Skip to main content
SpringerLink
Log in

Classic and Spatial Shift-Share Analysis of State-Level Employment Change in Brazil

  • Chapter
  • First Online:
Applied Regional Growth and Innovation Models

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

Abstract

The Brazilian economy has gone through a remarkable transformation since the difficult times of the last quarter of the twentieth century. Brazil is now seen as one of the engines of global economic growth and together with Russia, India and China makes up the often cited BRIC acronym. During the current decade, Brazil is expected to overtake the economies of Britain and France and become the world’s fifth largest economy, with São Paulo possibly the world’s fifth wealthiest city.

This chapter was written while the first author was a Ph.D. student at the University of Waikato, Hamilton, New Zealand. We thank Bill Cochrane for advice on computational aspects.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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.

    However, we do not use regression methods for shift-share analysis. This alternative approach was originally proposed by Patterson (1991).

  2. 2.

    Mitchell et al. (2005) apply Nazara and Hewings’s (2004) spatial shift-share decomposition to data on Australian regions. Mayor and López (2008) combined a variety of spatial analysis tools with the shift-share method.

  3. 3.

    An alternative assumption would have been to backcast the 1981–1991 Tocantins sectoral shares from 1996 by means of the observed trends in national sectoral shares. This has very little impact on the results reported in the tables in this chapter.

  4. 4.

    To calculate the employment growth rates, several assumptions have been made. There are states with zero sectoral employment as follows: for mining: Acre in 1981, 1986, 1996, 2001, and 2006; Alagoas in 1996, Roraima in 1981, and for Amapá in 1986 and 1996. For finance: Amapá in 1996. In these cases we used the population growth rate as a proxy for employment growth over the sub-periods to estimate sectoral employment in each of those years. The assumptions we made yielded results that are consistent with the overall pattern of employment data in Brazil. However, due to a lack of state population data for 1981 and 1986, we estimated the population in those years by interpolation within the available population time series.

  5. 5.

    Chahad et al. (2002) found a similar result when analysing employment change from 1985 to 1997 in Brazil. However, such findings contradict previous studies for the period 1960–1970 in which centripetal forces were apparently stronger than centrifugal forces, with high growth of the number of firms, the number of people employed, and gross value of production in the main metropolitan centres (Sao Paulo and Rio de Janeiro or former Guanabara) (Enders 1980).

  6. 6.

    Table 7.3 shows that these states have high location quotients in 1981 for those sectors that had relatively high subsequent growth (such as commerce, electricity, gas and water, mining and transport and communications).

  7. 7.

    Three sectors in which North and Center-West states had a comparative disadvantage are agriculture and fishing, manufacturing, and the financial sector. These latter two sectors had some of the highest growth rates in the sub-period 2001–2006, 127.5 % and 38.6 %, respectively (see Table 7.1).

  8. 8.

    With the exception of Rio de Janeiro which also had a positive industry-mix effect in all of the 5-year periods, but the lowest five-period average total employment growth due to a consistently high negative competitive effect.

  9. 9.

    These clusters are known in the spatial econometrics literature as: High-High = hot spots; Low-High = spatial outliers; High-Low = spatial outliers, Low-Low = cold spots. Other areas are those with no significant spatial autocorrelation.

  10. 10.

    On the other hand, rook contiguity and bishop contiguity consider regions as contiguous if and only if they share a common border and a common edge, respectively.

  11. 11.

    This result suggests interstate mobility among businesses may be low.

  12. 12.

    On the map for industry-mix average, these states are: Amapá, Roraima, Amazonas, Acre, Rondônia, Mato Grosso, Goiás, Distrito Federal, São Paulo, Rio de Janeiro, Rio Grande do Norte, and Paraiba. These states are essentially from north and middle-west which are the regions benefited from convergence from 1981 to 2006.

  13. 13.

    Hence queen contiguity is again adopted. The Distrito Federal is a region within Goiás state. They are assumed to share a border.

  14. 14.

    From Nazara and Hewings (2004, pp. 480–481) seven components can be identified. However, when we aggregate across sectors, two components individually add to zero in each region. These are: neighbor industry-mix effect and regional industry-mix effect (or, the negative own-region industry-mix effect). And there is a double counting for the other two: the neighbor-nation regional shift effect is equal to minus the neighbor-region regional shift effect. Thus, these components are excluded and we can use a simplified version of the spatial shift-share identity with only four components.

  15. 15.

    Excluding Maranhão.

  16. 16.

    In fact, the gravity equation suggests that the spatial interaction between regions is inversely related to distance between pairs of regions and positively related with the product of economic size of the two respective regions. Here we used population as an indicator of the scale of regional economy.

  17. 17.

    Graphs are not shown here but are available upon request.

References

  • Abreu MP (2008a) The Brazilian economy, 1930–1980. In: Bethell L (ed) The Cambridge history of Latin America, vol IX. Cambridge University Press, Cambridge, UK, pp 283–394

    Google Scholar 

  • Abreu MP (2008b) The Brazilian economy, 1980–1994. In: Bethell L (ed) The Cambridge history of Latin America, vol IX. Cambridge University Press, Cambridge, UK, pp 395–430

    Chapter  Google Scholar 

  • Abreu MP, Werneck RLF (2008) The Brazilian economy, 1994–2004. In: Bethell L (ed) The Cambridge history of Latin America, vol IX. Cambridge University Press, Cambridge, UK, pp 431–454

    Chapter  Google Scholar 

  • Anselin L (1995) Local indicators of spatial association – LISA. Geogr Anal 27(2):93–115

    Article  Google Scholar 

  • Arcelus F (1984) An extension of shift-share analysis. Growth Change 15(1):3–8

    Article  Google Scholar 

  • Barff RD, Knight PL (1988) Dynamic shift-share analysis. Growth Change 19(2):1–10

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (2004) Economic growth. MIT Press, Cambridge, MA

    Google Scholar 

  • Bavaud F (1998) Models for spatial weights: a systematic look. Geogr Anal 30(2):153–171

    Article  Google Scholar 

  • Berzeg K (1978) The empirical content of shift-share analysis. J Reg Sci 18(3):463–469

    Article  Google Scholar 

  • Berzeg K (1984) A note on statistical approaches to shift-share analysis. J Reg Sci 24(2):277–285

    Article  Google Scholar 

  • Bishop KC, Simpson CE (1972) Components of change analysis: problems of alternative approaches to industrial structure. Reg Stud 6(1):59–68

    Article  Google Scholar 

  • Brakman S, Garretsen H, van Marrewijk C (2001) An introduction to geographical economics: trade, location and growth. Cambridge University Press, Cambridge, UK

    Book  Google Scholar 

  • Chahad JPZ, Comune AE, Haddad EA (2002) Shifts in regional employment: an application of the Haynes-Dinc model for Brazil. Paper presented at the European regional science association, Dortmund

    Google Scholar 

  • Cingano F, Schivardi F (2004) Identifying the sources of local productivity growth. J Eur Econ Assoc 2(4):720–744

    Article  Google Scholar 

  • Cochrane W, Poot J (2008) Forces of change: a dynamic shift-share and spatial analysis of employment change in New Zealand labour market areas. Stud Reg Sci 38(1):51–78

    Article  Google Scholar 

  • Daumal M, Zignago S (2010) Measure and determinants of border effects of Brazilian states. Pap Reg Sci 89(4):735–758

    Article  Google Scholar 

  • Dinc M, Haynes KE (1999) Regional efficiency in the manufacturing sector: integrated shift share and data development analysis. Econ Dev Q 13(2):183–199

    Article  Google Scholar 

  • Dinc M, Haynes K (2005) Productivity, international trade and reference area interactions in shift-share analysis: Some operational notes. Growth Change 36(3):374–394

    Article  Google Scholar 

  • Dinc M, Haynes K, Qiangsheng L (1998) A comparative evaluation of shift-share models and their extensions. Australasian J Reg Stud 4(2):275–302

    Google Scholar 

  • Dunn ES (1960) A statistical and analytical technique for regional analysis. Pap Reg Sci Assoc 6(1):97–112

    Article  Google Scholar 

  • Enders WT (1980) Regional disparities in industrial growth in Brazil. Econ Geogr 56(4):300–310

    Article  Google Scholar 

  • Esteban-Marquillas JM (1972) A reinterpretation of shift-share analysis. Reg Urban Econ 2(3):249–255

    Article  Google Scholar 

  • Fausto B (1999) A concise history of Brazil (trans: Brakel A). Cambridge University Press, Cambridge, UK (Original work published 1998)

    Google Scholar 

  • Gazel CR, Schwer RK (1998) Growth of international exports among the states: can a modified shift-share analysis explain it? Int Reg Sci Rev 21(2):185–204

    Article  Google Scholar 

  • Getis A (1991) Spatial interaction and spatial autocorrelation: a cross-product approach. Environ Plann A 23(9):1269–1277

    Article  Google Scholar 

  • Glaeser EL, Kallal HD, Scheinkman JA, Shleifer A (1992) Growth in cities. J Polit Econ 100(6):1126–1152

    Article  Google Scholar 

  • Haynes K, Machunda ZB (1987) Considerations in extending shift-share analysis: note. Growth Change 18(2):69–78

    Article  Google Scholar 

  • Keil SR (1992) On the value of homotheticity in the shift-share framework. Growth Change 23(4):469–493

    Article  Google Scholar 

  • Knudsen DC (2000) Shift-share analysis: further examination of models for the description of economic change. Socio-Econ Plan Sci 34(3):177–198

    Article  Google Scholar 

  • Knudsen DC, Barff R (1991) Shift-share analysis as a linear model. Environ Plann A 23(3):421–431

    Article  Google Scholar 

  • Krugman P (1991) Increasing returns and economic geography. J Polit Econ 99(3):483–499

    Article  Google Scholar 

  • Le Gallo J, Kamarianakis Y (2011) The evolution of regional productivity disparities in the European Union from 1975 to 2002: a combination of shift–share and spatial econometrics. Reg Stud 45(1):123–139

    Article  Google Scholar 

  • Lobo EML (1996) Brazil since 1889. In: Tenenbaum BA (ed) Encyclopedia of Latin American history and culture. Simon & Schuster Macmillan, New York, pp 424–432

    Google Scholar 

  • Loveridge S (1995) A practical approach to shift-share analysis. J Community Dev Soc 26(1):111–124

    Google Scholar 

  • Loveridge S, Selting AC (1998) A review and comparison of shift-share identities. Int Reg Sci Rev 21(1):37–58

    Article  Google Scholar 

  • Markusen AR, Noponen H, Driessen K (1991) International trade, productivity, and U.S. regional job growth: a shift-share interpretation. Int Reg Sci Rev 14(1):15–39

    Article  Google Scholar 

  • Matlaba VJ, Holmes M, McCann P, Poot J (2012) Agglomeration externalities and 1981–2006 regional growth in Brazil. Stud Reg Sci 42(1):145–161

    Google Scholar 

  • Mayor M, López AJ (2008) Spatial shift-share analysis versus spatial filtering: an application to Spanish employment data. Empirical Econ 34:123–142

    Article  Google Scholar 

  • McDonough CC, Sihag BS (1991) The incorporation of multiple bases into shift-share analysis. Growth Change 22(1):1–9

    Article  Google Scholar 

  • Mitchell W, Myers J, Juniper J (2005) Extending shift-share analysis to account for spatial effects: a study using Australian census data. Working Paper #05-19, Centre of Full Employment and Equity, University of Newcastle, Callaghan, Australia

    Google Scholar 

  • Nazara S, Hewings GJD (2004) Spatial structure and taxonomy decomposition in shift-share analysis. Growth Change 35(4):476–490

    Article  Google Scholar 

  • Patterson MG (1991) A note on the formulation of a full-analogue regression model of the shift-share method. J Reg Sci 31(2):211–216

    Article  Google Scholar 

  • Resende GM (2011) Multiple dimensions of regional economic growth: the Brazilian case, 1991–2000. Pap Reg Sci 90(3):629–662

    Article  Google Scholar 

  • Rolim C (2008) Decomposing the GDP growth of the great Brazilian regions: dynamic shift-share on recent Brazilian economic cycles. Paper presented at congress of the regional science association international, São Paulo

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Vale Technological Institute, Rua Boaventura da Silva, 955, CEP 66055-090, Umarizal, Belém, PA, Brazil

    Valente J. Matlaba

  2. Department of Economics, University of Waikato, 3105, Hamilton, 3240, New Zealand

    Mark Holmes

  3. Faculty of Spatial Sciences, University of Groningen, Landleven 1, 9747 AD, Groningen, The Netherlands

    Philip McCann

  4. National Institute of Demographic and Economic Research (NIDEA), University of Waikato, 3105, Hamilton, New Zealand

    Jacques Poot

Authors
  1. Valente J. Matlaba
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mark Holmes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Philip McCann
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jacques Poot
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Valente J. Matlaba .

Editor information

Editors and Affiliations

  1. Department of Spatial Economics, VU University, Amsterdam, The Netherlands

    Karima Kourtit

  2. Department of Spatial Economics, VU University, Amsterdam, The Netherlands

    Peter Nijkamp

  3. Building and Planning Level 5 Architecture Building, University of Melbourne Faculty of Architecture,, Parkville, VIC, Australia

    Robert Stimson

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Matlaba, V.J., Holmes, M., McCann, P., Poot, J. (2014). Classic and Spatial Shift-Share Analysis of State-Level Employment Change in Brazil. In: Kourtit, K., Nijkamp, P., Stimson, R. (eds) Applied Regional Growth and Innovation Models. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37819-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37819-5_7

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37818-8

  • Online ISBN: 978-3-642-37819-5

  • eBook Packages: Business and EconomicsEconomics and Finance (R0)

Publish with us

Policies and ethics

Search

Navigation