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This is about "State and Growth Linkages of Non-farm Activities in Rural Bangladesh: A Case of Comilla Sadar Upazila". Poster paper presented at Doctoral Seminar during 15-17 October 2008, ...

This is about "State and Growth Linkages of Non-farm Activities in Rural Bangladesh: A Case of Comilla Sadar Upazila". Poster paper presented at Doctoral Seminar during 15-17 October 2008, Daisen, Tottori University, Tottori, Japan



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Ph D Presn Slides For Daisen Poster Ph D Presn Slides For Daisen Poster Document Transcript

  • Title State and Growth Linkages of Non-farm Activities in Rural Bangladesh: A Case of Comilla Sadar Upazila BY Mohammad Abdul Malek Managerial Economics Division The United Graduate School of Agricultural Sciences Tottori University Attachment: Yamaguchi University Major Supervisor: Professor Koichi USAMI, PhD Doctoral Seminar, Daisen , Tottori University 15-17 October 2008
  • Problem statement
    • In Bangladesh, recently livelihood diversification has become one of the major challenges.
    • The Government of Bangladesh in its national poverty reduction strategy paper (PRSP) has identified the non-farm sector (NFS) as a “leading sector” in the rural economy.
    • But in practice the NFS is not getting due attention like the agricultural sector (hereinafter farm sector).
    • Doubts, however, continue to persist about the employment generation and growth potentials of the NFS due to lack of information on types of activities, the nature of their operation and the constraints and opportunities (Hossain, 2004).
    • Hossain (2004), World Bank (2005) and Nargis and Hossain (2006) studies provided some overview on non-farm employments (NFEs) and livelihood changes mainly from late eighties to nineties.
    • Some studies (for example, FAO, 2002) argued that the understanding on linkages between farm and non-farm activities (NFAs) in rural areas are critically important which could be helpful to promote sustainable livelihoods without hampering farm sector growth, promote rural industrialization, reduce migration, narrow down rural-urban income gap and reduce rural poverty.
    • In this context, understanding state and available growth linkages in NFAs could be a worth clue for the development of NFS.
    • Objective
    • To enrich state of NFAs and
    • To assess available growth linkages between farm and NFAs in rural areas.
  • Farm/ non-farm Linkages Production linkages Consumption linkages Farm linkages Non-farm linkages Forward (Farm/Non-farm) Backward (Farm/Non-farm) Forward (Farm/Non-farm) Backward (Farm/Non-farm) Theoretical Linkages related with farm/non-farm activities Agricultural growth linked NFAs, by sector, extd. from Start (2001) Domestic services, transportation, sales of domestic goods Household items, home improvements Consumption Agricultural and veterinary services Agricultural tools and equipments Production: Backward Transportation and trade Processing and packaging industries, construction of storage and marketing facilities Production: Forward Tertiary Sector (Trading and services) Secondary sector (Construction and manufacturing) Linkage
    • Traditional dual economic theory (Lewis, 1954; Fei and Ranis, 1964; Jorgenson, 1967) paid little or no attention to NFS.
    • Hymer and Resnick (1969) first recognized the presence of a NFS in economic modeling and argued for low-quality non-farm goods (Z-goods).
    • Ranis and Stewart (1993) extended the Hymer and Resnick (1969) model by positing a two part Z-goods, one part produced in households (hhs) and villages and the other part relatively better quality produced in towns.
    • Mellor (1976)`s work became somewhat of a reference point for growth linkage literatures arguing that the viability of the sector would be determined largely by productivity gains in agriculture.
    Empirical Investigations on inter-sectoral linkages Review from farm/non-farm growth linkage literatures -Growth multipliers from certain structural relationships among agents (hhs, firms, the govt. and ROW) in the economy calculated and decomposed into various linkages -Detailed data on input/output table, an account of who receives income, both on the marginal expenditures of all agents required Social Accounting Matrices (SAM)
    • Relationship between growth in farm income and growth in employment or income in NFS estimated
    • Cross section or polled data used
    • Growth rates across regions for many reasons differed
    Econometric studies
  • Linkages as determinants of household non-farm enterprises` (HNFEs) success: An alternative approach for assessing farm/non-farm growth linkages in rural area Method of estimation: Probit regression The enterprise has consumption linkage (1 if yes) conslin The enterprise has forward linkage (1 if yes) Entfos The enterprise has backward linkage (1 if yes) Backlin Farm/non-farm linkage variables in rural business cycle Financial problem was perceived by entrepreneur as main? (1 if yes) Finp Did enterprise invest family thrifty savings? (1 if yes) Tfsav Did enterprise receive informal credit? (1 if yes) Infolend Did enterprise receive credit from NCBs, PBs? (1 if yes) Ncbpb Did enterprise receive any credit from MFI-NGOs, Coop.? (1 if yes) Mficr Hh income from other non-farm sources (except outcr and ent. Profit) is reinvested in enterprise? (1 if yes) Onfs Hh out-country remittance is reinvested in enterprise? (1 if yes) Outcr Financial capital related variables Hh farm income/land sale is reinvested in enterprise? (1 if yes) Finclands HH land size (acre) Landh Did the entrepreneur/hh members have any related prior exp./training? (1 if yes) Exptrg Employment size of the enterprise (Numbers) Emps Schooling age of the principle entrepreneur (Years) Sageentr Hh head profession is related with non-farming? (1 if yes) Hhhp Enterprise age (years) Entage Entrepreneur's learning curve and strength Is the enterprise working as sub-contractor/production for order? Subc The enterprise is owned by partnership beyond household (1 if yes) Ownd Organizational structure and relationship with other enterprises Sales in local market (1 if yes) Salesloc Inputs/raw materials purchased locally (1 if yes) Inploc Supply market (Local/non-local) Explanatory variables Performance of HNFEs by net sales growth (1 if success) Pent Dependent variable
  • Data collection Method Structured questionnaire, focus group discussion, and researcher's own o bservation. Sampling method : 2-stage sampling Population : 1148 Sample : 214 Sample enterprises : 81 from 67 hhs Study Location: Comilla Sadar Upazila Data Collection April-May 2008 Survey on growth linkages (67 hhs) Aug.-Sep. 2006 Survey on participation/state of NFAs (214 hhs)
  • Results and discussions: Participation, time allocation, and income share by sectors in Comilla Sadar Upazila 2005-06 (N=442) Evidences of HNFEs
    • The NFAs are undoubtedly no longer “marginal”.
    • Returns from the NFAs are higher compared to farming.
    • Majority of NFAs (68%) are low-productive in nature.
    • Household non-farm enterprises are the single most significant category.
    • Dependency on remittance employments (especially out-country) could be a threat for sustainability of local livelihoods.
    Vegetable trade: forward linkage Farm equipment workshop: backward linkage Mobile Phone Service Center: Consumption linkage Source: Own survey (2008) 100.0 100.0 100.0 Total 7.8 .. .. Others (rental income, pensions, interest, gifts, etc.) 19.1 16.2 15.0 Out-country remit. employments 5.7 4.7 6.0 In-country remit. employments 20.2 21.1 25.0 Non-farm wage employments 25.7 22.5 27.0 Non-farm self employments 5.9 6.4 11.5 Farm wage employments 87.5 77.4 82.6 NFS as a whole 12.5 23.0 17.4 Own farm production activities Income share ( %) Time allocation (%) Participation (%) Sectors
  • Mean characteristics of HNFEs` in Comilla Sadar Upazila in 2007 (N=81) Source: Own survey (2008)
    • The HNFEs are locally dependent.
    • The enterprises are informal in-nature.
    • Financing of the enterprises is diversified.
    • All three linkages exist, though the extent of consumption linkage is higher.
    50.0 47.0 30.0 50.3 48.9 33.1 26.4 46.5 41.8 33.1 43.4 2.6 48.2 1.6 39.1 4.4 9.5 31.6 26.4 24.2 28.3 42.6 S.D. 58.0 Conslin (%) 32.1 Entfos (%) 9.9 Backlin (%) Farm/non-farm linkage variables in rural business cycle 51.9 Finp (%) 38.3 Tfsav (%) 12.3 Infolend (%) 7.4 Ncbpb (%) 30.9 Mficr (%) 22.2 Onfs (%) 12.3 Outcr (%) Financial capital related variables 24.7 Finclands (%) 1.3 Landh (acre) 35.8 Exptrg (%) 2.0 Emps (numbers) 5.2 Sageentr (Schooling years) 81.5 Hhhp (%) 12.4 Entage (years) Entrepreneur's learning curve and strength 11.1 Subc (%) 7.4 Ownd (%) Organizational structure and relationship with other enterprises 93.8 Salesloc (%) 91.4 Inploc (%) Supply market (Local/non-local) 23.5 Pent (%) Mean Characteristics
  • HNFEs` success in Comilla Sadar Upazila in 2007: Probit Estimates (N=81) Source: Own survey (2008) Note: Coefficients under red mark show highly insignificance of the respective variables which are excluded in the restricted model. Statistical significance: *** at 1%, ** at 5%, * at 10% levels, respectively. @ the reference category for farm/non-farm linkage variables is forward linkage (Entfos). The variables are standardized.
    • The unrestricted model as a whole is not statistically significant.
    • Results from restricted model stress the importance of linkage variables.
    1.029973 .9464412 1.131781 .4391355 .8102144 .4342508 .5350931 .5908353 .4591295 .2432394 .8496144 .7103483 .8764796 .7543608 S.E. 1.516095 .9841969 1.244103 .4725168 .4499365 .8679487 1.309242 .4952501 .5762568 .6948799 .7081941 .017737 .5025735 .0366352 .6540089 .0026001 .2536936 .9477201 .7449853 .9508053 .7751354 S.E. Coefficient Coefficient 0.0188 0.1520 Prob>chi2 -1.961336 -2.160288 Constant -31.287852 -30.906944 Log likelihood 25.67 26.43 LR Chi2 2.515713*** 3.133173*** -.6858312 .. -1.287961 .. .2932874 -1.047243** .. -1.308359** .. -.6749022 .. .. .. -.1545087 1.992713** 1.590222** -1.336301 1.237942* Restricted model 2.441203 Conslin@ 3.204855 Backlin@ -.7754718 Finp .0643728 Tfsav -1.258733 Infolend .3392973 Ncbpb .3387797 Mficr -1.00396 Onfs .2155123 Outcr -1.05591 Finclands -.0086316 sLandh -.7120329 Exptrg -.0101985 sEmps .0009403 sSageentr .1875505 Hhhp -.1930935 sEntage 1.98651 Subc 1.60823 Ownd -1.207808 Salesloc 1.221825 Inploc Unrestricted model Variables
  • Conclusions
    • HNFEs are the single most significant category of income sources and growth linkages are contributing entrepreneurial success and NFAs as well.
    • The positive consumption effect indicates the lower stage of overall development of the rural economy. The stronger positive effect of backward linkage indicates the capital intensity of agriculture. And the insignificant positive effect of forward linkage indicates that the enterprises related with agro-processing is still not important in the overall economy.
    • HNFEs which can create consumption linkage and backward linkage depending on the local input market could get their success and strengthen the NFAs in rural areas as well.