Constraints on the Rural Non-farm Economy: An Analysis of the Hand Loom Sector

Constraints on the Rural Non-farm Economy: An Analysis of the Hand Loom Sector

Gezahegn AyeleEthiopian Development Research Institute (EDRI)

Lisa MoormanInternational Food Policy Research Institute (IFPRI)

Co-authors:

Jordan ChamberlinKassu WamishoXiaobo Zhang

October 23, 2009Ethiopia Strategy Support Program-II (ESSP-II)

Policy Conference 2009

ETHIOPIAN DEVELOPMENT

RESEARCH INSTITUTE

• Rural non-farm development is a strategic priority for DCs during their economic transformation from an agricultural to industrial society

• Rural non-farm development plays a role in generating local employment and linking with other sectors in developing countries (Haggblade et al. 2007).

• Rural non-farm development is particularly relevant to the Ethiopian context, emphasized in the Agricultural-Development Led Industrialization (ADLI) Strategy.

• The second PRSP- Economic Development’s Plan for Accelerated and Sustained Development to End Poverty (PASDEP) (2005/06-2009/10) further emphasizes the importance of this sector.

Background: Motivation of the study

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE – ETHIOPIA STRATEGY SUPPORT PROGRAM

There is a knowledge gap in how nonfarm activities are organized in rural areas, particularly with respect to the impact of infrastructure development.

To address this gap, this study examines the differences between urban and rural, electrified and non-electrified handloom weaving clusters.

The few studies of clustering within Ethiopia to date have maintained a geographical focus on the capital city of Addis Ababa and nearby areas (Abdella and Ayele 2007; Sonobeet al. 2006).

Objectives


This paper investigates issues related to rural industrial clusters through an in-depth case study of handloom clusters in Ethiopia (non-farm economy).

Research Questions


In particular, our study addresses the following questions:

• Does infrastructure impact rural/urban linkages?

• Does infrastructure impact firm network structure?

• Does infrastructure impact firm productivity?

The selection of the handloom sector was guided by three main characteristics:

• First, it is the most important non-agricultural source of income in the country (Central Statistics Agency 2003a), and the most important employer of rural families for livelihood after agriculture.

• Second, it is a traditional cotton value chain-based activity with strong patterns of geographically clustered handloom activities.

• Third, it is one of the few non-agricultural sectors with a discernable presence in both urban and rural areas.

This sector also produces semi-finished and finished goods for domestic consumption and processing as well as for international markets.

Why Handloom?


• In this study, we surveyed three urban clusters in Addis Ababa and six rural clusters in the southern part of Ethiopia

• The list of handloom weavers used for the study was given by the Medium and Small Scale Manufacturing desks of the urban kebeles and rural woreda

• Our sample comprised 488 producers and 154 traders

• Using this data, we mapped out the production structures and linkages among producers and traders.

• Detailed production data enable us to compare cluster performance both through labor productivity and working hours across different types of clusters

• The survey was conducted in May and June 2008

Survey Methodology


Study Sites (2008)• Addis Ababa: Shiro-Meda, Adisu-Gebeya, Kechene-Medhaniyalem

• Chencha woreda, Gamo Gofa Zone, SNNPR: 6 sites

Sample population

Sample size

% from sample

population size

Chencha woreda 12045 293 2.4

Electrified towns 7948 142 1.8

Chencha town 1774 52 2.9

Ezo town 2305 38 1.6

Dorze town 3869 52 1.3

Non-electrified towns 4097 151 3.7

Deco-mecho 1584 66 4.1

Mesho 493 20 4.1

Kale 480 20 4.1

Shaye 264 11 4.1

Losha 347 14 4.1

Zozo 922 44 4.8

Setena borche 430 20 4.8

Boyena tupa 239 11 4.8

Gendo gembela 253 12 4.8

Shama 1591 41 2.5

Shama town 829 21 2.5

Webera 762 19 2.5

Total 12045 293 2.4


Of the 50 kebeles in Chencha woreda, only 10% were classified as “electrified”

by the woreda administration.

Source: Ethiopian Atlas on the Rural Economy (2004)

Addis Ababa

%Rural

Electrified%

RuralNot

Electrified%

Producers 195 145 146

Household 109 56% 72 50% 114 78%Rented workspace 74 38% 72 50% 32 22%

Workshop 12 6% 0 0% 0 0%

Traders 97 52 5Shop 77 79% 1 2% 0 0%

Market 20 21% 43 83% 5 100%Roadside market 0 0% 8 15% 0 0%

Total 292 46% 197 31% 151 24%

Sample Composition (2008)


Addis Ababa Network Structure (2008)

Inputs Producers Initial Sales Final Sales


Electrified vs. Non-Electrified Network Structure (2008)

Electrified Clusters Non-Electrified Clusters




Addis Ababa Electrified Not Electrified

Producer Trader Producer Trader Producer Trader

Average value of starting capital (ET Birr)

194 6560 95 1332 115 1,660*

Average value of starting capital (USD)

22 732 11 149 13 185

Sources of starting capital (average % of starting capital coming from each source) Own savings 48.4 67.4 45.3 80.2 41.3 80.0

Borrowing from friends or family

27.4 22.0 34.5 10.2 43.2 20.0

Gift from family 19.1 5.7 18.6 5.8 14.8 0.0

Loan from microfinance 2.0 2.9 0.0 3.9 0.0 0.0

Loan from bank 0.0 0.0 0.0 0.0 0.0 0.0

Starting Capital (2008)

*Only 5 traders were found in the non-electrified sites, so this average reflects only 5 observations, compared to 52

for rural electrified and 97 for Addis Ababa.


Most Common Product Types


-20%

0%

20%

40%

60%

80%

100%


Other products

Kuta

Other traditional clothes

Linen

Shawl

Netella

Gabi

Kemis

Production and Profit (2008)


Producer Trader Producer Trader Producer Trader

Average sales price of 1 unit of most important product (ET Birr)

116.1 130.3 56.3 46.0 47.9 28.2

Cost of raw materials for 1 unit of most important product (ET Birr)

69.4 -- 39.4 -- 33.5 --

Average monthly production (in units*)

25.3 -- 15.6 -- 14.8 --

*Unit = one finished product (e.g. gabi, netella, shawl, etc.)


10.3

1.8

10.7

1.3

7.2

1.7

0.0

2.0

4.0

6.0

8.0

10.0

12.0

Hours Worked Per Day (Average)

Average number of workers per enterprise

Addis Ababa

Electrified

Not Electrified

Productivity Measures (2008)


4,427

14,859

2,544

8,461

1,796

6,021

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Average annual value added per

worker

Average annual revenue per worker

Addis Ababa

Electrified

Not Electrified

Labor Productivity (ET Birr/Worker) (2008)


8.9

5.3

8.4

4.2

8.0

4.3

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

Fixed Assets Plus Cost of Raw Materials and Operational Costs

Fixed Assets/Labor

Addis Ababa

Electrified

Not Electrified

Capital/Labor Ratios (2008)


Addis Ababa

Chencha* P-Value ElectrifiedNot

ElectrifiedP-Value

Hours worked per day (average) 10.3 9.0 0.001 10.7 7.2 0

Average number of workers per enterprise

1.8 1.5 0.003 1.3 1.7 0

Average annual revenue per worker 14,859 7,237 0.000 8,461 6,021 0.021

(In ET Birr/worker)

Capital/Labor Ratio 8.9 8.2 0.000 8.4 8.0 0.000

(Fixed Assets Plus Cost of Raw Materials and Operational Costs)

Average annual value added per worker

4,427 2,169 0.000 2,544 1,796 0.086

(In ET Birr/worker)

Capital/Labor Ratio 5.3 4.3 0 4.2 4.3 0.084

(Fixed Assets/Labor)

*All rural clusters, as a whole.

Note: Value added = revenue - fixed and variable capital costs + wage + taxes. 1 USD = 8.96 ET Birr. “Electrified” vs. “Not Electrified” indicates small towns or villages located in SNNPR.

Productivity Measures


(1)

(2)

Y = annual sales revenue for top three products

L = number of workers contributing to production

K = sum of fixed assets, operating costs, and annual cost of raw

materials

X = vector of enterprise type and community and infrastructure controls

ε is an error term

= annual value added for top three products

= total amount of fixed assets per enterprise

Value added is defined as the annual sales revenue of the three most

important products less the annual cost of raw materials and operational costs.

Specifications


Revenue/Labor Value Added/Labor

AllAddis Ababa

Chencha (1) Chencha (2) AllAddis Ababa

Chencha(1)

Chencha(2)

LN[(K + CORM)/L] 1.004*** 0.970*** 1.030*** 1.030*** 0.292*** 0.305*** 0.336*** 0.338***

(0.020) (0.032) (0.027) (0.027) (0.057) (0.082) (0.096) (0.097)

Electrified -0.042 -0.040 -0.043 0.175 0.213 0.209

(0.028) (0.027) (0.029) (0.139) (0.143) (0.145)

Addis Ababa 0.065** 0.461***

(0.032) (0.147)

Year Established 0.003*** 0.005*** 0.001 0.001 0.007* 0.018*** -0.002 -0.002

(0.001) (0.002) (0.001) (0.001) (0.004) (0.006) (0.005) (0.005)

Rented Workspace -0.029 -0.004 -0.044 -0.052* 0.206 0.091 0.236 0.224

(0.026) (0.050) (0.027) (0.030) (0.130) (0.247) (0.153) (0.167)

Workshop -0.085 -0.039 0.370 0.335

(0.071) (0.077) (0.348) (0.376)

Healthcenter 0.026 0.035

(0.035) (0.150)

Constant -5.545*** -8.479*** -2.740 -2.833 -8.538 -28.716** 8.933 8.784

(1.861) (3.066) (2.193) (2.205) (8.305) (12.711) (10.080) (10.185)

Adjusted R-Squared 0.919 0.892 0.920 0.920 0.215 0.201 0.066 0.063

AIC 94.688 80.974 3.515 4.751 1417.979 538.485 877.034 878.971

Observations 480 190 290 290 472 185 287 287

Regression Analysis: Producer Productivity


Value Added/LaborBottom Third Middle Third Top Third

Fixed Assets/Labor 0.535* 1.291*** 0.450

(0.283) (0.387) (0.303)Electrified 0.552** 0.546** -0.286

(0.234) (0.267) (0.271)Year Established -0.002 -0.002 0.001

(0.009) (0.009) (0.010)

Rented Workspace 0.780** -0.325 0.076

(0.316) (0.284) (0.278)Healthcenter -0.379 0.143 0.483*

(0.249) (0.250) (0.261)Constant 9.432 4.779 3.600

(18.293) (17.101) (18.875)

Adjusted R-Squared 0.184 0.058 0.028

AIC 278.667 296.584 302.721Observations 94 98 95

Segmented Regression AnalysisAttempt to capture differences between groups of producers, for the Chencha subsample.

Note: The sample for Chencha was divided into thirds based on the size of the capital to labor ratio. The symbols

"*", "**", and "***" stand for significance levels of 10%, 5%, and 1%, respectively. “Electrified” vs. “Not Electrified”

indicates small towns or villages located in SNNPR.

Robust standard errors are in parentheses.


Nonparametric Analysis – Chencha SubsampleIllustrating productivity differences between groups of producers

78

910

Ln

(Reve

nue

/Lab

or)

6 7 8 9 10 11Ln(Capital/Labor)

No electricity Electricity

Chencha Revenue/Labor on Capital/Labor


Note: Value added is defined as annual sales revenue of the three most important

products less annual cost of raw materials and operational costs.

66.5

77.5

8

Ln

(Va

lue

Add

ed/L

abo

r)

2 3 4 5 6Ln(Capital/Labor)

No electricity Electricity

Chencha Value Added/Labor on Fixed Assets/Labor

Nonparametric Analysis – Chencha SubsampleIllustrating productivity differences between groups of producers


• Infrastructure expands the options available to producers and traders.

– Networks are more complex.

– Linkages between rural clusters and urban markets are stronger.

Concluding Thoughts


• Electricity plays an important role in handloom weaver productivity, particularly for the rural portion of the population.

– Rural producers with access to electricity work, on average, 49% longer hours than do those without access to electricity.

– Rural producers with access to electricity also earn 41% more revenue per worker per year, and 42% more value added per worker per year.

– After controlling for enterprise age, capital to labor ratio, type of enterprise, and infrastructure, small-scale electrified rural producers are 55% more productive than their non-electrified counterparts.

Concluding Thoughts, cont.


Constraints on the Rural Non-farm Economy: An Analysis of the Hand Loom Sector

Technology

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