Johnson Economics

Johnson Economics developed a predictive redevelopment model that translated marginal shifts in key development variables into a geographically specific predicted development/redevelopment pattern.  The model was designed to qualitatively evaluate the impact of streetcar improvements on development patterns, allowing for a comparison of alternative alignments. The model was based on a series of simultaneous pro forma assessments of the highest and best use at the parcel level.  Outputs include aggregated development activity by type, physical form, and resulting impact on the value of improvements. The model further allows for easy testing of sensitivities to critical assumptions. The report was funded by a grant from the Federal Transit Administration (FTA).

Johnson Economics worked with the City of Eugene, Oregon to develop a predictive model of development and redevelopment activity based on current and anticipated market conditions. The model evaluated commercial, industrial, and residential development patterns, translating key market inputs and regulatory controls into associated conclusions concerning the highest and best use and predicted development/redevelopment forms. The work provided an assessment to inform the City by offering insights on how key districts might absorb future residential and commercial growth through development and redevelopment. The analysis provided a theoretical construct within which assumptions with respect to the nature and magnitude of future development and redevelopment activity can be generated. 

The results of this approach can be localized to specific districts and can be policy sensitive. The output included district carrying capacities and likely development patterns, with alternative scenarios developed based on a range of prospective policy interventions. 

Johnson Economics worked on a major evaluation of industrial and employment land needs within the City of Portland. Johnson Economics projected demand for specific product types on eighteen sites located throughout the metropolitan area. The assignment includes short- and long-term demand forecasts for industrial and office space, as well as forecasts over time by product type and configuration needs. As a second phase of the assignment, Johnson Economics worked with a design and engineering firm to run return on investment financials for development solutions on the eighteen sites. 

Johnson Economics developed a residential demand model for the Portland-Vancouver metropolitan area that converts projections of households by age, income, and household size into demand by ability, price point, preferred product type, and tenure. The model further disaggregates demand into psychographic characteristics based on Claritas' PRIZM clusters typologies. The model was linked to a series of prototypical residential development forms and associated financial characteristics to assess the likely market response to demand. This approach allows for a differentiation between preferred and realized demand, with the model solving for a realistic solution that may be suboptimal. 

Johnson Economics developed and utilized a predictive modeling framework to test the impact on development outcomes, employment and residential capacity, and financial implications of a change in wetland policy in the City of Portland. This analysis was followed by a similar assessment of a range of prospective alterations to the City’s tree ordinance. The work included GIS analysis of impacted parcels, pro forma modeling of multiple prototypical development forms, entitlement assessment, and the quantification of marginal impacts on development forms of various options. The output included impacts on residential and employment capacity, realized development patterns, underlying land values, the value of development outcomes, and the anticipated fiscal effects on the City.

Johnson Economics developed a Python-based predictive modeling structure for the Portland metropolitan area. The model is designed to predict the magnitude and form of likely development or redevelopment activity over an assumed time frame. The model solves for a development solution that represents the highest and best use at the parcel level under the assumptions used, as well as outputting an associated residual property value. The DSP model currently incorporates 44 prototypical programs covering a range of land use types and development forms. Key variables such as entitlements, achievable pricing, construction costs, return parameters, and other fundamental assumptions predict a highest and best use development form alongside secondary options. The model produces predicted rates of development and redevelopment at the parcel level, forecasting the prevailing form of this development and associated yield. The structure of the model allows for rapid testing of changes in policies and other interventions along with expected responses from the development market.

Johnson Economics was retained by METRO’s Transit Oriented Development & Centers Program to research the pricing effects of urban living infrastructure. The objectives of the projects were twofold: our team first documented if, and by how much, urban living infrastructure improves the financial feasibility of mixed-use residential development; the firm subsequently analyzed the potential of public investment in urban living infrastructure as a cost-effective strategy to catalyze the center development. The hedonic modeling evaluated a range of urban amenities hypothesized to represent critical components of an “urban experience,” adding value to an area that is realized in higher achievable pricing for residential development. Hedonic statistical modeling of 2006 home transactions proximate to various urban amenities revealed a range of price premium estimates for recent home sales, all else equal. Our study identified a substantive impact on achievable pricing associated with various tenant types.