1. 15 July 2013
Slide 0 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Farm- and Market-based Methods
Evaluating the Effect of Rural Finance on African Economies
Dr. Christian H. Kuhlgatz
Thünen Institute of Market Analysis
Accra, Ghana
15. July 2013

2. 15 July 2013
Slide 1 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Access to finance for enhanced agric. productivity
• Agricultural supply: variable, affected by climate change
• Price volatility on world markets
• Incomplete financial markets impede
consumption smoothing ability of households
• Precautionary savings to prevent food insecurity
• Focus on short-term income generation, lower expected return
 Reduced human capital accumulation
 Adoption of new technologies hindered
 Which tools of TI could be useful in the African context?

3. 15 July 2013
Slide 2 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Outline
- Investigate African markets with simulation models
- Impact assessment methods to measure the causal
effect of rural finance
- Inter-regional comparisons of farms with the agri
benchmark network
- Conclusions

4. 15 July 2013
Slide 3 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Price development: Staple food (wheat)
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Wheat, US, n° 2 Hard Red Winter (ordinary), FOB Gulf hist. Vola width = 12)
hist. Vola in %Nominal Price US$
1970s food crisis Food price crisis

5. 15 July 2013
Slide 4 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Price development: Export markets (cocoa)
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Cocoa beans, avg daily prices New York/London (¢/lb.) hist. Vola (width = 12)
Nominal Price ¢/lb. hist. Vola in %

6. 15 July 2013
Slide 5 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
AGMEMOD: Using partial equilibrium models for
policy consultancy in Africa
• At TI: AGMEMOD model used for simulating
the effects of EU agricultural policies
• Extending AGMEMOD to Africa
• June 2013: Visit of researchers from Kenya and
Ethiopia at TI
• In the current process, country models for
Ethiopia, Kenya, and Uganda with intended extensions to
other African countries
• Reduced set of 5 markets for the start
• Ethiopia with wheat, corn, sorghum, teff, and haricot beans
• Kenya with wheat, corn, sorghum, haricot beans, sweet potatoes or milk
• Uganda with corn, sorghum, cassava, haricot beans, and sweet potatoes

7. 15 July 2013
Slide 6 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
AGMEMOD goes Africa
Markets represented by area, yields, productions, trade, different
demand and prices
Drivers (exogenous variables)
• Policies – trade measures, board prices, investment support, input support
• Macro economic variables – GDP, inflation, exchange rates, population
• Others – rainfall, oil price, fertilizer price
Build a solid base for policy consultancy in African
countries
 so that African economies and farmers can respond adequately
on external shocks and build a resilient, productive agriculture
 Capture regional interactions and investigate multiplier effects

8. 15 July 2013
Slide 7 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Identifying the causal effect of finance on
agricultural productivity
- Ex-post analysis: What would have happened if the
household had no access to finance?
- Measurement problems: selection bias, spill-over effects
- Experiments (RCTs) or quasi-experimental approaches
- Typical impact assessment tools
- Propensity score matching, Regression
Discontinuity, DiD, Instrumental Variables, Heckman
selection model…
- Pitt & Khandker vs. Roodman & Morduch debate:
- Still no consensus on the impact of microfinance reached

9. 15 July 2013
Slide 8 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Sources of selection bias in capital markets
(examples)
- Monitoring costs
- Areas with high population density are preferred
- Adverse selection
- Higher interest rates attracts riskier borrowers
- Higher collateral requirements attracts riskier borrowers
- Moral hazard
- Insurances encourage farmers to behave riskier

10. 15 July 2013
Slide 9 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Example of an impact assessment: Ghana
• Causal effect of export crop cultivation on hh-income
• Self selection problem. E.g.: some farms cannot afford
participation in profitable but volatile export markets
• 1st part:
Identification of the determinants of export cropping
• Heckman selection model
• 2nd part: Impact assessment
• Propensity score matching
• GLSS 5 data of farm households, 2005-6

11. 15 July 2013
Slide 10 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Determinants of export crop cultivation in Ghana
(excerpt)
Participation in
export cropping
Intensity of
export cropping
coefficient (t-value) coefficient (t-value)
Female hh-head -0.139 (-1.43) -4.585* (-1.82)
Age of hh-head 0.013*** (5.25) 0.197*** (2.8)
Number of children -0.0007 (-0.04) -2.12*** (-4.63)
Institutional loans 0.0001 (1.04) 0.0011 (0.5)
Private loans 0.0001 (1.35) 0.0022** (2.46)
Savings -0.000001 (-0.05) 0.0011** (2.05)
Land with deed (%) 0.0021* (1.81) -0.029 (-0.99)
Owned land 0.00006*** (4.63) 0.0002*** (2.88)
Motor vehicle 0.221 (1.48) 7.673* (1.94)
Eco-zone: forest 0.228 (1.1) 13.41*** (3.37)
…
λ (Inverse Mills ratio) -9.673*** (-3.12)
F-test [p-value] 11.10 [0.00]
*, ** and *** indicate significance at 10%, 5% and 1% levels, respectively.

12. 15 July 2013
Slide 11 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Impact of export crop cultivation
• Results of propensity score matching
• Compares income and poverty of households that are
similar in their observable characteristics
Outcome
ATT
Critical level of
hidden bias (Γ)
No. of
treated
No. of
controls
Income/capita 97.58 ( 2.20)** 1.15-1.20 438 2,351
Poverty status -0.053 (-2.18)** 1.25-1.30 435 2,351
Poverty gap -6.16 (-2.67)** 1.15-1.20 438 2,351
Monetary values are reported in 10,000 cedi. Numbers in parentheses are t-values. ** indicate 5%
significance levels.

13. 15 July 2013
Slide 12 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Identifying the reasons of a causal relation
- Impact assessments can quantify the causal effect, BUT:
- “Impact” is most often context specific and changes over time
- Even if impact is identified without bias: can it be repeated in
other places or circumstances?
- For a better understanding of what mechanisms are at
work, there is need for in-depth analyses of farms
- Aim: identify impact pathways that explain the effect of access to
finance
- TI farm economics: agri benchmark network has the
ability to perform rigorous investigations by comparing
results of typical farms from different regions

14. 15 July 2013
Slide 13 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Unique features of agri benchmark
• Production systems approach
>>> more than financial data and reasons behind differences
• Cooperation with producers and advisors
>>> get the story behind the data
• Global coverage
>>> big players and emerging economies
• Using standardised methods world-wide
>>> global comparability
• Works in countries without / with limited statistics and accounting
>>> global comparability
• Expert knowledge
>>> access local expertise and overcome language issues
Main supporting partner

15. 15 July 2013
Slide 14 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Countries in the agri benchmark Network
Participating countries 2013
Contacts for further growth
New countries 2013
Ireland (beef/sheep)
Uruguay (beef/sheep)
China (sheep)
Myanmar, Laos, Zambia,
Mozambique (cash crop)
2013 Countries Farms
Cash crop 27 75
Cow-calf 23 55
Beef finishing 29 70
Sheep 14 25

16. 15 July 2013
Slide 15 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Financial market analysis in Africa
- TI can assist African research on capital markets with our
policy analysis toolkit
- Knowledge transfer in trade analysis methods & impact assessments
- Providing access to the agri benchmark network
- Ex-post analyses within single countries
- Evaluating the impact of improved financial access on productivity
- Model-based simulations
- Identify probable multiplier effects on other regions
- Analyze the effect of external shocks on whole economies

17. 15 July 2013
Slide 16 Christian Kuhlgatz
Evaluating the Effect of Rural Finance on African Economies
Thank you for your interest
christian.kuhlgatz@ti.bund.de
Thünen Institute of Market Analysis
www.ti.bund.de