Assignment Overview You will be ran domly matched into groups of 5 to complete a group research assignment. The objective is to provide a proposal for a policy – relevant research project. Think of yourselves as a research team working on behalf of an int

Assignment Requirements

 

I am charge on section3
Which is section3” Economic model: set up and solution”
Sections
Date/title/abstract (joint)
1. Introduction alice
v Motivate and present key policy issues
v Backup claims with basic evidence
v Briefly paper why your approach is new and better
2. Related Literature
3. Economic Model: Setup and Solution Jin
4. Economic Model: Derivation and Theoretical Predictions
5. Empirical Approach james (?)

References (joint)

1. Introduction alice
The agricultural sector in sub-Saharan Africa (SSA) is a key policy agenda on a number of levels: environmental, social and economic. Environmentally, agriculture is a key area of concern in water-shortage projections. UN estimates place 1.8 billion people living in regions of absolute water scarcity by 2025, as climate change projections coincide disastrously with population growth. Agriculture is by far the most significant human factor in water usage, accounting for 95% of the blue-water (or surface water) footprint in SSA. The pollutant released in the farming of grains is also a key contributor to the grey water footprint in SSA, seriously impacting on drinking water reserves in the region.
Socially, food instability has long been key policy issue in the region; due to the inefficiency of importing food from more abundant global regions, this crisis must be addressed via the local agricultural sector. WorldVision reports that in 2013, 19 million people in West Africa experienced food scarcity. Crop yields in SSA are extremely low compared to the rest of the world, and rapid population growth in the region is reducing per-capita farmed land, further straining food availability. Seasonal fluctuations in output coupled with inelastic staples markets and ineffective market access cause severe price swings throughout the year, and chronic food scarcity. Furthermore, malnutrition has serious long-term implications for a community. Children who experience chronic malnourishment are likely to suffer both physical and cerebral development problems, leading to long-term trans-generational negative impacts on the region. Additionally, as nutritional ‘poverty traps’ deepen, those most in need of income become too undernourished to work effectively, and can’t afford access to the food needed to increase their energy and thus earn more. Food insecurity is therefore a debilitating social concern, which can cripple the long-term development of a region.
Economically, agricultural income levels are extremely low; approximately “70% of Africa’s extremely poor populations depend primarily on agricultural production for their livelihoods”. Most farmers only earn subsistence yields from their plots, prohibiting them from investing in the capital needed to improve output.
Both food instability and small-holder poverty could be alleviated greatly by increased farmer productivity. The old economic adage that the best way to increase productivity is with technological innovation has been proven over and over in the agricultural industry. The ‘green revolution’ of the mid-twentieth century catapulted output levels in agriculture through a series of innovations in agricultural practice. More topically, the Farmer Managed Natural Regeneration (FMNR) movement in Niger demonstrates that low-cost practical improvements in agricultural practice can greatly benefit the productivity of small-holders, their income and economic wellbeing, and the food supply of the surrounding region. Paul Polak of International Development Engineering (IDE) reports similarly that since 1985, each dollar invested in low-cost agricultural innovations for small-hold farmers has returned a $12 increase in yield value.
Any policy initiative aiming to address the agricultural sector weaknesses must focus primarily on small-holders, who account for more than 90% of the agricultural industry in SSA and generate around 40% of the region’s GDP.
Simple drip irrigation (SDI) is a low-cost agricultural technology which greatly improves agricultural productivity, can be employed on very small plots of land, and reduces water usage by up to 80%, thus addressing the environmental, social and economic issues facing the agricultural sector in sub-Saharan Africa. SDI consists of very low-cost tubing which distributes tiny trickles of water to the root of crop plants, and is often coupled with rudimentary water-storage devices. The viability of distributed, small-scale irrigation systems as a means to dramatically improve small-holder output has been demonstrated in Burney et. al’s recent paper, The case for distributed irrigation as a development priority in sub-Saharan Africa. Consequently, IDE is planning a roll-out of drip technology to 100,000 (?) small-holders in the region, as a treatment policy to boost agricultural productivity, small-holder income and regional food stability. Group 6 has been asked to conduct an empirical investigation in anticipation of this roll-out, in order to advise on key aspects of the policy proposal.
Our approach is new and better because we recognise that the availability and proven value of technological innovation (or, indeed, any policy initiative) is not sufficient to ensure wide-spread adoption among those who would benefit most. While Barney et al have demonstrated successfully that micro-irrigation technology is a ‘policy priority’, there has not yet been any rigorous test of demand or likely adoption rates of SDI. Testing the demand for a treatment is crucial before implementing any policy as it could have significant implications for pricing structures, suitable roll-out procedures, long-term viability and local market autonomy.
Therefore, we are investigating a key factor that may constrain demand for SDI among small-holders: risk. Agriculture is a particularly risky investment, due to the dependence on climate for output, the volatility of food prices, and the other factors which can seriously constrain output value. We will also determine demand externalities of the roll-out, by geographically mapping take-up patterns over time.

Method
Institution:
Partnership of: IDE (for supply and education/installment)+ an NGO (for risk component/buying of yields)
Demand Shock
• Educate and promise supply/installation
• Effective marketing (enlist locals to preach benefits of increase yields etc.)to farmer to ensure that are receptive to the technology
Pricing
• Offer the technology at different price levels ($200 per acre, $150 p/a, $100, p/a, $50 p/a) (with almost no risk [farmers sell all produce to NGO]) This is randomized?
o Create demand curve and observe sensitivity (Y=a+B2.(1/X)+e]
o Observe an optimum price or maximum willingness to pay, seeing as we don’t bring the supply-side optimum price into it?
§ one that includes almost all the demand curve (so that enough people adopt, but not so much as to make the industry ineffective)
§ low enough so that demand is strong over all three irrigation offerings (i.e. if one farmer buys the tech at all three stages their farm still has some land not irrigated)
Risk Testing:
First Round
• Offer a set acreages worth of irrigation (e.g. 2 acres worth of IDE @non-prohibitive price level). Maybe make this 1 acre – smaller units à lower price?
o at minimal risk (offer to buy at market price all of the farmers yield)
o Disentangle price (now price is fixed) effects from 0 risk effects (necessary because of initial price testing)
o observe take-up rates compared to total IDE aware farmers (e.g. 40%)
Second Round
Offer same acreage same price
• for increasing irrigation for existing IDE-using farmers
o Randomize the levels of moderate risk (offer to buy 50%,40%,30% of yields)
o Observe difference in demand on pre-existing IDE farmers based on risk change
• for new adopters of IDE
o at second round risk levels (offer to buy @50%,@40%,@30%)
o this figure represents the positive externality of other farmers using irrigation
§ And gives impression of how a less-incentivized market new market would behave
Maybe include in here some data collection for geographic proximity to existing customers? Just to get a better idea of how externalities behave
• Observe at different risk levels the take up of the technology (one graph existing irrigators, other graph new adopting irrigators)
o Infer how risk sensitive both types of consumer are

Final Round
Offer the technology at with no assurance of yield purchase
• Observe the pre-existing irrigators demand
• Observe new adoption Demand
o This will give us information about the extreme end of our risk-payoff curve

Conclusions
• Now have a risk-investment relationship
o Useful information for how an industry should be structured (in terms of risk exposure) in the future to ensure maximum uptake of technology
o Relationship is not obscured by price effects because of pricing tests at the beginning
• Have data on the external benefits of early adopters (spill-over effects measured). As above, maybe include some geographic data collection in the method – then we could map the spill-over effect
• Have market information of the price sensitivity for this technology
o Future industry now can optimize supply given a risk-price trade-off (that they now have information about) (however optimal pricing takes into account the consumer only, not supplier) Maybe we could adjust wording to ‘maximum willingness to pay’ for consumers? – that separates our result from a supply/demand model, which we can’t really test for in this RCT, but still has useful implications for suppliers and policy-makers
• Selection effects measured between pricing experiment and risk experiment
Shortcomings/Problems
• No relationship between flexible prices and flexible risk levels
o Will a higher market price of irrigation affect the risk aversion of farmers? If we find an ‘optimum’ price in the first stage, then perhaps higher market prices are irrelevant?
• Ethical considerations for suppliers
o If maximum adoption of this technology is well below market price (or there is too much risk being absorbed by the supplier)then the suppliers will not be able to operate in the long-run
§ Or the price/risk levels will rise and the poorest farmers will be excluded (potential poverty trap). I don’t think this is a shortcoming, because if the RCT brings in this result then that is our policy recommendation: don’t go ahead, or rather be prepared to rely on donor support to prop up the supply side.
o Limiting the take-up (each round farmers can only receive 2 acres of irrigation) decreases farmers earning potential and well-being. Why limit this? If we measure the number of units sold at each round as the indicator of take-up, then it’s not a problem if farmers buy more than one unit each – it’s still the level of demand. In fact, maybe limiting this would obscure the real demand at each level? Unless you’re worried that farmers will run out of irrigate-able land before stage 3…I suppose you could remove farmers who are ‘at capacity’ from the market/total ‘n’, then use proportions on the remaining market to analyse take-up at each level?
§ Long run however these restraints will not be placed on consumer so this is not a major problem

Sections
Date/title/abstract (joint)
1. Introduction alice
v Motivate and present key policy issues
v Backup claims with basic evidence
v Briefly paper why your approach is new and better
2. Related Literature
3. Economic Model: Setup and Solution
4. Economic Model: Derivation and Theoretical Predictions
5. Empirical Approach james (?)

References (joint)

Jin, Nick and Zhuo: can you each take one section? Whoever does sections 3 and 4 will probably have to work together quite a bit.

Whoever does the related literature section, here are some articles you could look at:

The Paul Polak article that James found: http://www.paulpolak.com/media/OpeningAccesstoAffordableMicro-PlotIrrigationforSmallFarmers-SamplePolakNanesIDEOrlando.pdf

Also, his book ‘Out of Poverty’, part of which is on google books: http://books.google.com.au/books?id=Hd0TYcBRPkgC&printsec=frontcover&dq=paul+polak&hl=en&sa=X&ei=Di17U8bYKIinkwWipIGIAw&ved=0CC0Q6AEwAA#v=onepage&q=paul%20polak&f=false. You would maybe only need to look at Chapter 6.

There’s also Banerjee and Duflo, Duflo and Pascal’s stuff on uptake problems on policy treatments in developing regions, Easterly’s stuff on efficient markets and whatever other relevant scholarship you can find.

Also, I thought some more about what Russell said in the meeting, and I thought we could adjust our method to focus more on risk, as he suggested. James, I know this is a little different to what we talked about this morning – if you think it’s too much bother to change our idea like this that’s fine.

•        An RCT to determine the rate of uptake of drip irrigation technology as a function of risk.
•        We will do this in 3 stages (maybe??) – 1st, with full insurance packaged with the roll-out (ie. the maybe the company that does the roll-out will only offer to buy the farmer’s yield, therefore, if there’s no yield the farmer doesn’t lose out)
•        Then, we will offer the technology again the next year with less insurance against risk – maybe we will offer to buy half the farmer’s output, the farmer repays half the cost of the irrigation technology, and payments start after 6 months, with high flexibility for seasonal problems (ie. farmers get an extension on the loan if the crops fail)
•        Then, a third offer the following year with even less insurance against risk – the farmer pays back the full cost of the irrigation technology with fairly standard market loan terms
•        Given that this technology is modular, each year/stage the farmers who have existing irrigation could extend the acreage of their irrigation system, and we would also have new buyers as the technology’s ‘reputation’ increases.

That way, we’d be gradually approaching market conditions, while looking at the different rates of uptake at each stage. Ideally, we could show that subsidisation/donor support is not necessary in the long term, because the demand for the technology grows with its reputation, and eventually farmers in the area would be willing to take up the technology without unrealistic/inefficient insurance packages. That would pave the way for a local private supply market to develop, which is better than an international NGO sticking around long-term. The support for this idea would be the bed-nets experiment, in which demand for the nets increased in the communities where the initial roll-out had taken place.

Anyway, let me know what you think. I’m happy to stick to our original idea as well.

Cheers,

 

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