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A Systems View Across Time and Space

Table 3 Results based on panel data regressions

From: Does microfinance program innovation reduce income inequality? Cross-country and panel data analysis

Variables

POLS (1)

FE (2)

RE (3)

GLF

− 0.00028** (− 50.06)

− 0.0100 (− 1.18)

− 0.0100* (− 1.72)

GDP

0.037** (12.59)

0.0300 (0.48)

0.040* (1.81)

DCP

− 0.001** (− 5.36)

− 0.0005 (− 0.47)

− 0.00079 (− 0.93)

TRADE

0.0006 (3.51)

− 0.00007 (− 0.16)

− 0.06* (− 1.8)

2013yeardummy

− 0.006 (− 2.40)

0.00005 (0.01)

0.0006 (0.07)

MENA

− 0.33** (− 43.10)

–

–

LAC

− 0.35*** (− 31.29)

–

–

SSA

− 0.16** (− 12.85)

–

–

EAP

− 0.16*** (− 138.9)

–

–

ECA

− 0.44 (0.30)

–

–

Constant

3.65*** (81.96)

3.49*** (6.15)

3.44*** (19.07)

R-sq

0.62

–

–

Hausman test (Prob > chi2)

–

–

0.43 (0.91)

R-sq. within

–

–

0.06

R-sq. between

–

–

0.04

R-sq. overall

–

–

0.05

Prob > chi2

–

–

0.21

Observations

114

114

114

  1. . GLF and GDP variables are in logarithm. 2013 year dummy (2013 = 1, other = 0). POLS denote pool Ordinary Least Squares. FE denotes fixed-effects regression. RE denotes random-effects regression. Figures in brackets show t-statistic. Regional dummies with South Asia being the reference region: MENA Middle East and North Africa, SA South Asia, SSA Sub-Saharan Africa, EAP East Asia and Pacific, LAC Latin America and Caribbean, ECA Europe and Central Asia
  2. *, ** and *** indicate statistical significance at the 10, 5 and 1% levels, respectively