The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China
Abstract
:1. Introduction
2. Literature Review and Research Hypothesis
2.1. Literature Review
2.2. Research Hypothesis
3. Materials and Methods
3.1. Data Source
3.2. Variable Measurement
3.2.1. Explained Variables
3.2.2. Core Explanatory Variable
3.2.3. Other Control Variables
3.3. Model, Variable Processing, and Description
3.4. Identifying Strategy and Estimation Method
4. Results
4.1. Baseline Analysis
4.2. Robustness Check
4.3. Mechanism Analysis
4.3.1. The Role of Entrepreneurial Decision-Making
4.3.2. The Role of Risk Management Capabilities
4.4. Heterogeneity Analysis
4.4.1. Population Differences
4.4.2. Regional Differences
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Author, Year | Viewpoints | Critical Analysis | |
---|---|---|---|
First aspect | Qiu et al., 2022 [47] | Mobile payment can increase rural household income and reduce the health risks of family members | The data need to be further improved |
Yu et al., 2022 [48] | Using mobile payment helps reduce COVID-19 infection | The impact of the external institutional environment on mobile payment remains to be discussed | |
Suri et al., 2016 [49] | Mobile payment can lift households out of poverty and increase their consumption | The universality of mobile payment for vulnerable groups is not explained from the perspective of dynamic poverty | |
Kikulwe et al., 2014 [50] | Mobile payment can help to overcome some of the important smallholder market access constraints that obstruct rural development and poverty reduction | The impact mechanism of mobile payment on informal savings and insurance needs to be explored | |
Second aspect | Sun et al., 2020 [51] | Credit can reduce vulnerability to poverty | The mechanism of credit channels on poverty vulnerability remains to be explored |
Wang et al., 2022 [52] | Digital finance can reduce poverty vulnerability | The influence mechanism between the two needs to be explored | |
Zameer et al., 2020 [53] | Financial development positively contributes to poverty alleviation efficiency in China | Not considered from the perspective of dynamic poverty | |
Scandurra et al., 2020 [54] | External funds can reduce the vulnerability of small island developing states | The estimation is biased because the political purpose of external funds is not taken into account |
Variable | Definition |
---|---|
Mobile payment | Using mobile payment: 1, otherwise: 0 |
VEP1 | USD 1.9 poverty line, 29% vulnerability line |
VEP2 | USD 1.9 poverty line, 50% vulnerability line |
Age | Householder between the ages of 18 and 65 |
Gender | Householder gender; male: 1, female: 0 |
Education (years) | Householder education status; illiteracy: 0, primary school: 6, junior high school: 12, college/higher vocational school undergraduate college: 16, master’s degree: 19, doctoral degree: 22 |
Risk preference | Householder risk preference: 1, other: 0 |
Risk aversion | Householder risk aversion: 1, other: 0 |
Farmer | Householder is a farmer: 1, other: 0 |
Family size | Number of family members |
Family size squared | The square of the number of family members |
Debt | Household debt plus 1, then take the natural logarithm |
Transfer expenditure | Household’s transfer expenditure plus 1, then take the natural logarithm |
Unhealthy 1 | Number of people in the household who rated themselves as unhealthy |
Household nonfinancial assets | Household holdings of nonfinancial assets plus 1, then the natural logarithm |
Housing ownership | Family owns its own home: 1, other: 0 |
Rural | Household is in a rural area: 1, other: 0 |
Variable | Observation | Mean | SD | Minimum | Maximum |
---|---|---|---|---|---|
Mobile payment | 13,798 | 0.378 | 0.485 | 0 | 1 |
VEP1 | 13,798 | 0.028 | 0.166 | 0 | 1 |
VEP2 | 13,798 | 0.012 | 0.107 | 0 | 1 |
Age | 13,798 | 48.42 | 10.20 | 18 | 65 |
Gender | 13,798 | 0.839 | 0.368 | 0 | 1 |
Education | 13,798 | 9.970 | 3.936 | 0 | 22 |
Risk preference | 13,798 | 0.117 | 0.321 | 0 | 1 |
Risk aversion | 13,798 | 0.574 | 0.495 | 0 | 1 |
Farmer | 13,798 | 0.595 | 0.491 | 0 | 1 |
Family size | 13,798 | 3.291 | 1.411 | 1 | 14 |
Family size squared | 13,798 | 12.82 | 11.69 | 1 | 196 |
Debt | 13,798 | 4.415 | 4.992 | 0 | 15.54 |
Transfer expenditure | 13,798 | 0.474 | 0.507 | 0 | 4.879 |
Unhealthy | 13,798 | 0.382 | 0.727 | 0 | 6 |
Household nonfinancial assets | 13,798 | 12.69 | 1.764 | 5.303 | 16.36 |
Housing ownership | 13,798 | 0.851 | 0.356 | 0 | 1 |
Rural | 13,798 | 0.350 | 0.477 | 0 | 1 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
---|---|---|---|---|---|---|---|---|
VEP1 | VEP2 | |||||||
Mobile payment | −0.076 *** | −0.048 *** | −0.030 *** | −0.037 *** | −0.037 *** | −0.022 *** | −0.013 *** | −0.013 *** |
(0.007) | (0.007) | (0.005) | (0.006) | (0.004) | (0.004) | (0.003) | (0.005) | |
Gender | 0.025 *** | 0.016 *** | 0.016 *** | 0.008 ** | 0.005 * | 0.006 * | ||
(0.006) | (0.005) | (0.005) | (0.004) | (0.003) | (0.003) | |||
Age | 0.001 *** | 0.001 *** | 0.001 *** | 0.001 *** | 0.001 *** | 0.001 *** | ||
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |||
Education | −0.005 *** | −0.003 *** | −0.002 *** | −0.003 *** | −0.002 *** | −0.001 *** | ||
(0.001) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |||
Risk preference | −0.012 *** | −0.002 | −0.001 | −0.003 | 0.005 | 0.006 * | ||
(0.004) | (0.003) | (0.003) | (0.003) | (0.003) | (0.003) | |||
Risk aversion | −0.005 | 0.004 ** | 0.003 * | −0.002 | 0.003 ** | 0.003 ** | ||
(0.003) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | |||
Farmer | 0.047 *** | 0.027 *** | 0.024 *** | 0.027 *** | 0.019 *** | 0.018 *** | ||
(0.007) | (0.006) | (0.006) | (0.006) | (0.006) | (0.005) | |||
Family size | 0.053 *** | 0.054 *** | 0.033 *** | 0.032 *** | ||||
(0.003) | (0.003) | (0.002) | (0.002) | |||||
Family size squared | −0.004 *** | −0.004 *** | −0.002 *** | −0.002 *** | ||||
(0.000) | (0.000) | (0.000) | (0.000) | |||||
Housing ownership | 0.066 *** | 0.061 *** | 0.034 *** | 0.031 *** | ||||
(0.008) | (0.008) | (0.006) | (0.006) | |||||
Rural | 0.019 *** | 0.016 *** | 0.006 *** | 0.004 *** | ||||
(0.003) | (0.003) | (0.002) | (0.002) | |||||
Debt | −0.000 ** | −0.000 * | −0.001 *** | −0.001 *** | ||||
(0.000) | (0.000) | (0.000) | (0.000) | |||||
Transfer expenditure | −0.056 *** | −0.053 *** | −0.036 *** | −0.033 *** | ||||
(0.004) | (0.004) | (0.006) | (0.006) | |||||
Unhealthy | −0.000 | −0.001 | −0.000 | −0.000 | ||||
(0.001) | (0.001) | (0.001) | (0.001) | |||||
Household nonfinancial assets | −0.025 *** | −0.023 *** | −0.014 *** | −0.013 *** | ||||
(0.001) | (0.001) | (0.000) | (0.000) | |||||
Province fixed effects | YES | YES | YES | YES | YES | YES | YES | YES |
Observations | 12,030 | 12,030 | 12,030 | 11,984 | 10,394 | 10,394 | 10,394 | 10,354 |
Adj. R2 | 0.140 | 0.235 | 0.666 | 0.127 | 0.231 | 0.742 | ||
F test | 426.33 | 426.33 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
---|---|---|---|---|---|---|---|---|
VEP1 | VEP2 | |||||||
Mobile payment | −0.160 *** | −0.028 *** | −0.050 *** | −0.032 *** | −0.074 ** | −0.013 *** | −0.029 *** | −0.020 *** |
(0.051) | (0.005) | (0.007) | (0.005) | (0.031) | (0.003) | (0.007) | (0.004) | |
Controls | YES | YES | YES | YES | YES | YES | YES | YES |
Province fixed effects | YES | YES | YES | YES | YES | YES | YES | YES |
Observations | 13,796 | 12,030 | 13,798 | 13,798 | 13,796 | 10,394 | 13,798 | 13,798 |
Adj. R2 | 0.669 | 0.563 | 0.742 | 0.746 | 0.489 | 0.747 | ||
Kleibergen–Paap rk LM Statistic | 18.889 | 18.889 | ||||||
Cragg–Donald Wald F statistic | 157.721 | 157.721 | ||||||
Hausman test | 12.157 *** | 6.600 ** | ||||||
(p-value) | (0.002) | (0.016) |
(1) | (2) | (3) | (4) | (5) | (6) | ||
---|---|---|---|---|---|---|---|
Entrepreneurship | VEP1 | VEP2 | Entrepreneurship Survival | ||||
Mobile payment | 0.070 *** | 0.117 *** | 0.044 | 0.059 *** | |||
(0.023) | (0.026) | (0.031) | (0.016) | ||||
Entrepreneurship | −0.008 | −0.009 ** | |||||
(0.006) | (0.004) | ||||||
Entrepreneurship survival | −0.010 ** | ||||||
(0.004) | |||||||
Entrepreneurial exit | −0.003 | ||||||
(0.006) | |||||||
Start-up business | −0.002 | ||||||
(0.005) | |||||||
Controls | YES | YES | YES | YES | YES | YES | YES |
Province fixed effects | YES | YES | YES | YES | YES | YES | YES |
Observations | 13,750 | 4806 | 8944 | 12,030 | 10,394 | 10,394 | 13,750 |
Adj. R2 | 0.658 | 0.740 | 0.740 | ||||
F test | 426.33 | 25.28 | 267.42 | 426.33 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | |
---|---|---|---|---|---|---|---|---|---|
Unemployment Insurance | Business Insurance | Cost of Credit | VEP1 | VEP2 | |||||
Mobile payment | 0.207 *** | 0.146 *** | −0.037 ** | ||||||
(0.020) | (0.011) | (0.016) | |||||||
Unemployment insurance | −0.040 *** | −0.029 *** | |||||||
(0.014) | (0.008) | ||||||||
Business insurance | −0.027 *** | −0.016 *** | |||||||
(0.010) | (0.006) | ||||||||
Cost of credit | 0.008 ** | 0.008 *** | |||||||
(0.004) | (0.002) | ||||||||
Controls | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Province fixed effects | YES | YES | YES | YES | YES | YES | YES | YES | YES |
Observations | 13,750 | 13,750 | 13,750 | 12,030 | 12,030 | 12,030 | 10,394 | 10,394 | 10,394 |
Adj. R2 | 0.424 | 0.423 | 0.422 | 0.445 | 0.452 | 0.455 | |||
F test | 426.99 | 426.99 | 426.99 |
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
---|---|---|---|---|---|---|---|---|
VEP1 | VEP2 | |||||||
Mobile payment | −0.083 *** | −0.108 *** | −0.036 *** | −0.032 *** | −0.032 *** | −0.029 *** | −0.024 *** | −0.004 |
(0.023) | (0.010) | (0.004) | (0.008) | (0.011) | (0.007) | (0.003) | (0.005) | |
West | −0.064 *** | −0.035 *** | ||||||
(0.004) | (0.003) | |||||||
Mobile payment × west | −0.022 ** | −0.056 *** | ||||||
(0.009) | (0.005) | |||||||
Central | −0.017 *** | −0.006 *** | ||||||
(0.003) | (0.002) | |||||||
Mobile payment × central | 0.014 | 0.003 | ||||||
(0.009) | (0.005) | |||||||
Housing ownership | 0.066 *** | 0.034 *** | ||||||
(0.008) | (0.006) | |||||||
Rural | 0.019 *** | 0.006 *** | ||||||
(0.003) | (0.002) | |||||||
Mobile payment × household income | 0.006 ** | 0.002 ** | ||||||
(0.003) | (0.001) | |||||||
Household income | −0.000 | −0.000 | ||||||
(0.000) | (0.000) | |||||||
Mobile payment × housing ownership | 0.078 *** | 0.016 * | ||||||
(0.009) | (0.009) | |||||||
Mobile payment × rural | 0.004 | −0.013 * | ||||||
(0.009) | (0.007) | |||||||
Controls | YES | YES | YES | YES | YES | YES | YES | YES |
Province fixed effects | YES | YES | YES | YES | YES | YES | YES | YES |
Observations | 12,030 | 12,030 | 12,030 | 12,030 | 10,394 | 10,394 | 10,394 | 10,394 |
Adj. R2 | 0.667 | 0.666 | 0.666 | 0.666 | 0.744 | 0.742 | 0.744 | 0.743 |
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Li, Y.; Gong, X.; Zhang, J.; Xiang, Z.; Liao, C. The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China. Int. J. Environ. Res. Public Health 2022, 19, 14001. https://doi.org/10.3390/ijerph192114001
Li Y, Gong X, Zhang J, Xiang Z, Liao C. The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China. International Journal of Environmental Research and Public Health. 2022; 19(21):14001. https://doi.org/10.3390/ijerph192114001
Chicago/Turabian StyleLi, Yuhua, Xiheng Gong, Jingyi Zhang, Ziwei Xiang, and Chengjun Liao. 2022. "The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China" International Journal of Environmental Research and Public Health 19, no. 21: 14001. https://doi.org/10.3390/ijerph192114001
APA StyleLi, Y., Gong, X., Zhang, J., Xiang, Z., & Liao, C. (2022). The Impact of Mobile Payment on Household Poverty Vulnerability: A Study Based on CHFS2017 in China. International Journal of Environmental Research and Public Health, 19(21), 14001. https://doi.org/10.3390/ijerph192114001