1. Rufai A.M., Salman K.K. and Salawu M.B
INPUT UTILIZATION AND AGRICULTURAL LABOUR PRODUCTIVITY: A GENDER ANALYSIS
Rufai A.M., Salman K.K. and Salawu M.B
Department of Agricultural Economics, University of Ibadan, Nigeria

2. Introduction Agriculture and labour productivity
Women and labour availability
Employment in agriculture and economic growth
Low productivity and small scale farmers
Activities of women in agriculture

3. Introduction cont’d Feminisation of agriculture Division of labour
Gender imbalance
Labour productivity and input availability
Higher vulnerability among females

4. Objectives
The main objective of the study was to explore the relationship between input utilization and labour productivity among men and women in Nigeria.
The specific objectives of the study are to:
assess the extent of input utilization based on gender
examine the extent and type of labour utilized and the productivity of labour.
analyse the effects of input utilization on the productivity of labour.

5. Justification Past studies Efficient use of resources Methodology:
Data used
Quantile regression
Policy relevance
policy targeting
Economic growth
Food security

6. Results Use of inputs (Objective 1)
Yes (%)
No(%)
chi2
mean
Std.dev
T-test
Fertilizer
Total
41.17
58.83 -
Male
43.71
56.29
52.36***
8.34***
Female
21.85
78.15
Pesticide
8.37
91.63
627.99
7.95
92.05
4.61**
670.28
1.05**
11.59
88.41
411.69
456.58
Herbicide
23.46
76.54
379.02
551.84
22.31
77.69
14.29***
391.82
579.19
2.70***
32.12
67.88
286.13
267.32
Machinery/
equipment
15.90
84.10
20.88
8.58
15.24
84.76
6.31***
21.11
8.50
1.78*
20.86
79.14
19.57
10.52
Animal traction
19.02
80.98
3.25
3.24
0.66
18.30
81.70
6.67***
3.29
2.91
24.50
75.50
2.96
4.75

7. Labour input use (objective two)
MEAN
STD.DEV.
T-test
Family labour
Total
Male
Female
0.59
Hired labour
Total Hired labour
617.00
588.48
2.64***
833.32
Men
394.44
390.17
0.27
426.76
Women
198.61
172.06
1.81**
399.93
Children
23.96
284.06
2.91***
26.24
301.77
6.63
41.24

8. Productivity of labour (objective two)
mean
Std.dev
Min
max
Value of output (₦)
Total
500.00
Male
Female
Total labour (man-hour)
21.00
162.00
Labour productivity (₦/man-hour)
48.93
275.64
0.01
49.07
287.49
47.86
159.59
0.02

9. Gender specific labour productivity model (male)
Effects of Input Utilization on Labour Productivity by Gender (objective three)
Gender specific labour productivity model (male)
OLS
Quantile regression
25th quantile
50th quantile
75th quantile
95th quantile
Age
0.011
0.023
-0.011
-0.021
0.017
Age squared
-0.001
0.001
0.029
Education
0.118
0.041
0.078
-0.085
Fertilizer
-0.024
-0.034
-0.064
0.033
0.102
pesticide
0.073
0.260
0.298
0.281
Herbicide
0.556***
0.424**
0.512**
0.349**
0.585***
Machinery and equipment
-0.363*
-0.611**
-0.483**
-0.155
-0.030
Used Animal traction
0.134
0.152
-0.010
0.026
0.190
Own land
-0.257
-0.759**
-0.506
0.668
0.446
Multiple cropping (dummy)
0.288
0.772
0.181
0.218
0.781**
Mono-cropping (dummy)
0.433
1.168*
0.267
0.649*
Number of household males
-0.069**
-0.073*
-0.101**
0.712
Number of animals
0.003
0.019
-0.013
Rural
-0.437**
-0.343
-0.495**
-0.518***
-0.718**
Has savings
-0.416
-0.255
0.057
-0.046
0.099

10. Gender specific labour productivity model (Female)
OLS
Quantile regression
25th quantile
50th quantile
75th quantile
95th quantile
Fertilizer
-0.134
-0.418
-0.367
0.109
0.324
pesticide
-0.341
-0.167
-0.145
-0.389
0.579
Herbicide
0.185
0.339
0.154
0.157
-0.152
Machinery and equipment
0.268
0.531
-0.182
0.973*
-0.026
Used Animal traction
0.417
0.772
0.198
0.959*
-0.359
Own land
-0.387
0.054
0.826
0.213
-1.73
Multiple cropping (dummy)
2.015
3.195***
2.853*
2.387
2.544*
Mono-cropping (dummy)
1.945
2.820***
2.501*
2.367
2.232
Number of household males
-0.001
0.033
-0.009
-0.014
0.212
Number of animals
0.068*
0.093**
0.070*
0.015
-0.019
Rural
0.029
-0.143
0.473
-0.251
-1.51
Has savings
0.578
0.875*
0.893
0.516
1.11*

11. Conclusions and policy implications
Generally, very few farmers utilized inputs on their farms
The use of fertilizer was particularly low among female managed plots.
Though more female managed plots used other inputs, the quantity utilized was lower when compared to male managed plots.
Females used more hired labour in their production activities.
The payment of wages could affect the amount of resources available to females to invest in other inputs.

12. Recommendations
The agricultural policy of the country should be revised and effectively implemented.
Gender sensitive policies should be formulated to increase the access of female farmers to production inputs.
The agricultural labour market in Nigeria needs to be standardized to improve the performance of labour and promote labour use efficiency among farmers.
Training sessions especially for female farmers should be organised to enhance their resource use skills and production efficiency.

13. Thank you for listening!