In a recent article in the Journal of Planning Education and Research, Joshua Drucker of the University of Illinois at Chicago revisits the shortcomings of I-O analysis before highlighting ways analysts can enhance the technique’s accuracy. Drucker’s contribution to the field of planning is important, given the influence economic impact estimates have in influencing local decision-making regarding infrastructure investment, business attraction, and environmental review of new development, for example.
One case study Drucker provides comes from work Economic Development Research Group completed for the Fort Drum Regional Liaison Organization (FDRLO) in New York State’s North Country region over a number of years. As its name suggest, FDRLO acts as liaison between Fort Drum, a U.S. Army military reservation, and residents of the three counties that surround it. FDRLO first engaged EDR Group in 1998, when the membership organization commissioned a study of the regional economic and fiscal impacts of the military base. In 2004, EDR Group updated the study and developed an easy-to-use spreadsheet model that FDRLO staff could use to estimate impacts; another update in 2008 followed this work.
In his article, Drucker explains how, four years ago, FDRLO sought to construct a new, enhanced model that would address the shortcomings inherent in past I-O studies. EDR Group instead encouraged the organization to update its existing model with the latest economic data available at the time. EDR Group demonstrated the constraints faced by both I-O models and enhanced I-O models when estimating impacts at a regional level and, through doing so, convinced FDRLO that periodically updating the existing model’s underlying data would provide as much, if not more, accuracy than building an enhanced model. In addition, EDR Group stressed the importance of other model inputs to increasing the accuracy and credibility of future economic impact estimates. These other inputs included spending related to military operations at the base, obtained annually or even quarterly from the commander’s office, as well as information regarding military spouses and dependents who make purchases and pay taxes throughout the community, but also generate government expenditures by attending local schools, for example.
The decision of when to conduct I-O analysis and when to employ enhanced techniques such as computable general equilibrium modeling is critically important, and is something that EDR Group routinely educates its clients on. In general terms, this decision often comes down to the magnitude of an economic “shock,” or change in an industry’s (or group of industries’) output or employment. Relatively large shocks have the potential to disrupt an economy to the point at which prices and costs change, and other industries must adapt. When this happens, enhanced economic impact models are most appropriate.
One crude but helpful way of ascertaining the relative magnitude of a shock is by considering its geographic scope—a single company relocating to a single region, for example, is unlikely to affect prices throughout the country or even throughout its host state or region. In this case, I-O models areappropriate and credible when applied correctly (see past blog posts for more on this subject). In a more concrete example, researchers from the U.S. Department of Agriculture and two national laboratories published an article in a 2012 issue of Energy Policy that found that actual county-level economic impacts realized from wind energy development were consistent with those estimated by I-O models. In conclusion, the authors state that “...despite a number of known limitations to the standard application of input–output models to estimating economic development impacts, our results [using enhanced econometric methods to consider wind energy development at the county or local level] are of a similar general magnitude to input–output derived estimated impacts.”