Skip to main content

Regional Science Research and the Practice of Regional Economic Forecasting: Less Is Not More

  • Chapter
  • First Online:
Regional Research Frontiers - Vol. 1

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

Accurately forecasting regional economies for periods beyond a few months requires more than simple trend extrapolation. The forces that affect regional economies continually alter recent trends in the data. In addition, consumers of regional forecasts seek an understanding of the forces that underlie recent trends, which can be used in making sound policy or financial decisions. This essay argues for a greater role for research in forecasting regional economies. The central thesis is that current regional forecasting efforts need to be improved and supplemented with insights from regional science research. Major research areas of focus include dependence between sectors, dependence between regions, identifying demand from supply, labor market closures, incorporating a housing sector, the importance of occupational structure, benchmarking regional forecasts, sub-state forecasting and analysis, and industry trend analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Rickman and Miller (2002) also compared the accuracy of using input-output information in mixed estimation against using the information to specify which sectors to use in other sector forecasting equations in Bayesian Model Averaging. Rey (1998) discusses strategies for integrating input-output information into regional econometric models.

  2. 2.

    See Fallah et al. (2014) for a review of the studies and for additional evidence.

References

  • Bartik TJ (2012) The future of state and local economic development policy: what research is needed. Growth Chang 43(4):545–562

    Article  Google Scholar 

  • Beaumont PM (1990) Supply and demand interaction in integrated econometric input-output models. Int Reg Sci Rev 13:167–181

    Article  Google Scholar 

  • Bell FW (1967) An econometric forecasting model of a region. J Reg Sci 7(2):109–128

    Article  Google Scholar 

  • Brown JP (2014) Production of natural gas from shale in local economies: a resource curse or blessing? Fed Reserve Bank Kansas City Econ Rev 99(1):5–33

    Google Scholar 

  • Chang SW, Coulson NE (2001) Sources of sectoral employment fluctuations in central cities and suburbs: evidence from four eastern U.S. cities. J Urban Econ 49(2):199–218

    Article  Google Scholar 

  • Duranton G (2011) California dreamin’: the feeble case for cluster policies. Rev Econ Anal 3(1):3–45

    Google Scholar 

  • Fallah B, Partridge MD, Rickman DS (2014) Geography and high-tech employment growth in U.S. counties. J Econ Geogr 14(4):683–720

    Article  Google Scholar 

  • Gabriel SA, Mattey JP, Wascher WL (2003) Compensating differentials and evolution in the quality-of-life among U.S. states. Reg Sci Urban Econ 33:619–643

    Article  Google Scholar 

  • Glaeser EL, Tobio K (2008) The rise of the Sunbelt. South Econ J 74(3):610–643

    Google Scholar 

  • Glaeser EL, Kolko J, Saiz A (2001) Consumer city. J Econ Geogr 1:27–50

    Article  Google Scholar 

  • Gyourko J, Saiz A, Summers A (2008) A new measure of the local regulatory environment for housing markets: the Wharton residential land use regulatory index. Urban Stud 45(3):693–729

    Article  Google Scholar 

  • Jacobs AJ (2010) Collaborative regionalism and foreign direct investment: the case of the southeast automotive core and the ‘new domestics’. Econ Dev Q 26(3):199–219

    Google Scholar 

  • Keating JW (1992) Structural approaches to vector autoregressions. Fed Reserve Bank St Louis Rev 74(September/October):37–57

    Google Scholar 

  • Lee S (2010) Ability sorting and consumer city. J Urban Econ 68:20–33

    Article  Google Scholar 

  • LeSage JP, Krivelyova A (1999) A spatial prior for Bayesian vector autoregressive models. J Reg Sci 39(2):297–317

    Article  Google Scholar 

  • LeSage JP, Magura M (1991) Using interindustry input-output relations as a Bayesian prior in employment forecasting models. Int J Forecast 7(2):231–238

    Article  Google Scholar 

  • Moretti E (2013) Real wage inequality. Am Econ J Appl Econ 5(1):65–103

    Article  Google Scholar 

  • Munasib A, Rickman DS (2015) Regional economic impacts of the shale gas and tight oil boom: a synthetic control analysis. Reg Sci Urban Econ 50:1–17

    Article  Google Scholar 

  • Partridge MD, Rickman DS (1998) Generalizing the Bayesian vector autoregression approach for regional interindustry employment forecasting. J Bus Econ Stat 16(1):62–72

    Google Scholar 

  • Partridge MD, Rickman DS (1999) Which comes first, jobs or people? An analysis of the recent stylized facts. Econ Lett 64(1):117–123

    Article  Google Scholar 

  • Partridge MD, Rickman DS (2006) Fluctuations in aggregate U.S. migration flows and regional labor market flexibility. South Econ J 72(4):958–980

    Article  Google Scholar 

  • Partridge MD, Rickman DS (2010) CGE modelling for regional economic development analysis. Reg Stud 44(10):1311–1328

    Article  Google Scholar 

  • Partridge MD, Rickman DS, Olfert MR, Ali K (2009) Agglomeration spillovers and wage and housing cost gradients across the urban hierarchy. J Int Econ 78(1):126–140

    Article  Google Scholar 

  • Partridge MD, Rickman DS, Olfert MR, Ali K (2010) Recent spatial growth dynamics in wages and housing costs: proximity to urban production externalities and consumer amenities. Reg Sci Urban Econ 40(6):440–452

    Article  Google Scholar 

  • Partridge MD, Rickman DS, Olfert MR, Ali K (2012) Dwindling U.S. internal migration: evidence of spatial equilibrium or structural shifts in local labor markets? Reg Sci Urban Econ 42(1–2):375–388

    Article  Google Scholar 

  • Pesaran HH, Shin Y (1998) Generalized impulse response analysis in linear multivariate models. Econ Lett 58(1):17–29

    Article  Google Scholar 

  • Porter ME (2000) Location, competition, and economic development: local clusters in a global economy. Econ Dev Q 14:15–34

    Article  Google Scholar 

  • Rey SJ (1998) The performance of alternative integration strategies for combining regional econometric and input-output models. Int Reg Sci Rev 21:1–36

    Article  Google Scholar 

  • Rickman DS (2002) A Bayesian forecasting approach to constructing regional input-output based employment multipliers. Pap Reg Sci 81(4):483–498

    Article  Google Scholar 

  • Rickman DS (2010) Modern macroeconomics and regional economic modeling. J Reg Sci 50(1):23–41

    Article  Google Scholar 

  • Rickman DS (2012) Looking backwards and forwards. http://economy.okstate.edu/caer/files/state-of-oklahoma-j12.pdf

  • Rickman DS (2013) 2013 economic outlook: National, state and local forecasts. http://economy.okstate.edu/caer/files/Oklahoma-Economic-Forecast-Dan-Rickman.pdf

  • Rickman DS, Guettabi M (2015) The great recession and nonmetropolitan America. J Reg Sci 55(1):93–112

    Article  Google Scholar 

  • Rickman DS, Miller SR (2002) An evaluation of alternative strategies for incorporating interindustry relationships into a regional employment forecasting model. Rev Reg Stud 32(1):133–147

    Google Scholar 

  • Rickman DS, Treyz GI (1993) Alternative labor market closures in a regional model. Growth Chang 24:34–50

    Article  Google Scholar 

  • Rickman DS, Miller SR, McKenzie R (2009) Spatial and sectoral linkages in regional models: a Bayesian vector autoregression forecast evaluation. Pap Reg Sci 88(1):29–41

    Article  Google Scholar 

  • Saks RW, Wozniak A (2011) Labor reallocation over the business cycle: new evidence from internal migration. J Labor Econ 29(4):697–739

    Article  Google Scholar 

  • Treyz GI, Rickman DS, Shao G (1992) The REMI economic-demographic forecasting and simulation model. Int Reg Sci Rev 14(3):221–253

    Article  Google Scholar 

  • Wang H (2016) The Texas economic model, miracle, or mirage? A spatial hedonic analysis. Ann Reg Sci 56(2):393–417

    Article  Google Scholar 

  • Weinstein A (2014) Local labor market restructuring in the shale boom. J Reg Anal Policy 44(1):71–92

    Google Scholar 

  • Yu J, Jackson R (2011) Regional innovation clusters: a critical review. Growth and Chang 42(2):111–124

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dan S. Rickman .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Rickman, D.S. (2017). Regional Science Research and the Practice of Regional Economic Forecasting: Less Is Not More. In: Jackson, R., Schaeffer, P. (eds) Regional Research Frontiers - Vol. 1. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50547-3_8

Download citation

Publish with us

Policies and ethics