Agricultural Policy as a Social Engineering Tool



Table 3. Logistic Regression Results of Determinants of Social Engineering

Variable___________

Estimated Coefficient

t-ratio

Marginal Effect_______

Intercept

2.1474

(1.582)

Age3544

1.6843

(1.879)*

0.42

Age4554

0.5144

(0.80)

Age5564

0.2554

(0.408)

SalesunderlO

-2.2777

(1.55)

Sales 1049

-2.7828

(1.833)*

-0.69

Sales5099

-3.4854

(2.228)**

-0.87

Sales 100249

-2.4849

(1.664)*

-0.62

Sales250499

-1.2805

(0.866)

Sales500999

-3.2176

(1.582)*

-0.80

Incnone

3.1976

(3.043)***

0.79

Inc125

0.8645

-1.012

Inc2650

1.4929

(1.705)*

0.37

Inc5175

2.8685

(1.830)*

0.72

Grade

-1.0511

(0.580)

HS

-1.2811

(0.934)

HSDip

-1.3156

(1.750)*

-0.33

College

-2.342

(3.007)***

-0.58

BA

-1.4542

(2.175)**

-0.36

Sample size

116

Mc Fadden R2

.20

Chi-squareddf

31.9118

Significance level

.02

Correct prediction (%)

____________71____________

23



More intriguing information

1. Feature type effects in semantic memory: An event related potentials study
2. Methods for the thematic synthesis of qualitative research in systematic reviews
3. TLRP: academic challenges for moral purposes
4. A MARKOVIAN APPROXIMATED SOLUTION TO A PORTFOLIO MANAGEMENT PROBLEM
5. THE ANDEAN PRICE BAND SYSTEM: EFFECTS ON PRICES, PROTECTION AND PRODUCER WELFARE
6. The name is absent
7. Trade Openness and Volatility
8. AN ECONOMIC EVALUATION OF THE COLORADO RIVER BASIN SALINITY CONTROL PROGRAM
9. Activation of s28-dependent transcription in Escherichia coli by the cyclic AMP receptor protein requires an unusual promoter organization
10. The name is absent