Interlinked Transactions in Cash Cropping Economies: The Determinants of Farmer Participation and Benefits in Rural Mozambique - PowerPoint PPT Presentation

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Interlinked Transactions in Cash Cropping Economies: The Determinants of Farmer Participation and Benefits in Rural Mozambique

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Title: Interlinked Transactions in Cash Cropping Economies: The Determinants of Farmer Participation and Benefits in Rural Mozambique


1
Interlinked Transactions in Cash Cropping
Economies The Determinants of Farmer
Participation and Benefits in Rural Mozambique
  • Rui M.S. Benfica
  • Maputo, Mozambique
  • September, 2006

2
BACKGROUND
  • Predominance/persistence of Contract farming in
    cash cropping in Mozambique, due to
  • Cash constraints, poor access to inputs and
    credit
  • Intensive management and specific production
    techniques
  • Difficult to support under spot marketing or
    plantation arrangements
  • Processors needing raw materials to achieve scale
    and recover investments
  • Provide inputs on credit and extension assistance
  • Buy all the output from contract farmers at
    pre-determined prices (Monopsonic rights under
    Concession Agreements with the GOM)
  • Over 100,000 tobacco farmers engage in these
    contracts nationwide over 50,000 in the study
    area

3
MOTIVATION/CONTRIBUTION
  • Contract farming institutional arrangements
    studied at length
  • However
  • Lack of Empirical assessment with household Level
    data
  • Failure to appropriately account for selectivity
    bias
  • Use of limited data sets and poor specifications
  • In addition to accounting for possible selection
    bias, THIS PAPER
  • Recognizes heterogeneity among participants
    themselves
  • Investigates threshold effects of education and
    land holdings to identify the types of farmers
    that benefit
  • Gives important indications regarding the effects
    of contract farming on differentiation

4
OBJECTIVES
  • To understand the determinants of farmer
    participation /selection in tobacco growing
    schemes
  • To estimate the determinants of performance
    (profits) with the tobacco crop among
    participants
  • To assess the effects of participation on
    agricultural and total household incomes, and to
    explore what kind of participants are most likely
    to gain

5
HOUSEHOLD LEVEL SURVEYS
  • Monopsony concession Areas for two Firms
  • Mozambique Leaf Tobacco
  • DIMON Mozambique
  • Sample size 159 farmers
  • 117 tobacco contract growers
  • 42 non-growers
  • Households were visited twice
  • March 2004 Recall on pre-harvesting
    events
  • September 2004 Harvesting and post-harvesting
    events
  • Issues covered Household production, marketing,
    factor ownership and allocation, assets, off-farm
    income sources, cutting and planting of trees,
    etc Ultimately designed to build a SAM for CGE
    analysis

6
ECONOMETRIC MODELS
  • Sample Selection Models Account for unobservable
    factors that may affect both the likelihood of
    participation and performance
  • Control for selection bias in outcome regressions
  • 1st Stage Probit Equation for Participation
  • Pr(ci1zi) F(?zi), where c Participation
    dummy
  • z Exogenous
    determinants vector
  • ? Coefficient estimates for z
  • Vector z includes education thresholds (Eki),
    land thresholds (Aji), assets, demographics,
    technology, diversification, and location or
    agro-ecological/infra-structural fixed-effects
    (xi).

7
Econometric Models
  • 2nd Stage Selection Adjusted OLS Regressions
  • (1) Determinants of Cash Crop Profits
  • yi ßxi ??i(?zi)
    ui , if ci1
  • yi - Net profits from tobacco
  • Aji - Owned land area quartiles
  • Eki - Education attainment level dummies
  • xi - Other demographic, assets, technology
    and locational factors
  • ?i - Inverse Mills ratio
  • From the 1st Stage Probit, the IMR (?) Inverse
    mills ratio (selection hazard) is obtained for
    each
  • observation i as ?i ø(?zi)/F(?zi), where
    ø(?zi) and F(?zi) are the normal density and
    distribution
  • functions.
  • A, E and x are sub-sets of the set Z from the
    first stage. Elements in Z not included here are
    exclusion restrictions.
  • Equation returns estimates of the determinants of
    cash crop profits (a,d, and ß) and the sample
    selection bias coefficient (?).

8
Econometric Models
  • (2) Treatment Effects with Land and Education
    Thresholds
  • Yi ?Ci
    ßxi ?hi(?zi) ui
  • Yi Crop or total household income
  • Ci - Participation dummy
  • Aji - Owned land area quartiles
  • Eki - Education attainment level dummies
  • xi - Other demographic, assets, technology
    and locational factors
  • hi - selection hazard ratio
  • hi ø(?zi)/F(?zi) if Ci 1 and
    hi ø(?zi)/1-F(?zi) if Ci 0
  • Land and schooling interacted with participation
    to test for threshold effects

9
MODEL RESULTS (1) 1st Stage Determinants of
Participation
  1. Determinants of Net Income from Tobacco Production

Variables Coef. Pgtz Comments
Demographics Female headed household Age of household head Labor adult equivalents Education1-3 years Education gt 3 years - 0.375 - 0.013 - 0.154 - 0.071 0.024 0.40 0.38 0.20 0.84 0.95 - Weak Demographic Effects - No differences by gender, age, or education of the head
Assets and Technology Area_Q2 Area_Q3 Area_Q4 0.333 0.027 0.500 0.36 0.95 0.34 - No effect on participations of land ownership
Use of Animal traction Value of tools Value of other equipment 1.198 0.023 0.004 0.02 0.09 0.22 - Animal traction and household assets drive up participation
Diversification Activities Has livestock income Has Self-employment income Has wage labor income 1.026 0.257 0.879 0.06 0.37 0.00 - Households with livestock and wage labor less likely to grow tobacco inverse relationship
N 159 Wald chi2 (18) 45.25 Prob gt chi2 0.000 Pseudo R2 0.25 Prob gt chi2 0.000 Pseudo R2 0.25 Implications growth in the tobacco sector could reduce differentiation through employment linkages
1/ Probit equation for participation, 1 if
participates, 0 otherwise. 3/ Level of
significance (LS) 10, 5, 1.
10
MODEL RESULTS (2)2nd Stage Selection Adjusted
OLS Regressions(1) Determinants of Tobacco
Profits
  1. Determinants of Net Income from Tobacco Production

Variables Coef. Pgtz Comments
Demographics Female headed household Age of household head Labor adult equivalents Education1-3 years Education gt 3 years -405.56 -5.44 106.51 -148.86 17.55 0.05 0.42 0.21 0.51 0.94 Female headed households less profitable - No effects of education on profits
Assets and Technology Area_Q2 Area_Q3 Area_Q4 247.07 78.32 780.34 0.18 0.74 0.02 Land has an effect at the highest threshold
Use of Animal traction Value of tools Value of other equipment 198.83 8.47 3.86 0.63 0.08 0.13 Value of assets important
Agro-Ecological/Local Fixed Effects () () - Profits higher in mid/high altitude areas than in drier and lower altitude areas
Lambda (Inverse Mills Ratio) 229.53 0.31 No evidence of sample selection bias
N 117 F(16, 100) 4.12 Prob gt F 0.000 Adj-R2 0.46 Prob gt F 0.000 Adj-R2 0.46 Implications Economies of scale to be explored in tobacco
1/ Probit equation for participation, 1 if
participates, 0 otherwise. 3/ Level of
significance (LS) 10, 5, 1.
11
MODEL RESULTS (3)(2) Treatment
Effects/Thresholds Crop HH income
Variables Crop Income Crop Income Total Income Total Income Comments
Variables Coef. Pgtz Coef. Pgtz Comments
Participation in CF 407.70 0.46 85.87 0.88
Demographics Female headed Age of head Labor adult equivs 488.01 4.85 25.44 0.04 0.64 0.80 0.66 15.85 - 3.99 0.99 0.15 0.97 - Off-farm Income reduces gender differentiation
Education Thresholds Education 1-3 years Education gt3 years Education 1-3CF Education gt3CF 195.32 361.14 482.02 -637.32 0.45 0.25 0.40 0.28 269.76 718.92 452.16 - 703.27 0.30 0.03 0.44 0.23 No effect on crop income regardless of participation Effect on Total income, BUTno interaction effects
Land Threshold Effects Area_Q2 Area_Q3 Area_Q4 Area_Q2CF Area_Q3CF Area_Q4CF 527.93 665.13 723.32 -129.33 166.40 1,305.86 0.02 0.05 0.07 0.71 0.76 0.04 401.17 820.94 691.65 4.26 -18.28 1,575.96 0.12 0.00 0.06 0.99 0.97 0.02 Higher land areas reflected in both crop and total incomes Interaction Effects only strong and significant at the fourth quartile for both crop and total income Even large farmers appear strongly engaged in off-farm activities
Agro-Ecological/Local () () () () - No location fixed effects
Lambda (Inv Mills Ratio) 331.11 0.18 68.56 0.78 - No sample selection bias
N 159 R2 0.44 ProbgtF 0.000 N 159 R2 0.44 ProbgtF 0.000 N 159 R2 0.43 ProbgtF 0.000 N 159 R2 0.43 ProbgtF 0.000 The results driven by efficient use of readily available experienced labor in the area
12
POLICY IMPLICATIONS
  • Lack of returns to education suggest
  • high scope for improvement in productivity
    enhancing field practices capable of rewarding
    more educated farmers
  • Growth in tobacco through larger areas and
    increased productivity, associated with labor
    hiring may be inequality reducing
  • Important to promote growth as a
    poverty/inequality reduction strategy
  • Along with increased off farm opportunities also
    reduce gender differences
  • Linkage effects appear important, especially
    through labor markets
  • Issue need to be looked at on an economy-wide
    framework (CGE)
  • Important to keep open migration and trade policy
    with Malawi
  • Technological and environmental spillovers need
    more attention
  • On the positive side, fertilizer use in food
    crops by growers and non-growers
  • On the negative, long term consequences of
    deforestation and soil erosion
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