unit costs. Estimating trade costs from trade flows with the standard iceberg cost specification, however, yields multiplicative costs. Then, a natural question is how much this discrepancy matters for correctly predicting the impact of transport cost changes. Bergquist et al. (2019) provide an insight on this question. After estimating additive transport costs in levels from price gaps, they use a model-based approach to show the bias in average and distributional effects had they used an ad-valorem specification. Another source of potential bias from such misspecification comes from the well-known Alchian-Allen effect, or “shipping the good apples out” which implies that the quality and thus the unit cost _co_ of a traded product may itself be a function of per-unit transport cost. The reason is that given a per-unit cost _tod_ , selling a highquality version of a product with higher _co_ lowers the percentage cost _τod_ .<sup>10</sup> A change in per-unit transport costs will impact not only the quantity but also the quality and thus the unit price of shipments. A framework that assumes ad-valorem costs will then yield biased estimates for the responses of trade values and real incomes to transport cost changes.

Another important consideration in using existing data sources is to better incorporate the market structure and endogenous determination of mark-ups in trucking. This is critical for separating prices from costs and gauging the role for policies that could increase competition. Trucking sector is known to display a dual structure in many developing countries, with informal owner-operators forming a competitive fringe and formal, modern carriers operating large fleets.<sup>11</sup> In the segments that they serve based on routes and service quality, the latter group typically commands market power. Recent work by Allen et al. (2021) presents novel stylized facts on market concentration in trucking from Colombia, which inform a spatial imperfect competition model of carriers. When transport costs are high, they could be further magnified through endogenous entry decisions of carriers and high mark-ups. In a more general setting, high trade and transport costs could also affect market structure in downstream markets. Using market and farm-gate agricultural prices in India, Chatterjee (2020) estimates the role of spatial frictions in increasing the market power of intermediaries. Bergquist and Dinerstein (2020) provide similar evidence from Kenya using a randomized controlled trial (RCT) design.

Given the importance of data collection for the subject matter of this review, it would be befitting to conclude with a note on what data governments should aim to collect. The overall message is clear: there is need for high quality micro data on road freight transportation that is more direct and detailed than those usually available.

> 10Existing evidence on the presence and implications of the Alchian-Allen effect comes from studies of international trade (Hummels and Skiba, 2004; Irarrazabal et al., 2015).

> 11Also, the high level of informality and prevalence of owner-operators, as well as the general lack of list pricing in trucking, pose a challenge for using digital technologies such as web scraping to collect data.

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