Income Growth and Mobility of Rural Households in Kenya: Role of Education and Historical Patterns in Poverty Reduction



Table 3.Models Disaggregated by Poverty Status

(1)

General

(2)

Below Poverty

(3)

Above Poverty

LID

0.13

0.31***

0.02

(0.56)

(3.17)

(0.05)

LID*Secondary education

-1.40*

-3.04***

-1.24

(1.88)

(4.42)

(0.92)

Δ dtmrd

0.31

4.98*

-3.54

(0.15)

(1.75)

(0.90)

Δ mdist

7.26*

-1.35

9.10

(1.81)

(0.31)

(0.74)

Δ agehd

1.84

-1.15

13.79*

(0.71)

(0.22)

(1.70)

Δ agehd2

-0.02

-0.01

-0.12*

(1.03)

(0.18)

(1.66)

Δ seco

348.73**

534.02***

503.56

(2.13)

(4.36)

(1.28)

Δ malehd

40.48

86.66**

56.89

(1.31)

(2.30)

(0.61)

Δ padofe

108.26***

86.43***

134.46

(5.24)

(3.67)

(1.33)

Δ ldcult

-0.13

-2.02

-1.91

(0.16)

(1.49)

(1.18)

Δ nlvstok

1.20***

0.75**

2.20**

(4.76)

(2.26)

(2.12)

Δ nmalad

14.54**

1.61

49.76**

(2.06)

(0.24)

(2.55)

Δ nfemad

10.08*

11.70*

18.97

(1.85)

(1.83)

(0.89)

Δ month

-2.68

-3.70*

1.32

(1.33)

(1.74)

(0.30)

Δ grpmem

5.83

3.84

14.26

(0.51)

(0.20)

(0.42)

year dummy

-6.67

-22.70*

53.78

(0.39)

(1.89)

(0.75)

Observations

1324

935

389

Robust t statistics in parentheses

* significant at 10%; ** significant at 5%; *** significant at 1%
Source: Authors calculation

As for the other determinants of income growth, it seems that having a male head
of household positively influences income growth for those below poverty, but has no

19



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