To learn more about my projects, expand the section next to each figure or click on any underlined title to access the paper. Feel free to reach out at any time to verify the availability of updated versions of any ongoing project.
My main research agenda on tax enforcement and tax compliance with administrative micro-data.
We show that tax authorities can stimulate tax compliance by strategically releasing audit-relevant information. We rely on the Sector Studies, an Italian policy disclosing to small firms and the self-employed that audit risk drops above file-specific revenue thresholds. This allows us to pursue two empirical strategies, leveraging more than 26 million Sector Study files submitted between 2007 and 2016. First, we estimate a structural model to match the heterogeneous bunching we observe on the low-risk side of the disclosed thresholds. Relative to scenarios where these thresholds are secret, we determine that disclosure results on average in 6.3-7.7% higher declared revenues, but modest welfare costs. Second, we exploit a staggered Sector Studies reform that widens the initial audit risk discontinuity. In line with our theory, taxpayers who benefit from greater audit exemptions above the threshold tend to reduce their relative compliance, while those originally below the threshold improve it. However, mean reported profits increase by 16.2% in treated sectors over six years.
Awarded the 2022 Innovative Policy Research Award by the Asian Development Bank and the International Economic Association. Presented at the APPAM 42nd Annual Fall 2020 Research Conference, the NTA 114th Annual Conference on Taxation, the 2022 CESifo Area Conference on Public Economics, the 15th RIDGE Forum - Workshop on Public Economics, and the 2022 European Economic Association Congress.
The Business Cost of Tax Audits (in progress)
How disruptive is tax auditing for small firms and the self-employed? How willing are taxpayers to avoid the costs associated with fiscal inspections? Even when audits detect no evasion, they can place undue burden on the day-to-day activity of small taxpayers. With micro-level administrative data over the 2007-2016 period, I study the revenue response of Italian firms and the self-employed across two types of auditing policies. On one hand, I explore the effect of a reduction in the length of on-site audits mandated since 2011. On the other, I assess the extent of bunching below the exemption threshold of Sector Studies as it evolves across sectors and years. Observed responses can inform us on the relative costs that firms associate to tax audits, and guide policy choices for the optimal design of modern tax enforcement systems.
Rewarding Compliance: Effects of the 2011 Reward Regime on Italian Small Businesses (report), with Matteo Paradisi
We study the effects of a unique Italian reform incentivizing voluntary tax compliance among the self-employed and small businesses. Starting in 2011, taxpayers in a growing number of sectors were promised an increase in audit exemptions upon achieving a set of desirable conditions defined by the Revenue Agency. While policy rewards might induce a tax base rise among previously non-compliant filers, curbing audit risks for broad categories of the taxpaying population might prove revenue reducing. Over the first six years of implementation, our event-study analysis of more than 9 million anonymized records reveals a substantial expansion of average declared revenues, total costs, and gross profits, with little heterogeneity across macro-regions. Although aggregate compliance does not seem to improve by policy metrics, our distributional analysis shows that large gains obtain among taxpayers appearing non-compliant in the year before their sector's reform. We also provide a dynamic perspective on bunching at salient, audit-relevant revenue thresholds generated by the system. Relative revenue reshuffling from above and below these thresholds provide evidence that bunching in our context may emerge from both desirable and adversarial updating in compliance behavior.
Optimal Audit Rules and Disclosure (in progress) with Luca Maini, Matteo Paradisi, and Elia Sartori
My upcoming projects in collaboration with the Italian Tax Police (Guardia di Finanza) explore the potential of machine learning for audit targeting, the determinants of evasion heterogeneity across firm types, sectors, and places, and the role of optimal audit strategies and information provision to taxpayers for business tax compliance.
Recipient of the 2021/2022 Molly and Domenic Ferrante Economics Research Fund at Harvard.
My early work on public good provision and deficit dynamics in ethnically diverse and unstable societies.