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Structural Economicsand the Quality of LifeFaye Duchin & Anushree SinhaPublished online: 02 Dec 2010.

To cite this article: Faye Duchin & Anushree Sinha (1999) StructuralEconomics and the Quality of Life, Feminist Economics, 5:2, 125-132, DOI:10.1080/135457099338049

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STRUCTURAL ECONOMICS AND THEQUALITY OF LIFE

Faye Duchin and Anushree Sinha

ABSTRACT

People’s quality of life depends on the social relationships of their everydaylives and the technological choices that affect them. These features are readilydescribed within the framework of social accounting, provided that relevantcategories of households, workers, and economic activities are used. The tax-onomies can be devised in ways that reveal systematic differences in the rolesof different social groups (for example, those in the informal or formaleconomy; women or men) and the associated economic and social outcomes.The techniques of structural economics can then be used to explore theirimplications for the roles and outcomes of women in particular of alternativescenarios about economic development.

KEYWORDSStructural economics, social accounting, informal economy

[W]omen around the world are linking their struggle, and theiroppression, to their everyday lives. . . . [F]eminism dilutes the patri-archal dichotomy man/woman as it manifests itself in social insti-tutions and in social practice.

(Manuel Castells 1997: pp. 201–2)

People appear in economic theory in two explicit roles: as sellers of laborin factor markets and as buyers of consumer items in product markets. Inboth roles, economists assume that income and prices are the major deter-minants of their behavior. More general social considerations have beenexamined in particular contexts, such as discrimination in employment orcustomary patterns of authority within the household. In these cases it isgenerally recognized that aspirations, opportunities, and behavior, even inareas deemed to be economic in the narrowest sense of that term, are decis-ively in� uenced by features like race, ethnicity, age, and gender.

The characteristic of economics that most sets it apart from the othersocial sciences is its ability to conceptualize the economy as a single, inter-dependent system. This is achieved in different ways in microeconomic

Feminist Economics 5(2), 1999, 125–1321354–5701 © IAFFE 1999

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general equilibrium models and in macroeconomic models of the majoraggregates, such as in� ation, employment, trade, and investment. Modelsof both types, if they are credible, can deepen our understanding of the“big picture.” They also form the basis for the development and justi�cationof policies put in place by governments and by institutions like the WorldBank, International Monetary Fund, and World Trade Organization.Unfortunately, distinctions based on biological and cultural differenceshave no place in the theoretical re� ections underlying these frameworks.Therefore, the present situation and future prospects for women in par-ticular are invisible in conventional analyses because they are averaged withthe rather different situations and prospects of men.

Structural economics, by contrast with both macroeconomics and micro-economics, is fundamentally concerned with speci�c details about thesocial relationships and technological choices characterizing any realeconomy. Furthermore, it provides models for quantitative analysis that canhelp make operational the elusive concept of quality of life, and in par-ticular the quality of the lives of women, because of its focus on everydayactivities. The descriptive aspect of structural economics is most succinctlydescribed in terms of social accounting. See, for example, the early exampleof Graham Pyatt and Jeffrey Round (1977).

Social accounts have been collected mainly for developing economies.Many economic activities in developing countries take place on small plotsof land, in homes, and on the street. These “businesses” are not formallyregistered and for this reason do not have access to capital through formalintermediaries and do not pay taxes. Many of the workers operate as inde-pendent agents, or proprietors, and payments to those who work as employ-ees of small, informal enterprises are low and irregular, if they are made atall. The latter generally also make use of the goods and services that areproduced within the informal economy. This set of interrelationships, aswell as the relations between the informal economy and the formal one,can be revealed in appropriately de�ned social accounts. The units of analy-sis are broad categories of sectors, occupations, and households rather thanindividual � rms and consumers. The relations of the informal and formaleconomies are not well understood, but there is reason to believe that inboth the situation and needs of women may be substantially different fromthose of men. Fortunately, households and occupations can be de�ned inways that place differences in gender, age, or other social, demographic, oreven psychological characteristics in evidence. The purpose of the analysisthat will be carried out using the data in� uences how much disaggregationis justi�ed.

An illustrative social accounting matrix for Indonesia is shown in Table1: it quanti�es the income � ows among production sectors (two categories),factors of production (four categories), and institutions (three categories).(A table useful for empirical analysis will have several times as many sectors,

EXPLORATIONS

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factors, and institutions.) The factors of production include agriculturalworkers and all other workers, and there are two categories of households,urban and rural. To see the meaning of the �gures, note that the �rst rowdistinguishes the �ve sources of income for agricultural establishmentsresulting from: sales to agricultural establishments (6,988 billion rupiahs),manufacturing and service establishments (2,134 billion), rural households(7,537 billion), urban households (6,615 billion), and other institutions(3,022 billion). The seventh row, as a further example, quanti�es the extentto which rural households receive their income from agricultural labor andother workers and from capital, where the latter includes the estimatedincome of proprietors. The eighth row shows corresponding �gures forurban households.

While most social accounts are constructed solely in money terms, recentwork demonstrates the value of quantifying their components in otherunits. Table 2 shows the number of workers by household in terms of eightoccupational categories and ten kinds of households. It is the labor andcapital earnings of these workers that account for household incomes. Thisis the kind of information needed to build social accounts that are moredetailed than those in Table 1. Table 2 also provides a �rst glimpse of house-hold composition in Indonesia. For example, in both rural and urban set-tings in 1985, only the highest-income households averaged as many asthree workers per household.

Social accounts provide a basis for evaluating scenarios for the future.They have been used both within a neoclassical framework and within thefundamentally different conceptual and mathematical framework of struc-tural economics, a framework that distinguishes quantity and pricerelationships (see Faye Duchin 1998). Duchin used the of�cial socialaccounting matrix for Indonesia for 1985 with 17 sectors, 13 factors of pro-duction, and 12 institutions (including the worker and household cat-egories of Table 2) and built a scenario about possible future industrialdevelopments. She was able to examine various aspects of the effects of themodernization scenario on each category of household. But she did not dis-tinguish the implications for women.

For a study of the informal economy in urban and rural areas of India, itis our intention to build a new social accounting matrix. At present, thereis no of�cial social accounting matrix for India. A pilot one has been devel-oped at the National Council for Applied Economic Research in New Delhi,but it has no detail about households. Moreover, the one that is plannedwill be the �rst effort in India to systematically distinguish informal andformal economic activities. In addition, we are exploring, also for the �rsttime, the merits of working at a level of detail that would enable us toexamine the position of women in particular. We plan to describe theeconomy in terms of thirty production sectors, which distinguish informaland formal establishments producing roughly comparable outputs

STRUCTURAL ECONOMICS AND THE QUALITY OF LIFE

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Tab

le 1

Soci

al a

ccou

ntin

g m

atri

x fo

r In

done

sia

(bill

ions

of r

upia

hs)

Prod

uctio

n se

ctor

sFa

ctor

s of p

rodu

ctio

nIn

stitu

tions

Tota

l––

––––

––––

––––

–––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––1

23

45

67

89

10

Pro

duct

ion

sect

ors

1A

gric

ultu

re6,

988

2,13

40

00

07,

537

6,61

53,

022

26,2

962

Man

ufac

turi

ng a

nd s

ervi

ces

5,16

613

,640

00

00

3,14

07,

454

28,0

4257

,442

Fact

ors

of p

rodu

ctio

n3

Agr

icul

tura

l lab

or5,

357

00

00

00

00

5,35

74

Non

agri

cultu

ral l

abor

588

12,5

900

00

00

00

13,1

785

Agr

icul

tura

l cap

ital

7,32

70

00

00

00

07,

327

6N

onag

ricu

ltura

l cap

ital

022

,649

00

00

00

022

,649

Inst

itutio

ns7

Rur

al h

ouse

hold

s0

05,

052

1,23

76,

121

081

9032

112

,902

8U

rban

hou

seho

lds

00

304

11,9

410

21,3

3992

1,77

171

636

,163

9G

over

nmen

t, ca

pita

lac

coun

t, re

st o

f the

wor

ld87

16,

429

00

1,20

61,

310

2,05

220

,233

5,04

837

,149

10T

otal

26,2

9757

,442

5,35

613

,178

7,32

722

,649

12,9

0236

,163

37,1

49

Sour

ce: D

uchi

n (1

998:

Tab

le 5

.3).

Thi

s is

a h

ighl

y ag

greg

ated

ver

sion

of t

he o

f�ci

al ta

ble

for

1980

.

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Tab

le 2

Ten

cat

egor

ies o

f hou

seho

lds b

y pr

eval

ence

of e

ight

cat

egor

ies o

f wor

kers

in In

done

sia

in 1

985

(tho

usan

ds o

f wor

kers

)

12

34

56

78

Wor

kers

Agr

icul

tura

lPr

oduc

tion

Cler

ical

and

serv

ice

Prof

essio

nal

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

––––

–––

Tota

lH

ouse

hold

sW

orke

rs p

erH

ouse

hold

sPa

idU

npai

dPa

idU

npai

dPa

idU

npai

dPa

idU

npai

dw

orke

rs(th

ousa

nds)

hous

ehol

d

1La

ndle

ssag

ricu

ltura

l3,

407

252

398

130

186

262

323

4,67

03,

300

1.4

2Sm

all f

arm

s42

812

,025

631

687

267

941

8716

15,0

8210

,700

1.4

3M

ediu

m fa

rms

824,

418

174

172

6424

436

65,

196

3,70

01.

44

Larg

er fa

rms

815,

450

111

131

6320

339

66,

084

3,00

02.

05

Rur

al n

onfa

rm,

low

stat

us30

153

13,

196

1,77

678

82,

580

188

869,

446

5,20

01.

86

Rur

al, o

utsi

deth

e la

bor

forc

e18

684

727

316

914

631

974

122,

026

1,80

01.

17

Rur

al n

onfa

rm,

high

stat

us59

341

265

1,33

497

21,

595

964

895,

619

1,90

03.

08

Urb

an, l

owst

atus

5633

3,25

51,

516

1,77

82,

789

198

569,

681

3,70

02.

69

Urb

an, o

utsi

deth

e la

bor

forc

e15

2634

616

954

246

712

916

1,71

01,

000

1.7

10U

rban

, hig

hst

atus

1121

371

828

2,35

91,

702

1,02

811

36,

433

2,10

03.

1

Tot

al4,

626

23,9

449,

020

6,91

27,

165

11,1

022,

775

403

65,9

4735

,900

1.8

Sour

ce:D

uchi

n (1

998:

Tab

les

7.9

and

7.10

).

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(Anushree Sinha 1998). Available data may permit us to distinguish thefollowing categories of labor, with the possibility of further disaggregationof workers according to their gender:

1 casual agricultural labor2 regular agricultural labor3 casual nonagricultural wage labor4 regular nonagricultural wage labor5 informal proprietor6 formal proprietor7 unpaid helper in household enterprise.

Household categories for which data are available include the following:

1 informal rural households2 formal rural households3 informal urban households4 formal urban households.

“Casual” workers are considered part of the informal economy and haveno continuity of employment while “regular” workers are employed in theformal economy. The count of informal workers includes all those age 5and over. A household is called informal if most of its working membersare employed in the informal economy. These classi� cations and de� -nitions will receive closer scrutiny and re�nement as the work proceeds.Data on workers and households for 1993–94, including information onwages and salaries, will need to be integrated from various sources that donot necessarily use the same classi�cations and de�nitions (CSO 1997; NSS1997). We need to ask whether the additional data work that would berequired to disaggregate by gender can be justi� ed by the increased powerof the analysis.

If we divide all Indian households into informal and formal rural andurban categories, fully 75 percent of all workers lived in informal ruralhouseholds, and almost 90 percent of these were casual agriculturalworkers, proprietors of informal businesses, or unpaid helpers in house-hold enterprises. The data also shows that about 85 percent of the unpaidhelpers were in agriculture, as were 60 percent of the informal proprietors.Almost two-thirds of all Indian workers were employed in agriculture, withmost of the rest in service sectors. The service sectors are a mixture of bothtraditional and modern.

About one-quarter of the labor force, or some 75 million workers, werewomen. The question we need to address is whether the distribution ofwomen workers is similar to that of men.

In fact, women workers were also concentrated, and even considerablymore highly concentrated, than men workers, in informal rural house-holds, in the agricultural sector, and to a lesser degree in service sectors.

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At 26 percent of the labor force, women represented over half of theunpaid helpers in household enterprises but only about 10 percent of theproprietors, whether of informal or formal businesses. Yet women –although numbering only 120,000 – owned nearly half of the formal busi-nesses in education, scienti�c, and research services. Another 235,000women constituted over 60 percent of the workforce employed in themanufacture of beverages and tobacco, although they accounted for only4 percent of the formal proprietors in this sector. Women were also heavilyrepresented in the manufacture of food products and textiles and in edu-cation and health care. On the other hand, extremely few women con-tributed to the processing and fabrication of metals, capital goods, andtransportation goods and services.

The average wage of a woman worker relative to a man ranged fromunder 20 percent in some sectors to over 70 percent in others. Women’swages were closest to men’s in service sectors where women are well repre-sented, mainly education and health care, as well as in service sectors that,in India, are still dominated by male employees such as public adminis-tration or communication services.

The data that have been discussed con�rm that in India, as in othersocieties, the work experiences and earnings of women and men are quitedifferent. Women are disproportionately represented in agriculture and inthe informal sector, where earnings are lowest, and as unpaid helpers inhousehold enterprises. In addition, their unpaid work in collecting �re-wood and carrying water for domestic consumption is not re� ected in the�gures that have been cited. Furthermore, they earn substantially lowerwages than men, even in jobs in the formal sector. Distinguishing genderin the database would make it possible to assess the implications of alterna-tive development strategies for both women and men and to evaluate poli-cies that might improve the economic situation of women in particular. Theinformal sectors provide a buffer zone in the transition from a traditionalto a modern industrial society. Modernization affects not only industrial butalso social structures, including the roles and relations of women and men.A structural analysis can be expected to provide insight into the range ofplausible outcomes of the development process and to suggest the kinds ofactions required to ensure that certain outcomes rather than others areachieved.

Faye Duchin, Dean, School of Humanities and Social Sciences,Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA

e-mail: duchin@rpi.eduAnushree Sinha, National Council of Applied Economic Research,

11 Indraprastha Estate, New Delhi, 110 002, India

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ACKNOWLEDGMENT

The authors are grateful for the contribution of N. Sangeeta and K. A. Sid-diqui and to the Ford Foundation for funding the Indian project on theinformal sector, which made it possible to obtain the National SampleSurvey data.

REFERENCES

Castells, Manuel. 1997. The Power of Identity. Oxford: Blackwell.Central Statistical Organization (CSO). 1997. National Accounts Statistics. Govern-

ment of India, New Delhi.Duchin, Faye. 1998. Structural Economics: Measuring Change in Technology, Lifestyles and

the Environment. Washington, DC: Island Press.National Sample Survey (NSS), 50th Round. 1997. Employment and Unemployment in

India, 1993–94, Report No. 409, Government of India, New Delhi.Pyatt, Graham and Jeffrey Round. 1977. “Social Accounting Matrices for Develop-

ment Planning.” Review of Income and Wealth 23(4): 339–64.Sinha, Anushree. 1998. “Macroeconomic Analysis of the Indian Informal Sector

within a Social Accounting Matrix Framework,” presented at the 12th Inter-national Input–Output Conference, New York University, May.

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