Background
Effects of malaria on agricultural labour productivity
Methods
Study area
Sampling procedure and data collection methods
Theoretical framework of averting expenditure on malaria
Models and method of data analysis
Simple arithmetic summation
Conditional recursive mixed process
Variables | Definitions and measurements | Mean | Std. deviation | Min | Max |
---|---|---|---|---|---|
LP | Labour productivity (Mt/man-day) | 0.09 | 0.08 | 0.00 | 0.54 |
Cap | Capital (Gh¢) | 206.73 | 116.41 | 59.67 | 941.33 |
Fert | Fertilizer (kg) | 396.13 | 275.79 | 100.00 | 1600.00 |
Seed | Seeds (kg) | 88.84 | 59.57 | 15.00 | 459.00 |
Wd | Weedicides (L) | 4.08 | 4.70 | 0.00 | 25.00 |
Fs | Farm size (ha) | 1.18 | 0.62 | 0.40 | 4.05 |
Exp | Farming experience (years) | 38.12 | 13.84 | 3.00 | 75.00 |
Ext | Number of extension officers visits | 0.67 | 1.23 | 0.00 | 5.00 |
Sex | Sex (male = 1, female = 0) | 0.53 | 0.50 | 0.00 | 1.00 |
HHS | Household size | 7.86 | 2.53 | 2.00 | 16.00 |
Age | Age (years) | 51.28 | 13.56 | 25.00 | 86.00 |
Edu | Educational status of household head (educated) | 0.56 | 0.50 | 0.00 | 1.00 |
Mot | Ownership of motor bike (1 = yes, 0 = no) | 0.40 | 0.49 | 0.00 | 1.00 |
AEM | Averting expenditure for malaria (Gh¢) | 284.60 | 133.07 | 24.00 | 990.00 |
Bush | Presence of bushes around the house (1 = yes, 0 = no) | 0.64 | 0.48 | 0 | 1 |
Stg_wat | Presence of stagnant water (1 = yes, 0 = no) | 0.67 | 0.47 | 0 | 1 |
Pg_wmn | Presence of pregnant woman (1 = yes, 0 = no) | 0.18 | 0.39 | 0 | 1 |
HH_edu | Household members in education | 3.97 | 1.99 | 0 | 9 |
Off_Inc | Off-farm income of household (Gh¢) | 1650.48 | 1313.76 | 234.00 | 7495.00 |
Results and discussion
Summary statistics of variables
Determinants of averting expenditure on malaria and labour productivity
Variables | Coef. | Std. error |
---|---|---|
First model: averting expenditure | ||
Sex | 7.05682 | 17.98260 |
HHS | 7.32490* | 4.11162 |
Age | 0.04406 | 0.68027 |
Edu | 30.24928 | 18.44907 |
Bush | 50.67986*** | 18.53492 |
Stg_wat | − 5.69713 | 18.19524 |
Pg_wmn | 45.18058** | 22.64726 |
HH_edu | 11.20739** | 5.02365 |
Off_inc | 0.01444** | 0.00657 |
_cons | 98.85385 | 48.11921 |
Second model: maize labour productivity | ||
Cap | − 0.000074 | 0.000179 |
Fert | 0.000055* | 0.000030 |
Seed | 0.000730** | 0.000359 |
Wd | 0.002393** | 0.000984 |
FS | − 0.016151 | 0.012121 |
Exp | − 0.001852*** | 0.000610 |
Ext | − 0.004596 | 0.003355 |
Sex | 0.001231 | 0.008826 |
HHS | − 0.000584 | 0.002404 |
Age | 0.001614** | 0.000630 |
Edu | 0.001935 | 0.010474 |
Mot | 0.017812* | 0.009248 |
AEM | 0.000239* | 0.000128 |
HH_edu | − 0.004548 | 0.002910 |
_cons | − 0.038118 | 0.029423 |
/lnsig_1 | 4.772509*** | 0.050808 |
/lnsig_2 | − 2.855080*** | 0.090131 |
/atanhrho_12 | − 0.291986 | 0.274319 |
sig_1 | 118.2154 | 6.006326 |
sig_2 | 0.057551** | 0.005187 |
rho_12 | − 0.283962 | 0.252199 |
Number of obs | 194 | |
LR chi2 (23) | 157.03 | |
Log likelihood | − 914.37459*** | |
Prob > chi2 | 0.0000 |
Socio-economic determinants of averting expenditure on malaria
Effects of malaria averting expenditure on maize labour productivity
Farmers perceive benefit of averting expenditure on malaria
Variable | Strongly agree | Agree | Neutral | Disagree | Strongly disagree |
---|---|---|---|---|---|
Averting helps me increase the number of times I go to farm | 59.50 | 38.00 | 2.50 | 0.00 | 0.00 |
Averting malaria help you not to spend in treating malaria | 35.50 | 62.50 | 2.00 | 0.00 | 0.00 |
Averting malaria will help me save income | 43.50 | 51.50 | 5.00 | 0.00 | 0.00 |
Averting malaria will help me increase my labour productivity | 46.00 | 50.50 | 2.00 | 1.00 | 0.50 |
Averting malaria will make me be healthy and active | 51.50 | 41.50 | 2.00 | 0.00 | 1.00 |
Averting malaria will help reduce my health expenditure | 48.00 | 49.00 | 2.50 | 0.00 | 0.50 |
Averting malaria will help me avert other diseases | 48.00 | 47.50 | 3.50 | 1.00 | 0.00 |
Occurrences of sickness will reduce in my house if I avert malaria | 48.50 | 48.00 | 2.00 | 1.00 | 0.50 |