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DETERMINANTS OF HOUSEHOLD
RESILIENCE TO DRY SPELLS AND
DROUGHT IN MALAWI: A CASE OF
SALIMA DISTRICT
T.F BANDA, M.A.R PHIRI, L.D MAPEMBA and B.B MAONGA
LUANAR
Outline
• Statement of the problem
• Definition: Resilience
• Objectives
• Data and methods
• Results and Discussion
• Conclusions
• Policy Implications
Statement of the Problem
 Agric. has been identified as the most severely
affected by dry spells & drought
 These have presented new challenges to
smallholder farmers because they are
exogenous.
 For example, about 1.1 million people were
reported to be food insecure due to unreliable
rainfall patterns (FEWS NET,2013).
Definition: Resilience
The ability of a system, community or society
exposed to hazards to resist, absorb,
accommodate and to recover from the effects of a
hazard in a timely and efficient manner, Phiri
(2010: 19)
 The ability of the community, society or even a
household to “spring back” from a shock, UNDG
(Undated:38).
 The amount of change a system can undergo and
still remain in the same state, Falkenmark and
Rockstrom (2009:94)
Objectives
 Main objective:
 To determine how prolonged dry spells and
droughts have affected the resilience of maize
farming households in Salima district.
 Specific Objectives:
 Determine factors that affect a household’s
resilience to dry spells and droughts in Chipoka EPA.
 Determine the effect of drought resilience on the
welfare of farming households in Chipoka EPA
Methods
• Principal Components Analysis (PCA) used to
construct DRI
• Probit model used to identify determinants of
resilience
• Stochastic frontier approach used to determine
the effect of drought resilience on household
output (proxy with welfare)
Bartlett’s test of sphericity
Determinant of the correlation matrix 0.424
Bartlett test of sphericity
Chi-square 363.87
Degrees of freedom 6
p-value 0.00
H0: variables are not inter-correlated
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
KMO 0.52
Eigen values
Component Eigen value Difference Proportion Cumulative
Comp1 1.79 0.43 0.45 0.45
Comp2 1.36 0.87 0.34 0.79
Comp3 0.49 0.15 0.12 0.91
Comp4 0.35 . 0.09 1.00
n=427 Components = 4 Trace = 4 Rho = 1.0000
Principal components
Variable Comp1 Comp2 Comp3 Comp4 Unexplained
Production in good year 0.58 -0.40 0.12 -0.69 0
Production in bad year 0.57 -0.41 -0.07 0.70 0
Consumption months in good year 0.42 0.56 -0.71 -0.09 0
Consumption months in bad year 0.39 0.59 0.69 0.10 0
Results and Discussion
Variable n Mean Std. Dev. Min Max
DRI 427 -0.09 0 .88 -1.79 5.11
DRI >= 0 163 0.79 0.75 0.01 5.11
DRI< 0 264 -0.63 0.37 -1.79 -0.01
Results & Disc…
Results…
Coefficient P-value Marginal Effects P-value
Gender of household head -0.16
(0.17)
0.35 -0.06
(0.06)
0.34
Age of household head (years) 0.16**
(0.07)
0.03 0.06**
(0.02)
0.03
Size of household (number of people) 0.34***
(0.07)
0.00 0.12***
(0.02)
0.00
Years spent in school by household head 0.10
(0.75)
0.14 0.04
(0.03)
0.14
Land holding size (Acres) 0.39***
(0.09)
0.00 0.15***
(0.03)
0.00
Number of Chickens 0.07
(0.08)
0.38 0.03
(0.03)
0.38
Number of Goats 0.09
(0.09)
0.26 0.04
(0.03)
0.27
Number of Bicycles 0.01
(0.07)
0.84 0.01
(0.03)
0.84
Immediate family members in cities 0.07*
(0.03)
0.06 0.02*
(0.01)
0.06
Frequency of dry spells over 5 year period -0.03
(0.07)
0.64 -0.01
(0.03)
0.64
Participation in village savings and loans 0.23
(0.15)
0.12 0.09
(0.06)
0.12
Constant -0.33
(0.23)
0.16
N = 427 Wald chi2(11) = 79.8 Prob. > chi2 = 0.00 Log pseudo likelihood = -236.25 Pseudo R2 = 0.17
y = Pr(Resilience) = 0.37
***1% level of significance, **5% level of significance and *10% level of significance
Values in Parentheses are robust standard errors
Results…
Variable Coefficient Z P-value
Land (log) 0.08**
(0.04)
2.10 0.04
Seed (log) 0.18***
(0.04)
4.55 0.00
Lab (log) 0.07
(0.05)
1.41 0.16
Invest (log) 0.05**
(0.01)
5.86 0.00
Resilience Index 0.45***
(0.04)
12.69 0.00
Constant 5.78***
(0.24)
23.78 0.00
Likelihood-ratio test of sigma_u=0: chibar2(01)= 92.61 Prob.>=chibar2 = 0.00
Values in parentheses are robust standard errors
***1% level of significance and **5% level of significance
Conclusions
 62 percent are vulnerable to adverse effects
 Mean DRI of -0.0857 is below threshold of 0
for a household to be considered resilient.
 Determinants of resilience: age of Hh, Size of
Hh, Land and number of immediate family
members living outside household
 Resilience had a +ve effect on Hh welfare
Policy Implications
Govt. & non-state actors working in Chipoka to
consider introducing productivity enhancing
technologies such as irrigation in the study
area.
 Encourage farmers to diversify crop production
and participate in off-farm livelihood activities.
 Target beneficiaries to food aid and other relief
programs.
Acknowledgements
END
Thank You!!!

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DETERMINANTS OF HOUSEHOLD RESILIENCE TO DRY SPELLS AND DROUGHT IN MALAWI: A CASE OF SALIMA DISTRICT

  • 1. DETERMINANTS OF HOUSEHOLD RESILIENCE TO DRY SPELLS AND DROUGHT IN MALAWI: A CASE OF SALIMA DISTRICT T.F BANDA, M.A.R PHIRI, L.D MAPEMBA and B.B MAONGA LUANAR
  • 2. Outline • Statement of the problem • Definition: Resilience • Objectives • Data and methods • Results and Discussion • Conclusions • Policy Implications
  • 3. Statement of the Problem  Agric. has been identified as the most severely affected by dry spells & drought  These have presented new challenges to smallholder farmers because they are exogenous.  For example, about 1.1 million people were reported to be food insecure due to unreliable rainfall patterns (FEWS NET,2013).
  • 4. Definition: Resilience The ability of a system, community or society exposed to hazards to resist, absorb, accommodate and to recover from the effects of a hazard in a timely and efficient manner, Phiri (2010: 19)  The ability of the community, society or even a household to “spring back” from a shock, UNDG (Undated:38).  The amount of change a system can undergo and still remain in the same state, Falkenmark and Rockstrom (2009:94)
  • 5. Objectives  Main objective:  To determine how prolonged dry spells and droughts have affected the resilience of maize farming households in Salima district.  Specific Objectives:  Determine factors that affect a household’s resilience to dry spells and droughts in Chipoka EPA.  Determine the effect of drought resilience on the welfare of farming households in Chipoka EPA
  • 6. Methods • Principal Components Analysis (PCA) used to construct DRI • Probit model used to identify determinants of resilience • Stochastic frontier approach used to determine the effect of drought resilience on household output (proxy with welfare)
  • 7. Bartlett’s test of sphericity Determinant of the correlation matrix 0.424 Bartlett test of sphericity Chi-square 363.87 Degrees of freedom 6 p-value 0.00 H0: variables are not inter-correlated Kaiser-Meyer-Olkin Measure of Sampling Adequacy KMO 0.52
  • 8. Eigen values Component Eigen value Difference Proportion Cumulative Comp1 1.79 0.43 0.45 0.45 Comp2 1.36 0.87 0.34 0.79 Comp3 0.49 0.15 0.12 0.91 Comp4 0.35 . 0.09 1.00 n=427 Components = 4 Trace = 4 Rho = 1.0000
  • 9. Principal components Variable Comp1 Comp2 Comp3 Comp4 Unexplained Production in good year 0.58 -0.40 0.12 -0.69 0 Production in bad year 0.57 -0.41 -0.07 0.70 0 Consumption months in good year 0.42 0.56 -0.71 -0.09 0 Consumption months in bad year 0.39 0.59 0.69 0.10 0
  • 10. Results and Discussion Variable n Mean Std. Dev. Min Max DRI 427 -0.09 0 .88 -1.79 5.11 DRI >= 0 163 0.79 0.75 0.01 5.11 DRI< 0 264 -0.63 0.37 -1.79 -0.01
  • 12. Results… Coefficient P-value Marginal Effects P-value Gender of household head -0.16 (0.17) 0.35 -0.06 (0.06) 0.34 Age of household head (years) 0.16** (0.07) 0.03 0.06** (0.02) 0.03 Size of household (number of people) 0.34*** (0.07) 0.00 0.12*** (0.02) 0.00 Years spent in school by household head 0.10 (0.75) 0.14 0.04 (0.03) 0.14 Land holding size (Acres) 0.39*** (0.09) 0.00 0.15*** (0.03) 0.00 Number of Chickens 0.07 (0.08) 0.38 0.03 (0.03) 0.38 Number of Goats 0.09 (0.09) 0.26 0.04 (0.03) 0.27 Number of Bicycles 0.01 (0.07) 0.84 0.01 (0.03) 0.84 Immediate family members in cities 0.07* (0.03) 0.06 0.02* (0.01) 0.06 Frequency of dry spells over 5 year period -0.03 (0.07) 0.64 -0.01 (0.03) 0.64 Participation in village savings and loans 0.23 (0.15) 0.12 0.09 (0.06) 0.12 Constant -0.33 (0.23) 0.16 N = 427 Wald chi2(11) = 79.8 Prob. > chi2 = 0.00 Log pseudo likelihood = -236.25 Pseudo R2 = 0.17 y = Pr(Resilience) = 0.37 ***1% level of significance, **5% level of significance and *10% level of significance Values in Parentheses are robust standard errors
  • 13. Results… Variable Coefficient Z P-value Land (log) 0.08** (0.04) 2.10 0.04 Seed (log) 0.18*** (0.04) 4.55 0.00 Lab (log) 0.07 (0.05) 1.41 0.16 Invest (log) 0.05** (0.01) 5.86 0.00 Resilience Index 0.45*** (0.04) 12.69 0.00 Constant 5.78*** (0.24) 23.78 0.00 Likelihood-ratio test of sigma_u=0: chibar2(01)= 92.61 Prob.>=chibar2 = 0.00 Values in parentheses are robust standard errors ***1% level of significance and **5% level of significance
  • 14. Conclusions  62 percent are vulnerable to adverse effects  Mean DRI of -0.0857 is below threshold of 0 for a household to be considered resilient.  Determinants of resilience: age of Hh, Size of Hh, Land and number of immediate family members living outside household  Resilience had a +ve effect on Hh welfare
  • 15. Policy Implications Govt. & non-state actors working in Chipoka to consider introducing productivity enhancing technologies such as irrigation in the study area.  Encourage farmers to diversify crop production and participate in off-farm livelihood activities.  Target beneficiaries to food aid and other relief programs.

Notes de l'éditeur

  1. Reject the hypothesis that variables were inter-correlated
  2. Eigen values represent variances
  3. First component meets apriori expectations. The components are used as weights