How cell service fixed an Indian fish market
Jensen 2007 details an incredible observation on how the adoption of cell service by Keralan fishermen allowed them to carve out larger profit margin, while also stabilizing price for buyers and eliminating waste.
The Situation
Fishing is a significant industry for the coastal towns of Kerala. Each day at dawn, fishermen set out in droves to fish and return to sell their harvest in later the morning. Due to difficulty with storing and transporting the large quantities of fish, they usually sell off their entire harvest to distributors at local markets by the beach.
Fish yield is unpredictable — it is highly dependent on weather conditions or where the fish cluster around on any given day. As a result, fishermen sometimes find themselves undercutting each other in their local markets. The table below shows the wide variation in market prices in one such Tuesday morning, as well as buyers/fishermen (seller) who were unable to make any transaction.
This phenomenon of price dispersion is caused by inelasticity on the supply side. Fishermen simply have no control over their harvest, and they would be better off selling their entire yield at a lower price, rather than insisting on a more reasonable price point and causing a portion of their fish harvest to be left unsold. Unsold fish simply have to be discarded due to storage and transportation costs.
On the demand side, while buyers are usually willing to purchase the full load provided the price is sufficiently low, there are practical constraints to how much they can transport. This is worsened by the fact that fish tend to cluster, causing certain local markets to be oversaturated. The author estimates around 5–8% of harvest gets discarded on an average day.
The inefficiency is clear. while at Badagara there are eleven fish unsold, there are twenty-seven buyers within fifteen kilometers who are about to leave without purchasing any fish. — Jensen, 2007
Intervention
In the early 00s, cell service was introduced to this coastal region, and very quickly fishermen started adopting this technology to conduct their trade.
Chiefly, fishermen use cell service to contact buyers from neighboring markets to decide on 1. a reasonable price and 2. the market to disembark on and sell their harvest. Sometimes, fishermen also reach an agreement to sell specific quantities at specific price to willing buyers, effectively conducting auction via cell.
Prior to adoption, almost all fishermen sell their harvest at the nearest local market. After this practice becomes widespread, the author estimates that up 40% of fishermen end up picking neighboring markets with better prices.
A stunning outcome that resulted from this practice is that price stabilized significantly across all markets. Referring to Fig. 1, the standard deviation of one market is noted to have gone from 62–69 percent of the mean price to 14 percent or less. The author thus concludes that the price dispersion observed earlier was mostly due to incomplete information preventing fishermen from making optimal market decisions, and the introduction of cell service helped alleviate this problem.
Market Decisions
The author presents a framework for understanding the factors that led to this improvement.
Consider the decision that each fisherman has to contend with while at sea. If they are lucky, they find themselves near a high-density cluster of fish, and have a good harvest. In this scenario, they can choose either to sell it at a local market, or to venture to neighboring markets.
Intuitively, the fisherman knows that other fishermen from their locality will have a good harvest as well, since they fish in proximity to each other. There is thus potential gain from switching to a different market that is less saturated. However, they have little to no information about yield in other regions, and considering the time and fuel costs of embarking on a different shore, this could be a costly gamble. As a result, most fishermen are hesitant to try a different market, and the author notes that few such instances occurred.
Notice how incomplete information is the root cause.
After cell use became prevalent, fishermen were noted to have hundreds of buyer contact details on their phone, and they usually contacted a few from different markets to ascertain price conditions.
Through repeated messaging between pairs of fishermen and buyer, each market agent deduces sufficient information about the harvest conditions across different regions out in the sea to arrive at the best price and decision over which market to trade in. Cell service empowered fishermen to make the decision to switch markets, allowing them to be better compensated.
Market Dynamics
Who benefits from this change? Empirically, the average fishermen profit increased by 8%, while buyer cost decreased by 4%. The adoption of this technology led to win-win outcomes for both sides. Additionally, the author reports that waste is eliminated entirely.
The adoption of cell technology intuitively benefitted the fishermen, but how did this result in the reduction of price for buyers?
To understand how an improved flow of information benefited both sides, we examine the the changes in welfare with respect to the supply-demand curve, as shown in Fig. 2.
On any particular day, some markets will experience an influx of fishermen who decided to trade in those markets due to better prices. These are markets that correspond to fishing regions that did not observe fish clustering, causing local fishermen to have less yield compared to an average day. As such, fishermen from other regions will be incentivized to switch to these markets due to less competition.
This is represented by the graph on the left, where Q_t, representing total fish yield by local fishermen, is supplemented by X, the influx of harvest from other fishermen.
On the flipside, markets that correspond to fishing regions that did observe fish clustering is represented by the graph on the right, where Q_n, representing total fish yield by local fishermen, is subtracted by X, the loss of harvest from local fishermen who decided to switch market.
This analysis allows us to meaningfully quantify the impact of this (natural) intervention on the welfare of both the fishermen and the buyers. Welfare, which in economic terms is defined as price * quantity traded, is represented by the area under the curve in each graph.
Let’s take a look at the graph on the left. In markets that experienced an influx of fishermen, the welfare gain for buyers is the total area represnted by A+B. Fig 3. below shows why this is the case.
Similarly, the change in the welfare of fishermen is represented by C-A.
In aggregate, the change in welfare is quantified by (A+B) + (C-A), which sums up to B+C. Since B+C > 0, we know that net welfare is increased by the influx of harvests from other fishermen. Since A+B > 0, we also know that such incident is beneficial to buyers. However, C-A could be both positive or negative depending on the slope of the curve, sence the welfare impact on fishermen is dependent on the price elasticity (represented by the slope) of buyers.
We can apply the same on the right, to deduce the following:
- Net welfare gain: -E-F
- Buyer welfare gain: -D-E
- Fishermen welfare gain: D-F
Intuitively, buyers in markets that correspond to high-yield fishing zones experience loss because fishermen that would have traded there in the absence of cell service now have better options.
In total, the change in welfare is therefore characterized by B+C + (-E-F).
Mathematically, as long as the supply-demand curve is convex (which is a realistic assumption), B+C + (-E-F) > 0, implying total welfare gain from the introduction of this technology. The same can be said for fishermen’s welfare as well, (C-A) + (D-F).
The welfare impact on buyers, (A+B) + (-D-E), cannot be ascertained a priori to be positive or negative. It depends on the actual price elasticity of buyers: if elasticity is high, implying that the profit margins of buyers is high and they are flexible with higher price demand from the fishermen, then they will benefit from this change as a group.
Takeaways
The author conclusively showed that the introduction of cell service improved the welfare for fishermen, both theoretically and empirically. Perhaps more surprisingly, it was also shown that the net welfare gain is also positive, implying that the net gain for fishermen is greater than any (potential) loss for buyers.
This study is contextualized by broader debates around whether information and communication technology (ICT) helps or hurts smaller players in the economy. The claim made and proven here is that in markets such as the Kerala fish markets characterized by incomplete information, the introduction of such technologies is ultimately beneficial to the producers.
