The Article is titled “Estimating determinants of healthcare establishment locations with restricted federal administrative data. ” The abstract is below. This research contributes to our Economic Opportunity Mapping Project, in which you can interactively select different counties, regions, or states to see the types of business establishments that are currently there compared to those that an economic model predicts might be successful there.

Abstract

We model the locational determinants of nine categories of healthcare services in the contiguous United States using restricted access federal establishment data. These data enable close examination of rural health services, which are subject to suppression in publicly published data sources. After reviewing differences in public and unsuppressed restricted data and testing underlying data generation processes for each healthcare industry, including the Poisson, negative binomial, and their zero‐inflated counterparts, we estimate marginal effects for four categories of independent variables: place‐based factors, financial access, characteristics of population, and industry interdependencies. Findings show establishments are less likely to be found with high concentrations of Medicare and Medicaid recipients, while agglomerations are associated with more establishments. Nonemployer establishments serve a broader spectrum of people, but the rural poor still experience less access to health care.

We’ll walk you through questions that you should always ask when using secondary data, as well as discussion questions specific to the maps.

Check out the maps here: https://communities.tamu.edu/economic-opportunity-maps/.

An Economic Opportunity Map (EOM) is a unique way for individuals to interactively explore business opportunities in their county across various industries.

This document guides readers through the mapping tool itself as well as elements of each EOM. We will begin by considering the different types of industries represented across these EOMs followed by a more detailed look at the EOM interactive mapping dashboard. Finally, we will point out some additional tools to assist users in interpretations and guiding discussion.

The Economic Opportunity Maps for counties all over the continental U.S. can be found here: https://communities.tamu.edu/economic-opportunity-maps/.

We’re getting a lot of questions on their use and how to interpret them, so we put together a Frequently Asked Questions document (FAQ, https://communities.tamu.edu/files/2021/01/FAQ.pdf). Check it out and as always feel free to email me with any questions, ccarpenter@tamu.edu!

We find a negative association between the ability to complete financial calculations and age, with an even more negative relationship after retirement. This may suggest limits to career extension, or alternatively, that extending some types of careers could provide cognitive benefits.

Regardless, the implication that staying active as we age is clear!

You can see the full article here: https://onlinelibrary.wiley.com/doi/10.1111/joca.12353

Check out the new updates at either of the links below!

https://communities.tamu.edu/economic-opportunity-maps/

https://www.canr.msu.edu/economic_development/economic-opportunity-maps/

One of my favorite of their works from this year is titled “Funding Entrepreneurial Ecosystem Building” and is available here: https://files.constantcontact.com/c84c5a8b001/7c26622a-16dd-40c5-9f09-c2a80b296ba9.pdf

It has specific suggestions for funding and building the entrepreneurial ecosystem in your community! Check it out!

See the embedded and interactive maps here: https://communities.tamu.edu/economic-opportunity-maps/

The project was supported by the Agricultural and Food Research Initiative Competitive Program of the USDA National Institute of Food and Agriculture (NIFA), award number 2017-67023-26242.

See the embedded and interactive maps here: https://communities.tamu.edu/economic-opportunity-maps/

The project was supported by the Agricultural and Food Research Initiative Competitive Program of the USDA National Institute of Food and Agriculture (NIFA), award number 2017-67023-26242.