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Table 2 Determinants of and effects of malaria averting expenditure on maize labour productivity.

From: Averting expenditure on malaria: effects on labour productivity of maize farmers in Bunkpurugu-Nakpanduri District of Ghana

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  
  1. ***, ** and ** are significant at 1%, 5% and 10% respectively