S7 Ep49: Follow the paper trail

In Uganda, every sale between two VAT-registered firms reaches the tax authority twice. The seller reports it, and so does the buyer. But the two numbers rarely match. In Turkiye, a supplier that installs its first industrial robot doesn’t make an announcement, but the administrative records can track when the firms automate, and what happens next. Justine Knebelmann and Nuriye Melisa Bilgin tell Tim Phillips how they used those records to find out more about the choices firms make, and the effects on the firms around them. Justine and her co-authors worked with the Uganda Revenue Authority to send letters to firms whose reports did not match their trading partner’s, to find out under what conditions the firms amended their tax returns. Nuriye mapped robot adoption across Turkiye's firm-to-firm network, to find out the competitive effects. They also discuss how researchers can access administrative data, and how simply compiling it can change policy. The research behind this episode: Almunia, Miguel, David J. Henning, Justine Knebelmann, Dorothy Nakyambadde, and Lin Tian. 2023. "Firm Networks and Tax Compliance: Experimental Evidence from Uganda." CEPR Discussion Paper 18151, revised October 2025.  Bilgin, Nuriye Melisa, Ester Faia, and Gianmarco Ottaviano. 2024. "Technology Spillovers, Diffusion and Rivalry in Firm Networks." CEPR Discussion Paper 19804.  To cite this episode: > Phillips, Tim, Justine Knebelmann, and Nuriye Melisa Bilgin. 2026. "Follow the paper trail." *PEDL* (podcast). Centre for Economic Policy Research. **About the guests** Justine Knebelmann is an Assistant Professor in the Department of Economics at Sciences Po, Paris, and an Associate at the Institute for Fiscal Studies. Her research spans state capacity in developing countries, tax administration, digitalisation and land. She has worked with tax administrations in Sub-Saharan Africa since 2015. Nuriye Melisa Bilgin is a Lecturer in Economics at Koç University and a Senior Fellow at the Microsoft AI Economy Institute. Her research spans technology adoption, from industrial robots to generative AI, and how new technologies and shocks travel through production networks and global value chains, using large-scale firm-to-firm transaction data from Turkiye. She held postdoctoral positions at Bocconi University and the University of Turin. **About PEDL** Private Enterprise Development in Low Income Countries (PEDL) is a joint research initiative of the Centre for Economic Policy Research (CEPR) and the Foreign, Commonwealth & Development Office (FCDO), and part of CEPR's Growth Research Platform. Established in 2011, it funds research on private-sector development in low-income countries. Find out more at grp.cepr.org/pedl. **Research cited in this episode** **Value-added tax (VAT).** Firms charge VAT on their sales and reclaim the VAT they paid on inputs bought from other registered firms. Because every business-to-business sale appears on two returns, one from each side, the tax authority can in principle check one report against the other. Economists call this the VAT's self-enforcing property. In Uganda the VAT raises about 30% of total tax revenue, according to IMF figures cited by Almunia and co-authors; the IMF puts Uganda's VAT compliance gap at around 60% of potential VAT revenue. **Seller shortfall.** The Uganda team's term for a transaction in which the seller reports a smaller amount than the buyer. It lowers the tax bill and often signals evasion. In the 10 months before the experiment, from March to December 2017, seller shortfall appeared in 41.4% of monthly seller-buyer observations, and in more than 92% of those cases the seller had not reported the transaction at all. **Almunia, Hjort, Knebelmann and Tian (2024).** "Strategic or Confused Firms? Evidence from 'Missing' Transactions in Uganda," *Review of Economics and Statistics* 106 (1): 256-265. This earlier study measured the scale of the problem. Sellers and buyers reported different amounts for the same transactions 79% of the time, and the authors estimate that unilateral misreporting cost Uganda about USD 383 million in VAT revenue between 2013 and 2016. **Randomising pairs, not firms.** In a dense trading network, a letter sent to one firm can reach its partners by several routes and blur the results. The Uganda team randomised at the level of the seller-buyer pair instead, and selected 1,235 pairs so that no two shared a firm. Of these, 741 received letters, sent to the seller only, the buyer only, or both; the remaining 494 formed the control group. Because treated pairs were kept apart in the network, a correction by a firm that did not receive a letter points to communication between the two partners. **The final sales loophole.** Sales to consumers and to unregistered firms appear on a Ugandan VAT return as a single total, with no second report to check against. Sellers used this margin. When treated sellers amended their returns to add missing business-to-business sales, they cut their reported final sales by about 60% of that amount. The net gain in VAT was modest, but the letters still raised more than six times what they cost to send. **Electronic invoicing in Uganda.** After the 2018 experiment, the Uganda Revenue Authority expanded its data cross-checks. In 2021 it launched EFRIS (electronic fiscal receipting and invoicing), which requires input claims to be matched to VAT invoices, and in 2022 it began rolling out electronic billing machines that record transactions at the point of sale. **The reflection problem.** Charles Manski named it in "Identification of Endogenous Social Effects: The Reflection Problem" (*Review of Economic Studies*, 1993). When connected firms perform alike, it is hard to tell whether one influenced the other or whether similar firms simply chose to trade together. Nuriye's point about productive firms sorting into relationships with other productive firms is this problem in a supply chain. Her team addresses it by using the precise timing of each first-time robot purchase and checking for trends that predate it. **Knowledge spillovers and product market rivalry.** A firm can gain when a partner adopts a new technology and lose when a competitor does. Nicholas Bloom, Mark Schankerman and John Van Reenen set out the difficulty of separating the two effects in "Identifying Technology Spillovers and Product Market Rivalry" (*Econometrica*, 2013). Bilgin, Faia and Ottaviano separate them by the direction of the link. Suppliers pass gains down to their customers; rivals that sell to the same customers compete them away. **Turkiye's matched firm data.** The robot study links VAT returns covering firm-to-firm transactions, collected by the Ministry of Finance, with employer-employee records from the Social Security Institution, customs records from the Ministry of Trade, and registry and balance sheet data from the Ministry of Industry and Technology. The data run from 2007 to 2019. Robot purchases are identified by matching firms' fiscal codes with members of ENOSAD, the Turkish industrial automation manufacturers' association, and imported robots by their customs code, which also records the country of origin and whether an intermediary was involved. **Robot quality and technical support.** Robots from Switzerland and Germany, which sell at higher prices than those from China, generate larger spillovers to the adopter's customers. Robots bought through intermediaries that also provide technical support produce the largest effects. Four years after a supplier's first purchase, its customers' productivity is 14% higher when the robot came through an intermediary, against 6.3% when it came from a domestic producer. **Linking surveys to administrative records.** Justine mentions separate work by her co-author David Henning, who surveyed Ugandan firms and linked their answers to their tax returns. The combination reveals informal activity that administrative data alone cannot see, including among firms that had left the formal tax system. **Listen next** No taxation without administration: What makes tax authorities work, a VoxDev Talks episode in which Anders Jensen and Jonathan Weigel review the evidence on how tax authorities are organised, staffed and run, and why third-party data has limits where informality is high. **Related reading** Technology spillovers, diffusion, and rivalry in firm networks, a VoxEU column in which Bilgin, Faia and Ottaviano summarise the robot study. Strategic or confused? Firm behaviour and missing millions in Uganda's VAT, a VoxDev article on the earlier study that showed how often Ugandan sellers and buyers disagree about the same transaction. VAT in developing countries: flawed, but irreplaceable, a VoxDev article by Anne Brockmeyer, Giulia Mascagni, Mazhar Waseem, Miguel Almunia and Vedanth Nair, which draws on VAT administrative data from 11 countries to show where the tax falls short of its textbook design.