BusinessReport.com

There are disasters, and then there are disasters.

Depending on which kind hits you, things will get back to normal quickly, slowly or not at all. A team of LSU researchers is trying to get a handle on why business is bouncing back in some parts of New Orleans, but not in others.

It turns out post-Katrina New Orleans presents a once-in-a-lifetime opportunity for researchers to study the impact disaster has on business in the hope of creating a theoretical model that can serve as a guide to policies that govern development. While the focus is on New Orleans, the study’s findings ideally will be useful to communities anywhere that are vulnerable to disaster.

The project is an interdisciplinary collaboration between the LSU Department of Environmental Studies and the LSU Real Estate Research Institute, part of the E.J. Ourso College of Business, and Richard Campanella, a geographer at Tulane University’s Center for Bioenvironmental Research. Several factors are at work in the complex dynamics of recovery, though something called “spatial effects” is center stage.

Kelley Pace, an LSU finance professor, director of the real estate institute and project collaborator, says spatial effects are the effect your neighbors have on your home or business.

Usually, statistics assume that an event, such as a coin toss, is independent from another event, or another coin toss. Just because you got heads the first time doesn’t mean you’ll get it the second time.

Real estate is obviously different: Good or successful properties cluster together, as do bad or unsuccessful properties. Thus, spatial effects modeling comes in handy in trying to tease out trends or make predictions.

“When we talk about anything pertaining to real estate, we’ll always have that mantra: location, location, location,” Pace says.

Judgments based on spatial effects pervade all aspects of real estate, whether it’s a house appraisal or Starbucks deciding where to plant its next 500 locations. When Blockbuster closes an old store at one intersection and opens a new one a mile away, it’s doing so based on a spatial effects model. Spatial effects are why drug stores gang up on busy intersections and developers build TNDs here and not there.

They’re also at work in the impact the tumble-down, rat infested shotgun down the street is having on your Edwardian mansion’s property values. And they’re at work in New Orleans’ gradual reawakening—it’s just that nobody’s sure how. Obviously, New Orleans’ spatial effects were significantly rearranged by Katrina, as were those of the Mississippi Gulf Coast.

Nina Lam, a professor with LSU environmental studies and one of the collaborators on the project, says data has already been collected at street level by interviewing business owners about why they decided to reopen during the “post-catastrophe uncertainty.” The interviews took place on three streets in three different neighborhoods: one upper income, one lower income and one middle income. The street-level interviews were followed up with telephone surveys. The data-collection phase is wrapping up.

“We’re trying to look at models that we can develop to look at how people make decisions—in this case the people are businesses—when you don’t know the future,” she says.

Lam says the project was given an unprecedented opportunity to collect data soon after Katrina, when a just a handful of businesses were coming back amid the desolation, which was still fresh.

In some cases, the business owners themselves weren’t sure what caused them to reopen, Lam says. But the project has accumulated plenty of good data to be analyzed and “cleaned up.” The researchers are using Global Information Systems technology to geographically situate the businesses interviewed to be able to compare different neighborhoods. They know which neighborhoods have come back, though not why. Ideally, the number-crunching phase will provide some clues about how spatial effects in different parts of the city influence business vitality.

“We just have to try to decipher what is the major point,” Lam says. “Is there some sort of generalization we can use next time around in a disaster?”

While in some cases it may be fairly obvious why businesses bounced back relatively fast in certain parts of town, gut-level judgments don’t help build theoretical models useful in predicting the impact on business of future disasters.

“The point is to try and analyze it and see if we can get something that non-obvious out of this that might be informative in terms of what will happen there as we go along—if we have something that may reveal that—or for other disasters,” Pace says.

There are different schools of thought on the smartest way to allocate recovery dollars to help businesses get back on their feet in disaster zones in general and in New Orleans in particular.

The Urban Land Institute’s recommendation for New Orleans was to write off large portions of the city and concentrate on the “working parts,” Pace says, in hopes that recovery will spread out from the fringes. Spatially, this makes sense, since it’s much easier and less costly to spur new development on the edges of economically successful areas.

Another suggested approach is egalitarian: spread the money in equal amounts to all parts of the city. Politically, this is the simplest though probably not the most cost-effective, Pace says. The middle way: investing in clusters in different parts of the city—the method Pace thinks the project’s numbers will bear out as making the most sense.

“I call that the sodding approach,” he says. “You put in little plugs of sod and you hope that it fills in everything in between after a while.”

While the project may offer some clues to the direction of New Orleans’ resurgence over the coming years, the project’s main goal is to aid in future disasters. Lam says the ultimate goal is generating better planning in terms of development: Where are good places to develop? Where are bad places?

“Everywhere in the nation is subject to natural hazard,” she says. “The matter is how do you minimize the vulnerability?”