Constraints on the Rural Non-farm Economy: An Analysis of the Hand Loom Sector
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Transcript of 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
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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
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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
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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?
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• 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
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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
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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)
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Addis Ababa Network Structure (2008)
Inputs Producers Initial Sales Final Sales
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Electrified vs. Non-Electrified Network Structure (2008)
Electrified Clusters Non-Electrified Clusters
Inputs Producers Initial Sales Final Sales
Inputs Producers Initial Sales Final Sales
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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.
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Most Common Product Types
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-20%
0%
20%
40%
60%
80%
100%
Addis Ababa Electrified Not Electrified
Other products
Kuta
Other traditional clothes
Linen
Shawl
Netella
Gabi
Kemis
Production and Profit (2008)
Addis Ababa Electrified Not Electrified
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.)
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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)
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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)
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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)
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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
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(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
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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
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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.
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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
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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
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• Infrastructure expands the options available to producers and traders.
– Networks are more complex.
– Linkages between rural clusters and urban markets are stronger.
Concluding Thoughts
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• 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.
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