So, now you know how to use the Economic Opportunity Maps, but not sure how to discuss them with community stakeholders? Check out our discussion guide here: https://communities.tamu.edu/files/2021/01/Discussion-Guide.pdf
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/.
Our team of researchers from across the country continues to update the Economic Opportunity Maps to improve their accuracy and to add more industries. Our research team include faculty from Texas A&M, Iowa State University, University of Wyoming, and Michigan State University.
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/
https://www.energizingentrepreneurs.org/ is a great public resource and I encourage you to check out their website.
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!
My Economic Opportunity Maps project is entering its testing phase!
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.
The expansion of ethnic minorities evokes policy debate about their impact on the local economy, driving a need to measure their effects. We employ the confidential US Census data to investigate drivers of local economic performance with emphasis on the role of Latino-owned businesses (LOB) on convergence. The model also includes a number of controls. The model produces direct, indirect, and total impact estimates, and expected values for the non-LOB controls. The estimated total impact of LOB employment on county-level average annual growth rates is significant and positive, but a rurality interaction carries the opposite sign, such that the total impact in rural areas is negative.
Read the full article here: https://link.springer.com/article/10.1007/s00168-019-00942-x
Access to financial capital is vital for the sustainability of the local business sector in metropolitan and nonmetropolitan communities. Recent research on the restructuring of the financial industry from local owned banks to interstate conglomerates has raised questions about the impact on rural economies. In this paper, we begin our exploration of the Market Concentration Hypothesis and the Local Bank Hypothesis. The former proposes that there is a negative relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a positive effect on business deaths, while that latter proposes that there is a positive relationship between the percent of banks that are locally owned in the local economy and the rate of business births and continuations, and a negative effect on business deaths. To examine these hypotheses, we examine the impact of bank ownership concentration (percent of banks that are locally owned in a commuting zone) on business establishment births and deaths in metropolitan, micropolitan and non-core rural commuting zones. We employ panel regression models for the 1980-2010 time frame, demonstrating robustness to several specifications and spatial spillover effects. We find that local bank concentration is positively related to business dynamism in rural commuting zones, providing support to the importance of relational lending in rural areas, while finding support for the importance of market concentration in urban areas. The implications of this research are important for rural sociology, regional economics, and finance.
Read more here: https://ideas.repec.org/p/cen/wpaper/18-34.html
This article uses 127,000 observations from three confidential Census microdata sets at theindividual firm and establishment level to investigate Latino-owned business survival. The merged microdataallows us to control for a wide array of personal, business, and regional characteristics. The analysis is basedon hazard model. Relative to base categories, we find the following decrease in the odds of survival: Latina-owned, Puerto Rican owned, and selling to the federal government. Owner education and low barrier sectorshave no effect, while start-up from personal savings increase the odds by 4 percent. The findings informways to expand regional economies through businesses operated by Latinos.
Read more here: https://rrs.scholasticahq.com/article/7933-factors-associated-with-latino-owned-business-survival-in-the-united-states
Here is some new research authored by me. The article uses over 100,000 observations from limited-access and nationally representative US Census Bureau microdata sets to test determinants of employment growth among Latino-owned businesses (LOBs) in the Unites States. We draw variables from prior studies on determinants business growth in the general population and uniquely apply them to LOB using the robust data. Specifically, we examine the impact of numerous business owner, business, and regional characteristics on employment growth. We include industry and state-level fixed effects and test the robustness of results to various employment growth timespans. Some findings include (1) Latina-owned businesses grow faster than LOB, (2) formal education has a positive effect on employment growth and this effect is larger with education level and time, (3) Puerto Rican-owned businesses grow 2 percent slower than Mexican-owned establishments, (4) having multiple establishments reduces employment growth, (5) relying on personal savings for start-up capital impedes growth, and (6) nonmetro adjacency has a significant and negative effect, while population density does not. Our findings show that LOB may grow differently than other businesses and help advance the understanding of factors related to success of LOB. Implementing straightforward and low-cost policies aimed at better support for LOB could help bolster regional growth.
Read more at: https://doi.org/10.1177%2F0160017619826278
Growth of the U.S. Latino population translates into policy interest of how business owner, firm, and local characteristics may be different for Latinos. To explore ethnicity and business ownership, this study merges restricted-access data from 11 million businesses. Multinomial logistic regression estimates how characteristics associate with the probability of the business being Latino-owned relative to White-owned, Black-owned, or Asian-owned. There are differences in the source and amount of start-up funds, gender, and the sector of the business. The differences depend on the group to which Latinos are being compared; for example, manufacturing firms are less likely to be Latino owned than White owned, but more likely to be Latino owned than Black owned. An exception is college education and rurality; Latino owners are consistently less likely to be college educated and more likely to locate in rural areas than the other ethnic minorities. The results should be helpful to groups attempting to improve Latino business outcomes.
To read more, read the full article here: http://journals.sagepub.com/doi/full/10.1177/0891242418785466