Associate Professor, University of Hawaiʻi at Mānoa

Steven Bond-Smith

I am the Associate Director and an Associate Professor at the University of Hawaiʻi Economic Research Organization (UHERO). I am a co-editor for the journal Spatial Economic Analysis and a Fellow at The Productivity Institute (UK).

My research is about why economic outcomes differ across places, what that means for productivity and growth, and how it implies locally tailored policy responses. Recent work models how working from home reshapes urban systems, how AI affects cities of different sizes, and how careful policy design can reveal specific local issues and solutions. For Hawaiʻi I work on economic development and diversification: why the economy has grown slowly, where it could realistically diversify, and what policy can do about it.

Beyond scholarship, I contribute to policy development and economic discourse. I serve on Hawaiʻi's State Planning Act Task Force, the Tourism and Gaming Working Group, the Oʻahu Workforce Development Board, and the UK Department for Transport's Shadow Joint Analysis Development Panel. My comments regularly appear in local, national, and international media, including The Wall Street Journal, The New York Times, the Associated Press, Slate, Civil Beat, Hawaiʻi Public Radio, and the Honolulu Star-Advertiser.

Steven Bond-Smith standing on a hillside above Honolulu, with Diamond Head and the ocean behind him
Honolulu, Hawaiʻi

What I work on

Why do places differ, and why do some fall behind?

Distance, location, and scale play a critical role. If economic models capture how those factors operate, policy can be tailored to local characteristics.

The question came from growing up in Aotearoa New Zealand, where I became convinced that geography was the primary explanation for the country's economic outcomes, and I wanted to find solutions. It continued to motivate my work in Western Australia and now Hawaiʻi.

  1. 01

    How does location affect growth?

    Ideas spread more easily between people and firms that are close together. So where a firm locates changes how fast it can innovate. And once growth theory accounts for location, it gives different answers for different places.

    Related variety inside a growth model.

    I built a model that links knowledge spillovers between related technologies to mainstream urban economics, without relying on scale assumptions. In the model, clusters can form in the periphery as well as the core.

    Journal of Economic Geography, 2020

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  2. 02

    How does scale affect growth (or not)?

    Growth theory relies on increasing returns to scale, and taken literally that means bigger economies grow faster. The evidence says they don't.

    Agglomeration without scale effects.

    I combine agglomeration economies with endogenous growth without scale effects. Productivity and growth then depend on how activity is spread across space, and the size of the economy drops out.

    Spatial Economic Analysis, 2024

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  3. 03

    Why do prices matter when comparing places?

    The same income buys less in an expensive place. Compare places without adjusting for prices and a high cost of living looks like a high standard of living.

    A price index for US cities back to 1913.

    I built a regional price index from the Consumer Price Index. Cities can then be compared at the same prices over long periods, with their real advantages separated from a higher cost of living.

    Urban Studies, 2026

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  4. 04

    How does working from home affect different types of places?

    Working from home turns commuting into a choice. The benefits are biggest in large cities, and smaller cities nearby fall into their shadow.

    A work-from-home shadow effect.

    I treat how often people commute as a choice. Working from home then benefits large cities most, at the expense of smaller cities nearby.

    Journal of Regional Science, 2025

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  5. 05

    What can we do about it?

    If places differ for different reasons, policy should differ too. I work on matching policies to places, and on where Hawaiʻi could realistically diversify.

    Assigning policy to places by the data.

    Which places get which policy is often arbitrary or political. I use threshold models so the data groups places into policy regimes. Places close to a threshold can then be targeted, since a small change would put them in a different regime.

    Cities, 2024

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