A SOCIAL ACCOUNTING MATRIX FOR CAMEROON*

Madelei ne Gauthi er Steven Kyle

* T h i s p a p e r a l s o appeared a s a Department o f A g r i c u l t u r a l Economics Research Paper, Cornel l U n i v e r s i t y , I t h a c a , New York.

T h i s p a p e r p r e s e n t s p a r t i a l r e s u l t s of work done i n 1989-90 f o r t h e f i r s t a u t h o r ' s Ph.0. d i s s e r t a t i o n . The a u t h o r s w i s h t o ex tend t h e i r g r a t i t u d e t o David Blandford , t o Gerard Djophant from t h e M i n i s t 2 r e du P lan du Cameroon who p a r t i c i p a t e d i n t h e development o f t h e I/O t a b l e , t o Alexander S a r r i s , and t o t h e Cornel l Food and N u t r i t i o n P o l i c y Program, which provided p a r t i a l s u p p o r t f o r t h i s p r o j e c t .

The Cornell Food and Nutrition Policy Program (CFNPP) was created in 1988 within the Division of Nutritional Sciences, College of Human Ecology, Cornell University to undertake research, training, and technical assistance in food and nutrition policy with emphasis on developing countries.

CFNPP is served by an advisory committee of faculty from the Division of Nutritional Sciences, College of Human Ecology; the Departments of Agricultural Economics, Nutrition, City and Regional Planning, Rural Sociology; and from the Cornell Institute for International Food, Agriculture and Development. Graduate students and faculty from these units sometimes collaborate with CFNPP on specific projects. The CFNPP professional staff includes nutritionists, economists, and anthropologists.

CFNPP is funded by several donors, including the Agency for International Development, the World Bank, UNICEF, the U.S. Department of Agriculture, the New York State Department of Health, the Thrasher Research Fund, and individual country governments.

Preparation of this document was financed in part by the John D. and Catherine T. MacArthur Foundation and the U. S. Agency for International Development under USAID Cooperative Agreement AFR-0000-A-00-8045-00.

@ 1999 Cornell Food and Nutrition Policy Program

This Working Paper series provides a vehicle for rapid and informal reporting of results from CFWP research. Some of the findings may be preliminary and subject to further analysis.

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CONTENTS

TABLES

FOREWORD

1. INTRODUCTION

2. STRUCTURE AND DEFINIT IONS I N A SAM

3. DATA SOURCES

4. THE SAM FOR CAMEROON

5. DISAGGREGATED ACCOUNTS

Product ion Account Commodity Account Fac tor Account

Breakdown i n t o Fac tor Categories Di s t r i bu t i on o f Sectora l Val ue-Added t o Factor

Categories Househol d Account

Breakdown i n t o Househol d Groups Der i va t i on o f t h e Expenditure M a t r i x D i s t r i b u t i on o f Factor Income t o Households

6. AGGREGATE ACCOUNTS

Market ing Margin Account Government Account Cap i ta l Account Fore i gn Account

APPENDIX

Procedures Used i n Assembling t h e 1/0 Account Accounting I d e n t i t i e s o f t he SAM Determinat ion of Employment Categories from t h e EBC A1 1 o c a t i on of EBC Expenditure Items t o Commodity Categories Data Amendment i n t he I/O Table L i s t o f Product ion A c t i v i t i e s i n t he 1/0 Table o f Cameroon

REFERENCES

LIST OF TABLES

Accounts o f t h e Aggregate SAM

Aggregate SAM f o r Cameroon, 1984/85 (mi 11 i on CFAF)

Di saggrega ted SAM f o r Cameroon, 1984/85 (mi 11 i on CFAF)

Aggregate V a r i a b l e s o f t h e 11-Sector Inpu t /Outpu t Account (mi 11 ion CFAF)

Correspondence o f ~ r o d u c t i on S e c t o r s and Commodity Aggregates

D i s t r i b u t i o n o f S e c t o r a l Val ue-Added t o F a c t o r s and Average Ra tes o f Return by C a t e g o r i e s ( m i l l ion CFAF)

Average Expendi tu res o f Household Groups, by Commodity Aggregates (CFAF)

Expendi ture on Goods and S e r v i c e s o f Household Groups, by Commodity Aggregates (mi 11 i o n CFAF)

D i s t r i b u t i o n of F a c t o r Income (va l ue-added) t o Household Groups (mi 1 1 i on CFAF)

LIST OF APPENDIX TABLES

Correspondence o f S e c t o r s

C a p i t a l Output R a t i o s

Em~lovment bv F a c t o r Ca teaorv and bv S e c t o r

FOREWORD

This working paper presents the detai 1s of a Social Accounting Matrix (SAM) developed for Cameroon. The SAM represents an empirical 1 y consi s- tent and disaggregated data framework, presented in matrix format, tha t 1 inks economic transactions according to classif icat ion of production ac t iv i t i e s , factors of producti on , inst i tut ions, and socioeconomic groups. I t shows we1 1 the re1 a t i onshi ps in Cameroon ' s economic system, including the spending patterns and income sources. The SAM organizes the data and presents a framework tha t will serve as the basis for analyzing the effects of policy reform in Cameroon, one of the countries included in a larger research project t o determine the impact of reform on macro perfor- mance and househol d-1 eve1 outcomes in sub-Saharan Africa being undertaken as part of a Cooperative Agreement between the Africa Bureau of the US Agency for International Development and Cornel 1 Food and Nutrition Pol icy Program (CFNPP) .

The SAM provides considerable information on the key flows in the economy tha t a f fec t various household groups in Cameroon. As such, i t i s extremely useful in providing insights into how development policies wi 11 affect both growth and poverty a1 l eviati on. Moreover, the SAM also provides a basis for developing a model that will a1 low pol icy makers to link adjustment policies t o distributional outcomes. Therefore, the purpose of undertaking the labor-intensive ac t iv i ty of developing a SAM for Cameroon was primarily t o provide the base for constructing a comput- able general equil i b r i m model (CGE) . The CGE wi 11 map pol icy options into the SAM-based framework t h a t re lates macro policy changes t o growth and distributional outcomes.

Future CFNPP research publication wi 11 present such a SAM-based C G E model along with policy simulations making use of i t fo r Cameroon. For more de ta i l s on e i ther the underlying conceptual basis of the research strategy or the macro-micro modeling framework, the reader i s referred to CFNPP monographs 1 and 5, prepared by Grant Scobie and Alexander Sarr i s , respecti vel y .

Ithaca, New York January 1991

David E. Sahn Deputy Director, CFNPP

1. INTRODUCTION

This paper p re sen t s a s o c i a l accounting mat r ix (SAM) f o r Cameroon, cons t ruc ted on t h e b a s i s o f 1984/85 d a t a . Intended a s a t o o l f o r ana lyz ing t h e s t r u c t u r a l re1 a t i onship between product ion p a t t e r n s and income di stri bu- t i on, i t p r e s e n t s a d i saggrega ted t r ea tmen t o f product ive s e c t o r s and soc i o- economic groups. The p r i n c i p a l sources of information f o r cons t ruc t ion of t h e SAM were t h e na t iona l accounts , a 31-sector i npu t /ou tpu t (I/O) t a b l e , a d e t a i l e d r e p o r t on t h e s t r u c t u r e of pub l i c e n t e r p r i s e s , and a na t iona l consumption and expendi ture survey. A SAM f o r Cameroon was assembled a t t h e World Bank i n t h e first ha1.f o f t h e 1980s (Benjamin and Devarajan 1985a and b) with t h e main o b j e c t i v e of ana lyz ing t h e r o l e of o i l product ion and expor t s i n t h e Camerooni an economy. Consequent1 y , t h i s prev ious SAM has an emphasis on product ion s e c t o r s and con ta ins l e s s information on income and consumption. In o r d e r t o address t h e d i s t r i b u t i o n a l i s s u e s set f o r t h i n t h e p r e s e n t s tudy , the cons t ruc t ion o f a new ma t r ix was requi red .

In t h e next s e c t i o n the s t r u c t u r e of t h e SAM and r e l a t i o n s h i p s between i t s components a r e d iscussed . This i s followed by a s e c t i o n on sources o f information and t h e i r use i n t h e cons t ruc t ion o f t h e mat r ix . F i n a l l y , a d e s c r i p t i o n of each of t h e p r i n c i p a l accounts comprising the SAM is p resen t - ed. Reconci 1 i a t i o n of t h e va r ious sources of information i s d iscussed i n t h e appendix.

' This input /output t a b l e was cons t ruc t ed by M. Kingnfi and M. Ngnenevit a t t h e D i rec t ion de l a S t a t i s t i q u e , i n t h e Minis t&re du Plan , which provided t h e i n f o m a t i o n f o r t h i s s tudy .

2. STRUCTURE AND DEFINITIONS I N A SAM

A SAM i s a square matrix divided in to submatrices or accounts. Although most SAMs have the same basic s t ruc ture , t he treatment of individu- a1 accounts, par t i cu la r ly i n terms of level of aggregation, var ies widely between s tudies . The deta i led s t ruc ture of a par t i cu la r SAM r e f l e c t s both the objective of t he analysis and data avai labi 1 i t y . The features of t he Cameroonian SAM assembled f o r t h i s study were determined primarily in order t o analyze income d is t r ibu t ion and t o serve a s t he basis f o r a computable general equi 1 i bri um model (CGE) .

There a r e s i x basic accounts i n a SAM: production, fac tor , household, government, cap i ta l o r f i nanci a1 , and foreign (rest-of -worl d) accounts. Table 1 presents a schematic representation of a SAM showing each of the accounts. Other accounts a r e often added f o r various reasons, such a s t o 1 ink two accounts, accommodate data di screpancies, o r t o ease the process of calculat ing and balancing a highly disaggregated account. In t he present case study, t he SAM contains two additional accounts: a marketing margin account, which i s a t r ans fe r account and red is t r ibu tes funds between sectors of production, and a commodity account, which l inks the household and production accounts.

Accounts appear in a SAM a t d i f f e r en t l eve l s of aggregation. Typical l y the government, c ap i t a l , and foreign accounts a r e included a t a more aggrega te 1 eve1 than production, fac tor , and in s t i t u t i on (household) accounts, which a re di saggregated before bei ng incorporated. The produc- t i on account depicts the supply s ide of t he economy and can be di saggregated in to sectors representing d i f f e r en t production a c t i v i t i e s . The f ac to r account del ineates the d i s t r ibu t ion of val ue-added resul t ing from these a c t i v i t i e s and hence t he functional d i s t r ibu t ion of income. I t can be di saggregated i n to various f ac to r s of production, such as labor, cap i ta l , or land. Finally, the household account r e f l e c t s t he d i s t r ibu t ion of income from fac tors across househol ds, and depicts expendi t u r e and savings. The disaggregation of the production account i s based on an 1/0 table . A1 though s t r i c t l y speaking, the production account includes more than intermediate input consumption, i t i s often referred t o as the 1/0 account. This termi no1 ogy i s adopted here.

-

Households can be included i n a 1 arger ' i n s t i t u t i o n ' account including pr ivate companies and the government. In t h i s SAM, however, companies, a s recipients of capi ta l value-added, a re not separated from households. Government was maintained as a d i f fe ren t category from households, a1 though i t i s 1 i kewi s e a consumer of f ina l goods. Therefore, i t seemed appropriate t o drop the term ' i n s t i t u t i o n ' , and instead, t r e a t both the government and households a s accounts ra ther than subaccounts. For fu r ther discussion on t h i s subject , see Pyatt and Round (1985).

3. DATA SOURCES

Three main data sources were used i n the construction of the SAM. The most important was an I/O table constructed in 1988 by the Mini s tere du Plan i n Cameroon (Tableau entree-sort ie , Government of Cameroon 1988) .3 T h i s I/O table is based on the 31-sector national accounts from the year 1984/85 (Government of Cameroon 1987a) .&

A second source provided valuable information fo r t h i s analysis: the Repertoire des entreprises du secteur public e t (feconomie M e (Government of Cameroon 1989), which itemizes companies owned i n part or in whole by the government .5 The distinction between pub1 ic-sector and pri vate-sector enterprises permits analysis of the effect of a reduction of the government sector on the economy and of privatization issues. These policies are an important and controversial component of structural adjustment reforms pursued in recent years. A great deal of e f for t was therefore devoted t o modifying the production account for the requirements of t h i s analysis and t o incorporating new information.

The third source of data used i n the SAM i s the survey Enquete-budget- consonmation (EBC), conducted by the Government of Cameroon in 1983/84 (Government of Cameroon unpubl i shed data f i 1 es) . Thi s study col 1 ected data on expenditure and revenues from over 5.000 households and also contains information on thei r demographic and soci oeconomi c characteri s t i cs . Survey data was not ent irely processed when the SAM was constructed and therefore only the data on demographics and expenditure were used. The survey was the source of information for di saggregating both the factor and the householdaccounts. Other sources of information were usedoccasionally t o f i 11 remaining gaps i n data. References on these sources are given in the text.

The original SAM constructed by Benjamin and Devarajan (1985a) was based on an 1/0 table fo r the year 1979/80. This 1/0 table was produced by a private firm a t the request of the Cameroonian government. I t i s based on the National Accounts of Cameroon, which comprise 31 sectors. Almost no documentation was re1 eased concerning the construction of the matrix, which restricted i t s usefulness for the current study.

Cameroonian national accounts use a f iscal year s tar t ing July 1.

This document i ncl udes information on ownership (shareholders) , 1 egal s tatus, revenues, and the number and types of employees.

See Lynch (1990) for a description of the EBC data se t and analysis of i t s s t a t i s t i ca l character is t ics .

4. THE SAM FOR CAMEROON

The 1/0 table fo r the year 1984/85 was used as the s ta r t ing point in assembling the SAM for three reasons: (1) I t i s based on the national accounts and provides consi s ten t data on production, f inal demand, trade, and government; (2) the data were considered the most re1 iable available; and (3) the table i s a s e t of balanced accounts. Moreover, the I/O table provided control to t a l s f o r rows and columns used in constructing the other accounts. EBC data were used t o disaggregate the factor and household accounts. Re1 a t i ve shares were then calcul ated and appl i ed t o aggregate figures from the 1/0 account to derive the f inal values entered i n the SAM. Since a l l accounts were consistent with one data source, the task of balancing matrices was minimi zed. More detai 1 s on procedures fol 1 owed t o construct the accounts are given in Section 5 and in the appendix.

Accounts were constructed in an order reflecting the degree of r e l i - ab i l i ty of the data. As accounts are assembled, discrepancies a r i se tha t force adjustments to the data. Different methods exis t t o balance individu- al accounts such as the 1/0 matrix, including computerized procedures. The commonly used RAS method, fo r instance, i s an algorithm tha t i te ra t ive ly adjusts the rows and the columns of a matrix unti 1 convergence i s reached (Dervis, de Melo, and Robinson 1982, 472)

A SAM i s based on the accounting principle of doubl e-entry bookkeeping and every row account has an equivalent column account. The convention i s tha t receipts t o accounts are read along the rows and outlays o r expendi- tures down the columns. Tables 2 and 3 present the SAM for Cameroon assembled in t h i s study. Table 2 is an aggregate table and contains values of the aggregate variables identified in Table 1. Table 3 i s the complete SAM for Cameroon with di saggregated accounts. Data aggregates shown in matrix entr ies (Tables 1 and 2) correspond to to ta l s of individual accounts and are subtotals in the 1 arger SAM (Tab1 e 3). Row and column t o t a l s are economy-wi de aggregates and represent economic identi t i e s . The basic identity of the 1/0 tab1 e , the total cost equation, can be read from column 1. The accounting equations underlying the SAM are presented in the appendix under "Accounting Ident i t ies of the SAM." Row t o t a l s m u s t equal corresponding column to ta l s and t h u s serve as controls for balancing the whole matrix. Subtotals in Table 3 are t o t a l s of individual accounts and

' See Pyatt and Roe (1977) and Dervis, de Melo, and Robinson (1982) for a discussion of t h i s issue.

Details on t h i s procedure can be found in Bacharach (1970).

s if!

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Table 3 {continued)

Food agriculture

Export agriculture

Forestry

Modern agriculture

Private food industries

Public food

industries

Private manufacturing

Public manufacturing

Construction

Private services

Pub1 ic services

&&total

Traditional agriculture

Other

agriculture

Forestry

Food products

Manufacturing products

Construction

Sew i ces

StAy total

Marketing

margins

Agr

+ informal unskilled

Formal u

nskilled

Ski 1 led

Highly skilled

Agriculture/capital

Other

capital

Sill-total

Farm north poorest

Farm south poorest

Farm north+south richest

Nonfarm poorest

Nonfarm richest

C i t i es poorest

Cities richest

Si*>

- total

Government

Capital

Rest

-of-

wrld

TOTA

L

Ta

ble

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con

tin

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t281

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91

C301

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ric

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092

681,

057

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lit-

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1 33

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6 61

2.05

0 53

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8 1,

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3,22

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77

are therefore equal t o the values reported in Table 2. Row and column to ta l s by accounts as well as the grand total are the same in both tables.

The definition of aggregates i s not always the same in a1 1 data sources; those used in the SAM correspond t o those recorded i n the national accounts. In the case of Cameroon, the foreign account 1 s highly aggregated w i t h only one import component appearing separately as a receipt from the commodity account (intersection of row VIII and column 11, in both Tables 1 and 2). The import component of other accounts i s included i n to ta l consumption (intermediate, final , and capital consumption). Sectoral marketing costs, depicted in the marketing margins (MM) accounts, are calculated in the I/O table as nonproductive ac t iv i t i e s and sum t o zero (see section on marketing margins) . The MM account i s thus shown w i t h a zero entry in Table 2. In Table 3, however, entr ies in t h i s account are nonzero and instead contain marketing margin costs di saggregated by sector.

5. DISAGGREGATED ACCOUNTS

PRODUCTION ACCOUHT

The production account was assembled from the 110 table based on the national accounts and from the document ~~~~~~~~~e on public-sector enterprises (see "Data Sourcesn above). The sectoral sp l i t of the produc- t ion account was achieved by f i r s t aggregating the 31 sectors of the I/O table (Government of Cameroon) into seven sectors: food agricul ture, export agriculture* forestry, food industries manufacturing industries, construc- t ion* and services (see the appendix under 'Procedures Used in Assembling the 110 Account'' for the l i s t of industries included in each aggregate sector (Appendix Table 1) . Second* based on information drawn from the document Mpertoire* four of the seven sectors were divided between publ i c and private components. These four sectors are export agriculture, food industries~manufacturingindustries~andservices~ This procedure resulted i n a total of 11 sectors in the 110 block of the f inal version of the SAM. Private and publ i c agriculture are shown on the tab1 e as export agri cu1 ture and modern agricultures respectively.

The Government of Cameroon I10 table (1988) was used as the s ta r t ing point in constructing the SAM as i t was a s e t of balanced accounts and provided much of the necessary data. The task of constructing the aggregate 110 table for the production account (Table 4) was done in two steps, F i rs t , each vari abl e (interned! a t e consumpti on f 1 ows and aggregate vari - ables) was aggregated into seven sectors and then was s p l i t into private1 pub1 i c act1 vi t i es in the four sectors concernedexport agriculture* food industries, manufacturing industries and services (see previous para- graph). The f i r s t step was straightforward but the second was more problematic since data on the publ i c sector was not available for a l l variables. In most cases, the value of production (gross output) was known, so production shares were used t o make the s p l i t ,

These shares were cal cu1 ated in the four sectors concerned as the r a t io of the output of one component (private or pub1 ic ) over the output of private and public combined, The use of production values as a sharing factor is just i f ied i f the vari able t o be di saggregated i s correlated with production. In some cases, a variable other than production was used instead (detai ls on these particular procedures are given in the appendix under 'Procedures Used in Assembling the I10 Account"), Some adjustments were made a1 so in sp l i t t i ng exports in manufacturing i ndustri es. These adjustments were necessary because oi 1 exports represent a 1 arge portion of total exports for the sector and the oi 1 industry i s largely control led by the public sector through the Soci4?te Nationale des Hydrocarbures (SNH) .

Table

4 -

Aggre

gate

Va

ria

ble

s o

f th

e 1

1-S

ect

or

Inp

ut/

Ou

tpu

t ~

cc

ou

nt(

mi1

lio

n CFA

F)

Pri

va

te

Pu

bli

c

Foo

d E

xpo

rt

Mod

ern

Food

Foo

d P

riv

ate

P

ub

lic

A

gri

- A

gri

- F

ore

s-

Ag

ri-

Indus-

Indu

s-

Man

ufac

- H

anufa

c-

Con

s-

Pri

va

te

Pu

bli

c

cu

ltu

re

cu

ltu

re

try

c

ult

ure

tr

ies

tr

ies

tu

rin

g

turi

rtg

tr

uc

tio

n

Se

rvic

es

Se

rvic

es

To

tal

Co

tm v

ari

ab

les

Inte

rme

dia

te

cons

umpt

ion

82

,689

10

5,21

9 82

,233

8,

139

224.

030

26,7

77

640.

100

97,5

30

156,

213

586,

601

206,

086

2,21

5,61

7 V

alu

e- a

dded

48

8,43

5 41

0,67

0 62

,005

27

,435

48

,866

5,

524

766.

873

128,

713

323,

016

1,30

5,45

7 35

7,04

1 3,

924.

1H5

Ind

ire

ct

taxe

s l,8

1a

a.98

0 14

,510

69

5 9,

377

1,11

0 66

,489

10

,692

15

,261

13

0,73

2 38

,965

~

98

,62

9

De

pre

cia

tio

n

15,3

91

4,01

9 8,

303

4,64

1 6,

264

741

76,2

51

12,2

61

9,34

1 46

,563

13

,878

19

7,65

3

Pro

du

ct io

n 58

8,33

3 52

8,88

9 16

7,05

1 40

,909

28

8,53

6 34

,153

1,

549,

713

249,

196

503,

831

2,06

9,35

3 61

6,77

0 6,

636,

734

Ma

rke

tin

g m

arg

ins

92.7

24

47,4

15

25,5

80

3,66

8 48

.919

5,

823

349.

693

42,2

70

58,7

76

-652

,606

-2

2,26

2 0

To

tal cost

681,

057

576,

504

192,

631

44,5

77

337,

455

39,9

76

1,89

9,40

6 29

1.46

6 56

2,60

7 1,

416,

747

594,

508

6,63

6,73

4

ROW

va

ria

ble

s

Inte

rme

dia

te u

ses

50.3

29

201,

578

47,5

45

15,5

92

35,8

89

4,50

2 84

9,01

1 14

3,53

1 15

,450

72

1,50

5 13

0,68

5 2,

215,

617

Hou

seho

ld c

on

stm

ptio

n

583.

421

123.

016

100.

697

9.51

5 31

1,01

0 36

,636

1,

269,

914

85,3

75

13.7

65

590,

106

99,4

55

3,22

2,91

0 G

over

nmen

t co

nsu

mptio

n

0 0

0 0

0 0

0 0

0 0

345,

326

345.

326

Ca

pit

al

form

ati

on

52

,503

0

13,1

46

0 0

0 27

1.20

4 6,

138

530.

200

55,6

49

10,0

80

939,

000

Va

ria

tio

n i

n s

tock

s 5.

838

-2.5

03

-278

-1

94

3,69

9 45

7 5,

171

918

3,19

2 0

0 16

,300

E

xpo

rts

6,09

2 27

3.01

7 31

,521

21

,118

17

,817

2,

214

266,

569

97.1

99

0 71

,409

12

,934

79

9.89

0

To

tal usest

698,

263

595,

108

192,

631

46,0

31

368,

415

43,8

09

2,66

1,86

9 33

3.16

1 56

2,60

7 1,

438,

670

59S

.4m

7,

539,

043

Sou

rces

: G

over

nmen

t o

f C

amer

oon

(196

6 an

d 19

89).

The procedure impl ic i t ly constrains the composition of intermediate inputs i n publ i c and pr iva te enterpr ises t o be the same. Further research could focus on potent ia l d i f ferences in intermediate technology. The 1/0 matrix of intermediate consumption flows f o r the 11 sec tors i s shown in the SAM (Table 3) a t the in te r sec t ion of rows and columns 1 t o 11.

Aggregate var iables from the 1/0 t ab le serve a s control t o t a l s and can be dist inguished between column variables (accountin f o r t o t a l cos t s of sectors) and row var iables (accounting f o r t o t a l uses 1 . Aggregate values f o r the 11 sec tors of the Cameroon SAM are presented i n Table 4. The column variables can be read down the columns of the production account as payments t o other row accounts. Total cost by sector is equal t o production cos t plus marketing margins. Production values en te r the SAM (Table 3) i n terms of cost components: intermediate consumption pl us val ue-added a t f a c to r cost pl us depreciat ion pl us i ndi r ec t taxes (producer taxes) . Intermedi a t e consumption i s the sum of intermediate flows and i s paid back t o production a c t i v i t i e s ( the f i r s t row subtotal of the production account i n Table 3 ) . Value-added a t f a c to r cos t includes returns t o both labor and cap i ta l a s we1 1 as other fac tors . Indirect taxes paid by producing sectors t o the government en te r Table 3 a t the in tersect ion with the government account (row 33) . Depreciation, f i n a l l y , i s the replacement cost of fixed capi ta l and en te rs as a payment t o the capi ta l account (row 34). Marketing margins a re paid by producers t o the service sectors . They en t e r a s posi t ive (as expenditure) in a1 1 sec tors , except in the two service sec tors where they a re shown as negative (as receipts) .

In every case where separately iden t i f i ed , p r iva te sec tors a re more important in terms of production than public sec tors , as can be seen i n Table 4. Since the other var iables (both column and row var iables) were spl i t between publ i c and pr ivate components based on production shares- except f o r val ue-added and depreciation (see appendix under " Procedures Used in Assembl i ng the 1/0 Account1')-the re1 a t i ve importance of pr ivate over publ i c sectors i s the same f o r a l l variables. Pr ivate services i s the l a rge s t sec tor both i n terms of production and value-added. Private manufacturing has a small e r production b u t a 1 arger intermediate consumpti on than pr ivate services . ' Production ' has a simi 1 a r val ue i n each of the two t rad i t iona l agr icu l tu ra l sec tors , as does 'val ue-added' , a1 though consump- t ion of intermediate inputs i s higher in the export agr icu l tu re sector . Marketing margin cos t s a re much higher in food agr icu l tu re than i n the export agr icul ture sec tor .

These sectoral d i f ferences are important as they determine d i f f e r en t pat terns of i n d i r e c t e f f e c t s ; f o r instance, given an equiproportional change in production, the ind i rec t e f f ec t on fac tor income wil l be more important i f the change or ig ina tes from the services sector r a the r than from manufac- tur ing. However, a change i n manufacturing production wi 11 have a re1 a t ive- 1y higher impact on intermediate demand and hence will induce production responses i n o ther sectors . These sectoral production changes will in turn a f f ec t fac to r income through a second round of i nd i r ec t e f fec t s . The d i s t r ibu t ion and magnitude of these ind i rec t e f f e c t s wil l depend on the

structure of intermediate demand, and can be measured within the SAM using multiplier analysis.

The row variables from the 11-sector I/O table (Table 4) account fo r total uses of sectoral production. Row variables can be interpreted in the production accounts (rows 1 t o 11) as revenues from other accounts. The sum of the s ix row variables equal total uses. Household consumption represents a1 1 private f inal demand of products and services not accounted el sewhere since i t i s calculated as a residual . Household consumpti on represents more than 80 percent of total uses of food agriculture and private and publ i c food industries production; by comparison, i t represents 50 percent of modern agriculture uses and 40 percent of private services. The importance of intermediate uses i n these other sectors i s significantly hi gher. By constructi on, government consumpti on i s di rected enti rely to public services. The government i s treated as a sector of ac t iv i ty (i ncl uded here in publ i c services) b u t without commerci a1 ac t iv i t i e s . Intermediate transactions and services not provided t o households are included as final consumption of publ i c admini s t rat ion.

Capital formation was selectively attributed t o certain ac t iv i t i e s of the original 1/0 table (Government of Cameroon 1988, documentation on pages 17-19) that are included in the aggregate 1/0 account i n food agriculture, forestry, manufacturing industries, construction, and services. Capital formation in the forestry and food agriculture sectors comes from production of 1 ivestock for breeding and from seed1 ings, which are considered t o be capital goods. We note tha t more than 90 percent of production in the construction sector goes to capital formation. The sum of capital formation and variation in stocks i s the total payment of the capital account to ac t iv i t ies (column subtotal 34 in Table 3).

Exports are assumed t o be shipped direct ly by producers and hence, unl i ke imports, are not trans1 ated into commodities. Exports are receipts to ac t iv i t i e s from the foreign account (row subtotal 35, in Table 3). The 1 argest export sectors, in absolute magnitude, are export agriculture and private manufacturing. In proportional terms, however, exports represent only 10 percent of private manufacturing production while they account for more than 45 percent in both the export agriculture and forestry sectors. In proportional terms, they are more important in publ i c manufacturing than private because of the importance of oi 1 exports, which are mainly under government control. There are no exports in the construction sector, which i s the only pure nontraded sector in t h i s SAM.

I n terms of accounting, i t should be noted that the difference between total uses and total cost of sectors i s made u p by imports and import duties, which are included in f inal demand i n t h i s 1/0 table (see accounting ident i t ies l i s ted in appendix). Imports are sold in the domestic market and thus are included in the SAM as commodities rather than production goods.

COWODITY ACCOUNT

The commodity account i s the 1 ink between demand (from households and the government) and the supply of goods and services in the economy. Demand i s met by goods produced domestically and by imports. This SAM does not distinguish between private and public sector goods and they are aggregated in the commodity categories. Although t h i s i s jus t i f ied i n some cases, in others, such as services, i t i s 1 i kely tha t consumers do in f ac t distinguish between private and pub1 i c provision of goods. Further research could investigate the possi bi 1 i t y of taking into account t h i s imperfect substi t u - t ion between private and pub1 i c production of goods a t a 1 a t e r stage of the model i ng process.

The breakdown into commodity categories was determined from EBC data (Government of Cameroon unpublished data f i 1 es) . D i saggregated household expenditure was a1 1 ocated t o seven categories consistent with production ac t iv i t ies . Table 5 shows the l i s t of commodity aggregates and the correspondence with the 11 sectors of production. These data were used t o construct the expenditure matrix discussed in the "Household Account" section below. The commodity account (rows and columns 12 t o 18, Table 3) includes in columns the matrix of domestic supply and vectors of imports and import duties; these are discussed below in t h i s section. In the rows, the commodi ty account i ncl udes the matrix of household expenditure and vector of government expenditure. These are discussed in the two sections below that deal with household and government accounts.

The matrix of domestic supply maps the demand for consumption commodi - t i e s into production of goods and services. I t i s included in Table 3 a t the intersection of the production and the commodity account. Matrix ent r ies represent payments t o production ac t iv i t i e s in the domestic market. They also correspond to the portion of domestic output tha t goes t o f ina l consumpti on and are effective! calculated as household and government consumption minus total imports I inclusive of import duties). Imports enter a t the intersection of the commodity and foreign accounts (row 35) and represent payments from the domestic market t o the rest-of-the world. Import duties a re paid t o the government and thus are found a t the intersec- t ion with the government account (row 33) .

Manufactured products constitute the largest component of imports and account for 88 percent of the t o t a l . Manufactured imports also represent almost 50 percent of consumption of manufactures. In contrast , imports account for less than 10 percent of consumption in the two food categories (1 and 4) . T h i s re f lec ts Cameroonf s high 1 eve1 of food sel f -suff ici ency . There are no imports of wood products o r construction. The forestry sector, however, has an export component.

See the appendix f o r the l i s t of EBC product codes included in each commodi ty category ("A1 l ocati on of EBC Expendi ture t o Commodity Catego- ries") .

-17-

Tab1 e 5 - Correspondence of Production Sectors and Commodity Aggregates

PRODUCTION SECTORS

Food agr icul ture

Export agr icu l tu re

Forestry

Modern agri cul t u r e

Food i ndustri es/pri vate

Food i ndustri es/publ i c

Manufacturing i ndustri es /pr i vate

Manufacturing i ndustri es/publ i c

Construction

Servi ces/pri vate

Services/publ i c

COMMODITY AGGREGATES

Traditional agri cul t u r e [I]

Other agr icu l tu re P I + Dl

Forestry 131

Food products P I + [61

Manufacturing products [7] + [8]

Constructi on PI

[lo1 + [ill Services

FACTOR ACCOUNT

The factor account i s a crucial component i n an analysis of d i s t r i bu- tional issues as i t l inks the production s ide of the economy t o household income. In a SAM, the households are the owners of factors of production, and returns from productive ac t iv i t i e s accrue direct ly t o the households according t o t h e i r factor endowment. The val ue-added accruing t o d i f ferent factor categories (that i s , various types of 1 abor, capital , 1 and, e t c .) are determined in the factor account. The factor account maps the value-added from production t o household income and t h u s depicts the socioeconomic aspect of the income distr ibut ion.

The construction of the factor account requires the determination of rates of return t o each category of factors, which necessarily l imi ts the number of categories tha t can be defined in a meaningful way. Data on wage rates as well as rental rates fo r capital and land are scarce in most developing countries. Th i s i s the case in Cameroon where no value fo r 1 and can be assigned and values for productive capital can be determined only imperfectly. Value-added i s therefore disaggregated into four categories of 1 abor and two categories of capital . Different rates of return are associated with each of these categories and the share of capital i s treated as a residual.

The factor account contains two components requiring an in t r i ca te task of disaggregation and data reconcil ia t ion. The f i r s t component i s the matrix allocating sectoral value-added t o factor categories. The second i s the matrix di s t r i buting val ue-added by factor categories to individual s by household group. This matrix will be discussed in the "Household Account* section be1 ow.

Three sources of data were used in assembling the factor account. Employment figures by 1 abor categories, sector of ac t iv i t i e s , and household groups were a1 1 derived from the EBC. Complementary figures on employment by labor categories i n public sectors were obtained from the document Repertoire (Government of Cameroon 1988) . Employment figures were obtained from the EBC, which contains occupational data in the demographic f i l e . These data are not suff icient t o describe the labor market fully. Thus the factor account in t h i s SAM (as in most SAMs) does not portray a labor market in a functional sense but merely a mapping of value-added from production ac t iv i t i e s t o household factor income. In t h i s respect, however, i t i s the key component of income determination.

Land markets, where they exis t , are unreliable guides t o t rue land values. Traditional forms of 1 and tenure make determination of contribution t o val ue-added very di f f i cul t .

Breakdown into Factor Categories

EBC data allowed estimates to be made of the number of people employed, the i r sector of ac t iv i ty , and the i r s k i l l level. The allocation of individuals to ski 11 categories was primarily based on job description and t o some extent on education level and job status." The functional differ- ence between ski 11 categories takes place i n terms of the ra te of return, a higher ski11 level being associated with a higher wage rate . This hierarchy in wages i s only parti a1 1 y associated with an equivalent hierarchy i n education 1 eve1 , t r a i ni ng, and experi ence. In practice we observe, for example, tha t a successful entrepreneur without formal education can earn an income similar t o tha t of a high-level government employee or a profes- sional. A1 1 three are then classified in the same labor category on the basis of a similar ra te of return for t h e i r labor.

The fol lowing four categories of labor associated with increasing wage rates are distinguished in the SAM: agricultural - and informal -sector unskilled labor, formal-sector unskilled labor, sk i l led labor, and highly skilled labor. Categories 1 and 2 are mutually exclusive: category 1 includes a l l labor in traditional agricultural sectors (sectors 1, 2, and 3 in Table 3 ) . without sk i l l distinction, as well as unskilled labor i n private services (sector 10 in Tab1 e 3). Unski 11 ed labor in a1 1 other sectors fa1 1 into category 2. A1 1 individuals involved in agriculture, except those employed i n the modern sector, are classif ied in category 1. The available data did not a1 low the definition of a separate category fo r hi red 1 abor in the traditional agricultural sector. This problem should not, however, be too serious in the case of Cameroon because hired labor represents only about two percent of to ta l labor in traditional agriculture (Government of Cameroon 1987b). Since data was available fo r the modern sector, which consists mostly of hired labor, the disaggregation into the three categories 2, 3, and 4 was performed. Unski 1 led labor from private services was included in a lower wage category in order t o capture informal - sector effects (lower rate of employment and lower wages). Evidence indicates tha t the predominance of informal market labor in t h i s category generates, on average, a lower rate of return.

Capital included the various assets used in production. There i s no consistent data on markets for productive assets i n Cameroon, and such markets are, in most cases, rudimentary. The data avai lable i s for capital stock by sector, which i s derived from figures on sectoral capital output rat ios (see section on the "Production Account" above and Appendix Table 2 ) . Capital stock i s assumed t o be fixed and immobi 1 e between sectors. Residual value-added accrues to capital and therefore rates of return to capital are sector-speci f i c. In order t o emphasize di fferences between capital i n agriculture and capital in other a c t i v i t i e s in Cameroon, there are two categories of capital in the SAM: "agricultural capital " pertains

' Job s ta tus categories included sel f-empl oyed, permanent wage earner, temporary wage earner, and apprentice.

t o sectors 1, 2, and 3; "other capi ta ln pertains t o a l l other sectors. In the factor account, however, capital simply receives the residual value- added (total val ue-added minus 1 abor val ue-added) in each sector, whether in agriculture or in other sectors.

D i stri buti on of Sectoral Val ue-Added t o Factor Categori es

The dis tr ibut ion of sectoral value-added t o the s ix factor categories was done in two steps. The f i r s t step was t o construct the matrix of sectoral employment . Empl oyment figures by 1 abor category were derived from the EBC for aggregate sectors of ac t iv i ty and from the Repertoire f o r di saggregated pub1 i c sectors. Detai 1 s on procedures used t o construct the employment matrix are given in the appendix section on "Determination of Employment Categories from the EBC." The second step was t o t ranslate t h i s matrix of employment into a matrix of value-added, using sectoral figures from the production account. This required some simplifying assumptions. Firs t , i t i s assumed that the number o f workers in each category i s constant b u t i s mobi l e between sectors of production within each category. Thus wage rates are always equal ized across sectors and val ue-added from 1 abor 1 n each sector depends on employment. Value-added that i s not due t o labor accrues to capital . Since capital stock i s fixed and immobile in each sector, the rental rate of capital varies between sectors.

Value-added by sector i s recorded in the original I/O (Government of Cameroon 1988) table in separate headings fo r wage b i l l and operating surplus (return to other factors of production). These data, however, did not match our definition of 1 abor and capital as values of operating surplus in every sector were much too large in comparison t o the wage b i l l . Wage bi 11, in t h i s context, refers t o hi red 1 abor and does not incl ude returns to self-employed 1 abor, which i s incorporated into operating surpl us. The two variables (wage bi 11 and operating surplus) were therefore added together under the heading of " total value-added a t factor cost." A s e t of factor shares in production was used to fur ther divide value-added between 1 abor and capital .I2

The a1 location of labor val ue-added t o the four different categories of workers was achieved through the procedure described here (see also the appendix under "Procedures Used in ~ssembling the 10 Account"), In i t i a l ly , a se t of four re la t ive wage weights was determined. Labor in category 1 was chosen as the numeraire. These weights were determined to ref lec t wage d i f ferent ia ls between 1 abor categories and t o be consi s tent both with available wage information and with wage and saving rates underlying the

l2 Labor/capital ra t ios in production were provided by 0. Blandford of the OECD (personal communication). These are as follows: food agriculture = 0.9, export agriculture = 0.8, forestry = 0.8, modern agriculture = 0.6, food industries = 0.7, manufacturing industries = 0.7, construction = 0.75, services = 0.85.

SAM framework. Multiplication of the matrix of employment by the r e l a t i ve weights (which a r e the same f o r a l l sectors) yielded a matrix of r e l a t i v e re turns expressed i n terms of category 1 labor. Employment shares f o r each labor category were calculated from the t o t a l return by sec tor obtained i n the weighted matrix. These shares were then multiplied by sectoral labor val ue-added derived from the 1/0 t ab l e (Government of Cameroon 1988). Hence a d i s t r i b u t i o n of sectoral val ue-added t o categories of labor and capi ta l was obtained. These f igures a r e presented in Table 6 along with impl ied wage ra tes and average r a t e s of return t o cap i t a l . These r a t e s a r e calculated as the r a t i o of t o t a l value-added (across sectors) t o t o t a l employment of capi ta l stock by category.

The la rges t group in terms of employment is category 1 (agr icul tural and informal unskil led); in terms of value-added, however, the sk i l l ed worker category i s more important. Looking a t sectors , the la rges t value- added i s generated i n pr ivate services , predominantly from ski 11 ed labor, which represents 50 percent of t o t a l value-added in t h a t sector . Private manufacturing industr ies generate the la rges t capi ta l value-added outside agr icu l tu re and account f o r more than 35 percent of the t o t a l of t h a t category. The average r a t e of return t o each f ac to r category is given on the bottom 1 ine. Returns t o capi ta l in agr icu l tu re a re higher than in other sectors . T h i s can be seen as evidence t ha t re turns t o agr icul tural land a re impl i c i t l y incorporated in re turns t o agr icu l tu ra l cap i ta l f o r these sectors . The matrix depicting the d i s t r ibu t ion of value-added t o f ac to r categories i s included in the SAM (Table 3) a t the intersect ion of the f ac to r account (rows 20-25) and the production account (columns 1 t o 11).

HOUSEHOLD ACCOUNT

The household account depicts the demand s ide of the SAM. Households a re both the owners of fac tors of product

economy i n the on. from which i -

most of t h e i r income i s generated, and the main consumers of goods produced a t home and abroad. Household income i s e i t h e r saved o r consumed. Savings accrue t o the capi ta l account, w h i 1 e consumpti on i s di saggregated i nto categories of goods and services , t rans la t ing t o demand f o r goods produced i n the economy.

l3 Verification a t this stage was necessary t o ensure t h a t the d i s t r ibu- t ion of val ue-added t o f ac to r categories yielded consis tent values f o r wage r a t e s and average r a t e s of return on fixed cap i t a l . This check was performed by dividing to t a l val ue-added (across sectors) e i t h e r by t o t a l empl oyment o r by capi ta l stock category, yi el di ng under1 yi ng r a t e s of return t o factors . Adjustments t o weights were then made t o ensure t h a t r e l a t i ve re turns t o ski 11 categories ref lected the ascending pat tern observed empirically.

Tab

le 6 - D

istr

ibu

tio

n o

f S

ect

ora

l V

alue

-Add

ed t

o F

act

ors

and

Ave

rage

Rat

es o

f R

etu

rn b

y C

ate

go

rie

s (m

illi

on

CFA

FI

Ag

ric

ult

ure

+

Info

rma

l F

orm

al

Hig

hly

A

gri

cu

ltu

re

Oth

er

To

tal

Un

skil

led

U

nski

1 le

d

Sk

ille

d

Sk

ille

d

Ca

pit

al

Ca

pit

al

Val

ue-A

dded

(11

Food a

gri

cu

ltu

re

439,592

0 0

0 48,844

0

488.435

(21

Exp

ort

ag

ric

ult

ure

328,536

0 0

0 82,134

0 410,671

[31

Fo

rest

ry

49,604

0 0

0 12,401

0 62

,-

t41

Mod

ern

ag

ric

ult

ure

0

13,762

1,173

1,526

0

10,974

27,4

34

Bl

Pri

va

te f

oo

d i

nd

ust

rie

s 0

8,227

25,979

0.

0

14,660

48.-

t63

Pu

bli

c fo

od

in

du

stri

es

0 2,796

537

534

0 1,657

5,524

(71

Pri

va

te m

an

ufa

ctu

rin

g

0 139,758

343.469

53 , 584

0 230,1162

766,

873

t81

Pu

bli

cma

nu

fact

uri

ng

0

45,465

25,960

18,675

0 38,614

128,713

[91

Co

nst

ruct

ion

0

159,026

64.833

18,403

0 80.754

323,016

[I01

Pri

va

te s

erv

ice

s 58,800

0 647,790

403,048

0

195,818

1,305,457

[I 13

Pub1 ic

se

rvic

es

0 127,867

73,528

102,769

0 53,676

357,6&1

To

tal

valu

e-ad

ded

876,532

496,901

1,10

,2W

599.

539

143,379

626,215

3,924s5

tap

~o

ye

nt/

ca

pit

al s

tack

4,085,246

272.432

am

97

.9l6

1,967,683

9,731.9S9

Ave

rage

re

turn

214,560

1.623.W

5,08

3,36

0 6,112,783

72,134

64.3

46

Sou

rces

: G

over

nmen

t o

f C

amer

oon (1988

and

un

pu

blis

he

d d

ata

f i

les

CEBG

1).

Breakdown I n t o Househol d Groups

The d i saggregati on of the household account i nvol ved t he speci f i c a t i or o f funct ional groups according t o one o r more socioeconomic c r i t e r i a . This task i s c ruc i a l f o r an ana lys is o f income d i s t r i b u t i o n and the select ion o f household groups should a1 low d i f f e r e n t i a t i o n o f as many o f the detenni - nants o f t h i s d i s t r i b u t i o n as possible. Several c r i t e r i a o f household c l a s s i f i c a t i o n are d i scussed i n the l i tera tu re (Hayden and Round 1983). Two are commonly used, sometimes as a s ing le c r i t e r i o n t o c l a s s i f y house- holds, and can be a t t r i b u t e d t o d i f f e r e n t approaches t o the study o f income d i s t r i bu t i on .

The f i r s t del i neates a household c l assi f i c a t i on according t o income percent i le , thus emphasizing the s t a t i c aspect o f income d i s t r i b u t i o n . The second c r i t e r i o n speci f i e s household groups based on f a c t o r ownership (Dervi s, de Me1 o, and Robinson 1982) and concentrates on income de r i ved from fac to r ownership, emphasizing the funct iona l aspect of income d i s t r i bu- t ion.I4 To the extent possible, the grouping i s based on a combination o f s t a t i c and funct iona l c r i t e r i a , i nc lud ing socioeconomic charac te r i s t i cs such as r u r a l /urban sp l it, e thn ic groups, agroecologi ca l d i fferences between regions, and i n general any f ac to r t h a t i s a source o f unequal access t o the means o f production.

The EBC was used t o disaggregate the household on the basis o f a combination o f charac te r i s t i cs . Households were f i r s t c l a s s i f i e d according t o a poor / r ich c r i t e r i o n . Total expenditure (on goods, durables, services, and value o f home consumption) was used as a proxy f o r household revenues due t o the lack o f ava i lab le data on household income. A l l expenditure var iables were de f la ted using a regional commodity p r i c e index i n order t o account fo r d i f fe rences i n cost o f 1 i v i n g between regions. Per cap i ta income qu in t i l e swe rede r i ved from the de f la ted household t o t a l expenditure. Households i n the two bottom q u i n t i l e s were then c l a s s i f i e d as poor, whi l e households i n the top three q u i n t i l e s were c l a s s i f i e d as r i c h .

Socioeconomic character i s t i c s o f households were used t o complete the c l ass i f i ca t i on . These cha rac te r i s t i c s were chosen according t o t h e i r relevance t o the Cameroon case. Two geographical c r i t e r i a were re ta ined i n order t o capture regional income d i s ~ a r i ti es. F i r s t , households were d iv ided i n two groups: " r u r a l " and "Ye mdE-Douala" (urban). The second c r i t e r i o n appl i ed on ly t o r u r a l poor households, which were d iv ided between

l4 When income from abroad (remittances, t ransfers , etc.) i s important, domestic factor ownership w i 11 no t be an accurate i n d i c a t o r o f income d i s t r i bu t i on . However, i t w i 11 capture changes i n income d i s t r i b u t i o n r e s u l t i n g from s h i f t s i n domestic production, which i s the most important determinant o f i ncorne v a r i a t i on.

north and south.15 A f i na l c r i t e r i on was used t o capture di f ferences in functional determinants of income: rural households were divided between agr icul tural and nonagricultural on the basis of whether o r not the head of t he household was a farmer.

Table 7 shows the breakdown of household groups in the SAM. Shares of t o t a l average expenditure a r e given a s an indication of t he r e l a t i v e income underlying this household c l a s s i f i ca t i on . The d i s t r ibu t ion follows an expected pattern: urban households have higher expenditure shares than rural households; poor households in Yaounde-Doual a have a r e l a t i ve ly high share i n average expenditure (15 percent) compared t o rural households, and only the r iches t nonagricul t u r a l households (20 percent) have a higher share. This seems t o ind ica te t h a t the poor i n l a rge urban areas may be re la t ive ly be t t e r off than i n rural areas a t l e a s t in terms of average expenditure. The th ree poorest groups in rural areas have s imi la r expendi - t u r e shares (7-8 percent). Most farm households, however, produce agri cul- tu ra l goods t h a t they can consume a t home. A1 though adjustments were made t o take home consumption in to account i n calculat ing household expenditures, i t i s probably underestimated. I f so, expenditure shares of farm households should be somewhat higher. I t i s important t o note t ha t s ince farm households with home consumption a re l i ke ly t o be l e s s affected in t h e i r consumption pattern by increases i n food pr ices than a re nonfarm households, t he l a t t e r group is po ten t ia l ly more vulnerable t o economic recession or pol ic ies affect ing food markets.

The treatment of household account involved two main tasks. One was t o determine household consumption in terms of goods and services produced domestically; this i s t o construct the mapping between the household and the production block in Table 3. The second was t o determine household endowment of fac tors of production in order t o construct the mapping w i t h the f ac to r account. We wi 11 f i r s t discuss the construction of the expendi - t u r e matrix and then t u r n t o the discussion of the f ac to r income matrix.

Derivation o f t he Expenditure Matrix

Households a re the main consuming agents of f ina l goods i n a SAM. The expenditure matrix depicts to ta l household demand, which included both imported and/or domestically produced goods by commodity category and by household group. Data on imports by commodity i s obtained from the national accounts and a1 1 ow derivation of the demand f o r domesti c a l l y produced goods. T h i s demand i s included i n t he matrix of domestic supply f o r the commodity account (see "Commodity Account" section above). In order t o build the expenditure matrix, data from both the national accounts and the EBC were required: the data on household f ina l demand by commodity category was

" Cameroon i s divided i n t o 10 administrat ive provinces. Based on these, the north region i n the SAM includes t he f a r nor th and the northern provinces, and the south includes a1 1 the r e s t .

Tab

le 7

- A

vera

ge E

xpe

nd

iture

s o

f H

ouse

hold

Gro

ups,

by

Com

mod

ity A

ggre

gate

s (C

FAF)

[*I

121

r31

c41

[SI

r61

m

Farm

Fa

rm

Farm

N

onfa

rm

Non

farm

Y a

ound

h/

Yao

unde

/ N

ort

h

Sou

th

N+S

N+S

N+

S O

ouaL

a O

oual

a P

oore

st

Poo

rest

'

Ric

he

st

Poo

rest

R

ich

est

P

oore

st

Ric

he

st

To

tal

111

Tra

dit

ion

al

ag

ric

ult

ure

366,965

187,663

444,360

185,066

453,938

230.884

372,539

2,241.413

t21

Oth

er a

gri

cu

ltu

re

15,303

60,434

98,053

61,886

134,302

61,995

79,525

511.499

El

Fo

rest

ry

267

235

1,452

2.115

5,351

. 10,178

10,0

75

29,6

72

(41

Foo

d p

rod

uct

s

[Sl

Ma

nu

fact

uri

ng

161

Co

nst

ruct

ion

9,016

17.1%

23,425

17,880

38.964

120,312

173,098

Wf.m

t71

Se

rvic

es

5,911

44,712

40,047

48,854

87,020

157,717

298,429

682.

690

To

tal

m.m

421.914

800,961

456,871

1.136.213

866,437

ls6Z9,fi3i?

5,781.135

Sha

re o

f to

tal

(pe

rce

nt)

0.

06

0.07

0.14

0.08

0.20

0.15

0.28

1.00

Mur

tier

of

hous

ehol

ds

159,275

322.327

523.077

127,503

241,394

11,053

155,647

1,540,274

Sou

rce:

G

over

nmen

t o

f C

amer

oon

un

pu

blis

he

d d

ata

f i Le

s.

obtained from the national accounts, whi 1 e the disaggregation by household group was derived from EBC data. For each household group, expend! t u re data on goods and services was aggregated i n t o the seven commodity categories defined in the commodity account. Since the number of households per group var ies , average f igures were calculated by dividing expenditure by category by the number of people i n each household group. The shares of each household group i n to ta l average expenditure by commodity category were then calculated. These shares were applied t o the I/O data (Government of Cameroon 1988) t o yie ld the d i s t r ibu t ion of f ina l demand by commodity aggregates and household group.

The expenditure matrix is shown i n Table 8. The share of each house- hold group i n t o t a l average household demand i s shown on the bottom l i n e of the table . This d i s t r ibu t ion is comparable t o the one obtained from EBC data, discussed in the previous section (see a l so Table 7 ) . On a disaggre- gated level , we can see t h a t demand f o r t rad i t iona l agr icul tural products (category I ) , which includes basic food products, ranges from 8-10 percent f o r the poorest households t o 17-20 percent f o r the r iches t households. Poor households from the north account f o r 16 percent of basic food to t a l demand, a share substant ia l ly higher than t h a t of other poor household groups. T h i s can be explained by the f a c t t h a t they produce mostly s tap le food, i n contras t t o farm households i n the south, which a re involved t o a 1 arger extent i n export agr icul ture (cocoa, coffee, and tobacco, included i n category 2) . Moreover, farm households from the north spend more than 75 percent of t h e i r t o t a l expenditure on category 1 (shares are calculated from EBC data and a re not shown in the t ab l e ) , which shows a large depen- dence on consumption of own production. The r iches t farm households (group 3) from both the no r th and the south consume 55 percent of t h e i r t o t a l expenditure in category 1. This share i s subs tan t ia l ly lower f o r urban households a t around 25 percent of t o t a l expenditure.

Demand f o r processed food products comes mostly from the two r iches t household groups (5 and 7). which together account f o r 52 percent of t o t a l f ina l demand of t ha t commodity category. Demand f o r manufacturing and services comes mainly from these two groups as well, although poorer households in Yaounde-Douala a lso account f o r a s ign i f ican t share of t o t a l f i na l demand of these two commodity categories.

D i stri buti on of Factor Income t o Househol ds

The second task i n assembling the household account i s the mapping from the fac tor account t o the household account. T h i s requires the t rans la t ion of val ue-added from production into household income by group.

The number of workers and t h e i r employment category i n each household group were determined from the EBC data. Differences in household s i z e were taken i n t o account by dividing these f igures by the number of people in each household group. This yielded a tab le depicting the average number of workers by labor category and by household group. The shares of each

Ta

ble

8 -

Exp

en

dit

ure

on

Goo

ds a

nd S

erv

ice

s o

f H

ouse

hold

Gro

ups,

by

Con

mod

ity A

gg

reg

ate

s (m

ill i

on

CFA

FI

111

r21

r31

[41

is1

161

c71

Farm

Fa

rm

Farm

N

onfa

rm

Non

farm

Ya

ound

e/

Y aou

ndd/

N

ort

h

So

uth

N

+S

N+S

N+S

D

ou

ala

D

du

ala

P

oo

rest

P

oo

rest

R

ich

est

P

oo

rest

R

ich

est

P

oo

rest

R

ich

est

T

ota

l

111

Tra

dit

ion

al

ag

ric

ult

ure

95,518

48,847

115.663

48,171

118,156

60,097

96.969

SB3.421

121

Oth

er

ag

ric

ult

ure

3,965

15,659

25,406

16,035

34,798

16,063

20,605

132.531

131

Fo

res

try

[&I

Foo

d p

rod

uct

s

151

Ma

nu

fact

uri

ng

(61

cons t

rk

t i on

ITS

Se

rvic

es

To

tal

153.693

20&, 145

343,181

235.

938

612,050

532,118

1,139,TO5

3,222,910

Share

of

tota

l (p

erc

en

t)

0.05

0.06

0.11

0.07

0.19

0.17

0.35

1 .00

Sou

rce:

G

over

nmen

t o

f C

amer

oon (1988

and

un

pu

blis

he

d d

ata

fil

es

[E

BC

I).

household group i n t o t a l l abor by category were then calculated. These shares, f i n a l l y , were appl i e d t o val ue-added by category, as given by the f ac to r account t o obta in a mat r i x o f value-added by labor category and by household group.

The procedure f o r a1 l oca t i ng cap i ta l value-added was based on the assumption t h a t only r i c h households own cap i t a l . A l l r e tu rns from product ive c a p i t a l therefore accrue t o three categor ies o f households. Ag r i cu l t u ra l cap i t a l i s a1 1 ocated t o the r i ches t farm households (group 3). Other cap i t a l i s a1 located t o t he r i ches t nonfarm r u r a l households and the r i ches t urban households i n the propor t ion o f 25 and 75 percent, respect ive- l y . Thus a complete mat r i x of value-added by f a c t o r category and by household group was obtained. This matr ix i s shown i n Table 9. The bottom 1 i ne o f t h i s t a b l e shows the share of each household group i n t o t a l value- added. The d i s t r i b u t i o n i s , i n general, as expected. We observe t h a t the d i f fe rence between poor and r i c h households i s much l a r g e r i n urban areas than i n r u r a l areas.

Tab

le 9

- D

istr

ibu

tio

n o

f F

act

or

Inco

me

(val

ue-a

dded

) to

Hou

seho

ld G

roup

s (m

illi

on

CFA

F)

[TI

(21

[31

[41

C51

[6Y

t73

Farm

Fa

rm

Farm

N

onfa

rm

Non

farm

Ya

@/

Yao

unde

/ N

ort

h

Sou

th

N+S

N+S

N+

S O

oual

a

Dou

ala

Poo

rest

P

oore

st

Ric

he

st

Poo

rest

R

ich

est

P

oore

st

Ric

he

st

To

tal

HI

Ag

ricu

ltu

re

info

rma

l un

ski 1

led

26

1,79

8 26

8,45

6 19

2,93

1 65

,176

25

,397

'

45,1

51

17,6

23

876,

532

(21

For

mal

un

sk

ille

d

8,45

4 16

,543

11

,906

99

,534

89

,381

16

0,89

3 11

0,18

8 49

6.90

1

(31

Sk

ille

d

0 16

,800

13

,713

19

6,79

5 25

5.43

0 30

3,68

0 39

6,85

2 1.

183.

269

C41

Hig

hly

sk

ille

d

C51

Ag

ric

ult

ure

ca

pit

al

(61

Oth

er c

ap

ita

l 0

0 0

0 15

6,55

4 0

469,

661

626.

215

To

tal

270.

2S3

306,330

363,

725

471.

5%

681,

180

653,

513

1,17

8,23

9 3,

924,

835

Sha

re o

f to

tal

(pe

rce

nt)

0.

07

0.08

0.

09

0.12

0.

17

0.17

0.

30

1.00

Sou

rce:

ti

vern

men

t o

f C

amer

oon

(198

8 an

d li

sh

ed

da

ta f

ile

s).

6. AGGREGATE ACCOUNTS

MARKETING MARGIN ACCOUNT

The marketing margin account, shown in row and column 19 of Table 3, represents differences between producer costs and consumer out1 ays. These margins include transport and hand1 i ng costs, intermediaries ' fees, etc., and are proportional t o production. The 110 table for Cameroon (Government of Cameroon 1988) was constructed in such a way that marketing margins in each sector are paid t o one sector (commerce) that i s included in private services in the aggregate 110 account. Marketi ng margins are not considered t o be productive act iv i t ies (although they are the o u t p u t of one sector) and therefore are treated in a separate account. From th i s perspective, the account reveals positive entries for sectors paying a margin and negative entries for sectors receiving payments, and as a result the row sum of sectoral marketing margins i s zero. The corresponding column i s empty, however, since bo th payments and receipts are included in the row account.

GOVERNMENT ACCOUNT

The government account appears in row and column 33 of the SAM (Table 3 ) . The row account depicts government revenues, which are generated by taxes paid by the various agents (Table 1). A1 1 figures on tax revenues are derived from national accounts data. Indirect taxes paid by producers are the major source of revenues for the government (Tables 2 and 3) and are included in the 110 table. Import taxes, or t a r i f f s , are shown a t the intersection with the commodity account. Figures for direct taxes paid by households from factor income were obtained from the national accounts. The disaggregation by household group was based on the assumption that a single average tax rate applied t o every household group. The rate was calculated as the rat io of aggregate direct taxes to aggregate household income, net of transfer (that i s , aggregate factor income) and i s equal to 0.49.

The column for th i s sector depicts government expenditure. This i s divided into final consumpti on, transfers, and savings (Tab1 e 1). Govern- ment consumption of goods and services i s fully translated into demand for public services (Table 3). This treatment follows that in the original I10 table. The aggregate figure on government transfers i s obtained from the national accounts. Most government transfers in Cameroon are given in the form of pub1 ic employee benefits. Since government employees are mainly members of household groups 5 and 7, a11 transfers accrue to these two groups. Government savings, f inally, are treated as a residual and

therefore a re equal t o the di f ference between government revenue (from taxes) and government expenditure (consumption plus t r ans f e r ) . Government revenue i s derived from taxes and thus can vary endogenously (as production and income change). Government expenditure, however, i s f ixed and can only be changed exogenously. T h u s changes in government savings a r e f u l l y determi ned by revenues.

C A P I T A L ACCOUNT

The capi ta l account appears in row and col umn 34 of t he SAM (Tabl e 3) . The row account represents t he various sources of savings i n the economy whi 1 e the column account represents investment expenditure. There a r e four components of savings: depreciat ion, househol d savings, government savings, and foreign savings. Depreciation i s paid by production sec tors as rep1 acement cos t s on fixed capi t a l . Sectoral depreci a t i on i s i ncl uded i n the 1/0 t ab le and i s shown i n Table 4. These data a re a l so discussed i n the appendix .

Household savings a r e determined f o r each household group as the di f ference between income and expenditure. A1 though household savings a r e f i r s t cal cul ated a s a residual , they a r e important var iables i n an analysi s of income d i s t r i bu t i on . Saving r a t e s and average propensity t o save spec i f ic t o each household group can be derived from these f igures . Government revenue i s derived from taxes and thus can vary endogenously (as production and income change) . Government expendi t u r e , however, i s f ixed and can only be changed exogenously. Thus government savings a r e f u l l y determined by revenues. Final l y , foreign savings a r e calcula ted as an overall residual between i nvestment and domestic savings by househol ds and government, and can be negative a s i s t he case here, showing t h a t Cameroon invested abroad in the year 1984/85. This i s due t o Cameroon's cap i ta l surplus from oi 1 revenues, which was t o a 1 arge extent saved i n foreign accounts. Oil exports s t a r t e d t o decline a f t e r 1985 as o i l reserves decl i ned. In more recent years, the country has experienced foreign account defi c i ts and net overseas borrowi ng .

The column capi ta l account dep ic t s investments i n the economy. Invest- ments have two components: cap i ta l formation and var ia t ions in stocks. These are combined in the SAM and appear a t t he in te r sec t ion of column 34 and rows 1 t o 11 in Table 3. Thus they a re read as payments t o production sectors . These f igures were obtained from the 110 t ab l e (Government of Cameroon 1988) and a re par t of t o t a l uses of production goods (Tabl e 4). While stocks can be accumulated in any sec tor producing commodities, only some sectors produce capi ta l goods f o r investments. They a re included in sec tors 1, 3, and 7 t o 11. In food agr icul ture ( sec tor 1) and fo r e s t ry ( sec tor 3 ) , production of capi ta l goods comes mainly from breeding 1 ivestock and t r e e crop nurser ies ; i n manufacturing indus t r i es (sectors 7 and 8), a var ie ty of capi ta l goods are produced, mostly equipment and materi a1 s; almost a1 1 production of the construction sec tor ( sec tor 9) goes t o cap i t a l formation as buildings a re c l a s s i f i e d as capi ta l goods; in the services

sectors (sectors 10 and 111, real es ta te and various types of land and building improvement services are considered t o be capital goods and t h u s add t o capital formation. In Table 3, export agriculture and modern agriculture show negative entr ies . This imp1 i e s tha t variation in stocks was negative tha t year (these sectors do not produce capital goods) and capital was borrowed from the r e s t of the economy.

FOREIGN ACCOUNT

The foreign account appears i n row and column 35 of the SAM (Table 3). This account i s highly aggregated with only imports of consumption goods and services disaggregated. These are recorded in the commodity account as discussed above i n the "Commodity Account"secti on. Imports of i nterme- d ia te goods used in production are included i n to ta l intermediate consump- tion in the 1/0 account (row and column 1 t o 11) and do not form a separate account. Exports are read from column 35 and are assumed to be shipped direct ly by production sectors. They are included as to ta l uses of products (see the "Production Account" section above and Tab1 e 4). The l a s t entry of t h i s account i s foreign savings, discussed above. Foreign capital bridges the gap between imports and exports. Since Cameroon had a trade surplus in 1984/85, i t s foreign capital account i s i n de f i c i t by the same amount.

APPENDIX

PROCEDURES USED I N ASSEMBLING THE 110 ACCOUNT

Value o f Product ion

The value o f p roduct ion i s taken f rom t h e n a t i o n a l accounts f o r t h e seven aggregate sectors. For t h e f o u r p u b l i c sectors, t h e value o f t u r n - over,16 as g iven by t h e document Repertoire (Government o f Cameroon 1989), was used as a proxy f o r t h e va lue o f product ion. We can i d e n t i f y two problems i n making such an approximation. F i r s t , t u rnove r w i 11 r e f l e c t t h e value o f p roduct ion if t h e r e i s no i nven to ry v a r i a t i o n f rom beginning t o end o f the per iod. Therefore, t h e smal le r t he average r a t i o o f i n v e n t o r y t o p roduct ion o r t h e 1 ess v a r i a b l e i n v e n t o r i e s are, t h e more accurate t h e f i g u r e s f o r our purposes. Secondly, d iscrepancies can a r i s e i n t h e case o f a t r u s t f i r m o r an umbrel la o rgan iza t i on if p a r t of t h e a c t i v i t i e s o f t h e dependent f i r m s i s i n c l uded i n t h e tu rnover o f t h e head company. Thi s p a r t i c u l a r p rob l em was encountered w i t h t h e soci a1 s e c u r i t y organi z a t i on, Caisse Nationale de Prevoyance Sociale (CNPS). Turnover i n Repertoire amounts t o 50,221 m i l l i o n CFAF w h i l e p roduct ion i n t he n a t i o n a l accounts amounts t o 8,198 m i 11 i o n CFAF. CNPS i s an umbrel 1 a o rgan iza t i on and manages a l a r g e budget t h a t inc ludes funds f o r a c t i v i t i e s t h a t i t does n o t per form i t s e l f . The value o f p roduct ion as g iven by the n a t i o n a l accounts was used i n t h i s case.

Aggregat ion o f t h e 31-Sector 110 Table

The 1/0 t a b l e i n 3 1 sec tors was aggregated i n t o 12 groups f o l l o w i n g t h e d e f i n i t i o n o f sec tors i d e n t i f i e d i n t h e SAM (Appendix Table 1).

P r i v a t e n o n p r o f i t serv ices and domestic serv ices (D.S.1-respective1 y sec t ions B-2 and C o f sec to r 31-were t r a n s f e r r e d t o the aggregate s e c t o r 10 ( p r i v a t e serv ices) i n t he SAM. The values o f p roduct ion and i n te rmed ia te consumption f o r these two serv ices were g iven i n t h e n a t i o n a l accounts and cou ld be d i r e c t l y subt rac ted f rom sec to r 31 (group X I I ) and added t o group X. In te rmed ia te f lows i n column 31 were d i v ided on t h e bas i s o f t h e r e l a t i v e share o f these serv ices i n p roduct ion o f sec to r 31. There i s no in te rmed ia te use o f sec to r 31 ( o f e i t h e r pub1 i c admin i s t ra t i on , n o n p r o f i t

l6 Turnover i s t rans1 ated f rom chiffres d'affaire and corresponds rough ly t o gross revenue.

-34-

Appendix Table 1 - Correspondence of Sectors

Group Sectors of t he SAM Sectors of the 110 Tablea

I I I

I I I I V v

V I VII

VIII I X x

XI XI I

a The numbers r e f e r t o those production a c t i v i t i e s defined in National Accounts of Cameroon (see t he "Lis t of Production Act iv i t i es" sect ion be1 ow) .'

services , o r domestic s e rv i ce s ) . Furthermore, i n terms of t o t a l uses of sec tor 31, f i na l consumption of nonprofit services were included in government consumpti on of domestic consumpti on; f i na l consumpti on of domestic services was included i n household c o n s ~ m p t i o n . ~ ~ In the SAM, f ina l consumpti on from both services i s incorporated in household consump- t ion of pr ivate services .

Sectors t h a t could be d i r e c t l y i den t i f i ed as e i t h e r r i va t e o r public were kept separate (e.g., groups IV, VI, VIII, X , and XI1 ? ; otherwise they were combined i n t o aggregate sec tors (groups 11, V , VII, and XI). These aggregate sec tors were then s p l i t using r e l a t i v e production shares.

Production Share Factors

Production share fac tors were calcula ted f o r four aggregate sectors : export agr icu l tu re (2/4), food indus t r i es (5/6), manufacturing indus t r i es (7/8), and services (10111) . These a r e equal t o t he val ue of turnover f o r public-sector en te rpr i ses (from the document Repertoire) divided by the

l7 These f igures can be found i n the national accounts.

value of product ion f o r t h e agg rega te s e c t o r (from t h e I/O Table) . The c a l c u l a t i o n s a r e a s fo l lows ( f i g u r e s a r e i n m i 11 ion CFAF) :

Export a g r i c u l t u r e (2/4) : 40,909/569,798 = 0.072 Food i n d u s t r i e s (5/6) : 34,153/305,021 = 0.112 Manufacturing i n d u s t r i e s (7/8) : 188,367/1,613,788 = 0.117 Se rv ices (10/11) : 244,086/1,591,673 = 0.153

Spl i t i n Val ue-added

A s i m i l a r procedure was used wi th employment f i g u r e s i n s p l i t t i n g val ue-added between p r i v a t e and pub1 i c s e c t o r s . These f i g u r e s were der ived from EBC and from t h e document Repertoire ( s e e t h e "Fac to r Accountu s e c t i o n ) . Employment s h a r e f a c t o r s were app l i ed t o wage b i l l f i g u r e s of t h e 1/0 t a b l e ( a s given by t h e nati 'onal accounts) whi le ope ra t ing s u r p l u s was sp l i t using product ion sha re s . These two v a r i a b l e s were f i n a l l y combined ( a s t o t a l s e c t o r a l n e t value-added) before assembling t h e f a c t o r account . Ca lcu la t ions of employment s h a r e f a c t o r s a r e t h e f o l l owing:

Export a g r i c u l t u r e (2/4) : 38,113/2,224 = 0.017 Food i ndus t r i e s (5/6) : 4,697/20, 572 = 0.228 Manufacturing i n d u s t r i e s (7/8) ; 11,050/59,039 = 0.187 Se rv ices (10/11) : 172,716/502,166 = 0.344

Spl i t i n Depreciat ion

A more appropr i a t e f a c t o r t o use i n s p l i t t i n g dep rec i a t ion between s e c t o r s should be based on c a p i t a l s t o c k r a t h e r than product ion. Value of c a p i t a l s tock by s e c t o r i s ob ta ined by t h e formula:

where k t i s t h e c a p i t a l ou tpu t r a t i o i n s e c t o r i . Capi ta l ou tpu t r a t i o s a r e der ived from Benjamin and Devarajan (1985b, 42) . Due t o d i f f e r e n c e s i n aggregat ion, t h e s e f i g u r e s need t o be r e l a t e d t o t h e 11 s e c t o r s o f t h i s SAM. The correspondence between t h e two s e c t o r a l breakdowns i s a s f o l 1 ows:

f o r manufacturing i n d u s t r i e s and s e r v i c e s , where our SAM i s a t f i r s t more aggregated, a weighted average o f t h e r a t i o s was c a l c u l a t e d using production va lues a s weights;

f o r t h e p r iva t e /pub l i c s p l i t , t h e same r a t i o was assumed i n food indus- t r i e s , manufacturing i n d u s t r i e s , and s e r v i c e s ;

i n t h e a g r i c u l t u r a l s e c t o r , i t was assumed t h a t t h e r a t i o i n t h e modern s e c t o r was twice a s l a r g e a s i n t h e t r a d i t i o n a l expor t a g r i c u l t u r e s e c t o r .

Sec to ra l c a p i t a l o u t p u t r a t i o s and c a p i t a l stocks18 a r e shown i n Appendix Table 2. We assumed t h a t t h e r a t e o f c a p i t a l d e p r e c i a t i o n was t h e same i n p r i v a t e and pub1 i c s e c t o r s and s p l i t d e p r e c i a t i o n c o s t s between two s e c t o r s t h e f o l l o w i n g way:

When t h e r a t i o s a r e t h e same i n bo th p r i v a t e and p u b l i c sec to r s , t h e second t e r m i s 1 and t h e procedure s i m p l i f i e s t o t h e use o f r e l a t i v e p r o d u c t i o n shares. I n t h e case o f t h e combined s e c t o r 2/4, however, t h e second t e rm i m p l i e s t h a t some adjustment was made f o r t h e d i f f e r e n c e i n c a p i t a l p r o d u c t i o n r a t i o between t h e p r i v a t e and p u b l i c sec to r s .

I n d i r e c t Taxes and I m p o r t Taxes

I n d i r e c t and i m p o r t t axes were s p l i t u s i n g t a x r a t e s . We assume t h a t these r a t e s were t h e same i n t h e p r i v a t e and p u b l i c s e c t o r and c a l c u l a t e d t h e r a t e s t h a t app l y t o s e c t o r s as aggregates. Tax r a t e s i n bo th cases were m u l t i p l i e d by r e s p e c t i v e va lues o f p r o d u c t i o n t o o b t a i n t h e amount o f t axes p a i d i n each sec to r .

Appendix Table 2 - C a p i t a l Output Ra t i os

Sec to r s k K ( m i l l . CFAF)

[I] Food a g r i c u l t u r e [2] Expor t a g r i c u l t u r e [3] F o r e s t r y [4] Modern a g r i c u l t u r e [5] P r i v a t e f ood i n d u s t r i e s [6] P u b l i c food i n d u s t r i e s [7] P r i v a t e manufac tu r ing i n d u s t r i e s [8] Publ i c manufac tu r ing i n d u s t r i e s [9] Cons t ruc t i on [ l o ] P r i v a t e s e r v i c e s [ll] Publ i c s e r v i c e s

Ki = ki Qi.

Adjustments t o Exports

Adjustment f o r o i l exports was made i n manufacturing sectors where re1 at ive shares of private and publ i c industries d i f f e r s ignif icant ly from those of nonoil exports. I t i s estimated tha t 40 percent of o i l export revenues go t o the SocitW National e des Hydrocarbures (SNH) , which i s a publ i c enterprise. Thus, using re1 at ive production shares (88 percent of aggregate production i s private and 12 percent publ i c ) t o spl i t exports in the manufacturing industry woul d resu l t in an underestimation of the publ ic - sector share. Oi 1 export revenues (evaluated a t 204,666 mi 11 ion CFAF in the national accounts) were subtracted from to ta l exports of the aggregate sector 7/8; nonoi 1 exports were then spl i t proportional ly t o production shares, while o i l exports were s p l i t i n the proportion of 40~60.

ACCOUNTING IDENTITIES OF THE SAM

Col umn Identi t i e s

Total cost = intermediate consumption +marketing margins + value-added a t factor cost + indirect taxes + depreciation

Production = intermediate consumption + value-added a t fac tor cost + indirect taxes + depreciation

Domestic absorption = domestic supply + imports + import duties

Domestic supply = household f inal demand + government final demand - (imports + import duties)

Value-added a t fac tor cost = factor income = labor value-added + capital val ue-added

Household expenditures = f inal demand + direct taxes + savings

Government expenditures = f inal demand + t ransfers t o households + savings

Total investment = capital formation + variation in stocks

Total exports = exports of goods and services + foreign savings

Foreign savings = trade balance = imports - exports

Row Identities

[k] Total uses = domestic o u t p u t + imports + import duties

[I] Domestic o u t p u t = intermediate consumption + domestic supply + capital formation + variation in stocks + exports

[m] Domestic sales = household final demand + government final demand

[n] Household income = factor income + transfers (from the government)

[o] Government revenues = indirect taxes + import taxes + direct taxes

[p] Total savings = depreciation + household savings + government savings + foreign savings

[q] Household savings = household income - household expendi tures

[r] Government savings = government revenues - government expenditures

[s] Foreign savings = capital account balance = total savings - total investments

DETERMINATION OF EMPLOYMENT CATEGORIES FROM THE EBC

The EBC survey records an employment code number, referring to a t i t l e o r a type of job (from a code book), and a sector of activity for a l l working individuals covered. For the purpose of constructing the factor account, only active people were exami ned-that i s , people who were employed during the preceding week, whether a t a wage-earning or a t a self-employed job. Using the employment code description, the sector of activity, the education level, and the status in the job, every individual was a1 located to one of five sectors of activity:

Agri cul ture, Food i ndustri es,

[I l l ] Manufacturing industries, [IV] Construction, or [V] Servi ces;

and assigned one of four employment categories:

[i] Agricul tural , [ i i] Unskilled, [ i i i ] Skilled, [iv] Highly skilled.

Individuals assi gned to employment category i could be a1 1 ocated only . t o ac t iv i ty sector I ; the three other employment categories could be

a1 located t o any of the f ive sectors of ac t iv i t ies . The two character is t ics in combination were used t o determine the corresponding number of individu- a l s per labor category and (aggregate) sectors of production in the SAM. Sectoral employment was further broken down into 11 sectors. T h i s required dividing agricultural employment between four sectors and food industries, manufacturing , and services between private- and publ i c-sector employment.

The document Repertoire contains figures on the number of employees by categories in publ i c-sector enterprises. Three types of empl oyees are di stingui shed: workers, trained workers, and manageri a1 s t a f f . They were considered t o be of types i i , i i i , and iv, respectively. For food industry and manufacturing industry sectors, the data were complete. For services and agriculture, however, other sources of information had to be found i n order t o compensate for missing data. In the f i r s t case, di saggregated data on publ i c administration employment (as part of sector 11, publ i c services) was lacking. The figure on total number of government employees was obtained from the International Monetary Fund document; a breakdown by labor types, however, could not be found. Me applied re la t ive shares between categories, calculated from publ i c-service enterpri ses data (from the Repertoire) t o government employment.

In the second problematic case, the EBC figure on to ta l employment in agri cul ture had t o be spl i t between four sectors: food agri cul ture, export agriculture, modern agriculture, and forestry. The three t radi t ional sectors (food agriculture, export agriculture, and forestry) have no breakdown into 1 abor types and therefore only to ta l employment figures were needed. However, in the modern sector, t h i s breakdown exis t s as i t i s composed of 1 arge publ i c enterpri ses. Employment by categories i n that sector was obtained d i rec t ly from the Repertoire, Note tha t unskilled 1 abor in the modern sector agriculture i s included in category i i , tha t i s , "formal sector unskilled labor." For the forestry sector, the data was obtained from off ic ia l sources in Cameroon. After subtracting employment in the modern sector agriculture and forestry, we were 1 e f t with a figure corresponding to employment in both sectors i and i i . This figure was spl i t between export agriculture and food agriculture in proportion t o the number of farms in each category as reported in the agricultural census (Government of Cameroon 1987b):

Total number of farms in the traditional sector: 1,155,500 Number of export crop farms with sales: 630,200 Ratio number of export crop farm t o total number

of farms : 0.55

Thus 55 percent of residual employment was allocated t o export agricul- ture. The final dis tr ibut ion of employment by labor category and by production sector are shown in Appendix Table 3.

Appendix Table 3 - Employment by Factor Category and by Sector

Agriculture + Informal Formal Highly

Unski 1 led Unski 1 led Ski 1 led Ski l led Total

111 Food agriculture 121 Export agriculture [31 Forestry [41 Modern agriculture [51 Private food industry [61 Public food industry 171 Private manufacturing t81 Public ~anufacturing t91 Corwtruction El01 Private services t i l l Public services

Total 4.Oa5.246 272.432 232.773 97.916 4,6iEi,367

ALLOCATION OF EBC EXPENDITURE ITEMS TO COMMODITY CATEGORIES

Commodity Category Product CodesE

[I] Wadi tional agricultural products 1, 2, 9-12,14-15, 17-21, 23-26, 30, 37-, 44-46, 57;

[2] Other agricultural products 3, 22, 31-35, 47-48, 54-55, 59; [3] Forestry 74-75, 80; [4] Food products 4-8, 13, 16, 27-29, 36, 43, 49-52; [5] Manufactured goods 53, 56, 58. 60-69, 72-73, 76-79,

82-88, 94-98; [6] Constructi on Imputed rent ib [7] Services 81, 89-93, 99-103.

a These codes re fer t o the first-round aggregation 1 i s t of products and expenditures selected in the EBC.

Imputed rent i s determined f o r each household, e i the r homeowner or renter . I t was allocated to the category construction on the ground tha t rent and mortgage expenditure f ina l ly t rans la tes into demand f o r construction.

DATA AMENDMENT I N THE I / O TABLE

The I/O table used i n constructing the SAM was a preliminary version and contained some errors. They were corrected with the best available information and i n order t o balance the matrix. These amendments a re reported here.

1. The sum of intermediate flows of sector 20 exceeded to ta l interme- d ia te consumption (column sum) by 28 mi1 lion CFAF. This amount was subtracted from the three largest individual intermediate flows according to the i r share in to ta l intermediate consumption of sector 20:

11 million was subtracted from sector 19 14 mi11 ion was subtracted from sector 20 3 mi 11 ion was subtracted. from sector 29 2,723-3=2720] .

To maintain the row identi t i e s , househol d consumpti on in these three sectors was increased by equi val ent amounts subtracted from total intermediate use (row sum). Household consumption i s , by construction, a residual in to t a l use of sectoral production.

2. Total intermediate use (row sum) of sector 2 exceeded the sum of intermediate flows by 2 m i 11 ion CFAF. The to ta l entry was corrected and in order t o maintain the row ident i ty , the same amount was subtracted from household consumption.

3. Total intermediate use (row sum) of sector 28 exceeded the sum of intermediate flows by 32,370 million CFAF. The source of t h i s large discrepancy was found t o be the resul t of an inconsistency in the account (see below). So the entry was corrected and household consumption was increased by the same amount t o maintain the row identity.

4. The sum of intermediate uses ( total of row sums) exceeded the sum of intermediate consumptions ( total of column sums) by 32,400 mi1 lion CFAF. This amount corresponds t o what i s recorded in the national accounts as adjustments for financial intermediaries ." I t refers t o the difference between value of production and receipts in sector 28 (financial in s t i tu - ti ons) . This amount was added in the I/O tab1 e t o total intermediate use of sector 28 b u t not allocated t o individual intermediate flows. After making the three corrections reported above, to ta l intermediate ses equal to ta l intermediate consumption. The adjustments for financial i r vnediar- i e s , included in to ta l uses of sector 28, were thus transferred t o household f i nal demand.

L I S T OF PRODUCTION A C T I V I T I E S I N THE 1/0 TABLE OF CAMEROON'^

[I] Agricultural crop production [Z] Agricultural production f o r industry and exports [3] Breeding and hunting [4] Fishing [5] Forestry and logging [6] Mining and quarrying [7] Production of f l o u r and vegetables [8] Processi ng of agr icul tura l products [9] Bakery, pastry, and fancy pastes production [lo] Other food production [ll] Beverage and tobacco production [12] Text i le and apparel production [13] Shoe and l ea the r industry [14] Processing of wood and wood products (including fu rn i t u r e manufacture) [15] Paper and paper goods production, pr int ing , and pub1 i shi ng [16] Processing of chemical s and chemi cal products (except rubber) [17] Rubber and p l a s t i c production manufacture [18] Production of construction mater ia ls [19] Basic metal indus t r i es [20] Fabricated metal products, machinery, and equipment manufacture [21] Fabricated t ranspor t equipment manufacture [ZZ] Other manufacturing indus t r i es [23] E lec t r i c i ty , gas, and water [24] Construction [25] Wholesale and r e t a i l t rade [26] Restaurant and hotel t r ades [27] Transport, s torage, and communi c a t i on i ndustri e s [28] Financi a1 i n s t i t u t i o n s 1291 Real e s t a t e and business services 1301 Services [31] 13-1) Pub1 i c admini s t r a t i o n s

B-2) Producers of pr ivate nonprofi t services t o households C) Domestic services of households

j 9 The English names of production sec tors come from the National Accounts of Cameroon (1984/85), which a r e presented both i n French and in Engl i sh.

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