Progressive taxation is central to high-income countries' tax systems, but developing countries typically rely on less progressive instruments. We study the introduction of progressive property taxation in a large Congolese city through a citywide field experiment conducted in partnership with the provincial government. Neighborhoods were randomly assigned to a progressive or a proportional schedule. The progressive schedule increased revenue by 56% relative to the proportional one. Gains occurred throughout the property value distribution: at the top, higher statutory rates mechanically raised revenue despite modest compliance losses; at the bottom, lower rates induced compliance gains large enough to offset lower liabilities. Cross-randomized information treatments show that taxpayers responded primarily to their own rates, not to others' rates or to the perceived fairness of the overall schedule. Effective tax rates – taxes paid as a share of property value – declined with property value and were most regressive under the progressive schedule. However, after a progressive schedule was scaled up citywide in subsequent years, targeted enforcement among high-value properties reversed this pattern, aligning statutory and effective rates. Together, the results suggest that progressive property taxation can raise fiscal capacity in low-income settings and, when paired with targeted enforcement, further shift the tax burden onto wealthier property owners. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Governments in the world’s poorest countries face severe revenue constraints. They typically collect less than 10 per cent of GDP in taxes, compared to 25–50 per cent in high-income countries. The literature on state capacity and development argues that inability to collect taxes is at the heart of why low-income countries are as poor as they are. It suggests that the path to economic prosperity may begin with investment in governments’ capacity to collect the tax revenue necessary to provide public goods that enhance productivity. Property taxation is often the primary source of government revenue at the local level, and is essential for provision of local public goods.1 However, it remains one of the most under-utilised taxes in developing countries. This is partly because taxing properties requires mapping and assessing the value of properties, which is complex and expensive. Only 39 per cent of non-OECD countries and 15 per cent of sub-Saharan African nations have mapped their largest city’s private plots. Several approaches have been proposed to map and value properties (see Zebong, Fish and Prichard (2017) for a review). Some countries rely on in-person appraisal visits, but, while accurate, these are typically costly and prone to corruption. For this reason, many countries, such as Pakistan, Sierra Leone, and Malawi, have instead adopted simplified valuation methods. The most common approach is points-based valuation, which consists of assigning points based on the surface area of the land and buildings. Additional points are awarded for positive features, and deducted for negative features.

Delegating tax collection to informal leaders could raise tax revenue but runs the risk of undermining the local accountability of those leaders. We investigate this trade-off by exploiting whether city chiefs in the Democratic Republic of the Congo (DRC) were randomly assigned to collect property taxes in 2018. To measure accountability, we study the other side of the social contract: the distribution of resources by chiefs in a government cash transfer programme in which they had discretion over the recipients of development aid. In line with the preferences of citizens, chiefs who collected taxes allocated more programme benefits to poorer households and thus made fewer inclusion and exclusion errors. They were no more or less likely to pocket benefits themselves or allocate them to their families. Across a range of measures, citizens appear to have updated their beliefs of chiefs who collected taxes. We provide evidence that collector chiefs allocated aid to poorer households because door-to-door tax collection created opportunities to learn which households were in greatest need. In contrast to concerns of ‘decentralised despotism,’ the paper thus finds evidence of a chief’s accountability benefiting from delegating tax responsibilities to local leaders in low-capacity states.

Institutions are a key determinant of economic growth, but the critical junctures in which institutions can change are not precisely defined. For example, such junctures are often identified ex post, raising several methodological problems: a selection on the outcome of institutional change; an inability to study beliefs, which are central to coordination and thus the process of institutional change; and an inability to conduct experiments to identify causal effects. We argue that critical junctures are identifiable in real time as moments of deep uncertainty about future institutions. Consistent with this conception, the papers reviewed ( a ) examine changes to institutions, i.e., the fundamental rules of the game; ( b ) are real-time studies of plausible critical junctures; and ( c ) use field experiments to achieve causal identification. We also advocate for more systematic measurement of beliefs about future institutions to identify critical junctures as they happen and provide an empirical proof of concept. Such work is urgent given contemporary critical junctures arising from democratic backsliding, state fragility, climate change, and conflicts over the rights of the marginalized.

This paper investigates how tax rates and tax enforcement jointly impact fiscal capacity in low‐income countries. We study a policy experiment in the D.R. Congo that randomly assigned 38,028 property owners to the status quo tax rate or to a rate reduction. This variation in tax liabilities reveals that the status quo rate lies above the revenue‐maximizing tax rate (RMTR). Reducing rates by about one‐third would maximize government revenue by increasing tax compliance. We then exploit two sources of variation in enforcement—randomized enforcement letters and random assignment of tax collectors—to show that the RMTR increases with enforcement. Including an enforcement message on tax letters or replacing tax collectors in the bottom quartile of enforcement capacity with average collectors would raise the RMTR by about 40%. Tax rates and enforcement are thus complementary levers. Jointly optimizing tax rates and enforcement would lead to 10% higher revenue gains than optimizing them independently. These findings provide experimental evidence that low government enforcement capacity sets a binding ceiling on the revenue‐maximizing tax rate in some developing countries, thereby demonstrating the value of increasing tax rates in tandem with enforcement to expand fiscal capacity.

We study the evolution of belief systems that suppress productive effort. These include concerns about the envy of others, beliefs in the importance of luck for success, disdain for competitive effort, and traditional beliefs in witchcraft. We show that such demotivating beliefs can evolve when interactions are zero-sum in nature, i.e., gains for one individual tend to come at the expense of others. Within a population, our model predicts a divergence between material and subjective payoffs, with material welfare being hump-shaped and subjective well-being being decreasing in demotivating beliefs. Across societies, our model predicts a positive relationship between zero-sum thinking and demotivating beliefs and a negative relationship between zero-sum thinking (or demotivating beliefs) and both material welfare and subjective well-being. We test the model's predictions using data from two samples in the Democratic Republic of Congo and from the World Values Survey. In the DRC, we find a positive relationship between zero-sum thinking and the presence of demotivating beliefs, such as concerns about envy and beliefs in witchcraft. Globally, zero-sum thinking is associated with skepticism about the importance of hard work for success, lower income, less educational attainment, less financial security, and lower life satisfaction. Comparing individuals in the same zero-sum environment, we observe the divergence between material outcomes and subjective well-being predicted by our model.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Developing countries often lack the financial resources to provide public goods. Property taxation has been identified as a promising source of local revenue, because it is relatively efficient, captures growth in real estate value, and can be progressive. However, many low-income countries do not collect property taxes effectively due to missing or incomplete property tax rolls. We use machine learning and computer vision models to construct a property tax roll in a large Congolese city. To train the algorithm and predict the value of all properties in the city, we rely on the value of 1,654 randomly chosen properties assessed by government land surveyors during in-person property appraisal visits, and property characteristics from administrative data or extracted from property photographs. The best machine learning algorithm, trained on property characteristics from administrative data, achieves a cross-validated R2 of 60 per cent, and 22 per cent of the predicted values are within 20 per cent of the target value. The computer vision algorithms, trained on property picture features, perform less well, with only 9 per cent of the predicted values within 20 per cent of the target value for the best algorithm. We interpret the results as suggesting that simple machine learning methods can be used to construct a property tax roll, even in a context where information about properties is limited and the government can only collect a small number of property values using in-person property appraisal visits.

How might fragile states escape a low-capacity trap in which citizens pay little tax and the government has insufficient revenue to increase enforcement or provide public goods? We argue that governments can escape such traps by regularizing tax collection. When citizens observe taxes being collected in a systematic, non-arbitrary manner, they are likely to update positively about the procedural performance of the government, increasing their intrinsic motivation to comply. We test this idea in the first door-to-door property tax collection campaign in Kananga, Democratic Republic of the Congo, which raised compliance from near zero to 10.3%. Linking pre-campaign surveys with administrative tax data, we document a strong relationship between citizens' prior perceptions of government performance and property tax payment. Then, exploiting the campaign's random roll-out, we find that systematic tax collection caused citizens to update positively about the government's procedural performance. Together, these results are consistent with a virtuous cycle of perceived government performance and fiscal capacity.

Psychological and cultural evolutionary accounts of human sociality propose that beliefs in punitive and monitoring gods that care about moral norms facilitate cooperation. While there is some evidence to suggest that belief in supernatural punishment and monitoring generally induce cooperative behaviour, the effect of a deity's explicitly postulated moral concerns on cooperation remains unclear. Here, we report a pre-registered set of analyses to assess whether perceiving a locally relevant deity as moralistic predicts cooperative play in two permutations of two economic games using data from up to 15 diverse field sites. Across games, results suggest that gods’ moral concerns do not play a direct, cross-culturally reliable role in motivating cooperative behaviour. The study contributes substantially to the current literature by testing a central hypothesis in the evolutionary and cognitive science of religion with a large and culturally diverse dataset using behavioural and ethnographically rich methods.