: Nikhil Kaza, Gerrit Knaap, and Kelly Clifton (2009)
Report
Synopsis: This paper illustrates the use of scenarios in land use, environmental and transportation planning in and around the State of Maryland. Different assumptions about futures result in different patterns of growth with differential impacts on particular sectors of the economy. Such different patterns require formulation of contingent plans as well as robust plans. In this paper, we illustrate the quantitative modelling methodology of loosely linked economic demographic, transportation and other impact assessment models in constructing two scenarios; one of which represented the best possible guess about the continuation of the future and other involving rapid changes to energy prices and Federal spending. We illustrate the spatial development outcomes and the transportation and environmental plans that are necessary to deal with these different outcomes. Further, we illustrate that different planned actions have different efficacies in different futures and thus multiple futures should be carefully considered. Finally, we illustrate the notions of contingent plans and robust plans.
Authors: Nikhil Kaza, Gerrit Knaap, and Douglas Meade (2008)
Report
Synopsis: This paper illustrates the application of various forecasting methodologies in constructing multiple scenarios for the state of Maryland using Long term Inter Industry Forecasting Tool that tracks inter-industry outputs at a macro scale, and State Employment Model that disaggregates these outputs to the states. We then use accessibility, land availability and observed relationships of employment categories to distribute employment at a county level. In this paper, we identify the possible advantages and pitfalls of using large scale economic models to drive employment forecasts at the county level. This framework allows for simulating the implications of macroeconomic scenarios such as changes in exchange rates and unemployment levels, as well as local land use and transportation policies on local employment and demographics. In particular, we focus on two scenarios as test cases both of which involve very different ideas about how future might unfold and their effects on land use and transportation policy prescriptions. One of the scenarios involves, among others, rises in health care spending over the next few years and the other involves increases in energy prices. As will be shown, they have different spatial effects and suggest different policy actions on the part of various governments.
Authors: Nikhil Kaza, Gerrit Knaap, and Kelly Clifton (2009)
Report
Synopsis: This paper illustrates the use of scenarios in land use, environmental and transportation planning in and around the State of Maryland. Different assumptions about futures result in different patterns of growth with differential impacts on particular sectors of the economy. Such different patterns require formulation of contingent plans as well as robust plans. In this paper, we illustrate the quantitative modelling methodology of loosely linked economic demographic, transportation and other impact assessment models in constructing two scenarios; one of which represented the best possible guess about the continuation of the future and other involving rapid changes to energy prices and Federal spending. We illustrate the spatial development outcomes and the transportation and environmental plans that are necessary to deal with these different outcomes. Further, we illustrate that different planned actions have different efficacies in different futures and thus multiple futures should be carefully considered. Finally, we illustrate the notions of contingent plans and robust plans.
Exploring Alternative Futures Using a Spatially Explicit Econometric Model
Authors: Nikhil Kaza, Gerrit Knaap, and Douglas Meade (2008)
Report
Synopsis: This paper illustrates the application of various forecasting methodologies in constructing multiple scenarios for the state of Maryland using Long term Inter Industry Forecasting Tool that tracks inter-industry outputs at a macro scale, and State Employment Model that disaggregates these outputs to the states. We then use accessibility, land availability and observed relationships of employment categories to distribute employment at a county level. In this paper, we identify the possible advantages and pitfalls of using large scale economic models to drive employment forecasts at the county level. This framework allows for simulating the implications of macroeconomic scenarios such as changes in exchange rates and unemployment levels, as well as local land use and transportation policies on local employment and demographics. In particular, we focus on two scenarios as test cases both of which involve very different ideas about how future might unfold and their effects on land use and transportation policy prescriptions. One of the scenarios involves, among others, rises in health care spending over the next few years and the other involves increases in energy prices. As will be shown, they have different spatial effects and suggest different policy actions on the part of various governments.