Agricultural Policy as a Social Engineering Tool



Table 2: Descriptive Statistics for the Dependent and Independent Variables

Variable__________________________________

Number_________

____________Percent*

Dependent Variable

Restrict

123

100

Yes

64

52

No

59

48

Independent Variables

Educational Attainment

142

100

Grade School

3

2

Some High School

6

4

High School Dip.

32

23

Some College

32

23

Bachelor’s Degree

39

27

Advanced Degree

30

21

Sales

139

100

Under $10,000

66

47

10k-$49,999

32

23

50k-$99,999

11

8

100k-$249,999

12

9

250k-$499,999

7

5

500k-$999,999

4

3

$1,000,000 and over

7

5

Age

140

100

35-44years

20

14

45-54years

42

30

55-64years

37

26

65 years and over

41

29

Farm income

138

100

None

21

15

1-25%

62

45

25-50%

22

16

51-75%

3

2

76-100%_____________________

30________________

_____________22

“*” may not add to 100 because of rounding.

22



More intriguing information

1. Evidence of coevolution in multi-objective evolutionary algorithms
2. TOMOGRAPHIC IMAGE RECONSTRUCTION OF FAN-BEAM PROJECTIONS WITH EQUIDISTANT DETECTORS USING PARTIALLY CONNECTED NEURAL NETWORKS
3. IMPROVING THE UNIVERSITY'S PERFORMANCE IN PUBLIC POLICY EDUCATION
4. EMU's Decentralized System of Fiscal Policy
5. The fundamental determinants of financial integration in the European Union
6. The Impact of EU Accession in Romania: An Analysis of Regional Development Policy Effects by a Multiregional I-O Model
7. Restricted Export Flexibility and Risk Management with Options and Futures
8. The name is absent
9. SAEA EDITOR'S REPORT, FEBRUARY 1988
10. Constrained School Choice