Reducing farmers' poverty vulnerability in China: The role of digital financial inclusion

• Published date: 01 August 2023
• Author: Bo Yang,Xiangnan Wang,Tong Wu,Weihua Deng
• Date: 01 August 2023
• DOI: http://doi.org/10.1111/rode.12991

SPECIAL ISSUE ARTICLE

Reducing farmers' poverty vulnerability in

China: The role of digital financial inclusion

Bo Yang

1

| Xiangnan Wang

2,3

| Tong Wu

4

| Weihua Deng

5

1

School of Economics, Yunnan

University, Kunming, China

2

Chinese Academy of Social Sciences,

Beijing, China

3

T.H. Chan School of Public Health,

Harvard University, Boston, USA

4

School of Business, Sun Yat-sen

University, Guangzhou, China

5

College of Economics & Management,

South China Agricultural University,

Guangzhou, China

Correspondence

Weihua Deng, College of Economics &

Management, South China Agricultural

University, Guangzhou, China.

Email: dengweihua@stu.scau.edu.cn

Funding information

the Basic Research Program of Yunnan

Province Science and Technology

Department, Grant/Award Number:

2060206; the Chinese National Social

Science Fund Granted Project,

Grant/Award Number: 20VSZ006

Abstract

This paper applies exogenous shocks to investigate the

impact of digital financial inclusion (DFI) on farmers'

poverty vulnerability in China. We find that farmers in

highly developed DFI areas are less vulnerable to the

poverty trap. The result is robust to various checks,

including propensity score matching and difference-in-

differences method and the instrumental variable

approach. Moreover, we find that income diversification

is the possible economic channel through which DFI

affects farmers' poverty vulnerability. Further analyses

show that DFI has a “targeting”effect on thos e who are

poor and vulnerable, and a synergistic effect by working

with medical insurance and informal finance in terms of

reducing farmers' poverty vulnerability. Our research

findings provide new theoretical insights and useful

guidance in enhancing financial inclusiveness and

sustainable development in the post-COVID-19 era.

KEYWORDS

digital financial inclusion, exogenous shocks, income

diversification, poverty vulnerability

JEL CLASSIFICATION

I32, J43, Q14, R51

1|INTRODUCTION

China has made remarkable achievements in erasing farmer absolute poverty in recent decades,

which is well recognized in the international community. However, poverty not only involves

absolute poverty—for example, material shortages, low educational levels, or poor health—but

Received: 15 April 2022 Revised: 9 March 2023 Accepted: 10 March 2023

DOI: 10.1111/rode.12991

Rev Dev Econ. 2023;27:1445–1480. wileyonlinelibrary.com/journal/rode © 2023 John Wiley & Sons Ltd. 1445

also includes vulnerability (World Bank, 2001). Poverty vulnerability refers to how susceptible

an individual is to poverty when subjected to unexpected external shocks (Chaudhuri

et al., 2002). Individuals who are vulnerable to poverty could easily return to a poor economic

state even after immediately leaving it. Therefore, how to reduce poverty vulnerability has

become a major subject of concern for both policy-makers and scholars.

The literature on poverty vulnerability has proposed several key strategies to reduce poverty

vulnerability, for example, traditional finance development (Han et al., 2019; Khandker, 2007;

Phan et al., 2023), public fiscal transfer payments (Azeem et al., 2019; Brugh et al., 2018;Li&

Huang, 2022; Wang et al., 2021), and social security (Carter & Janzen, 2018; Khosla &

Jena, 2022; Tirivayi et al., 2016; Zhang et al., 2020). In addition, informal risk-coping mecha-

nisms, such as the sale of livestock to smooth consumption, are supported by a large number of

documents (Dube & Ozkan, 2022; Fafchamps et al., 1998; Kurosaki, 1995; Ngigi et al., 2021;

Rosenzweig & Wolpin, 1993; Udry, 1995). Among them, the literature on traditional finance

and poverty vulnerability is directly related to our research. However, in the past 10 years in

China, such financial services have been proven in practice to lack business sustainability

(Razzaq & Yang, 2023). Moreover, these methods either represent ex post compensation with a

time lag in practice (e.g., social security) or are accompanied by a possible increase in later vul-

nerability (e.g., sales of productive livestock). As a result, rural households are more likely to

return to the poverty trap.

In recent years, digital financial inclusion (DFI) has gradually become an irreplaceable part

of China's financial system. The “G20 High-Level Principles for Digital Financial Inclusion”

released by the Global Partnership for Financial Inclusion in 2016, defines DFI as “all actions

to promote financial inclusion through the use of digital financial services”. Specifically, it

involves the use of digital technology to provide a range of formal financial services to groups

that have no access to or lack financial services. These financial services are delivered responsi-

bly and affordably. Supported by big data, cloud computing, artificial intelligence, blockchain,

and other digital technologies, DFI can help reduce the cost of providing and acquiring finan-

cial services for both institutions and consumers, improve the coverage and depth of financial

services even in remote rural areas, and create a diversified financial market. As such, DFI

could widely alleviate farmers' financing constraints and meet the capital requirements of

investments in the agricultural sector, which may greatly support or boost rural and agricultural

development in the Digital Age.

The literature has focused on whether and how DFI affects farmers' absolute poverty at the

macro and micro levels (Demir et al., 2022; Lee et al., 2021; Mushtaq & Bruneau, 2019; Suri

et al., 2021; Ye et al., 2022). Evidence shows that internet finance

1

plays the role of risk manage-

ment for rural households (Carter, 2022; Jack & Suri, 2014; Li et al., 2022). As such, it can help

them cope with unexpected needs and increase their resilience to shocks (Suri et al., 2021; Yang

et al., 2022). However, the research has not paid enough attention to whether DFI could allevi-

ate poverty vulnerability. Moreover, as farming is highly dependent on the natural environ-

ment, the climate variations (i.e., climate changes, exposure, and anomalies) increase farmers'

vulnerability (Ahmed et al., 2009; Angelsen & Dokken, 2018; Bobonis et al., 2022; Salvucci &

Tarp, 2021). Therefore, different from the literature, in this paper, we integrate DFI, shocks,

and vulnerability into the same analytical framework. To the best of our knowledge, these fac-

tors have not yet been systematically examined.

In this paper, we aim to extend the literature on poverty vulnerability by exploring two

research questions: can DFI reduce poverty vulnerability, particularly when the subject

undergoes shocks such as climate anomalies and diseases? If so, by what mechanism? Thus, we

1446 YANG ET AL.

combine data from the China Labor-force Dynamic Survey (CLDS) and Digital Inclusive Index

released by Peking University to verify these research questions. The results show that DFI can

reduce farmers' poverty vulnerability when suffering from shocks. The results are consistent

across a broad series of robustness tests, including a new identification strategy, the “Broadband

Plan in China”, as well as the instrumental variable (IV) approach (i.e., the geographical dis-

tance to Hangzhou) to address potential endogeneity, and alternative robustness checks. Specif-

ically, when shocks are introduced, including weather shocks (i.e., precipitation or temperature

change) at the macro level and disease shocks at the micro level, DFI alleviates the negative

impact of weather or disease shocks on farmers' poverty vulnerability. Moreover, channel ana-

lyses reveal that DFI helps reduce farmers' poverty vulnerability by broadening their income

channels, including farmers' agricultural, operational, wage, and property income. Further-

more, we find that DFI shows a “targeting”effect—that is, DFI is helpful for farmers who are

poor and vulnerable—and that DFI has a synergistic effect by working with medical insurance

(i.e., a formal risk-sharing mechanism) or informal finance (i.e., an informal risk-sharing mech-

anism) in terms of reducing farmers' poverty vulnerability.

The main contributions of this paper are as follows: (1) Given that climatic anomalies and

disease shocks are two main causes of farmers' poverty vulnerability in China, we design an

integrated framework to explore whether developing DFI could protect farmers from such

shocks and thereby reduce their poverty vulnerability. (2) To further confirm the result, we pro-

vide a new identification strategy, namely, the policy of the “Broadband Plan in China”,

because the variation in regional DFI could be driven by the benefits of broadband strategy.

This strategy provides solid supporting evidence for our results. (3) Considering that vulnerabil-

ity is a type of future risk and that DFI is thus treated as a kind of formal risk-sharing mecha-

nism, we further examine how DFI works with another two types of risk-sharing mechanisms

(i.e., insurance and informal finance) with respect to vulnerability. Therefore, discussing three

types of risk-sharing mechanisms together is helpful for us to explore theoretically the combina-

tions that could alleviate poverty vulnerability effectively.

Our findings also have significant policy implications for developing countries, which

should prioritize supporting DFI development. This suggestion is particularly true in the post-

COVID-19 era because vulnerability can also be induced by significant public health events. In

addition, we find that DFI and insurance (i.e., the formal risk-sharing mechanism) work syner-

gistically in addressing vulnerability in China. Thus, in areas where commercial medical insur-

ance is difficult to access, related medical care arrangements should be introduced. As a result,

China could thus make full use of the pooled effects to support the development of the real

economy.

The remainder of this paper is arranged as follows. Section 2describes the background and

hypotheses development. Section 3introduces the data, variables, and methodology. Section 4

presents the baseline regression results. Section 5provides the robustness tests. Section 6pre-

sents the further analysis. Section 7offers the conclusions and policy implications.

2|BACKGROUND AND HYPOTHESES DEVELOPMENT

2.1 |Institutional background

In this section, we briefly introduce the present state of poverty in China, the Chinese govern-

ment's anti-poverty measures in recent decades as well as the institutional background of DFI.

YANG ET AL.1447