Fintech, financial inclusion and income inequality: a quantile regression approach

Figures & data

Table 1. Description of the variables.

Variable	Source	Definition and measurement
Panel A: Dependent Variables
Gini	The Standardized World Income Inequality Database (SWIID)	Net Inequality
Panel B: Financial Inclusion Indicators
Account	Global Findex	Having an account at a formal financial institution (% age 15+),
Saving	Global Findex	Saving at a formal financial institution (% age 15+),
Borrowing	Global Findex	Borrowing from a formal financial institution (% age 15+)
Panel C: FinTech Indicators
FinTech	Global Findex	Mobile phone used to pay bills (% age 15+)
Panel E: Control Variables
Financial Development	International Money Fund	Financial development index
Education	World Development Indicators 2017 (World Bank)	School enrolment, secondary (% gross)
Redistributive policies	World Development Indicators 2017 (World Bank)	General government final consumption expenditure (% of GDP)
Trade	World Development Indicators 2017 (World Bank)	Trade (% of GDP)
Population growth	World Development Indicators 2017 (World Bank)	Population growth (annual %)
Growth	Author's calculations using data from World Development Indicators 2017 (World Bank)	Author's calculations
GDP	World Development Indicators 2017 (World Bank)	GDP (constant 2010 US$)
Institutional quality	World Governance Indicators 2017 (WGI) (World Bank)	Author's calculations using data from World Governance Indicators 2017 (WGI) (World Bank)

Note: This table presents the variables used in the paper, their definitions and/or measurement, and the sources of raw data.

Table 2. Summary statistics.

Variable	Obs	Mean	Std. dev.	Min	Max
Inequality	383	37.680	7.723	24.002	59.879
Account	405	53.021	31.238	1.520	100
Savings	405	22.207	18.904	0.690	79.330
Borrowing	405	11.453	7.113	0.419	40.510
FinTech	332	4.558	5.904	0.030	37.100
School	404	101.281	15.965	17.546	145.249
Ins. quality	420	−0.003	0.900	−1.978	1.861
Trade	402	89.417	50.561	23.702	286
Gov exp	399	15.720	5.171	4.371	36.604
Inflation	411	6.682	9.748	0.054	62.169
Population	417	16.473	1.479	11.299	21.060
GDP	411	8.600	1.518	5.363	11.589
GDPgr	366	3.601	3.477	−20.490	25.560
Fin dev	363	48.280	22.147	11.739	99.278

Notes: This table presents the summary statistics of the variables used in the estimations. Obs. stands for the number of observations. Std. Dev. is the standard deviation of each variable for a panel of 140 countries for years 2011, 2014 and 2017. Mean is the arithmetic average of each variable in our sample; Min is the minimum value of each variable in the sample; Max is the maximum value of each variable in our sample. Inequality denotes income inequality, measured by the Gini coefficient. Account is the percentage of adults having an account at a formal financial institution. Savings is the percentage of adults saving at a formal financial institution. Borrowing is the percentage of adults that borrow from a formal financial institution. Accounts, Savings and Borrowing are used as measures of financial inclusion. FinTech is a proxy for financial technologies and is measured by the percentage of adults that use of their mobile phone to pay bills. School denotes secondary school completion rate and is used as a proxy for human capital. Ins. quality stands for the quality of institutions. Trade denotes international trade and is measured by the sum of exports and imports as a percentage of GDP; Gov exp refers to government expenditure as a percentage of GDP. Inflation is the inflation rate and is measured by the rate of change of the consumer price index. Population refers to the population growth rate. GDPgr refers to the GDP growth rate. Financial development denotes an index of financial development.

Table 3. The impact of FinTech on financial inclusion.

	(1)	(2)	(3)
VARIABLES	Account	Savings	Borrowing
FinTech	0.673**	0.727**	0.285**
	(0.097)	(0.116)	(0.065)
GDP	10.616***	2.848***	1.104
	(0.248)	(0.261)	(0.392)
School	−0.019	−0.029	0.031*
	(0.017)	(0.011)	(0.010)
Population	0.881*	1.190***	−0.433
	(0.274)	(0.078)	(0.167)
Ins. quality	12.211***	11.352***	1.393*
	(0.183)	(0.113)	(0.382)
Constant	−54.128***	−22.386**	4.776**
	(3.754)	(3.134)	(0.897)
Observations	263	263	263
R-squared	0.769	0.726	0.326

Note: This table reports the regression results for the impact of FinTech on financial inclusion. The dependent variables are Account, Savings and Borrowing, where: Account = % of adults having an account at a formal financial institution; Savings = % of adults saving at a formal financial institution; and Borrowing = % of adults borrowing from a formal financial institution. The explanatory variables are: FinTech = % of adults using their mobile phone to pay bills; GDP = real Gross Domestic Product; School = secondary school completion rate; Population = population growth rate; Ins. quality = Institutional quality. These variables are further described, with sources of data indicated, in Table 1.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 4. The impact of FinTech on income inequality.

	(1)	(2)	(3)	(4)	(5)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality
FinTech	−0.237***	−0.175***	−0.063	−0.050	−0.071
	(0.015)	(0.047)	(0.045)	(0.048)	(0.052)
Account			−0.087***
			(0.015)
Saving				−0.122***
				(0.026)
Borrowing					−0.480***
					(0.125)
GDPgr		0.387***	0.293**	0.327**	0.372***
		(0.122)	(0.133)	(0.130)	(0.139)
School		0.041*	0.046**	0.047**	0.045**
		(0.021)	(0.020)	(0.020)	(0.021)
Trade		−0.046***	−0.032***	−0.038***	−0.039***
		(0.009)	(0.010)	(0.010)	(0.011)
Gov exp		−0.481***	−0.327***	−0.343***	−0.251*
		(0.104)	(0.110)	(0.113)	(0.132)
Inflation		0.006	−0.062	−0.046	−0.033
		(0.056)	(0.058)	(0.059)	(0.059)
Population		−0.073	0.201	0.085	−0.077
		(0.276)	(0.275)	(0.274)	(0.281)
Constant	38.821***	45.318***	41.609***	41.976***	46.273***
	(0.342)	(5.635)	(5.629)	(5.637)	(5.849)
Observations	270	259	256	256	258
R-squared	0.035	0.312	0.361	0.347	0.298

Note: Table 4 reports regression results for the impact of FinTech and financial inclusion on income inequality. The dependent variable is income inequality, measured by the Gini coefficient. FinTech is measured by the percentage of adults who use their mobile phone to pay bills. Financial inclusion is measured in three ways, by Account (the percentage of adults that have an account at a formal financial institution), Savings (the percentage of adults that save at a formal financial institution), and Borrowing (the percentage of adults that borrow from a formal financial institution). GDPgr = denotes the GDP growth rate. School refers to the secondary school completion rate. Trade denotes international trade and is measured by the sum exports and imports over GDP. Gov exp denotes government expenditure as a percentage of GDP. Inflation is the inflation rate and is measured by the rate of change of the consumer price index. Population refers to the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 5. The impact of FinTech and financial inclusion on income inequality: Quantile regression results.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)	(13)	(14)	(15)
	(0.10)	(.25)	(.50)	(.75)	(.90)	(0.10)	(.25)	(.50)	(.75)	(.90)	(0.10)	(.25)	(.50)	(.75)	(.90)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality
FinTech	−0.090	−0.063	−0.059	−0.067	−0.071	−0.023	−0.002	−0.021	−0.094	−0.090	−0.066	0.004	−0.088	−0.121	−0.101
	(0.114)	(0.057)	(0.063)	(0.076)	(0.163)	(0.105)	(0.070)	(0.067)	(0.066)	(0.183)	(0.089)	(0.082)	(0.065)	(0.084)	(0.172)
Account	−0.067**	−0.084***	−0.097***	−0.111***	−0.149***
	(0.033)	(0.016)	(0.018)	(0.022)	(0.047)
Savings						−0.138***	−0.137***	−0.141***	−0.141***	−0.191**
						(0.048)	(0.032)	(0.031)	(0.030)	(0.084)
Borrowing											−0.380**	−0.562***	−0.416***	−0.349**	−0.696**
											(0.162)	(0.149)	(0.118)	(0.152)	(0.313)
GDPgr	0.161	0.142	0.458***	0.439***	0.504*	0.196	0.257**	0.423***	0.452***	0.597*	0.196	0.339**	0.466***	0.427***	0.274
	(0.202)	(0.101)	(0.111)	(0.135)	(0.289)	(0.176)	(0.116)	(0.112)	(0.110)	(0.305)	(0.153)	(0.141)	(0.112)	(0.144)	(0.296)
School	0.036	0.029	0.024	0.059**	0.057	0.040	0.048*	0.035	0.050**	0.043	0.050	0.055*	0.033	0.027	0.074
	(0.044)	(0.022)	(0.024)	(0.030)	(0.063)	(0.039)	(0.026)	(0.025)	(0.024)	(0.068)	(0.034)	(0.031)	(0.025)	(0.032)	(0.065)
Trade	−0.045***	−0.045***	−0.033***	−0.019*	0.006	−0.061***	−0.060***	−0.040***	−0.028***	0.006	−0.056***	−0.058***	−0.042***	−0.044***	0.001
	(0.017)	(0.008)	(0.009)	(0.011)	(0.024)	(0.014)	(0.009)	(0.009)	(0.009)	(0.025)	(0.012)	(0.011)	(0.009)	(0.012)	(0.024)
Gov exp	−0.113	−0.434***	−0.460***	−0.544***	−0.032	−0.047	−0.354***	−0.504***	−0.538***	0.018	−0.101	−0.316***	−0.571***	−0.638***	−0.250
	(0.154)	(0.077)	(0.085)	(0.103)	(0.220)	(0.136)	(0.090)	(0.087)	(0.086)	(0.237)	(0.114)	(0.105)	(0.083)	(0.108)	(0.221)
Inflation	−0.149	−0.155***	−0.126**	0.061	−0.133	−0.191**	−0.144***	−0.113**	0.079	−0.123	−0.070	−0.132**	−0.104**	0.102*	−0.010
	(0.092)	(0.046)	(0.051)	(0.062)	(0.132)	(0.081)	(0.053)	(0.051)	(0.051)	(0.140)	(0.070)	(0.064)	(0.051)	(0.065)	(0.134)
Population	−0.323	0.156	0.382	0.359	0.205	−0.164	−0.240	0.014	0.291	0.177	−0.399	−0.563	−0.051	−0.131	0.104
	(0.552)	(0.276)	(0.303)	(0.370)	(0.791)	(0.480)	(0.317)	(0.307)	(0.301)	(0.835)	(0.413)	(0.379)	(0.301)	(0.389)	(0.798)
Constant	42.615***	44.460***	43.086***	43.200***	43.204**	39.108***	46.760***	47.024***	43.041***	40.449**	42.860***	53.506***	51.498***	56.248***	47.368***
	(11.734)	(5.861)	(6.447)	(7.861)	(16.805)	(10.305)	(6.814)	(6.587)	(6.469)	(17.925)	(8.921)	(8.188)	(6.508)	(8.398)	(17.238)
Equality test					(account)4.41					(saving)5.12					(borrowing)3.93
					p = 0.009					p = 0.008					p = 0.010
R-squared	0.342	0.354	0.412	0.431	0.455	0.201	0.221	0.302	0.325	0.345	0.301	0.339	0.358	0.412	0.447
Observations	248	248	248	248	248	248	248	248	248	248	248	248	248	248	248

Note: This table reports quantile regression results for the impact of FinTech and financial inclusion on income inequality. The dependent variable is income inequality, measured by the Gini coefficient. FinTech is a proxy for FinTech, measured as the percentage of adults that use a mobile phone to pay bills. Financial inclusion is measured using three proxies, namely: Account (the % of adults having an account at a formal financial institution), Savings (the % of adults saving at a formal financial institution), and Borrowing (the % of adults borrowing from a financial institution). GDPgr denotes the GDP growth rate. School denotes the secondary school completion rate and is used as a measure of human capital. Trade refers to foreign trade and is measured by exports plus imports as a percentage of GDP. Gov exp denotes government expenditure as a percentage of GDP. Inflation is a measure of inflation, which is measured as the rate of change of the Consumer Price Index. Population denotes the population growth rate. The equality test applied is the F-test where the null hypothesis purports that the estimated slope coefficients for financial inclusion variables (account, saving and borrowing) are not statistically different across all the quantile estimates.

Standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 6. The impact of FinTech and financial inclusion on income inequality in high-income, upper-middle income, lower-middle income and low-income countries.

	(1)	(2)	(5)	(6)	(7)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality
High-Income Countries
FinTech	−0.143**	−0.009*	0.014	0.027	0.021
	(0.066)	(0.012)	(0.018)	(0.055)	(0.016)
Account			−0.121***
			(0.010)
Savings				−0.071**
				(0.033)
Borrowing					−0.125**
					(0.063)
Observations	114	114	100	100	111
R-squared	0.040	0.322	0.425	0.652	0.544
Upper-Middle Income Countries
FinTech	−0.026*	−0.041	−0.066	−0.147**	−0.031**
	(0.015)	(0.074)	(0.150)	(0.069)	(0.013)
Account			0.214***
			(0.074)
Saving				0.379***
				(0.078)
Borrowing					−0.325***
					(0.084)
Observations	90	75	79	79	79
R-squared	0.055	0.321	0.432	0.543	0.602
Lower-Middle Income Countries
FinTech	0.143***	0.044	0.047	0.123	0.008
	(0.048)	(0.058)	(0.051)	(0.129)	(0.042)
Account			0.070***
			(0.024)
Saving				0.195*
				(0.097)
Borrowing					0.397**
					(0.169)
Observations	88	79	66	65	74
R-squared	0.045	0.201	0.234	0.240	0.321
Low Income Countries
FinTech	0.236**	0.562***	0.464***	0.455***	0.244**
	(0.098)	(0.151)	(0.145)	(0.150)	(0.119)
Account			0.146***
			(0.054)
Saving				0.226**
				(0.098)
Borrowing					1.316***
					(0.296)
Observations	58	46	46	46	46
R-squared	0.182	0.356	0.465	0.501	0.582

Note: This table reports regression results for the impact of FinTech and financial inclusion on income inequality in countries with varying income levels. The dependent variable is income inequality measured by the Gini coefficient. FinTech is a proxy for FinTech, measured by the percentage of adults using a mobile phone to pay bills. Financial inclusion is measured using three proxies: Account (the percentage of adults having an account at a formal financial institution), Savings (the percentage of adults saving at a formal financial institution), Borrowing (the percentage of adults borrowing from a financial institution). GDPgr denotes the GDP growth rate. School refers to the secondary school completion rate. Trade refers to foreign trade and is measured by the sum of exports and imports over GDP; Gov exp denotes government expenditure as a percentage of GDP. Inflation is a measure of inflation and is calculated as the rate of change of the Consumer Price Index; Population denotes the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 7. The impact of FinTech and financial inclusion on income inequality, where the IMF financial development index is used as a proxy for financial inclusion.

	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
				(0.10)	(.25)	(.50)	(.75)	(.90)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality	Inequality
FinTech	−0.237***	−0.175***	−0.090	−0.121**	−0.084	−0.098**	−0.111*	−0.126
	(0.015)	(0.059)	(0.063)	(0.053)	(0.066)	(0.046)	(0.056)	(0.090)
Fin Dev			−0.078***	−0.027	−0.070***	−0.083***	−0.113***	−0.068**
			(0.020)	(0.022)	(0.018)	(0.016)	(0.026)	(0.034)
GDPgr		0.387***	0.311***	0.270*	0.203**	0.219***	0.236*	0.443***
		(0.110)	(0.115)	(0.158)	(0.086)	(0.073)	(0.140)	(0.155)
School		0.041*	0.044*	0.048	0.043	0.023	0.023	0.064**
		(0.024)	(0.025)	(0.039)	(0.032)	(0.024)	(0.022)	(0.032)
Trade		−0.046***	−0.033***	−0.051***	−0.044***	−0.040***	−0.057***	−0.012
		(0.009)	(0.009)	(0.010)	(0.010)	(0.011)	(0.011)	(0.011)
Gov exp		−0.481***	−0.294***	−0.329***	−0.524***	−0.455***	−0.432***	−0.503***
		(0.086)	(0.090)	(0.072)	(0.078)	(0.052)	(0.124)	(0.192)
Inflation		0.006	−0.047	−0.340	−0.106	−0.077	−0.069	0.004
		(0.045)	(0.048)	(0.217)	(0.124)	(0.063)	(0.084)	(0.079)
Population		−0.073	0.519	0.228	0.460	0.316	0.564	0.200
		(0.300)	(0.342)	(0.399)	(0.366)	(0.329)	(0.349)	(0.353)
Constant	38.821***	45.318***	34.147***	32.983***	36.749***	43.489***	44.035***	44.382***
	(0.342)	(6.469)	(7.041)	(8.632)	(7.254)	(6.476)	(6.942)	(7.499)
Equality Test								(Fin Dev) 4.43
								p = 0.008
Observations	270	249	248	239	259	233	251	239
R-squared	0.035	0.312	0.412	0.375	0.389	0.399	0.423	0.456

Note: This table reports regression results for the impact of FinTech and financial inclusion on income inequality, where financial inclusion is proxied by the IMF financial development index (Fin Dev). The dependent variable is income inequality measured by the Gini coefficient. FinTech is a proxy for FinTech and is measured by the percentage of adults using a mobile phone to pay bills. GDPgr refers to the GDP growth rate. School denotes the secondary school completion rate. Trade refers to the sum of exports and imports over GDP; Gov exp denotes government expenditure as a percentage of GDP. Inflation is the rate of change of the Consumer Price Index; Population refers to the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 8. The impact of FinTech and financial inclusion on income inequality for countries with different income levels- the IMF financial development index is used as a proxy for financial inclusion.

	(1)	(2)	(3)	(4)
	High Income	Upper middle-income	Lower middle-income	Low Income
VARIABLES	Inequality	Inequality	Inequality	Inequality
FinTech	0.010	−0.052*	0.047	0.547***
	(0.009)	(0.030)	(0.054)	(0.150)
Fin Dev	−0.047**	−0.079**	0.119***	−0.212
	(0.019)	(0.036)	(0.035)	(0.172)
GDPgr	0.031	−0.020	0.224*	0.069
	(0.021)	(0.050)	(0.115)	(0.190)
School	−0.018***	−0.024**	0.100***	0.067***
	(0.007)	(0.012)	(0.033)	(0.020)
Trade	0.005	−0.006	−0.073***	0.024
	(0.005)	(0.013)	(0.008)	(0.029)
Gov exp	−0.170***	−0.173	−0.758***	0.093
	(0.054)	(0.123)	(0.086)	(0.123)
Inflation	0.050	−0.006	−0.079	−0.014
	(0.032)	(0.015)	(0.078)	(0.063)
Population	1.051**	1.753	−1.739***	−0.569
	(0.435)	(1.177)	(0.397)	(1.174)
Constant	21.568***	17.664	73.415***	40.980*
	(7.222)	(20.594)	(7.869)	(21.941)
Observations	114	70	68	44
R-squared	0.065	0.212	0.321	0.326

Note: This table reports regression results for the impact of FinTech and financial inclusion on income inequality for countries with different levels of income. The IMF financial development index (Fin Dev) is used as a proxy for financial inclusion. The dependent variable is income inequality measured by the Gini coefficient. FinTech is a proxy for FinTech and is measured by the percentage of adults using a mobile phone to pay bills. GDPgr denotes the GDP growth rate. School refers to the secondary school completion rate. Trade refers to foreign trade and is measured exports plus imports as a percentage of GDP. Gov exp denotes government expenditure as a percentage of GDP. Inflation is the rate of change of the Consumer Price Index. Population refers to the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 9. Re-estimation of Table 4 with panel country and time fixed effects.

	(1)	(2)	(3)	(4)	(5)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality
Gini(−1)	0.121**	0.114**	0.113**	0.113**	0.114**
	(0.055)	(0.050)	(0.055)	(0.048)	(0.049)
FinTech	−0.037**	−0.031**	−0.010	−0.011	−0.013
	(0.018)	(0.015)	(0.022)	(0.022)	(0.021)
Account			−0.009**
			(0.004)
Saving				−0.009**
				(0.004)
Borrowing					−0.003**
					(0.001)
GDPgr		0.017	0.012	0.013	0.014
		(0.013)	(0.013)	(0.013)	(0.012)
School		−0.005	−0.004	−0.004	−0.005
		(0.003)	(0.003)	(0.003)	(0.003)
Trade		0.001	0.001	0.001	0.001
		(0.004)	(0.004)	(0.004)	(0.004)
Gov exp		−0.055*	−0.061**	−0.060**	−0.062**
		(0.030)	(0.030)	(0.030)	(0.030)
Inflation		−0.006	−0.005	−0.006	−0.005
		(0.008)	(0.008)	(0.008)	(0.008)
Population		−0.289	−0.241	−0.276	−0.253
		(0.797)	(0.781)	(0.783)	(0.775)
Constant	37.763***	43.330***	43.132***	43.400***	43.971***
	(0.086)	(13.378)	(13.082)	(13.134)	(12.995)
Observations	269	222	219	219	219
R-squared	0.121	0.135	0.146	0.139	0.160
Number of id	132	113	112	112	112

Note: This table reports the panel fixed effects results for the impact of FinTech and financial inclusion on income inequality. The dependent variable is income inequality measured by the Gini coefficient. FinTech is measured by percentage of adults using a mobile phone to pay bills. Financial inclusion is measured in three ways, by Account (the % of adults having an account at a formal financial institution), Savings (the % of adults saving at a formal financial institution), and Borrowing (the % of adults borrowing from a formal financial institution). GDPgr = denotes the GDP growth rate. School is the secondary school completion rate. trade denotes international trade and is measured by exports and imports over GDP. Gov exp denotes government expenditure as a percentage of GDP. Inflation is the rate of change of the consumer price index. Population is the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.

Table 10. Re-estimation of Table 4 for each of the years 2011, 2014 and 2017.

	(1)	(2)	(3)	(4)	(5)
VARIABLES	Inequality	Inequality	Inequality	Inequality	Inequality
Estimation of Table 4 for 2011
FinTech	−1.028***	−0.783**	−0.381	−0.480	−0.519
	(0.251)	(0.321)	(0.370)	(0.367)	(0.355)
Account			−0.079**
			(0.036)
Saving				−0.097*
				(0.056)
Borrowing					−0.394*
					(0.217)
Observations	131	112	111	111	111
R-squared	0.115	0.272	0.305	0.293	0.295
Estimation of Table 4 for 2014
FinTech	−1.096***	−0.453**	0.038	0.032	0.044
	(0.282)	(0.217)	(0.321)	(0.332)	(0.352)
Account			−0.128***
			(0.031)
Saving				−0.180***
				(0.049)
Borrowing					−0.638***
					(0.210)
Observations	121	107	106	106	106
R-squared	0.112	0.262	0.379	0.355	0.330
Estimation of Table 4 for 2017
FinTech	−1.204***	−0.445**	0.112	0.077	−0.078
	(0.341)	(0.215)	(0.385)	(0.396)	(0.396)
Account			−0.104***
			(0.030)
Saving				−0.141***
				(0.048)
Borrowing					−0.415**
					(0.187)
Observations	117	103	102	102	102
R-squared	0.098	0.362	0.436	0.417	0.395

Note: This table reports the OLS regression results for the impact of FinTech and financial inclusion on income inequality for the years 2011, 2014 and 2017. The dependent variable is income inequality measured by the Gini coefficient. FinTech is measured by the percentage of adults using a mobile phone to pay bills. Financial inclusion is measured in three ways, by Account (the % of adults having an account at a formal financial institution), Savings (the % of adults saving at a formal financial institution), and Borrowing (the % of adults borrowing from a formal financial institution). GDPgr refers to the GDP growth rate. School denotes the secondary school completion rate. Trade denotes international trade and is measured as the sum of exports and imports over GDP. Gov exp denotes government expenditure as a percentage of GDP. Inflation is the rate of change of the consumer price index. Population refers to the population growth rate.

Robust standard errors in parentheses: ***p < 0.01, **p < 0.05, *p < 0.1.