The tax behavior of small firms in low income countries shapes government revenues and the welfare of poor entrepreneurs. This paper provides evidence that how these firms respond to tax instruments diverges from traditional models of compliance in ways that have unintended and regressive consequences. Using the universe of administrative filings in Rwanda, I document perverse responses to changes in liability: an income tax reform that standard models would predict should lead all taxpayers to pay lower taxes in fact caused firms to increase tax paid by 75%. To explain this behavior, I establish a new stylized fact: firms consistently target past liability when paying taxes, even when the structure of liability changes. Many firms bunch sharply on their previous amount of tax paid year after year and stick to this level despite changes in their tax rate. Others increase tax paid rather than deviating downward from past levels when changes to the tax schedule remove their ability to pay the same amount as before. Evidence from a survey of filers and a randomized information experiment imply that firms’ uncertainty about own earnings generates reliance on the heuristic of previous liability, while enforcement perceptions and peers influence how firms select target amounts. Ultimately, this behavior produces regressive outcomes: less educated and less profitable entrepreneurs are more likely to overpay relative to their true liability.
How do states in a low-tax, low-capacity equilibrium spur citizens to start paying taxes? We implement a field experiment embedded in a property tax campaign in Kananga, a large city in the Democratic Republic of Congo (DRC). In collaboration with the Provincial Government of Kasai Central, we randomly assign the city's neighborhoods to central tax collection, conducted by agents of the provincial tax ministry, or local tax collection, conducted by local city chiefs. We also implement two hybrid collection interventions and cross-randomized information treatments to elicit the mechanisms through which central and local tax collection shape citizen compliance. In addition to tax compliance, we examine a range of other outcomes, such as corruption, engagement with the formal state, and the accountability of city chiefs. Implementation and data collection began in July 2017 and will conclude in December 2018.
How does tax compliance vary with the tax burden when opportunities for evasion are high? This paper estimates the elasticity of property tax compliance to the tax rate through a field experiment in Kananga, Democratic Republic of the Congo, a low-compliance setting where the status quo level of compliance is 10%. We randomly assign four tax rates to properties as part of a door-to-door city-wide tax collection campaign. Individuals face between 33 to 100% of their true liability. We study how the rate of compliance varies with the rate, controlling for the tax collector effort and spillovers. The findings of this intervention – including the slope and shape of the relationship between compliance and rate – will contribute to knowledge about the design of tax liabilities and the setting of efficient tax rates in environments where enforcement capacity and compliance are low. Implementation and data collection began in July 2017 and will conclude in December 2018.
This paper leverages technological solutions to understand potential hiring frictions faced by small and medium firms in the blue-collar service sector in Bangalore, India. Firms seek to expand operations but face difficulties in finding qualified and trustworthy candidates while experiencing high turnover. To address these concerns, we cross-randomize two interventions—premium recruitment and screening services— to understand whether and how these hiring frictions individually and jointly affect the growth and performance of firms specializing in retail sales and delivery logistics. Our subsidized premium recruitment services provide firms with access to a larger applicant pool and recruitment assistance by customer service staff, while third-party screening services assure employers that candidates on the platform are who they claim to be and serve to increase trust between potential jobseekers and employers. We implement these interventions in collaboration with the leading online classifieds portal for blue-collar recruitment in India, beginning in October 2018 and ending in July 2019.