Warehouse Finance Model and Its Impact on Farmers

This blog presents a response we shared with one of our funding partners during a due diligence process. They posed two important questions:

1. What is the minimum guaranteed impact embedded in the Gramhal model? What happens to that impact if the model is implemented by a profit-maximizing entrepreneur? How much can such an entrepreneur potentially extract in profits from farmers?

2. What will happen to market-level prices if a majority of farmers begin using the Gramhal model to benefit from seasonal price increases?

Before diving into our responses, let’s first understand the broader context and the solution Gramhal implemented.

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Context

Across developing world, farmers face large and regular seasonal fluctuations in grain prices. The price difference can be anywhere between 20% to 100% between post-harvest lows and pre-harvest peaks. However, farmers, especially smallholders, face difficulty in storing their grain to benefit from high prices. This is mostly due to lack of access to credit and storage facility. Hence, farmers sell their produce immediately to meet urgent cash needs.

Gramhal model

A farmer can store her produce at a warehouse. She can request for a credit up to 60% of the produce value. The credit smoothens her cash flow and provides her the agency to hold the harvest. The farmer receives prices on her phone every day. Whenever the prices become favorable to her, she can sell the produce through a click on her phone. These bundled services of storage, credit, and market linkage build the farmer’s agency to access better price.

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Question - 1: What is the minimum baked-in-impact in Gramhal model? What will happen to the impact if the model is implemented by a greedy entrepreneur? How much the greedy entrepreneur can squeeze profit out of farmers?

Gramhal model increases farmers’ income through two pathways – 25% of it is through bringing efficiency in the supply chain and shifting profits from intermediaries to farmers. While the rest 75% is by providing farmers the agency to access seasonal price gains. A greedy entrepreneur can keep the value created by bringing the efficiency in the supply chain to himself. It will be quite difficult for him to take away the gains of seasonal price increase from the farmers.

Gramhal brings efficiency in the agri-supply chain by connecting smallholder farmers directly with the end buyers and by-passing a long chain of intermediaries. When a farmer sells through village aggregator or commission agent, she incur 3-4% of value of produce as post-harvest expenditure for transport, labor, weighing, commission fee, and cash discount. In comparison, when a farmer sells through Gramhal, she incur almost negligible post-harvest expenditure. Further, Gramhal brings efficiency in the market by eliminating multiple handling of grains and reducing unnecessary transports. This helps in shifting the profits from intermediaries to farmers. A farmer gains around 5-10% higher price from Gramhal in comparison to any other option available in the market on any given day.

A farmer will use Gramhal services only when the price offered by Gramhal on any given day is greater than or equal to any other option available to the farmer to sell her crop. The most a greedy entrepreneur can do is offer the same price as the local trader is offering on that day. He cannot go below that. Otherwise, the farmer will shift to the local trader. A greedy entrepreneur can keep all the 5-10% price gains from supply chain to himself and yet farmers will use his services. Because Gramhal model’s bundled services of storage, credit, and market linkage builds farmer’s agency to shift her grain from time T1 to time T2. In absence of Gramhal she is forced to sell the crop at time T1 itself.

To shift the grains from time T1 to T2, the farmer has to pay rent on warehouse and interest on credit.

Time	Local Trader’s price	Greedy Entrepreneur’s price (assumption – keeps all the supply chain price gains to himself)	Expenditure	Net price realization by farmers
T1	P1	P1	-	P1
T2	P2	P2	Rent + Interest	P2- Rent - Interest

Using Gramhal services, the farmer gains an additional income of Increase in income = (Price 2 – Price 1) – (Rent + Interest) A greedy entrepreneur can’t change Prices P1 and P2, as these are decided by the market. He can only increase rent and interest to increase his profits. However, both rent of warehouse and interest on credit in Gramhal model are standardized, and driven by market. Thus, a greedy entrepreneur cannot squeeze farmer’s seasonal price gains.

In some cases, a third type of price gain will happen to farmers, who are not users of Gramhal model. This is an unique case that happens in contexts, where Gramhal model influences market-level prices in positive way. In this case, even farmers who are not using Gramhal services receives a higher price, without changing their selling timing. These positive spillover increase income of the whole community. A greedy entrepreneur cannot take any fee from non-users farmers, who have received spillover effects from his work.

We can say that the seasonal price increase and positive spillover price effects on the non-user farmers are the minimum baked-in-impact in the Gramhal model that even a greedy entrepreneur cannot take away from the farmers.

Question 2

What will happen to market-level prices if majority of farmers adopt Gramhal model to gain benefit from seasonal price increase?

The effects of large-scale adoption of Gramhal model on market-level price will be visible if Gramhal model shifts a sufficiently large portion of the available grain supply in the market. This can happen when (i) the market is isolated, such that local prices are at least partially determined by local supply, (ii) substantial percentage of local farmers store their produce, such that local food grain supply faces a sizable shock. Hence, the changes in market-level prices will depend on (i) inter-spatial price difference, (ii) the variance of seasonal price difference, (iii) the size of the market, and (iv) the proportion of the farming population storing the grains. Let’s understand each of these conditions in detail for a better clarity on their role in the impact on market-level prices.

• The inter-spatial price difference: It is the difference in prices between two regions at any given point in time.

High inter-spatial price difference

Low inter-spatial price difference

Generally, this condition exists in the low-income countries. The reasons can be: absence of infrastructure (like roads, vehicles, warehouses, cold storage, and electricity) that increases the overall logistics cost; legal restriction on inter-regional sales, dietary preferences. This makes the prices local in nature. Hence, if majority of farmers in the region stores their produce it will smoothens the market- level prices. This means that prices immediately after harvest will be significantly higher, and prices during the lean season will be lower. Hence, it will reduce the arbitrage opportunity available to farmers and will decrease their profitability. EXAMPLE: If a farmer stores one quintal of food grain, the per quintal price of which fluctuates between $80 to $120. She takes a loan of $50 for six months at an interest rate of 1% per month. The warehouse rent costs 16 cents per quintal per month. The total expenditure will be $4. Farmer net gain is [(120-80)-4] = $36. Now suppose, over 50% of the farmers stores their produce, the price smoothens and fluctuates between $90 to $110. Then the same farmer receives a reduced net gain of [(110-90)-4] = $16.

In more advanced and market friendly countries, the inter-spatial price difference for food grains is very low. o Due to better infrastructure, the produce can travel long distance. o The strong legal rights and friendly inter-regional business regulations bring the trade cost down and make is easy to purchase and sell agri- produce across geographies. The integrated agri-markets of these countries makes the prices national in nature. Hence, if majority of farmers in one region store their produce, it will not have an effect on market-level prices. This means that the gap created by farmers storage will be filled by bringing in produce from different region. In our example the price will remain $80 even after over 50% farmers within a region store their produce. This is because in the nearby market the produce will be available in $80, and the buyer will not increase the price to $90 for the farmers to sell. Hence, in integrated markets, even after majority of farmers of a region store their produce, the arbitrage opportunity available to farmers will not reduce.

• The variance of season price difference: It means how far the prices between post-harvest low to pre-harvest high are spread out from the average price. If the prices of a crop in a particular market is very volatile and have a difference of 50-150%. Then, as number of farmers storing the produce increase, the price becomes smoother and its volatility will decrease. However, if the price are not very volatile, then the farmers action of storing their produce will not affects the seasonality of market-level prices in tangible way.

• Size of market: In a small-markets, if majority of farmers store their produce, it will immediately affect the market-level price. Whereas, in a big market, to have an effect on the market-level price, it will require a relatively large number of farmers to store their produce. In a country like India, where we have over 140 million farmers, it will require millions of farmers of any single crop to affect the market-level price of that crop.

• Proportion of the farming population storing the grains: If more farmers store the grains than the market-level price will be affected and it will get smoother.

It is difficult to estimate the intensity of the effects. However, we can estimate the directions. The below table summarizes the conditions under which the market-level prices will be affected:

Factors	Affect market-level prices	Does not affect market-level prices
Inter-spatial price difference	High	Low
Variance of seasonal price difference	High	Low
Market size	Small	Big
Proportion of the farming population storing the grains	Large	Small