-Urban and Regional Report No. 81-23

Y..

LIMITED SEARCH PROCEDURES AND MANUFACTURING

LOCATION BEHAVIOR:

A CASE STUDY OF SAO PAULO, BRAZIL

by

Andrew Marshall Hamer

November 1981

(This report was prepared under the auspices of the National Spatial Policiesin Brazil Research Project (RPO 672-13) as NSP Working Paper No. 9. Theviews reported here are those of the author, and they should not be inter-preted as reflecting the views of the World Bank or its affiliatedorganizations. This report is being circulated to stimulate discussion andcomment.

-Urban and Regional Economics DivisionDevelopment Economics Department

Development Policy StaffThe World Bank

Washington, D.C.

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INTRODUCTION

Thiis paper presents some initial results of work being under-

taken on industrial location behavior in Greater Sao Paulo and its

hinterland by the World Bank. The purpose of this presentation is

to bring the research to the attention of those interested in regional

issues and to do so at an early stage of the work. In the interest of

brevity no attempt is made to link these initial findings to a review of

the existing literature on industrial location. Furthermore, given the

preliminary nature of the work, quantitative analysis using multivariate

techniques will be dealt with in later papers.

Rationale for Brazil National Spatial Policies Project

Responding to World Bank and member countries' concerns about

the size and growth rates of major world metropolises, a research team

of urban and regional economists was assembled in 1980 by the Bank's

Urban and Regional Division in the Development Economics Department.

We chose for our first case study a middle income country,

Brazil, with a relatively high degree of urbanization and undergoing

rapid growth in terms of both population and employment. Within Brazil

we selected an area dominated by a major metropolis and large enough

to allow for an examination of a hinterland extending out over a radius

of several hundred miles. This led the project team to Southeast Brazil

and, within it, to Greater Sao Paulo plus a surrounding region whose

size has varied somewhat according to the individual research tasks

undertaken.

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Greater Sao Paulo and the state of Sao Paulo are responsible

for a high proportion of economic activity in Brazil..-/ With 10% and

20% of the nation s population, respectively, Greater Sao Paulo and the

State as a whole contribute approximately one-quarter and two-fifths of

net domestic product. Their importance in industrial production is

even more dramatic: Greater Sao Paulo has one-third of the nation's

industrial employment and captures over 40% of industrial value-added;

the state is responsible for almost half of the industrial employment

and nearly 60% of national industrial value-added.

Greater Sao Paulo's very high proportion of employment in

manufacturing (38%) - led us to concentrate on manufacturing location

decision-making. The working assumption was that, in the system of

cities under consideration, manufacturing held out the greatest potential

for transforming the local economies. This assumption, in turn, was

based on the belief that manufacturing firms are relatively more flexible

than other sectors in their choice of location and more likely to rank

higher in such measures as the generation of multiplier effects which

contribute to the expansion and diversification of the local economies.

One final point should be made. In choosing to study a region

such as Sao Paulo, we selected an area where policies that impinge on

the development of different types of cities are largely indirect and

where neither a national nor a state urban policy has yet been put into

place. The public sector is heavily involved in the provision of infra-

structure, in the distribution of long-term capital, and in the promotion

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of selected industrial sectors; all of these are assumed implicitly to

encourage certain spatial patterns. But with explicit policies absent,

project resources were directed at establishing a behavioral framework

for policy-making rather than drawing conclusions about specific policies

in place.

Spatial Patterns of Economic Activity

Initial findings on the changing pattern of spatial activity

suggested some evidence for a hypothesis that spontaneous decentralization

a was underway in Sao Paulo state. We defined that geographic entity,

which covers an area roughly equivalent to the Federal Republic of

Germany or the United Kingdom, into Greater Sao Paulo; an Inner Region

or Eastern Hinterland within a radius of approximately 150 kilometers

from the center of Sao Paulo city; and Western Sao Paulo, covering the

rest of the state.

A process of polarization reversal can be defined as beginning

when the growth rate of secondary centers located outside a primate

metropolis exceeds that of the core. 4/ The 1980 Demographic Census

shows that the rate of population growth in Greater Sao Paulo fell

sharply in the 1970s, while the rate of growth among secondary cities and

agglomerations in Sao Paulo state stabilized at a level above that of

the core (Table 1). The hinterland's growth is being led by the nine

centers which, in 1970, had populations of between 100,000 and 250,000

and by the two centers whose population exceeded 250,000 in that year

. (Table 2). More generally, population growth rates outside Greater

4 -

Table 1

Average Annual. Growth Rates of Urban Population for Areas

of the State of Sao Paulo 1950-1980

(Growth Rates in Percent)

Areas within Urban Population (b)

the State (a) 1950-60 1960-70 1970-80

Metropolitan Sao Paulo 6.8 5.8 4.6

City of Sao Paulo 6.1 5.1 3.8

Builtup Fringe 10.8 8.1 6.2

Outer Suburbs 9.2 9.7 9.6

Hinterland 5.8 4.8 4.8

Large City Inner Region 5.9 5.5 5.8

Other Inner Region 5.2 4.6 5.3

Western Sao Paulo 5.9 4.2 3.6

State of Sao Paulo 6.4 5.4 4.7

Notes: (a) Areas have constant boundaries corresponding f%Qundaries

existing in 1950. Metropolitan Sao Paulo as defined by

Davidovich and Lima (1975). "Inner Region" includes all

areas within 150 kilometers of the Metropolitan Area plus

all of the. Paraiba Valley. "Large City" refers to nine

urban agglomerations.

(b) Urban populatiorn is urban population as defined by the

Brazilian Demographic Census for municipios with 20,000

or more iahabitants in 1970 or cities within urban

agglomerations.

Source: Fundacao IBGE. Censo Demografico 1950, 1970;

Censo Demo rafico Preliminar, 1960, 1980

Table 2

Average Annual Population Growth Ratesfor Different Size Cities 1/

Index Number 1950-60 1960-70 1970-80

MetropolitanSao Paulo 1 6.8 5.8 4.6

Secondary Cities

-20,000-50,000 45 5.6 4.0 4.1

-50,Q00-l00,000 14 6.2 4.9 4.3

-100,000-250,000 9 6.0 5.2 5.3

-250,000 + 2 5.5 5.3 5.4

l

1/City size classes defined by the urban populatibn of cities in 1970.Cities do not move from one class to another over time.

K

Source: Fundacao IBGE, Censo Demografico, 1950, 1970; Censo Demografico

Preliminar, 1960, 1980.

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Sao Paulo are faster in the larger centers, in the centers close to the

core, au&d in centers with good road links to the metropolis.

The changes in trends should not shift attention away either

from the relatively low rate of growth of Western Sao Paulo or from the

very large absolute numbers still associated with Greater Sao Paulo.

Between 1970 and 1980 Greater Sao Paulo grew by 4.4 million persons,

a total exceeding the 1980 population of all but one of the other eight

Brazilian metropolitan areas. -'5/ Having 10% of the nation's p&pulation,

Greater Sao Paulo captured 17% of the nation's population growth over

the previous decade.

There is evidence that the phenomenon of polarization reversal,

foreshadowing future shifts away from the core which eventually may be

reflected in absolute totals as well, is being helped along by the

pattern of industrial employment growth (Table 3). Among all size

classes of secondary cities above the 20,000 mark, manufacturing growth

now exceeds the rate found in metropolitan Sao Paulo. This pattern

emerged prior to the reversal of population growth rate rankings.

Reinforcing these findings are others. If shift share analysis is used,

it is apparent that a significant, positive differential shift is

contributing to hinterland growth, implying a swing away from the metro

area in the balance of comparative advantage for a wide range of industries.

This is demonstrated in Table 4 for employment changes over the period

1970-1975; unpublished tabulaticns reconfirm this for the period 1960-1970

and for both time periods using value added data. These results are.

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Table 3

Average An-nual Growth Rates of Employment forSelected City Sizes (a)

ManufacturingEmployment

Metropolitan 1960-70 1970-75Sao Paulo 4.47% (b) 6.43

Secondary Cities

- less than 20,000 3.80 7.24

- 20,000-50,000 5.21 8.80

- 50,000-100,000 5.97 9.88

- 100,000-250,000 4.05 8.70

- 250,000+ 6.34 7.62

(a) City size classes defined by the urban population of cities in1970. Cities do not move from one class to another over time;1960 is the base year for city toundaries.

(b) Growth rates are average annual compounded.

Source: Fundacao IBCE, Censo Industrial, 1960, 1970, 1975.

TAL.E 4 SHIFT-SHARE *COMPONENJrS OF EMPLOYHIENT CIIANGE 1970-1975 FOIR EIGCIIT SUBREGIONS IN TIlE STA,TE OF SAO PAULO n

Suibregion SF-bregion Sijbregion LaIrge /City of Inner Ouiter of Paraiba of of City

Sao Paulo Suburbs Suburbs Santos Valley Sorocaba Campinas Westrtn Sl' TOTA l1 -

Tot:il 1970 Employment 643,672 235,277. 27,958 21,766 47,364 40,730 140,773 76,524 1,234,064

'rotal Employyment Cihange1970-1975 180,334 103,163 17,619 5,012 20,237 16,801 71,062 40,216 454,444

A\nanumal Emp i oyment Growthrate 1970-1975 5.06 7.54 10.27 4.23 7.37 7.15 8.52 8.81 6.47

(In Percenit)

Amotint of EmploymentChange due to State 237,0323/ 86,641 10,296 8,015 17,442 14,999 51,840 28,180Growth (131.4)- (84.0) (58.4) (159.9) (86.2) (89.3) (73.0) (70.1)

aoAmouinLt of Employment

Change due to Industrial 17,839 -257 515 1 -4,887 -6,871 -4,558 -1,783Mix of Subregion (9.9) (-0.3) (2.9) (0.0) (-24.2) (-40.9) (-6.4) (-4.4)

Amo,unt of lmnploymentChange doe to Differenitial -74,538 16,779 6,809 -3,005 7,682 8,673 23,780 13,819Shiift in Suibregion (-41.3) (16.3) (38.6) (-60.0) (38.0) (51.6) (33.5) (34.4)

l/ Data missing for cities below 20,000 population in the Western Sao Paulo.2/ Total is stim of previouis eighit columns, excluding small Western Sao Paulo cities,P/ Percent of total employment change in subregion. The three percentages in each column sum to 100.

Source-: IBGE, Censo Industrial (Sao Paulo) 1970, 1975

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reinforced by information on value-added per worker, expressed in

constant cruzeiros (Table 5). At a two-digit level of disaggregation

areas outside the core have undergone a transformation which has

brought the hinterland into a position of increasing parity with the

metropolis. As noted before, these data underline the fact that the

process is being led by the cities and agglomerations whose populations

exceeded 100,000 in 1970. Western Sao Paulo, as a region, continues to

lag considerably behind Greater Sao Paulo and the Inner Ring.

All of this appears to provide some grounds for optimism on

the part of government sector planners who might wish to reinforce

trends with policies that encourage the outward movement of plants and

jobs. Further evidence of the role of mobility and decentralization is

found in examining published and unpublished data from the 1970 and

1975 industrial censuses. The period between 1970 and 1975 was one of

high industrial growth; Metropolitan Sao Paulo's industrial employment

rose by 37%, while the hinterland, registered an increase of 51%,for an

overall state expansion of 41%. During that same time period 56% of the

state's net employment growth was generated by establishments that had

to make explicit decisions about a new location (Table 6). In most

regions "mobile growth" accounted for 60% or more of the increase in

employment (core city, Inner Ring small cities, Western Hinterland small

cities); only in the inner suburbs of the metropolis did stationary

expansions provide more than half of the recorded net rise in employment.

As a matter of clarification, net employment growth, as defined, implicitly

deducts not only declines in situ but also deaths and closures due to trans-

fers. Thus gross stationary expansion may be considerably more important

than suggested by the data.

RECENT EVOLUTION OF SECTORAL VALUE-ADDED PER EMPLOYEE IN MNUFACTURINGFOR REGIONS OF SAO PAULO STATE

(Value-added in thousands of 1970 cruzeiros)

HinterlandCities and Agglomerations

Greater Inner 1' 2/ over 100,000 populationSectors Sao Paulo Ring Western SP in 1970

1960 1975 1960 1975 1960 1975 1960 1975

Mlineral extraction 12.7 21.6 11.5 27.2* 5.9 13.8 12.9* 37.2*Non-nmetallic minerals 10.3 28.6 9.7 22.4 6.7 17.5 11.8* 27.1Metallurgy 11.8 29.9 10.7 34.2* 7.4 15.4 8.8 38.9*Mlachinery 12.7 33.2 9.5 29.1 8.0 25.3 10.0 30.8Electrical 16.3 33.6 8.3 40.2* 9.8 19.2 9.0 46.0*Transport 22.2 36.0 14.2 32.9 4.1 11.9 6.8 34.8Wood 9.2 22.1 8.3 26.1* 7.2 12.1 8.9 27.6*Furniture 9.5 20.7 7.0 17.8 5.2 13.1 7.5 18.6Paper 15.7 30.9 16.3* 48.8* 7.4 21.2 17.1* 46.3*Rubber 25.2 44.0 13.1 72.7* 9.0 20.6 13.0 51.1*Leather 8.9 16.8 9.3* 15.1 8.7 12.3 9.9* 15.0Chemicals 18.8 92.6 41.3* 1.82.2* 18.0 58.9 47.5* 218.0*Pharmaceuticals 16.9 97.6 4.5 91.3 6.3 34.1 4.4 89.6Perfume 25.6 78.2 14.5 102.1* 19.5 36.2 14.7 98.9*Plastics 11.7 27.7 12.6* 28.1* 0.3 21.6 15.7* 31.6*Textiles 8.5 23.3 6.1 17.0 9.6* 18.2 6.6 18.9Clotlhing 9.0 16.1 8.6 16.4* 12.4* 9.1 8.1 19.4*Food 14.7 30.2 14.8* 35.5* 14.7 31.0* 14.2 31.5*Beverages 20.7 69.3 13.5 35.4 9.9 40.42 10.3 42.6Tobacco 31.6 119.3 4.7 56.5 5.2 -- 4.7 56.5Printing and publishing 12.1 40.5 7.0 16.8 5.8 13.3 7.5 16.5Other activities 9.9 25.6 6.7 28.5* 7.5 18.2 6.7 31.7*

1/ In.ner Ring, slhown in Ilap One, includes areas of Sorocaba, Santos, Campinas, and Sao Jose dos Campos.2/ Western Sao Paulo includes area of State beyond Inner Ring.3/ No eniployinent for tobacco Industry in Western Sao Paulo at end of 1975.

* indicates Inner Ring, Western regioni, or large city/agglomiieration where two-digit industry outperformGSP in the particular year.

Sourcq: Fundacao IBGE, Censo Industrial fSao Paulo), 1960, 1975.

TABLE 6

Components of Change in Manufacturing Employment by Region, Sao Paulo State, 1970-1975

Region Stationary Branches Births UnclassifiedExpansions and

Transfers

1. City of Sao Paulo 36% 8% 55% 1%

2. Inner Suburbs 65% 9% 26% -

3. Rest of Mletro Sao Paulo 40% 13% 46% 1%

4. Adjacent Major Cities in Inner Ring 45% 8% 47% -

5. Other Large Cities in Inner Ring 49% 14% 37%

6. Smaller Cities in Inner Ring 22% 14% 63%

7. Large Cities in Western Sao Paulo 40% 6% 53% 1%

8. Smaller Cities in Western Sao Paulo 35% 9% 54% 2%

9. Total 44% 10% 46% 1%

Source: Fundacao IBGE, Censo Industrial 1970, 1975.

J0

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Branches played a relatively small role in the reported mobile

growth. They rarely accounted for more than 10% of the net growth in any

part of the state. The t-ulk of mobile growth was due to births and plant

transfers, which were not separated from one another by the Brazilian

Census Bureau,

On a secteral level, a process of relative decentralization com-

bined with considerable mobility can be identified as well. Of the 21 two-

digit sectors, 16 --accounting for 80% of total state industrial growth --

grew more rapidly in the hinterland than in metropolitan Sao Paulo. Accompany-

ing the relatively fast growth of industrial employment, one finds that mobile

growth exceeded 40% of net employment growth in 17 sectors, accounting for

64% of period growth. The cautionary comment, cited above, about an under-

estimate of the role of gross in situ expansion applies here as well.

Complementing the above is evidence that plant transfers from

metropolitan Sao Paulo (in practice, the core city alone) played an imiportant

role in the mobile portion of the growth of employment in Inner Ring

communities, while having relatively little impact on the Western Hinterland.

All new plant investments in Sao Paulo are licensed by a state agency, as

reported below. Firms are required to report the planned employment

expected in connection with these investments. A sample of these firms

derived from the 1977-1979 licenses was surveyed by the World Bank, again as

reported below. Information from the sample, appropriately expanded, suggests

that plants that relocated from or had headquarters in Greater Sao Paulo are

responsible for 41% of the planned employment reported in newly located

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plants in Inner Ring urban agglomerations and 46% of the same in

smaller cities and towns of the Inner Ring. For Western Hinterland

communities the proportion drops to 6%. This information is merely

indicative,for the employment reported need not match actual employment.

Furthermore intra-city or intra-region transfers have not been netted

out, in the interest of faithfully reflecting the sources of all new

plant origins. Nevertheless, it is clear that the dynamism of the Inner

Ring is due, in part, to the limited decentralization from the core city.

The 1980 Industrial Location Survey

The universe of manufacturing companies in the state of Sao Paulo

Which opened new production facilities during 1977-1979 was obtained

from the state pollution control agency, the Companhia de Tecnologia de

Saneamento Ambiental (CETESB). All companies have to obtain licenses to

invest in industrial plant facilities and another license to start

production; for new facilities, the absence of CETESB licenses means

the denial of electric utility hook-ups and a tax code number. The

research team -/identified 1961 new plants from this license file from

8022 permits given across 183 of the state's 571 counties. From this

universe of new plants, a sample of 600 was taken for interview purposes.

A decision was made not to spend limited resources on interviews of

firms that made in situ expansion decisions. In the latter case it was

assumed that management would not be in as good a position to report on

alternate locations as their mobile counterparts. The sample was weighted,

by distance from the city of Sao Paulo and by plant size. All new plants

located more than 50 kilometers from the city's center and employing 50 or

more were included. The remainder all employed 10 or more workers and were

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selected with a bias against smaller plants establishing themselves within

metropolitan Sao Paulo. The responses were weighted to reflect the sampling

pattern, given 581 usable interviews. 7/ The interviews were normally held

with the most senior executive of the plant concerned, though for some

branch plants the meetings were held at the supervising headquarters.

A Review of Working Hy,theses

In approaching the data, a set of hypotheses were laid out

8/that could be matched with the survey resulVs. -/It was assumed that

location decisions are rare and episodic in the life of a company.

Firms are not looking constantly at a set of all possible alternatives

and monitoring the discounted returns from investments in each area,

ready to move or establish branches at the first sign of better

oppo'tunities elsewhere. Instead these companies, especially where

family-owned and/or relatively small, acknowledge the need for location

related decisions only when the pressures on existing facilities threaten

to become a matter of serious concern. Comparing alternatives to in situ

investment is then affected by the presumed uncertainty of information

available and by fears of the post-facto consequences of investments

elsewhere. For transfers there is the additional consideration of the

transactions costs associated with closing and opening a plant. For

that reason, new locations imply considerably more complex investment

decisions than would be the case if in situ investments were to be

undertakr'i. This, in turn, suggests a strategy to limit the uncertainty,

risk, complexity and transactions costs of decisions by comparing in situ

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expansion with locations in only a few, well-known areas close to the

existing plant. For births, the presumption would be that decision-makers

investing capital derived from other ventures would tend to favor the

area of previous activity. To the extent that this picture of relative

immobility can be by-passed by branch plants having limited tasks and

supervised from headquarters, the results might be different. Branch

plants might mean less disruption than plant transfers, and reduce the

all or nothing risk associated with the latter. Where a tradition of

branch plants is limited, as suggested by the components of change data

reviewed above, or where branch plants are closely supervised by family-

run concerns, this footloose alternative may not be terribly important.

The Survey Results: Push Factors

The usual caveats apply in analyzing the survey results

of factors associated with a decision to move. It is possible that the

individual interviewed is not the one appropriate for the questions

asked. Even if this poses no problems, one cannot dismiss the twin

issues of poor memory and post-hoc rationalizations. Nevertheless

within the limits of attitudinal questions some conclusions can be

gleaned from this survey.

The survey confirms the hypothesized association of the need

to consider new locations and the pressures brought on by production

growth, fully occupied premises, internal reorganizations needs, and the

desire to introduce a new line of products. For suburbanizing and exurbanizing

movers there are additional pressures related to traffic congestion, high

land costs, high building lease costs,and, more recently, pollution control

IS;:,£.->F 6

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requirements. Not relevant to the decision are variables more clearly

associated with a model where firms are constantly shopping around for alterna-

tives. Labor, access, and utility variables prove to be relatively unimportant

in the initiation of new location decisions.

Table 7 highlights these results, excluding from consideration

all firms listed as births. These responses cover 459 plants and represent

the pattern expected for the 1461 plants identified in the universe as trans-

fers or newr branches. The results have been analyzed under other headings

including plant size, sector, capital intensity, space use intensity, owner-

ship type, and mark.t orientation. These do not modify in any substantial way

the patterns that emerge in Table 7. In the aggregate the key reasons cited

as of major importance or decisive in looking for a new plant site are

a) increased production pressures (81%), b) pressures created by fully

occupied premises (81%), c) the need to undertake internal reorganization (62%)

and d) the requirements associated with the introduction of a new product line

(44%). There is no significant difference between transfers and branches

in the proportion listing "increased production" or "fully occupied" as

reasons. Branches are, however, more likely to cite "new product line"

(59% vs. 39%) while transfers list "internal reorganization" more frequently

than do branches (67% vs. 47%). Looking across the spatial categories does

not alter the aggregate rankings; aside from the factors cited all others are

of relatively little importance. The exception to this helps explain why all

moves are not completely local in character. Twenty to 33% of the suburban-

izing or exurbanizing movers also mention traffic congestion, high land costs,

and high leasing costs as important variables. To a lesser degree, firms

in other cities, some of which are quite large, also raise these three issues.

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Table 7:- Reasons for New Plant Siteby Destination, Transfers and Branches

(Percentage of replies specified as "Major Importance" and "Decisive")

Reasons for Seeking Across Suburban- Exurban- Other moves out-

a New Location City 1/ zing 2/ ising 3/ side Sao Paulo 4/ Total

(T) (T+B)-5 (T) (T+B) (T) (T+B) (T) (T+B) Total

A. Expansion

1. Increased production 83 83 78 79 76 79 78 80 81

2. New product line 37 43 41 44 44 47 37 45 44

3. New are of activity 00 43 76 87 75 65 22 22 4

B. Access

4. To existing andnew markets 1 3 7 6 5 6 9 9 5

5. Location of markets 0 1 0 0 0 0 0 1 1

6. To suppliers ofcomponents 1 2 3 3 1 0 2 1 2

7. To suppliers of rawmaterials 0 1 3 3 1 5 1 1 2

8. To suppliers ofservices 0 1 0 1 0 0 2 1 1

C. Labor Difficulties

9. Finding skilled labor 10 7 7 7 5 9 12 9 8

10. Finding unskilledlabor 2 4 7 7 7 6 6 4 5

11. Union difficulties 0 1 2 2 0 0 1 1 1

12. Finding administra-tive staff 1 1 3 3 0 0 4 3 1

13. High labor costs 3 7 5 4 8 11 5 4 6

14. Finding femaleworkers 1 2 2 7, 2 6 0 0 2

D. Building and Site

15. Wanted internalreorganization 67 55 58 57 75 76 77 76 62

16. Fully occupied 85 83 77 76 80 83 82 84 81

17. Increasing trafficcongestion 10 7 21 20 27 29 17 13 14

18. Premises unsafe 10 7 13 13 18 17 11 9 10

19. High cost lease 5 4 27 25 22 19 22 17 13

(Continued)

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(Table 7 - Reasons for New Plant...)

Reasons for Seeking Across Suburban- Exurban- Other moves out-a New Location City 1/ izing 2/ izing 3/ side Sao Paulo 4/ To

(T) (T+B)-/ (T) (T+B) (T) (T+B) (T) (T+B)

20. Opportunity to sell 8 10 1 1 2 2 3 221. Eviction 9 7 9 8 15 14 7 622. Cost of land 5 4 19 22 31 33 17 15

E. Government. Actions

23. Expropriation 1 1 11 10 1 2 2- 124. Pollution controls 9 6 16 16 16 18 15 1225. Zoning 1 1 6 5 12 11 5 3

F. Other

26. Community opposition 0 0 10- 9 6 6 15 1127. Electrical supply 0 0 0 0 0 0 6 228. Combining scattered

units 0 0 0 0 8 4 2 029. Owner reasons 4 4 6 6 10 9 13 1230. Other 11 8 5 5 5 5 4 6

Number of firms in theweighted sample 420 642 333 370 149 173 196 276 146

1/ "Across City" = 106 moves within the City of Sao Paulo, and within the innermetropolitan municipalities and from these suburbs into the city.

2/ "Suburbanizing" = 126 moves from the City of Sao Paulo to the 17 innermetropolitan municipalities.

3/ "Exurbanizing" = 84 moves from the city and inner suburbaln municipalitiesto the rest of the State.

4/ "Other Moves" = 135 moves within the State from origins outside the innermetropolitan area.

5/ T = Transfers, B = Branch MIoves.

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Finally, 15% to 20% of the plan-s that decentralized mentioned actual or

potential problems with pollution controls as encouraging the setting up of

plants in non-core locations. Zoning controls were cited by far smaller

proportions. On a sectoral basis, however, there are clear divergencies on

the latter issue; chemicals, metal working, textiles, plastics, rubber and

iron and steel plants all registered positive response rates well above the

cited averages.

The patterns of Location Uncovered by the Survey

A high proportion of the moves are very local in character (Table 8).

Generally speaking, transfers and branches Located tn the vicinity of the

previous plant or headquarters facility. In fact 82% of branches located

within the county of the headquarters plant; while 51% fall tranfers were

intra-county,as well. There is one exception to this local focus of moves.

While the central city of the metropolis is the principal generator of movement,

there is a noticeable trend to destinations in the inner and outer suburbs.

Even so out of-66 intermunicipal branching operations, 71% involved moves of

less than 50 kilometers; among the 532 intermunicipal transfers, 87% covered

fewer than 50 kilometers. Furthermore, there is a clear distance decay effect;

few moves decentralize to areas beyond 150 kilometers from the center of the

core city. This is obvious from the fact that the Western Hinterland drew

virtually all of its plant. from local transfers and branches plus births.

Table 9 lists the "origin" and destination of planned employment. Once again,

outside the core city 88% to 100% of the employment is located in the region

of "origin'. The core city, however, is the recipient of only 28% of eXmploy-

ment that transferred from other core city locations; furthermore, only 38%

of the employment created by core city-based new branches was located within

the core area.

Table 8: Origins and Destinations ofTransfers and Branches by Area and Location of Births 1977-1979

(Universe Reconstructed from 1980 Survey)

(branch moves in brackets)

* WithinSame Region Destinations

Same Different City of Inner Outer Small Large WesternMunicipio Municipio Sao Paulo GSP GSP City Ring City Ring Hinterland Total 2 )

338 0 338 333 89 20 30 1 812City of Sao Paulo (160) (0) (160) (37) (0) (6) (10) (1) (214)

52 26 2 78 0 0 6 0 6Inner GSP ( 66) (2) (0) (68) (6) (0) ( 0) (1) ( 75)

0 0 0 6 0 0 0 0 6Outer GSP ( 9) (0) (0) (0) (9) (0) (0) (0) ( 9)

44 0 0 0 0 44 0 0 44Small City Ring r 8) (0) (0) ( 0) (0) (8) ( 0) (0) ( 8)

bt

.^ 56 9 0 3 0 4 65 0 72o Large City Ring (18) (1) (0) (0) (0) (0) (19) (0) (19)

63 3 0 0 0 0 0 66 66Hinterland ( 17) (2) (0) ( 0) (0) (0) ( 0) (20) ( 19)

554 38 341 420 89 68 lul 67 1087Totals (278) (5) (160) (105) (15) (14) (29) (22) (344)

Location of Births 91 226 24 40 29 82 492

Notes: (1) Areas as on Map One(2) Plus two transfers from other states and 4 no resportses and two branch moves from other states- Properly

weighted, these bring the total to 1961 plants. All palnts have planned employment of ten or more andare manufacturing establishments.

Source: 1980 Location Survey.

Table 9

Origins and Destinations of Transfer and Branch Plants (By Planned Employment)and Planned Employment of Births by Location(a)

City of Inner Outer Small City Large City Hinterland TotalSao Paulo Suburbs Suburbs Ring Ring

Branch 5522 2401 0 2343 3728 540 14533City of Sao PauloTransfer 21729 35394 14564 2514 4047 154 78402

n Branch 0 4084 165 0 0 60 4309Inner SuburbsTransfer 575 9052 0 0 653 0 10280

Branch 0 0 698 0 0 0 698Outer SuburbsTransfer 0 207 0 0 0 0 207

Branch 0 0 0 1126 0 0 1126Small City RingTransfer 0 0 0 2828 0 0 2828

Branch 0 0 0 0 2407 0 2407-4 Large City Ring Transfer 0 217 0 111 5994 0 6322

H Branch 0 0 0 0 0 3257 3257HinterlandTransfer 0 0 0 0 4466 4466

T Branch 5522 6485 863 3469 6135 3857 26330 (b)TotalsTransfer 22304 44870 14565 5453 10694 4620 102504 (c)

Location of NewEmployment by Births 3173 7990 3013 1534 1498 3418 20627

Total (planned 30999 59345 18441 10456 18327 11895 149'461employment)

Notes: (a) Weighted by Expansion Factors

Source: 1980 Location Survey

- 22 -

Evidence on the Decision-Maktng Process

The decision-making process uncovered by the survey is

consistent with the working hypotheses developed above. Among companies

starting operations, transferring plants, or opening branches, few

considered other states or other regions. Most considered only the

municipality chosen or neighboring municipalities.

Specifically, only 7% considered locating outside Sao Paulo

state, and they rejected svich options primarily because of concerns

about access to markets (62%) or suppliers (32%). Infrastructure

deficiencies played no significant role in this process, nor did

concerns about labor. The reasons that other companies did not

bother to consider other states remain unknown. Some 15% of the surveyed

firms considered another region of the state, where a region was

defined as a small cluster of counties adjacent to one another. Not

surprisingly, 32% of the exurbanizing branches and transfers considered

another region other than the one selected, suggesting that once a

relatively long distance move was considered the company was willing

to be unusually flexible. The reascns for rejecting other regions are

known only for those companies explicitly considering them. The

categories from which firms could choose an answer were quite general,

nevertheless the first or second main reason was a vague "other",

accompanied by concern about market access (for births and intra-

hinterland moves) or "costs". Such vagueness is not unexpected given

that only 38% of these firms did any "in depth" analysis of the rejected

options.

- 23 -

Even within the region chosen, half the firms considered

nothing beyond the immediate neighborhood finally selected. At this

level rejections were overwhelmingly associated with problems concerning

land and buildings.

The information gathered in the process of making location

decisions was quite limited. Decision-makers apparently tried to

satisfy the prerequisites for production facilities with a feasible

location rather than concerning themselves greatly with relative costs

of alternate sites. Thus, for example, of those firms responding, a

sizeable minority did not even use visits to the chosen sites as a

means of evaluation (Table 10). The majority failed to visit local governments

or other companies in the regiorn chosen for location. More sophisticated

approaches, like the use of published materials or consultants,were

very rare. The exurbanizing group rated consistently above other

categories in seeking out alternate sources of information; even then

site visits were utilized by only a minority of such firms.

In fact,comparative costing of alternatives proved to be

rare, possibly because only neighboring areas were usually under

consideration. Only 54% of the firms provided information on such a

process. Among these 25-30% acknowledged making a land cost, a building

cost, a transport cost, or a 'labor cost comparisons. There is little

evidence, once again, to suggest a process of widespread search.

There is no evidence of a major role to be played by the

type of locational incentives likely to be used by counties. Part of

this may reflect limited experience. only 13% of the firms (weighted)

Table 10: Inf. :rmation Used in Site Selection

(percentages)

Categories of New PlantOther Moves

2/ 3/ 4/ OutsideInformation Sources Births Branch Transfer Across City2- Suburbanizing- Exurbanizing- Sao Paulo

Visits to.sites 56 82 47 57 59 42 58

Visits to localgovernments 23 19 26 14 32 42 21

Visits to othercompanies inthe region 15 16 15 3 24 34 10

Use of published.material 4 7 4 2 3 11 8

Use of specia'lconsultants 15 9 4 4 4 15 1

Weighted numberof firmsresponding!' 165 180 591 313 213 117 127

1/ Percentages do not add to 100 because some companies said "yes" to more than one information source.

2/ Moves within core city or within 17 inner suburbs and from inner suburbs to core city.31 Moves from core city to 17 inner suburbs.41 Moves from core city and 17 inner suburbs to rest of state.5/ Moves within state with origins outside inner metropolitan area.

Source: 1980 Location Survey.

C-'. , , s,c

- 25 -

received any type of incentive or-beneflt for their plant from public

authorities. These ranged from the exemption from relatively minor

county taxes and fees (40%), to county grants of land and facilities

(33%), and financing by state or federal agencies (47%) on the basis

of sectoral priorities unrelated to space. As these percentages indicate,

some plants were beneficiaries of multiple subsidies.

The survey contained a question meant to test the degree to

which a battery of incentives at the disposal of the counties could induce

more flexibility in locational decision-making (Table 11). The most inter-

esting conclusion comes from examining the hypothetical impact of a grant of

both site and building combined with an exemption from local taxes and

fees for a minimum of 10 years. There is little inducement to move to

another state. There is, with the exception of births (37%), and across

inner metropolis movers (25%) and exurbanizers (24%) , little interest in

considering other regions in the state. A sizeable minority or a majority

would, however, raise their horizons sufficiently to consider a neighboring

municipality. The survey instrument did not probe the impact of a battery

of state- or federal-level incentives on inter-regional or inter-state

mobility. Work underway on the impact of subsidies on attracting plants

into the low-income Northeastern markets from Sao Paulo state should help to

overcome this omission.

Table 11: Possible Incentives and Relocation

(percentages)

Movement CategoryStatus

1/ 2/Other Moves-Incentive Alternative Location Birth Branch Transfer Across City- Suburbanizing-/ Exurbanizing-/ in Sao Paulo

Grant of Site Another State 3 0 1 1 1 2 1

Another Region 14 5 8 2 10 14 7

NeighboringMunicipality 36 47 56 55 61 55 40

No Influence 48 47 34 42 28 28 52

Grant of Site Another State 5 4 3 3 4 5 3and buildingadaptable to Another Region 26 19 16 21 16 19 10accommodatecompany Neighboring

Municipality 46 49 57 47 63 57 55

No Influence 23 28 23 29 18 19 32

'.0

Exemption from Another State 3 1 2 2 2 0 3taxes and muni-cipal charges Another Region 19 10 11 11 11 10 10for a minimumof ten years Neighboring

Muncipality 43 36 51 *38 58 53 41

No Influence 34 53 36 49 30 37 46

All of the above Another State 12 13 10 10 11 8 11

Another Region 37 23 22 28 20 24 16

NeighboringMunicipality 42 39 52 41 57 52 49

No Influence 9 26 16 21 12 15 24

Number of firms inweighted sample 559 315 1,074 445 478 200 269(=100)-

1/ Moves within core city or within 17 inner suburbs and from inner suburbs to core city.2/ Moves from core city to 17 inner suburbs.3/ Moves from core city and 17 inner suburbs to rest of state.4/ Moves witlhin state witlh origins outside inner metropolitan area.

Source: 1980 Location Survey.

27 -

Factors Considered Significant in Differing Locations

Considered

To the cautionary remarks listed earlier about attitudinal

surveys, others should be added at this stage. It is likely that

locations perform well in some ways and poorly in others; the essence

of the choice is a trade-off between advantages and disadvantages along

a multidimensional vector of attributes. Therefore the site chosen may

not rank favorably in all the ways deemed desirable. Also, bottlenecks

are likely to be stressed in interviews, while other necessary conditions

go uncited because they are not important to the choice between a

limited set of alternatives actually under consideration.

Thus, for example, Sao Paulo state is unusually well provided

with infrastructure, as Table 12 illustrates with a series of household-

level data. The cities of the hinterland of the state most likely to

receive industry have better service levels for electric power, water,

and sewer than does the metropolitan area. Telephone service is

roughly comparable between the two areas. Such widespread availability

would undoubtedly lead to less emphasis being placed on infrastructure

than might otherwise be the case.

Table 13 considers separately transfers, transfers plus

branches, and births; under the first two headings, the spatial categories

previously utilized are again employed. Seven variables rate highly

across all nine headings as being of major importance and decisive.

In most cases 40% or more of the firms in each category picked the cited

factors. Two of these are site-specific, namely a suitable plot with

space for expansion. Among urban services the availability of electric

- 28 -

Table 12

Access to Infrastructure, Sao Paulo State

Metro InteriorSao Paulo Cities *

Percent Urban Households with

- electrical connection 80% 85%

- water connection 60% 74%

- sewer connection 32% 57%

Telephones per urban household .30 .26

Number of municipios 37 54

* Municipios with urban populations over 30,000 in 1970 or comprisingunofficial urban agglomerations as defined by Brazilian censusi.

Source: Fundacao IBGE: Censo Demografico 1970, 1980.BNM: Censo Nacional de Saneamento 1978CESP: Unpublished listingsFundacao IBGF: Censo de Telecomunicacoes

Table 13: Location Factors tar Transfer and Branch Plant Move. by Origin/Destination Group (weighted totals)(Percentages of replies specified as "Major Importance" and "Dectiuvie")

Origins/Destination Groupi As Moves withip City of Sea Paulo and Viithiq the suburbs CMoHves from the inner metropolitan area out to the rest of the State8' Moves from City of Baa ?aulo, to the i'nner suburbs D- Hove. within the rest of the State

Reasorts for Choice Transfer* Only Transfers and Uracoh Pllants Births

of New LocationD

A C Other Hove.0

A Other Move. otlDlAcross City Suburbanizing ExurbaniginC outside Sao Paulo Total Across City Suburbanizing Exurbanizing outside Sao Paula oa U r

(ni- 420) tit- 333) (n- 149) (n- 196) (n. 1099) (n- 646) (n" 310) (n 174) -(n - 282) (n- 1473) (n-42

A. Labor Supply

1. Plentiful svpply 64 60 38 41 55 59 57 42 38 52 57

2. Cheap labor is 14 13 14 16 19 14 13 10 16 29

3. With required skills 57 29 16 30 38 59 28 1s 29 41 48

4. Little competition for labor In area 9 6 10 6 8 7 7 12 5 7 a

5. Little unionacetivity 0 1 2 2 1 0 9 2 1 1 2

6. Available technical training 5 6 6 18s 5 6 7 . 14 7 5

7. Quality of basic schools 5 3 18 17 85 6 7 14 7 3

S.HMobility of labor -3 10 13 9 7 5 9 13 9 81

B. Accessibility

9. Close to main suppliers 5o 50 41 30 49 53 49 51 27 47 49

10. Close to main customers 60 49 57 37 52 55 50 55 38 50 54

11. To airport 1 5 14 7 4 2 5 13 2 4 2

12. To mritime port 1 a 7 2 4 3 9 7 8 5 6

13. Easy road access 39 69 83 58 57 43 69 86 53 57 57

14. Easy rail access 2 2 10 1 3 6 4 9 2 S 3

15. Municipality *asmarket 0 0 1 a, 0 1 0 1 0 1 0

C. Government Influences

o ~16. Guidaimce and requirements 15 14 9 2 II 10 13 a 1 9 6

cS 17. Stat.i financial pressures 0 0 2 0 0 0 0 2 0 0 0

18. Hun1fcipsl Incentives 0 0 12 7 3 0 0 13 7 3 2

19. Law,'3 and infrast'ructutre 0 0 16 19, 5 0 1 11 19 5 6

20. JT.dustrial districts 6 17 19 37 16 4 18 19 35 15 9

21. izuaicipal assistance 0 3 22 14 6 0 3 26 13 7 5

D. Urban Services

22. Maintenance and technical 46 26 21 17 32 39 26 21 16 29 16

23. Consulting, computing, accounting 17 9 a 4 11 I5 9 7 4 11 a

24. Employment agencies 1 2 2 1 2 3 2 2 2 3 3

25. Electric power 44 66 77 55 57 55 66 79 51 60 5226. Public water supply 38 26 30 27 31 44 25 32 26 34 32

27, Proximity to springs 1 13 19 10 a 0 1s is 8 8it

28, Disposal of wastes 4 12 9 7 7 3 14 9 6 712

29. Public transport to site 57 41 28 34 44 56 38 31 30 44 32

30. Telephone and telex 56 49 64 6152 54 50 66 38 51 33

E. Site

31, Suitable plot 35 69 84 18 60 28 68 84 63 31 32

32. Suitable building 4 7 6 5 5 8 7 7 3 7 10

33. Space for expansica 47 68 so 74 63 46 66 82 78 61 49

34. Property to lease 63 25 12 14 36 65 26 12 26 41 58

35. Cost of land 10 55 69 24 35 9 5-3 69 24 30 27

IF. other

36. Low competition for products I 0 3 13 3 2 2 3 10 3 11

37. Local tradition In sector 12 3 13 24 12 1s 5 15 20 14 21

38. Health facilities 20 4 19 19 15 21 4 21 15 16 20

39. Environment attractive to managers 4 7 19 7 a 15 a 19 5 12 17

40. Personal and family reasons of ownter 24 19 23 53. 28 19 18 20 42 23 29

Source: 1980 Location Survey.

--awdffiVi

- 30 -

power and telephone-telex connections were mentioned. Here the earlier

caution about how to interpret the variables should be recalled. A

substantial minority of firms (and most of those locating in the inner metro-

polis) did not list electric power availability as a key variable even

though its absence in a particular area would presumably preclude

sites in that county from being selected. In the context of the

widespread availability of electric power in Sao Paulo state, the

omission should be interpreted as evidence that power is no longer a

crucial bottleneck to be worried about for the mentioned plants.

Also important are easy road access for the truck movement

of inputs and outputs and proximity to principal suppliers and

customers. The latter variables could have been explored more effectively

if the freight-delivery time limits had been specified and if the key

origin and destination points had been listed. Without this information

it is difficult to pin down the role played by increasing distances

from the center of the city of Sao Paulo in constraining locational choices.

Finally firms placed considerable emphasis on having a

plentiful supply of labor at their disposal and, to a lesser degree, on

having labor with the mix of skills required by the firm. Significantly,

only births placed any emphasis on low-cost labor. Since wage levels,

standardized by various labor force characteristics do vary widely

9/between the core city and the Western Hinterland, -9the lack of interest

in looking for low-wage labor suggests, once again, a search process

limited to geographically contiguous labor markets.

.ae N .1. .. '...' t.t .. :->+...L"' .. Q-.4.., -i. ... ,-"fi:,-.t- ...

- 31 -

Though cited less frequently, other variables emerge as

important. Substantial numbers of firms, and always one-quarter or

more in each category, listed the availability of public water supplies

and public transport facilities as important to their decision. Among

the intra-hinterland moves, 37% of the firms cited the availability of

industrial estates as a key factor. Conversations with managers in

some of the Western Hinterland cities suggests that industrial estates

are seen as providing mechanisms for rapid and coordinated installation

of public services by local governments acting as "godfathers" with the

supplying agencies. Elsewhere, there is minimal evidence of interest in

the estates. The survey provides little to back the enthusiasm

of those planners who see estates as magical magnets in much the same

manner as certain New Guinea cargo cult followers view the link betwaen

makeshift runways and the free delivery of the fruits of the industrial

world.

The same intra-hinterland movers are the only ones who, in

substantial numbers (53% of the transfers; 42% of the transfers and

branches), list personal and family reasons as important in their

locational choices. Elsewhere no more than a quarter of firms in each

category, including that of births, consider personal reasons as worth

citing. Given widespread hypothesizing about the role of this variable

the results may appear surprising. It is not possible to rule out

self-censorship in this case, since the listing of this variable might

seem "unbusinesslike" to many of the respondents.

- 32 -

Some factors were cited by a significant number of firms in

only a few categories. Most of these cases are easily explained.

Births, presumably constrained by investment resource and cash flow

problems to a greater degree than other firms, are found to cite cheap

labor, property to lease, and cheap land as factors that influenced

their location decision.

Transfers and branches locating within the inner metropolis cited

certain factors often associated with agglomeration economies:

maintenance and technical services and the availability of property to

lease. Suburbanizing transfers and branches cited

property to lease as well but added cost of land, suggesting one major

reason for decentralization. In this they were joined by transfers and

branches moving out from the inner metropolitan area, for whom land costs

rated as very important or decisive in 69% of the cases.

From the public sector's vietwpoint it is interesting to see

what policy levers appeared to rate as less than crucial. Using less

than a 20% response rate as a guide, otne finds little mention of the

quality and availability of conventional and technical schools,

municipal incentives, municipal assistance (except for exurbanizing

firms), health facilities, or an environment attractive to managers.

These conclusions apply regardless of category considered. How one

interprets these results is problematic, for they reflect existing

conditions and existing differences in variable values between counties

considered. Nevertheless the conclusions about municipal incentives

complement those already discussed concerning potential municipal

incentive packages.

- 33 -

Unpublished tabulations confirm that, as a general rule,

breaking out the results by industrial sector does not modify substantially

the conclusions. There are cases, like transfer and branch chemicals

firms, -hich are capital-intensive and thus place little emphasis on

the need for adequate supplies of labor and public transport to the

site; alternatively this same sector has production requirements that

tend to set it apart in its above-average ranking of road access and

the desirability of locating in an industrial district. More labor-

intensive, traditional technology sectors like clothing and leather

(transfers and branches) put greater-than-average emphasis on labor

supplies, while having much less need to be close to particular focal

points of supplies or sales. But, in general, factors that ranked low

in the aggregate, ranked low, as well, in each sector; less emphatically,

variables that rated high marks in the aggregate also performed well

at the sector level of disaggregation.

Disaggregation of the results by plant planned employment

size, capital intensity, space intensity, or market orientation proved,

similarly, to be relatively uninformative. One exception appears to

be those plants classified as large (75 or more workers) in planned

employment size. Among births, for example, these firms ranked industrial

districts, access to maintenance and technical services, availability

to telephones and telex, suitable plots, space for expansion, and land

costs well above the average for other firms. Even here the differences

are less apparent among across inner metropolis movers, suburbanizers,

exurbanizers and other movers, except for variables like space for

expansion and land costs.

- 34 -

43

Conclusions

The Sao Paulo project began as an exercise to determine the

constraints within which industrial mobility operated. It was

hypothesized that firms tend to address the locational aspects of an

investment decision with considerable reluctance, preferring in situ

expansion and choosing familiar locations where relocations or branching becomes

necessary. The survey results for mobile plants are generally consistent with

this view. Branches and relocations appear to be generated by severe

production constraints rather than by the mere emergence of attractive

alternate locations. In evaluating new locations, firms avoid sophisticated

search processes and tend to locate in or near the county "of origin".

The exception to this lies among central city firms, who face pressures

from land costs, traffic congestion, and administrative controls; and

who look favorably upon new plants that lie within a radius of no more

than 150 kilometers from the core's center.

Policy-makers are unlikely to find that the most conventional

locational incentives will encourage more than a broadening of the search

to counties neighboring the chosen one. The evidence of polarization

reversal is, in fact, consistent with an outward crawl of center city

firms into the hinterland. Even then virtually all of the new activity

in the Western Hinterland is indigenous to the region. The margin for

effective policy intervention in this vast area may thus be quite narrow

in the absence of far more massive subsidies than those conventionally

considered.

- 35 -

Footnotes

1. Acknowledgements are due to Peter Townroe, William Dillinger,

and David Keen, who have prepared various project working papers bearing

on the aspects of the topics dealt with in this paper. Some of the

tables used in this report also appear in one or more of those working

papers.

2. The population data is drawn from the 1980 Demographic Census.

Industrial data based on the 1975 Industrial Census. Net domestic

product data derived from calculations made available by the Getulio

Vargas Foundation, using 1970 census information.

3. Fundacao I.B.G.E., Pesquisa Nacional por Amostra de

Domicilios - 1978: Area Metropolitana Sao Paulo, Volume 3, Number 10,

Rio de Janeiro, Brazil, 1980, p. 23

4. The concept of polarization reversal is reviewed in

H. Richardson "Polarization reversal in developing countries", Papers

of the Regional Science Association, 45, 1980 , pp. 67-85.

5. Information drawn from the 1970 and 1980 demograplic censuses.

6. The survey was undertaken in collaboration with the Institute

for Economic Research (FIPE) at the University of Sao Paulo and with the

state Secretariat of the Interior.

7. Weights were based on the planned employment of the new

plants. UporL surveying the plants divergences were found between

planned employment totals reported to CETESB arid those listed to the

World Bank at the later date. These differences were most noticeable

-36-

for the categories "50-99 employees" and "100-199 employees". The

expansion factors continued to be based on the plants' original

reported planned employment totals. To avoid complicating the

sampling process no attempt was made to duplicate the sectoral repres-

entatives of the urniverse of firms. The match between the sectoral

profile of the universe and of the weighted sample appears in Appendix A.

8. For further background see R. Schmenner, "Choosing new

industrial capacity: on-site expansion, branching, and relocation",

Quarterly Journal of Economics, 95(1), 1980, pp. 103-119. Also

P. Townroe, Industrial Movement: Experience in the U.S. and the U.K.,

Farnborough (Great Britain), 1979.

9. Unpublished tabulations from the 1970 demographic census

suggest that, controlling for education, and setting median metropolitan

nominal wages equal to 100, Inner Ring pay scales are 10% to 50% lower

and Western Hinterland wages are 30% to 100% lower, depending on years

of education. These differentials tend to persist when individual

sectors are broken out in each region of the state.

-37-

Appendix A

Sectoral Breakdown of Planned Employment byBirths Branches, and Transfers in Sao Paulo State

(% of Total Planned Employment)

1977-79 1980 Survey Survey Coverage asCETESB File (Weighted) Percent of CETESB

Coverage

Non-Metallic Minerals 2.8% 2.4% 86%Metallurgy 17.9 17.1 96%Machinery 17.2 17.0 99%Electrical 7.6 13.6 179%Transport 5.4 5.0 93%Wool 0.9 1.1 122%Furniture 2.4 3.9 163%Paper 1.7 1.1 65%Rubber 2.6 1.3 50%Leather 0.3 2.0 667%Chemicals 2.7 3.3 122%Pharmaceuticals 1.1 1.3 118%Perfume 1.9 4.4 232%Plastics 8.2 7.2 88%Textiles 5.9 2.7 46%Clothing 9.5 12.0 126%Food 4.3 2.3 - 53%Beverages 2.4 1.7 71%Tobacco 0.0 0.0 -Printing 1.4 1.2 86%Other 8.4 3.4 40%

Total (-100%) 162,661 151,904 93%

F:;

IE