Does Weather Risk Explain Low Uptake of Agricultural Credit? Evidence from Ethiopia

1. Does Weather Risk Explain Low Uptake of Agricultural Credit?
Evidence from Ethiopia
By: Bethelhem Koru
(Guush Berhane, Kibrom Abay and Jordan Chamberlin)
International Food Policy Research Institute
July 19, 2019
Addis Ababa

2. 2
Introduction
 Access to credit is widely acknowledged as a key means of transforming the livelihoods
of poor rural households in developing countries
 Enhancing access to appropriate credit service on timely basis plays a crucial role in
catalyzing the development of the agricultural sector
 Empirical studies have shown that microcredit can stimulate agricultural investments,
including use of modern agricultural inputs (Giné and Yang, 2009; Zerfu and Larson,
2010; Abate et al., 2016)
 Despite the improved coverage of MFIs and financial cooperatives in recent years ,
rural financial markets in Ethiopia are mostly dominated by informal financial
schemes. (CSA: only about 10 percent of smallholders in Ethiopia have access to formal
credit)
 In this paper we investigate the impact of rainfall uncertainty on the expressed
demand for credit among rural households in Ethiopia and its implication on
agricultural investment

3. 3
Data
 The primary source of data for this study is Ethiopian socio-economic survey (ESS)
2011/12, 2013/14 2015/16, a collaborative project between the Central Statistics
Agency of Ethiopia (CSA) and the World Bank. (Other data source-PSNP AGP FtF)
 It is nationally representative dataset covering a large sample of rural and urban
households throughout the country.
2011→ 3776 HH (Only rural and small towns)
2013/14 and 2015/16 → 5262 (rural and urban HH)
 We use spatial time-series rainfall data from the National Aeronautics and Space
Administration (NASA)
 The ESS data provides GPS coordinates of households’ residences, enabling us to
construct enumeration area level daily rainfall data for the last 29 years, from
which we construct measures of weather risk

4. 4
Estimation and Identification Strategy
 we estimate the following credit demand equation
 Where
𝐶ℎ𝑡 is households’ uptake of credit from formal sources
𝛽1 quantifies the impact of rainfall variability (CV or std of rainfall)
𝛽2 captures the impact of the most recent season’s rainfall
𝛽3 captures the effect of additional household characteristics

5. 5
Descriptive Statistics
Table 1: Households’ uptake of formal credit(ESS data)
 Rural credit participation is very low, with less than 10 percent rural households
taking credit
 Consistent result from other data
 AGP-High Agriculture Potential areas (10%)
 PSNP- Food insecure part of Ethiopia(6%)
Survey year (round) 2011/12 2013/14 2015/16 All
Households who took credit (%) 7.8 9.5 7.0 8.1
Number of obs. 3589 3503 3454 10647

6. 6
Credit..(Gender)
0
2
4
6
8
10
12
All Male Female
HHwhotookcredit(%)
AGP
0
1
2
3
4
5
6
7
All Male Female
HHwhotookcredit(%)
PSNP
 Substantial gender differences in households’ access to financial services
 Importantly, female headed households have lesser access to formal credit

7. 7
Supply side.…(Credit)
Table 2: Availability of Credit and Saving Association in the Community
 In line with the government effort, the result show that many rural villages have at
least one microfinance or credit and saving association
 On average half of the community confirmed the availability of financial institution in
their kebele.
 Despite the need for further progress, several microfinance institutions and cooperatives
have been established to resolve households’ access to financial services
PSNP AGP FtF
Is there rural saving and credit cooperatives in this
Keble ( % )
52 40 38
How many RUSACCOs operate in this Kebele?
(average)
1 2 3
How many microfinance institutions operate in this
Kebele? (average)
- 1 1
Number of observation/woredas … 252 282 252

8. 8
Descriptive Statistics
Table 3: Purpose of credit from financial institution
 Consistent with the Ethiopian government’s agenda of expanding access to credit for
agricultural investment,
 More than half of the credit taken from the formal sources is used for purchase
of agricultural inputs
 The next important reason appears to be starting up or expanding businesses.
 The purposes for which credit is used remains comparable across years
Survey Year 2011/12 2013/14 2015/16 All
Purchase agricultural inputs 59% 56% 53% 56%
Business startup/expanding
business
19% 15% 20% 17%
Purchase house/lease land 2% 2% 3% 2%
Purchase nonfarm inputs 1% 3% 4% 3%
Other purposes 18% 23% 19% 21%
Number of obs. 284 328 242 854

9. 9
Descriptive Statistics
Table 4: Reasons for not taking credit from financial institution
 Households not participating in credit market face one or more credit rationing(risk
rationed, transaction rationed and price rationed)
 The most important constraint limiting rural households’ credit uptake is risk
rationing. (fear of loss of assets or additional risk of having to bail out fellow group
members in the case of group lending)
Survey year (round) 2011/12 2013/14 2015/16 All
Unconstrained 6% 12% 13% 10%
Fear of being in debt 52% 44% 50% 49%
Interest rate and processing cost 20% 14% 14% 16%
Other reasons(personal/religion) 22% 29% 23% 25%
Number of obs. 3389 3181 3211 9781

10. 10
Econometric Estimation Results
Table 5: Rainfall variability (measured by coefficient of variation) on Credit uptake
Table 6: Rainfall uncertainty (measured by standard deviation) on Credit uptake
Explanatory variables 1 2 3 4
Coefficient of variation for the last 10 years -0.551***
-0.694***
-0.722***
-0.395**
Log (last year rainfall in mm) -0.044**
-0.048**
-0.018
HH and community variables controlled NO NO YES YES
Household fixed effects NO NO NO YES
No. observations 10623 10623 10519 10408
Log (standard deviation of rainfall) -0.089***
-0.097***
-0.103***
-0.054**
Log (last year rainfall in mm) 0.026 0.027 -0.016
HH and community variables controlled NO NO YES YES
Household fixed effects NO NO NO YES
No. observations 10623 10623 10519 10408
 1% increase in variability of rainfall decrease uptake of credit by about 5-10 percentage point

11. 11
Cont..
Table 7:Multinomial logit estimates (base outcome is unconstrained)
 Those households exposed to substantial rainfall variability are more likely to be risk-
rationed in their quest for credit market participation.
 Implication
-Discourages demand for agricultural credit
-Forced HH to engage in low risk and low return agricultural investment
Risk
rationed
Transaction
cost
Price
rationed
Personal
issue
Coefficient of variation for the last 10
years
2.267**
6.815 -2.992 0.818
HH and community variables
controlled
YES YES YES YES
No. observations 9658 9658 9658 9658

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Rainfall Risk and Agricultural Investments
Table 8:Impact of rainfall uncertainty on agricultural investment
 Rainfall uncertainty negatively affects the propensity to adopt chemical fertilizers
 Part of lower fertilizer adoption comes through lower demand for agricultural credit
 Those households exposed to more variable rainfall are more likely to invest in
defensive agricultural inputs, including herbicides, fungicides and pesticides
 Rainfall uncertainty is driving the allocation of investment resources from productive-
enhancing agricultural investments to defensive agricultural investments
Explanatory variables Fertilizer use Fertilizer use
Agro-chemical
use
Coefficient of variation for the last 10
years
-1.774***
-1.658***
0.313***
Access to formal credit(1=yes) 0.208***
0.149***
R-squared 0.016 0.029 0.011
No. observations 10620 10620 10623

13. 13
Conclusion
 We find evidence of lower participation of credit in rural part of Ethiopia primarily
due to risk of default (i.e fear of being in debt or distress of losing assets in case of
default)
 we showed that rainfall variability is negatively associated with formal credit
participation
 Rainfall uncertainty is driving the allocation of investment resource from productive
enhancing agricultural investment to defensive agricultural investment
 It contributes to the evolving evidence on how rural farmers adapt and cope with the
consequences of climate change

14. 14
Thank You