Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
The Annals of Regional Science
Erschienen in: The Annals of Regional Science 3/2014

01.11.2014 | Original Paper

Does rural broadband impact jobs and income? Evidence from spatial and first-differenced regressions

verfasst von: Brian Whitacre, Roberto Gallardo, Sharon Strover

Erschienen in: The Annals of Regional Science | Ausgabe 3/2014

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In order to better understand the association between broadband and jobs/income in non-metropolitan counties, this study conducts spatial and first-differenced regressions using recent data from the Federal Communications Commission and the National Broadband Map. The relationships between broadband adoption/availability and jobs/income in rural areas are analyzed after controlling for a host of potentially influential variables such as age, race, educational attainment, transportation infrastructure, and the presence of natural amenities. Results from spatial error models using 2011 data provide evidence that high levels of broadband adoption in non-metro counties are positively related to the number of firms and total employees in those counties. The first-differenced regressions use data from 2008 and 2011 to suggest that increases in broadband adoption levels are associated with increases in median household income and the percentage of non-farm proprietors in non-metro counties. Interestingly, simply obtaining increases in broadband availability (not adoption) over this time has no statistical impact on either jobs or income.
Vorheriger Artikel Homicides, exchange rates, and northern border retail activity in Mexico
Nächster Artikel Agglomeration economies and firm R&D efforts: an analysis of China’s electronics and telecommunications industries

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
The FCC’s definition of broadband has changed over time. Historically, the definition has been 200 kilobits of data transfer per second (kbps) in at least 1 direction. The most recent (2010) definition is 4 megabits (mbps) download and 1 mbps upload. This report incorporates various thresholds, depending on the data used for analysis.
 
2
We recognize the difference between rural/urban (defined at the community level) and metro/non-metro (defined at the county level). Our data are county oriented, so we generally speak in terms of metro/micro/non-core; however, we still use the term “rural” to connote a lack of population density.
 
3
Initially, 3,109 counties were included, but Virginia independent cities were meshed with the counties where they reside to ultimately come up with 3,073.
 
4
The FCC used this speed (768 kbps down, 200 kbps up) at one point as a definition for broadband, and it is also used by the Broadband Technology Opportunities Program (BTOP) for reporting purposes. The current broadband definition (enacted in 2010) from the FCC is 4 mbps download and 1 mbps upload.
 
5
The FCC report notes that “...we have concerns that providers are reporting services as meeting the broadband speed benchmark when they likely do not. ... although mobile networks deployed as of June 30, 2010, may be capable of delivering peak speeds of 3 Mbps/768 kpbs or more in some circumstances, the conditions under which these peak speeds could actually occur are rare.” (FCC 2012, pp. 25–26).
 
6
The highest level of broadband availability is where \({<}2\,\%\) of the county’s population lacks access to wired broadband.
 
7
Multiple spatial weights matrices were tested before settling for the queen first order (including queen second order as well as rook first and second order).
 
8
We note that the aggregate SARMA model can test for the inclusion of both spatial autocorrelation and spatial heterogeneity. However, the spatial structure of these models is complex and is more difficult to interpret than individual spatial error or spatial lag parameters. The focus of this paper is on the broadband component, and as such the easier-to-interpret SEM specification was chosen.
 
9
The Local Moran’s I maps displayed in “Appendix” are compiled from a spatial weight matrix using 5 nearest neighbors, mitigating any potential geometric errors that may exist in the continental shapefile. Maps using a queen’s contiguity matrix had similar quantitative and qualitative results.
 
10
Kolko (2012) contains a useful discussion of how the relationship between broadband and employment could vary by location—and how it could hypothetically have a negative impact as technology is used as a substitute for labor.
 
11
Recall that a 1-unit increase in broadband adoption corresponds to a roughly 20 % increase in county household adoption rates due to the categorical nature of the FCC data.
 
12
The FCC data do contain information on the number of residential providers in a county, though it is not as detailed as the NBM data. For this analysis, we use FCC provider data, since the NBM data were not available until 2010.
 
Literatur
Allison P (1990) Change scores as dependent variables in regression analysis. Sociol Methodol 20:93–114CrossRef
Anselin L (1988) Spatial econometrics: methods and models. Kluwer Academic Publishers, Dordrecht
Anselin L (2003) Spatial externalities, spatial multipliers, and spatial econometrics. Int Region Sci Rev 26(2):153–166CrossRef
Anselin L, Bera AK, Raymond F, Yoon MJ (1996) Simple diagnostic tests for spatial dependence. Reg Sci Urb Econ 26:77–104CrossRef
Chi G (2010) The impacts of highway expansion on population change: an integrated spatial approach. Rural Sociol 75(1):58–89CrossRef
Czernich N, Falck O, Kretschmer T, Woessmann L (2011) Broadband infrastructure and economic growth. Econ J 121:505–532CrossRef
Ferguson M, Ali K, Olfert M, Partridge M (2007) Voting with their feet: jobs versus amenities. Growth Change 38(1):77–110CrossRef
Ford G (2011) Challenges in using the National Broadband Map’s data. Phoenix Center Policy Bull 27:1–21
Galloway L (2007) Can broadband access rescue the rural economy? J Small Bus Enterp Dev 14(4):641–653CrossRef
Goetz S, Fleming D, Rupasingha A (2012) The economic impacts of self-employment. J Agric Appl Econ 44(3):315–321
Goldfarb A, Prince J (2008) Internet adoption and usage patterns are different: implications for the digital divide. Inf Econ Policy 20(1):2–15CrossRef
Grubesic T (2012) The U.S. National Broadband Map: data limitations and implications. Telecommun Policy 36:113–126CrossRef
Holt L, Jamison M (2009) Broadband and contributions to economic growth: lessons from the US experience. Telecommun Policy 33:575–581CrossRef
Kandilov I, Renkow M (2010) Infrastructure investment and rural economic development: an evaluation of USDA’s broadband loan program. Growth Change 41(2):165–191CrossRef
Kolko J (2012) Broadband and local growth. J Urb Econ 71(1):100–113CrossRef
LaRose R, Strover S, Gregg J, Straubhaar J (2011) The impact of rural broadband development: lessons from a natural field experiment. Gov Inf Q 28:91–100CrossRef
Mack E, Anselin L, Grubesic T (2011) The importance of broadband provision to knowledge intensive firm location. Reg Sci Policy Pract 3(1):17–35CrossRef
Mack E, Grubesic T (2009) Broadband provision and firm location: an exploratory data analysis. Tijdschrift voor Economische en Sociale Geografie 100(3):298–315CrossRef
Malecki EJ (2003) Digital development in rural areas: potentials and pitfalls. J Rural Stud 19(2):201–214CrossRef
Mayo J, Wallsten S (2011) From network externalities to broadband growth externalities: a bridge not yet built. Rev Ind Organ 38(2):173–190CrossRef
McGranahan D, Wojan T, Lambert D (2011) The rural growth trifecta: outdoor amenities, creative class and entrepreneurial context. J Econ Geogr 11:529–557CrossRef
Mills B, Whitacre B (2003) Understanding the metro-non-metro digital divide. Growth Change 34(2): 219–243
Parker EB (2000) Closing the digital divide in rural America. Telecommun Policy 24:281–290CrossRef
Sobel R, King K (2008) Does school choice increase the rate of youth entrepreneurship? Econ Educ Rev 27(4):429–438CrossRef
Stephens H, Partridge M (2011) Do entrepreneurs enhance economic growth in lagging regions? Growth Change 42:431–465CrossRef
Strover S (2001) Rural Internet connectivity. Telecommun Policy 25:331–347CrossRef
Voss PR, Long DD, Hammer RB, Friedman S (2006) County child poverty rates in the US: a spatial regression approach. Popul Res Policy Rev 25(4):369–391CrossRef
Whitacre B, Mills B (2007) Infrastructure and the rural–urban divide in high-speed residential internet access. Int Reg Sci Rev 30(3):249–273CrossRef
Winship C, Morgan S (1999) The estimation of causal effects from observational data. Annu Rev Sociol 25:659–707CrossRef
Wu J, Gopinath M (2008) What causes spatial variations in economic development in the United States? Am J Agric Econ 90(2):392–408CrossRef
Metadaten
Titel
Does rural broadband impact jobs and income? Evidence from spatial and first-differenced regressions
verfasst von
Brian Whitacre
Roberto Gallardo
Sharon Strover
Publikationsdatum
01.11.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
The Annals of Regional Science / Ausgabe 3/2014
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI
https://doi.org/10.1007/s00168-014-0637-x

Weitere Artikel der Ausgabe 3/2014

The Annals of Regional Science 3/2014 Zur Ausgabe

Original Paper

Homicides, exchange rates, and northern border retail activity in Mexico

Original Paper

Land use and rent gradients with a monopoly vendor and two central business districts

Original Paper

Firm entry in the Swedish wholesale trade sector: Does market definition matter?

Original Paper

Okun’s law and urban spillovers in US unemployment

Original Paper

Sectoral productivity gains in two regional economies: key sectors from a supply-side perspective

Original Paper

Agglomeration economies and firm R&D efforts: an analysis of China’s electronics and telecommunications industries