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

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

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

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.

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

Results Use of inputs (Objective 1) Yes (%) No(%) chi2 mean Std.dev T-test Fertilizer Total 41.17 58.83 - 8594.79 26022.87 Male 43.71 56.29 52.36*** 9491.82 27177.53 8.34*** Female 21.85 78.15 1792.42 12639.14 Pesticide 8.37 91.63 627.99 2877.45 7.95 92.05 4.61** 670.28 3139.57 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

Labour input use (objective two) MEAN STD.DEV. T-test Family labour Total Male 196641.00 804835.00 Female 199468.70 824542.90 0.59 Hired labour 175203.60 636546.90 Total Hired labour 617.00 3130.44 588.48 2761.82 2.64*** 833.32 5478.61 Men 394.44 2354.33 390.17 2374.17 0.27 426.76 2201.47 Women 198.61 1972.33 172.06 1032.25 1.81** 399.93 5033.54 Children 23.96 284.06 2.91*** 26.24 301.77 6.63 41.24

Productivity of labour (objective two) mean Std.dev Min max Value of output (₦) Total 156290.90 226417.70 500.00 3059000.00 Male 159344.10 Female 133138.60 191071.80 1590000.00 Total labour (man-hour) 204576.20 875834.70 21.00 23400000.00 208266.60 902707.60 176592.20 636619.80 162.00 6865532.00 Labour productivity (₦/man-hour) 48.93 275.64 0.01 9976.19 49.07 287.49 47.86 159.59 0.02 1376.81

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

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*

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.

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.

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