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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