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Na Shen, Hong Kong Shue Yan UniversityLei Xu, UniSA
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Background Literature and hypotheses Method Descriptive results
Regression results Discussion and conclusion
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informal financing is more popular in smaller and younger firms
(Allen et al., 2019)
the scope of informal finance has expanded into the broader
universe of shadow banking (Tsai, 2015)
Shadow banking refers to all financial instruments that fulfil
functions of credit intermediation typically performed by banks
(such as liquidity, maturity, and credit risk transformation), but
reduce the burden of or bypass banking regulation (Ehlers et al.,
2018).
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Due to its unregulated character, internet finance is regarded
as part of shadow banking in China (Tsai, 2015).
Internet finance includes the internetization of finance, mobile
and third-party payments, internet currency, using big data for
credit scoring and network loans, peer-to-peer (P2P) network loans,
and crowdfunding (Xie et al., 2015).
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Research question: will the development of shadow banking,
particularly, internet finance, helps in private firms’ financing
in China?
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Chinese private firms face significant barriers in accessing
credit from banks
Internet finance develops fast in China There are large
institutional variations among
different regions in China
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There is only limited literature discussing private firms’
financing and shadow banking.
Tsai (2017) argue shadow banking can be productive to provide
financing to small and medium enterprises in China, though no
empirical analysis is provided.
H1: There is a positive relationship between internet finance
development and private firm’s debt from internet finance
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As to the interest rate, incremental liberalization of interest
rates on loans has occurred since the late 1990s, and the upper
limit on lending rates was removed in 2013 (Tsai, 2017).
As players in internet finance are driven by business profits,
they seek risk-adjusted returns.
H2: There is a positive relationship between internet finance
development and private firm’s debt interest rate from internet
finance.
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We obtain data from a Chinese private enterprises survey
The survey applied multistage, stratified sampling to select a
sample that represented the firm populations of all the regions and
industries in China
The nationwide survey is done every two years We use data from
2013 (n=6144) and 2015
(n=8114)
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DV internet debt dummy internet debt interest rate IV internet
finance development index
published by Institute of Internet Finance, Peking University
starting from Jan 2014National index as well as index for each
province
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Debt amount from: commercial bank> small financial
institutions>private loans>internet finance
For debt from commercial bank and small financial institutions,
2015>2013
For private loans and internet debt, 2015
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region Fromcommercialbank
From smallfinancialinstitutions
From privateloans
From internetfinance
1.Beijing 1992.53 48.80 74.78 0.002.Tianjin 4410.01 1516.38 9.71
0.483. Hebei 2500.73 304.50 36.72 0.004. Shanxi 296.97 164.94 74.51
66.095. InnerMongolia
3812.25 663.53 213.61 0.00
6. Liaoning 821.64 114.58 9.53 0.587. Jilin 545.63 23.58 23.01
0.078. Heilongjiang 210.93 19.48 14.72 0.009. Shanghai 1515.72
66.03 9.62 4.4410. Jiangsu 1370.34 266.35 25.06 17.4911. Zhejiang
3303.53 573.38 41.32 0.2412. Anhui 1654.39 456.64 122.64 0.0013.
Fujian 6490.69 108.52 64.66 0.3314. Jiangxi 1603.59 261.85 15.22
0.0015. Shandong 6504.19 434.20 190.79 3.3516. Henan 47233.54
1062.33 107.82 0.0017. Hubei 2560.47 295.43 83.38 1.8918. Hunan
958.95 78.51 20.12 4.1119. Guangdong 881.39 180.93 51.84 5.6620.
Guangxi 2203.37 228.21 14.56 0.0021. Hainan 146.05 170.61 18.67
0.2422. Chongqing 1914.88 173.82 172.54 0.0023. Sichuan 1075.60
381.62 67.38 7.8124. Guizhou 1678.74 436.55 142.18 0.0025. Yunnan
694.65 415.78 87.98 0.0026. Xizang 210.37 107.86 10.00 0.0027.
Shaanxi 1298.44 355.02 50.00 0.0028. Gansu 3942.59 308.49 65.28
0.0029. Qinghai 1951.20 3415.00 116.00 0.0030. Ningxia 9103.66
127.25 53.93 0.0031. Xinjiang 9636.70 273.08 56.84 0.00Total
3598.67 334.16 67.78 4.44
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region Fromcommercialbank
From smallfinancialinstitutions
From privateloans
From internetfinance
1.Beijing 2436.59 80.73 86.13 0.022.Tianjin 3141.23 50.72 4.90
0.003. Hebei 1637.53 366.08 65.44 3.574. Shanxi 1573.21 39.47 58.45
0.005. Inner Mongolia 360.88 12.09 2.45 0.00
6. Liaoning 954.28 294.22 106.29 0.367. Jilin 248.11 19.54 68.24
0.058. Heilongjiang 100.15 17.88 13.52 0.189. Shanghai 1203.12
73.73 18.74 0.0010. Jiangsu 1551.81 213.31 30.15 0.4411. Zhejiang
3443.53 838.99 29.81 2.2512. Anhui 1276.40 86.55 47.63 0.6413.
Fujian 1779.88 94.54 30.49 0.5314. Jiangxi 518.97 2938.79 4.42
0.6615. Shandong 69856.08 3940.12 14.22 0.0016. Henan 1504.47 98.44
24.12 0.0017. Hubei 732.90 44.00 28.49 2.8318. Hunan 526.51 52.58
19.33 0.2819. Guangdong 1139.10 132.58 42.63 0.2420. Guangxi
2056.61 683.27 7.55 0.0021. Hainan 181.26 9.35 13.96 0.0822.
Chongqing 2388.57 991.56 17.75 0.0823. Sichuan 1262.55 46.93 113.46
1.1224. Guizhou 319.51 26.82 15.20 0.2825. Yunnan 4509.71 52.66
219.12 0.0126. Xizang 1686.96 210.50 55.00 0.0027. Shaanxi 2294.18
158.81 76.34 0.0928. Gansu 2832.31 41.03 29.21 0.0029. Qinghai
3542.88 94.76 57.14 0.0030. Ningxia 4380.62 9.75 0.09 0.0031.
Xinjiang 427.81 67.21 52.09 0.00Total 5005.97 456.97 45.66 0.64
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As to interest rate, internet finance>private loans>small
financial institutions>commercial banks
Interest rate in 2013>2015 Large variations among regions
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region Fromcommercialbank
From smallfinancialinstitutions
From privateloans
From internetfinance
1.Beijing 8.82 9.04 11.45 N.A.2.Tianjin 8.64 7.42 9.25 31.003.
Hebei 9.28 6.94 23.40 N.A.4. Shanxi 7.90 9.27 9.77 485.
InnerMongolia
6.13 5.43 6.05 N.A.
6. Liaoning 9.24 8.91 14.00 N.A.7. Jilin 10.97 15.26 13.32
20.008. Heilongjiang 10.42 9.85 13.50 N.A.9. Shanghai 7.12 7.85
8.43 19.0510. Jiangsu 7.42 9.63 13.19 24.7511. Zhejiang 7.70 7.07
10.04 24.0012. Anhui 11.17 11.95 12.71 N.A.13. Fujian 7.94 9.25
14.62 9.0014. Jiangxi 7.40 8.73 13.59 N.A15. Shandong 8.09 7.40
11.93 21.3616. Henan 7.01 7.21 12.11 N.A.17. Hubei 7.51 10.25 7.96
N.A.18. Hunan 6.88 7.26 11.59 N.A19. Guangdong 8.24 7.69 12.68
15.4520. Guangxi 8.35 9.46 17.44 N.A21. Hainan 8.96 12.95 22.50
13.0022. Chongqing 7.99 14.37 16.45 9.0023. Sichuan 10.78 9.79
10.46 15.0024. Guizhou 8.10 8.18 15.00 N.A25. Yunnan 8.05 8.42
16.45 N.A26. Xizang 4.67 3.26 12.00 N.A.27. Shaanxi 7.48 11.71 7.00
N.A28. Gansu 7.65 9.19 9.61 N.A.29. Qinghai 6.35 6.85 2.00 N.A30.
Ningxia 6.27 7.83 12.25 N.A31. Xinjiang 6.05 6.68 28.67 N.A.Total
8.02 8.87 12.88 20.80
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region From commercialbank
From smallfinancialinstitutions
From privateloans
From internetfinance
1.Beijing 7.55 13.57 9.14 16.52.Tianjin 6.74 8.88 12.5 N.A3.
Hebei 6.94 9.71 17.41 15.44. Shanxi 9.23 13.45 11.72 N.A5. Inner
Mongolia 6.05 7.52 8.49 N.A
6. Liaoning 7.44 13.12 12.82 N.A.7. Jilin 10.55 7.86 10.71 6.58.
Heilongjiang 7.38 3.77 10.29 N.A9. Shanghai 6.93 6.12 11.58 N.A10.
Jiangsu 6.46 7.53 8.51 1711. Zhejiang 6.49 7.57 9.59 12.3512. Anhui
6.77 10.22 12.45 10.5313. Fujian 7.22 11.89 13.93 7.514. Jiangxi
8.19 11.86 12.44 8.0015. Shandong 7.13 6.64 9.25 N.A16. Henan 7.35
9.44 10.01 N.A.17. Hubei 7.64 8.23 11.24 14.1718. Hunan 7.96 7.23
10.54 8.7719. Guangdong 5.82 6.18 13.61 10.520. Guangxi 7.09 6.65
10.98 N.A.21. Hainan 6.55 9.00 10.69 9.0022. Chongqing 7.62 6.28
10.5 20.0023. Sichuan 6.53 7.94 8.97 12.0024. Guizhou 6.42 7.37
13.11 18.5025. Yunnan 6.12 6.15 7.98 N.A.26. Xizang 3.41 5.17 12.00
N.A27. Shaanxi 7.83 8.39 10.46 6.628. Gansu 7.41 8.00 8.05 N.A.29.
Qinghai 6.89 9.45 15.00 N.A.30. Ningxia 5.45 5.96 N.A. N.A.31.
Xinjiang 7.27 11.56 14.78 N.A.Total 7.05 8.47 11.29 12.08
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1 2 3 4DV in the model Internet Debt
Dummy in 2013Internet Debt Dummy in 2015
Internet Debt Interest Rate in 2013
Internet Debt Interest Rate in 2015
IV: Internet finance development index
0.007*(0.004)
0.003*(0.002)
0.038(0.071)
0.067*(0.027)
Controls:Firm age -0.113**
(0.057)-0.030(0.039)
1.216(0.653)
0.252(0.340)
Firm size 0.128(0.195)
0.218(0.145)
-1.707(2.41)
-1.323(2.077)
Debt ratio 0.026***(0.009)
0.029***(0.008)
-0.079()0.153
0.091(0.153)
Debt from national banks
0.000(0.000)
0.000(0.000)
1.181(0.825)
0.211(0.730)
Debt from financial institutions
0.000(0.000)
0.000(0.000)
0.259(0.307)
0.865(0.505)
Private lending 0.000(0.001)
0.000(0.000)
-0.114(0.105)
0.009(0.524)
Model fit: R2 0.07 0.08 0.45 0.92Observations 3642 4747 41
45
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internet finance development index is significantly and
positively related to internet debt by private firms in 2013 and
2015
H1 is supported internet finance development index is
significantly and positively related to internet debt interest
rate by private firms in 2015, not in 2013
H2 is partly supported
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this study reveals the big picture of private firms’ financing
behavior in China
This study is the first to investigate the relationship between
private firms’ debt from internet finance and regional internet
finance development
this study will help to promote internet finance
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For further communications, please write to [email protected];
[email protected]
mailto:[email protected]:[email protected]
Private firm financing and shadow banking: the role of regional
internet finance developmentAgenda Background Slide Number 4Slide
Number 5Slide Number 6Why ChinaInternet finance development index
by city as of Dec 2015. Source: Institute of Internet Finance,
Peking University Literature and hypotheseSlide Number
10MethodSlide Number 12Descriptive results �Table 1 average debt
amount by region (Year 2013)Table 3 average debt amount by region
(Year 2015)�Slide Number 16Table 2 average debt interest by region
(Year 2013)Table 4 average debt interest by region (Year
2015)�Regression resultsSlide Number 20Discussion and conclusion
�Slide Number 22
