Local digital lending development and the incidence of deprivation in Kenya

Financial Innovation

Table 2 The effect of local digital lending development on food deprivation

	(1)	(2)	(3)
	Null model	Level 1 controls	Level 2 controls
Log of age		0.072***	0.071***
		(0.012)	(0.012)
Female		− 0.019***	− 0.019***
		(0.007)	(0.007)
At least secondary education		− 0.089***	− 0.088***
		(0.008)	(0.008)
Log of household size		0.016**	0.016**
		(0.007)	(0.006)
Wealth score		− 0.151***	− 0.149***
		(0.017)	(0.017)
Log of income		− 0.031***	− 0.030***
		(0.002)	(0.002)
Bank account		− 0.065***	− 0.065***
		(0.011)	(0.011)
Formal loans		− 0.034**	− 0.034**
		(0.015)	(0.015)
Other loans		− 0.004	− 0.004
		(0.020)	(0.019)
Informal loans		0.052***	0.052***
		(0.010)	(0.010)
Rural		0.027**	0.027**
		(0.011)	(0.011)
Local digital lending		− 0.392***	− 0.382***
		(0.041)	(0.094)
Log of reported death			0.039
			(0.026)
Log of total size			0.006
			(0.013)
Log of extreme poverty			0.031
			(0.023)
Log of GCP per capita			− 0.080
			(0.059)
Regional variance (\(\sigma_{u}^{2}\))	0.208	0.117***	0.085***
	(0.044)	(0.022)	(0.017)
ICC	0.172	0.105	0.079
Year dummy	No	Yes	Yes
No. of observations	17,311	16,176	16,176
Number of regions	47	46	46

The Table reports average marginal effects. The outcome variable, food deprivation, equals 1 if any member of the household has sometimes or often gone without food. The main independent variable is local digital lending development which is the regional level effect of the likelihood to access digital credit. Standard errors are adjusted via cluster bootstrapping with 400 replications. Robust standard errors are in parentheses
***p < 0.01, **p < 0.05, *p < 0.1