tax payment through withholding by employers observed in the second half of the 20<sup>th</sup> century among high-income nations (Besley and Persson 2014) likely freed up resources dedicated to marshaling tax collections through visits, in-person collections, and so on. This shift could account to some extent for the greater shares of staff in audit and investigation roles in higher-income countries relative to lower-income countries we note above.

On the other hand, technology can clearly offer productivity gains for staff by expediting formerly cumbersome processes – like managing tax records or checking returns for errors – and facilitating reallocation of effort towards higher-return activities. The introduction of a digital tax collection technology within a Ghanaian municipality sheds light on this dynamic. In 2021, the municipal tax authority provided a tablet-based technology containing a geospatial database of properties and revenue management software that helped property tax collectors more easily locate properties in the field. A randomly selected subset of local property tax collectors – whose task is to deliver tax bills and collect payments manually – were provided with this new technology. These collectors delivered almost one-third more bills and collected double the amount of revenues compared to collectors persisting in the old, entirely manual system (Dzansi et al. 2022). The timeline of the evolution of visits and payments suggests that the technology assisted collectors in learning more quickly which households were willing and able to make payments and to target their in-person collection efforts accordingly. Technology can thus have high returns in even low resource, low compliance settings.

However, tax authorities face two major challenges. The first is how best to strike a balance between using technology to improve on potential error, bias, or manipulation in the work of human agents –– while retaining the value of rich contextual knowledge of an environment that tax officials can acquire from repeated interactions with taxpayers. The tradeoffs involved likely vary with the nature of the task, even within the same setting. As an example, in Senegal, property assessment officials using a “discretionary” method produced real estate valuations that with more regressive tax implications than those produced by a computer algorithm (Knebelmann et al., 2023), while officials charged with identifying firms with high evasion for audit performed better than a newly-introduced algorithm directed toward the same purpose (Bachas et al., 2023).

An example from Tajikistan, in which a set of small- and medium-sized businesses in were experimentally encouraged to adopt e-filing (Okunogbe and Pouliquen 2022), highlights the tensions around using technology to replace interactions between taxpayers and officials. Firms that adopted the electronic filing system – replacing a process by which taxes were filed in-person with tax officials – reduced their time spent on tax matters by 40 percent and also freed up the time of tax officials previously tasked with receiving declarations. However, e-filing did not change the average amount of taxes or bribes paid by firms, due to counterbalancing patterns among two types of businesses. One type of firm, identified as being more likely to evade pre-adoption, approximately doubled their amount of taxes paid. The study suggests that e-filing disrupted previous collusion between these firms and tax officials that had reduced tax liabilities. For the other type of firms, those deemed less likely to evade, e-filing reduced taxes paid, which is consistent with e-filing leading to less direct monitoring by officials who could have had private 15