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20 01 16 6 A Af fr ri ic ca an n E Ec co on no om mi ic c C Co on nf fe er re en nc ce e 2 C R C C O A A N F F A P P R : M C T S D M Y : RE ED DI IT ON NS ST TR RA AI IN NT TS ND AR RM RO OD DU UC CT TI IV VI IT TY MI IC CR RO O- - E E V F F R S S M F F A I I N L E M R S N LE EV VE EL VI ID DE EN NC CE RO OM MA AL LL LH HO OL LD DE ER AR RM ME ER RS L E T E TH HI IO OP PI IA A Adamon N N. . Mukas asa, , Anthony M. Simpasa, and Adeleke O. Salami Development Research Department, African Development Bank, Abidjan, Cote d’Ivoire 5-7 December 2 2016, A Abuja, , Nigeria

Outline 1. 1. Introduction  Background  Motivation and objectives of the study 2. 2. Methodology  Model of farmers’ access to and demand for credit  Credit constraints and farm productivity  Productivity loss due to credit constraints 3. 3. Data an and d descriptive statistics 4. 4. Results 5. 5. Conclusio ion a and r recommendations

Introductio ion (Background)  Positive correlation between access to credit and targeted outcomes (Feder et al, 1990; Sial and Carter, 1996; Carter and Olinto, 2003; Foltz, 2004): o Acquisition on production inputs (short term) and realisation of profitable investments (long term) o Transition from subsistence farming to agri-business o Poverty reduction  Imperfe fections of credit markets are the norm (Stiglitz and Weiss, 1981; Carter, 1989; Feder et al, 1990): o Asymmetric information (adverse selection and moral hazard) in the credit markets o Misallocation of resources and a sub-optimal use of inputs o Lower income, volatile welfare and food insecurity (Jappelli, 1990; Petrick, 2004; Ali et al, 2014)

Introductio ion (Background) …  In Eth thio iopia, credit market imperfections are more acute in th the agric icult ltural l sector: o Small ll-scale le farmers (crop production is dominated by subsistence farm households and more than 90% 90% of the farms with at most 10 acres) o Relia iance on own resources for input and consumption purchases, labor hiring , investments,… o Vulnerabil ilit ity to vagarie ies of nature (droughts, floods,…) and to market t insta in tabil ilit itie ies (price volatility, high transaction costs,…)  Improvements ts in financial inclusion but still in insuffic icie ient: o Agriculture receives less than 10 percent of the banks’ lending o 22% 22% of adult Ethiopians hold an account at a financial institution in 2014 vs 29% 29% in SSA, 45% 45% in South Asia, 51% in Latin America, and 69% in East Asia o Only 3 bank branches per 100,000 inhabitants in 2014 vs 4 branches in SSA countries and 14 14 in the world.

Introductio ion (Motivation)  How limited access to credit (or lack thereof) affects farm productivity? o Are cr credit constrained and unconstrained farmers intrinsically different? o To what extent credit constraints affect farm p productivity in Ethiopia? o What is the potential productivity gain from removing credit constraints in Ethiopia?  Our contributions to the understanding of the potential linkages between credit constraints and farm productivity: o Analysis of the nature and det eterminants of credit constraints in Ethiopia’s agricultural sector (supply - and demand-side factors) o Use of econometric techniques to disentangle the differential e l effects o of f various t types of c credit c constraints on farm productivity o Evaluation of the potential productivity lo loss due to credit constraints (or potential gains from removing them)

Methodology  Access to and demand for credit o Simultaneous estimation (latent notional demand for credit) ( 0) ( observable demand for credit) (latent notional access to credit) ( 0) ( observable access to credit) o Estimation using bivariate probit model with partial observability: ( , ) ( , ) (1 ) ( , )

Methodology…  Credit constraints and farm productivity ty o Issu sues: unobserved heterogeneity and endogenous sample selection o Way out: endogenous regime switching regression model (Freeman et al, 1998; Lokshin and Sajaia, 2004; Ali and Deininger, 2012) using FIML method: 0 Selection equation 1 0 0 1 Productivity equations 0  Productiv ivity l loss due to credit constraints 1

Data and descriptive statistics  2011-2012 Ethiopia Rural Socioeconomic Survey (ERSS) and 2013- 2014 Ethiopia Socioeconomic Survey (ES ESS) as part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA)  Three r rounds p per s survey: o The first round in September and October (2011 for ERSS and 2013 for ESS) for information on households’ post -planting activities. o The second round in November-December (2011 for ERSS and 2013 for ESS) for livestock activities. o The last round in January-March 2012 for ERSS and in February- April 2014 for ESS with post-harvest information  Balanced sample of 2, 2,654 h households engaged in agricultural activities

Data and descriptive statistics…  Defi finition o of f credit c constraint s status: Direct e elicitation a approach - No need, have enough resources Unconstrained Interest rates too high Price constrained - Inadequate collateral - Absence of lender nearby - Transaction cost Do not know where to apply - constrained No bank account - Too much trouble - Do not like to be in debt - Risk constrained - Believed would be refused Why not? Fear not be able to pay - NON Applied for a loan in the past 12 months? - Loan rejected Quantity Partially approved - Received NON constrained YES total amount applied for? YES Unconstrained

D escriptive statistics… Pooled sample 2011-12 2013-14 Number Relative Number Relative Number Relative frequency frequency frequency Unconstrained 1,771 33.36 520 19.59 1,251 47.14 Constrained 3,537 66.64 2,134 80.41 1,403 52.86 Quantity- 264 7.46 145 6.79 119 8.48 constrained Price- 238 6.73 147 6.89 91 6.49 constrained Risk-constrained 2,546 71.98 1,555 72.8 .87 991 70.6 .63 Transaction 507 14.33 294 13.78 213 15.18 costs-constrained Observations 5,308 100 2,654 100 2,654 100

Descriptive statistics… Description All panel households Credit constrained No Yes Household characteristics Age of the head (in years) 45.66 (15.18) 45.22 (14.31) 45.88 (15.59) Education of the head (in years) 1.70 (3.04) 1.73 (2.97) 1.69 (3.07) Female-headed household (in %) 20.43 18.74 (39.03) 21.28(40.94) ** Household size 5.28(2.23) 5.40 (2.21) 5.22 (2.23) *** Monthly consumption ( ETB) 603.21 580.02 614.82 (1,808.46) (1,371.43) (1,991.66) Access to extension services (%) 15.79 (36.47) 12.76 (33.38) 17.30 (37.83) *** Farm characteristics Crop output (in ETB) 9,736.68 14,879.73 7,146.51 (81,854.51) (139,201.5) (18,343.46) *** Land size (in acres) 3.82 (17.38) 4.26 (13.25) 3.60 (19.11) Land productivity (ETB/acre) 6,783.94 10,906.07 4,719.95 (63,496.29) (106,647.5) (18,575.11) ** Family labor (in hours) 1,089.86 1,147.31 1,061.09 (1,976.07) (1,442.52) (2,194.65) *

Descriptive statistics… All ll p panel h household lds Credit c constrained No Yes Hired labor ( person-days) 56.67 (390.57) 82.38 (614.04) 43.80 (199.28) *** Chemical fertilizer use ( kg/acre) 8.97 (23.65) 10.17 (21.72) 8.37 (24.53) ** % of plots with certificate 36.20 (43.58) 39.06 (43.38) 34.77 (43.62) *** Land slope (% of flatted plots) 54.95 (36.67) 58.27 (35.66) 53.29 (37.06) *** Distance to nearest main road (km) 16.70 (19.81) 16.18 (17.93) 16.96 (20.68) Distance to main market (km) 67.27 (48.97) 65.03 (46.53) 68.39 (50.12) ** Distance to main population center (km) 37.57 (26.52) 37.53 (26.34) 37.60 (26.62) Distance to nearest commercial bank 23.81 (26.45) 22.50 (27.23) 24.46 (26.03) ** (km) Distance to nearest microfinance 13.22 (19.01) 14.00 (18.77) 12.83 (19.12) ** institution (km) Tropical Livestock Units 8.74 (10.83) 8.83 (10.68) 8.70 (10.91) Asset index 0.17 (3.61) 0.06 (2.05) 0.23 (4.18) * Observations 5,308 1,771 3,537

Results (1)  Determinants o of f access t to a and d demand fo for credit i in Ethiopia Bivariate probit with partial observability Access Demand Farm size (acre) 0.025 (0.014) ** 0.035 (0.016) ** Household size (number) 0.07 (0.019) *** 0.026 (0.006) *** Adult rate (%) 0.458 (0.133) *** -0.157 (0.168) Female (female=1) -0.089 (0.090) 0.113 (0.112) Age (years) 0.000 (0.003) -0.017 (0.003) Age squared 0.001 (0.000) 0.002 (0.002) Years of schooling 0.006 (0.010) -0.016 (0.013) Share of titled lands (%) 0.131 (0.076) * 0.005 (0.102) Objective of credit 2.497 (0.144) *** 2.203 (0.141) *** (Input purchases=1) Tropical Livestock Units 0.010 (0.005) *** -0.003 (0.007) (number) Asset index 0.042 (0.053) -0.007(0.025) Rural (Rural=1) 0.063 (0.163) -0.330 (0.245) Commercial bank 0.117 (0.278) in the village (Yes=1) Distance to commercial 0.002 (0.005) bank (km) Microfinance institution in the village 0.464 (0.163) *** (Yes=1) Distance to microfinance institution (km) 0.008 (0.006) Distance road (km) -0.007 (0.007) Distance market (km) 0.002 (0.001) Distance population center (km) -0.00 (0.004) ** Survey wave 2 (Panel 2=1) 0.024 0.016 (0.009) * (0.015) Constant -1.38 (0.238) *** 2.932 (2.617)