This is the fifth in this year's series of posts by PhD students on the job market.
We are “missing” a large proportion of trade flows
In low- and middle-income countries, informal trade accounts for a substantial fraction of total trade and is not recorded in official trade statistics. Informal trade is conducted by small-scale unregistered businesses, mostly women with little education and from rural communities. Traders maximize their profits by locating low-priced markets for buying and high-priced markets for selling. Informal traders can therefore be domestic traders or cross-border traders; and they either use official border crossings or instead choose to cross the border at unofficial crossings to avoid taxes. I refer to their choice of domestic trade, formal crossing or informal crossing as “routes”.
Due to the scarcity of the data on informal trade, little is known about the costs incurred by these small-scale traders, who likely face a different cost structure than larger scale traders. There are a number of plausible economies of scale in trade, including information acquisition. These traders tend to operate outside traditional business circles, complicating access to market information as well as information about taxes or regulations related to crossing the border.
Understanding informal trade and its inherent frictions is important for policy in my study area (Kenya-Uganda border) and in sub-Saharan Africa generally. First, informal traders contribute to livelihoods and food security. Second, governments and other organizations have implemented several policies (e.g., Simplified Trade Regimes for small-scale traders, One Stop Border Posts) to formalize trade as a way to increase tax revenues, reduce smuggling and limit corruption and harassment at border crossings. These efforts have been relatively unsuccessful at making informal traders switch to official crossings (J.Siu, 2020). It also isn’t clear that a full formalization of trade maximizes overall welfare.
My job market paper uses the 2020 closure of the Kenyan-Ugandan border due to Covid-19 and a RCT, accompanied by extensive data collection to (1) document traders’ specialization in markets and trade routes, (2) investigate the role of information frictions about market prices and (true) tax costs in driving traders’ stickiness to a single market and trade route and (3) explore how these information frictions distort agriculture markets.
Who are informal traders? A sample of small-scale traders
In February 2020, I conducted a census of Kenyan markets located within 40 km of the Kenya-Uganda border crossing. 1100 small-scale traders were randomly selected and extensively surveyed through multiple rounds of data collection throughout 2020 and 2021. 80% of traders in the sample trade in agriculture goods and 20 % trade shoes and clothing. At baseline, 45% are domestic traders, buying and selling in Kenya. 19% are cross border traders who buy in Uganda and use official border crossings to sell in Kenya and 36% use informal crossings instead. Most small-scale traders are foot traders or transport goods using bicycles or small motorbikes.
What can we learn about the informal trade sector?
Informal traders’ profits are 17% of traders’ sales. Costs faced by traders include border costs that take the form of taxes and bribes to officials when they cross the official border (officials overcharge traders, potentially exacerbated by gender dynamics) and bribes to the police when they use informal crossings. Despite large variation in prices across markets which should invite arbitrage, traders specialize in routes and markets. At baseline, 60% of traders always trade along the same route and 70% always sell in the same market.
As part of the restrictions imposed during Covid-19, the official border was closed to individuals -and therefore to small-scale traders between April and October 2020. This completely disrupted supply chains for cross-border traders who used to trade through the official crossing. I use this shock to derive key facts about the informal trade sector. I explore whether a large enough shock makes traders switch route and/or markets and find that cross-border traders who relied on official routes did adapt when the official border was closed and only 5-16% of them went out of business, differentially less than domestic traders themselves. They switched to informal crossings and to domestic supply chains, crowding out domestic traders. This shows traders can profitably trade using other routes and markets. Surprisingly, when the border reopens, only 25% of traders returned to their initial markets and routes (Figure 1).
This stickiness—i.,e. the fact traders did not return to their initial market/routes once the border reopened—can be rationalized by various theories. Traders could be optimizing rationally and the change in market and route choice is just a response to new prices and costs (possibly unobserved to me). Other possible explanations include that the border closure pushed traders to pay the cost needed to explore new markets, which led them to better outcomes. Alternatively, traders may be better off switching back to their initial market or route but the cost of acquiring up to date information is too high. The last two possibilities are examples of information frictions (in line with T.Allen, 2014) and I hypothesize that information frictions play a role in explaining this stickiness. The fact that over 50% of traders report not always knowing what taxes they should be paying at the border and 62% report not knowing market prices for their goods in other markets reinforces this hypothesis. I build a model that includes information frictions about market prices and official border costs (i.e., taxes) and test the model’s predictions using an RCT.
Treated traders get access to information through a phone platform
A random 50% of traders in my sample received access to a phone platform (accessible on all phones) that gives price information for goods in markets across East Africa as well as official taxes and tariffs they should be paying when crossing the official crossing. I additionally vary the intensity of treatment at the market x industry level (industry here is agriculture versus shoes/clothing), i.e., some markets had more treated traders than others. This allows me to account for potential spillovers and to evaluate price impacts in general equilibrium.
Contrary to the literature on the role of cell-phones in reducing market price dispersion for traders, which often relies on the expansion of mobile network towers as variation (J.Aker et al, 2012; R. Jensen, 2007), I have variation in actual access to information. I know both who has access to information and how they use it, allowing me to identify mechanisms.
Information makes traders better-off
Access to information about market prices and taxes increases the likelihood of trading by 4% and the likelihood that trading is traders’ primary source of income by 4%. Treatment also increases the number of types of goods traded by each trader by 8%. Turning to supply chains, in line with the model predictions, traders explore new markets: the number of selling and sourcing markets increases by 7-11% for treated traders, and the number of trips increases by 0.4 trips. Access to information raises traders’ sales and profits by 6 and 7% respectively. Treatment increases the probability that traders choose cross-border trade over domestic routes by 20%, specifically through official border crossings - leading to trade formalization. However, I find no substantial effects of treatment on levels of bribery or instances of corruption and harassment. Consistent with the fact traders buy goods at cheaper prices and pass the cost reduction through to consumers (I see no treatment impacts on markups), I find general equilibrium market price effects: intensively treated marketplaces see a reduction of 7% in consumer prices. These significant effects on market prices demonstrate that information frictions heavily distort markets.
How large are information frictions and should informal crossings be closed down?
I quantify the magnitude of the information treatment through back of the envelope calculations. First, I show that the reduction of information frictions about market prices and true tax costs, induced by the intervention is large and equivalent to transport costs incurred by being 150 kms away from the border (when the sample markets are all within 40 kms of the border). Second, relatively cheap information technologies like this one are very cost effective: the large welfare gains from consumer and government surplus mean that the cell phone app studied here has a cost benefit ratio of 1%. Third, through counterfactual simulations of the model, I can for example predict the effect of closing specific routes on prices. What would have happened if informal crossings did not exist when the official border closed? I show that informal crossings play an important role in limiting price spikes. Despite welfare improvements from formalization (due to increased tax revenues), there is a risk of a larger decrease in overall welfare (due to high consumer prices) if informal crossings are no longer existent to smooth border shocks.
Policy implications
This paper sheds light on a sector that is excluded from the majority of theoretical and applied research on trade as well as trade policies, despite playing a large role in low-and middle-income countries. Informal traders have characteristics and face frictions that are different from the larger scale traders the literature usually addresses. Including informal trade in the narrative therefore seems crucial. In addition, my results highlight the promise of new information technology to unlock the potential of small-scale border trade.
Eleanor Wiseman is a PhD student at U.C. Berkeley. Twitter: @EleanorWiseman
Join the Conversation