Research

We investigate gender discrimination in an online marketplace in Pakistan. Employing buyer profiles that signal gender, we experimentally engage in transactions with sellers on the platform. We find no evidence of discrimination in pricing or product quality, suggesting that digital marketplaces may neutralize traditional economic biases. However, significant gender differences persist in non-price interactions. Female buyers are significantly more likely to receive unsolicited messages and friend requests following transactions, primarily from male accounts. Linguistic analysis further reveals that male sellers exhibit greater verbosity, enthusiasm, and flirtatiousness towards female buyers. While these interactions may not constitute overt harassment, in conservative and patriarchal settings, such unsolicited contact, regardless of intent, can carry reputational and social costs for women. Our findings highlight that online marketplaces, even as they remove discrimination on economic outcomes, may pose subtle barriers to equitable participation.

We study possible labor market discrimination by workers towards their out-group employers as manifested via social preferences (altruism and reciprocity). We run a well-powered, model-based, lab-in-the-field experiment, recruiting 6,000 white American worker subjects from Amazon's M-Turk platform for a real effort task. We also hire trainer subjects, our stand-in for employers, from a university. To worker subjects, we randomly (and unobtrusively) reveal the racial identity of the trainers, who may be white or black. We find evidence that white workers may discriminate against white employers based on altruism (working harder due to concern for the employer's well-being). However, they may discriminate based on reciprocity in favor of their white employers (working harder because of a small gift). From the perspective of black (white) employers, altruism evokes a stronger (weaker) effort response, but gift-giving has no (positive) effect. The combined effect of altruism and reciprocity on worker effort is the same for black and white employers.

This chapter examines Pakistan's tax system's structural challenges and reform opportunities, highlighting its inefficiencies, inequities, and reliance on distortionary taxes. It advocates for a scientific approach to tax policy, emphasizing evidence-based decision-making, data-driven interventions, and institutional reforms. The chapter provides actionable pathways to improve tax compliance, enhance equity, and promote sustainable economic growth.

Digital monitoring technologies promise "automated enforcement," but in many low-capacity states, compliance cannot be mandated — firms must be induced to opt in. We study what such reforms deliver when participation is voluntary, and enforcement credibility is limited. Using administrative panel data matched to transaction-level device records from a real-time reporting program in Pakistan, we track both selection into integration and the dynamic effects of adoption. Take-up is sharply selected: adopters are firms already more engaged with the tax system before integration. Conditional on adoption, reported activity and tax payments rise immediately but fade within months, consistent with learning about the authority's ability to sustain follow-up. Finally, incentive design shapes the reform's equilibrium effects: linking preferential rates to restrictions on input-credit claims shifts reporting away from inputs documentation, weakening the self-enforcing VAT chain. The results highlight credibility and design — not technology alone — as central to digital state-building.

This paper analyzes the impact of the 2022 floods on agricultural supply networks in Punjab, Pakistan. We unlock high-frequency agriculture supply chain data on quantities and merge it with spatial remote-sensing data from February 2022 to December 2022 to assess disruptions to the movement of agricultural commodities between "source" supply regions and "destination" consumption districts. Using an event study design, we find statistically significant pre-event anticipatory effects that increase supply by 35%, followed by a reduction of up to 34% in the overall quantities compared to the baseline in the aftermath of the floods. We document heterogeneity over crop types and district sizes.

This paper estimates the causal impact of messages displayed on dynamic message signs adjacent to roads on reported near-to-sign crashes and crash severity. We match accident reports to displayed messages using minute-level time and location metrics, along with hourly data on traffic and weather conditions in Vermont from June 2016 through the end of 2018. We show that behavior messages causally decrease the number of accidents by about 45% and the number of vehicles involved in accidents by 30%, while information messages do not, and neither causally impact whether or not an accident induced an injury or fatality.

In this paper, we examine the effect of COVID-induced lockdowns and compliance on the potato supply chain in Punjab, Pakistan. By combining granular price level information from various sources and primary survey data of over a thousand farmers, we show that the middlemen were the clear winners in the supply chains during COVID-induced lockdowns. During COVID, the middlemen retained a higher share of prices, both upstream and downstream of the vertical supply chain.

This study investigates whether informal markets remain stuck in low formalization due to self-reinforcing dynamics, which we call the "informality trap." We conduct a randomized field experiment among restaurants, targeting two channels: bringing informal businesses into the tax net and improving compliance among already registered firms. By experimentally varying the enforcement intensity across areas, we aim to understand whether improving the formalization of some businesses can trigger broader shifts across other businesses in the same area.

Economic growth in developing countries is often limited by the state's inability to raise tax revenue. This study addresses this challenge in two steps: first, by developing a computer vision algorithm that can use property images to predict property assessments and second, by testing how well the algorithm performs in identifying properties for reassessment.

Farmers in low-income countries typically suffer from low productivity. This research studies the reasons for price divergence between consumers and producers and specifically explores the role of information asymmetries as well as output market linkages as a barrier that prevents farmers from getting better returns on their productive investments. This work is funded by the IGC and J-PAL.

This paper shifts the focus from the demand side (employers) to the supply side (workers) for a more nuanced understanding of labor market discrimination. We outline a simple principal-agent model and show that workers' identity-based social preferences imply that the workers are more productive for the same identity employers, leading to assortative matching and segregation of the labor force.

Tax expenditures — preferential treatments such as exemptions, deductions, and reduced rates — are widely used by governments to pursue social and economic objectives without direct outlays. This ongoing study develops a unified, data-driven framework to answer whether these concessions translate into lower market prices for staple commodities, or whether the benefits are captured by input suppliers, distributors, or retailers.

Digital marketplaces promise to lower barriers for entrepreneurs, yet women often encounter hidden obstacles. This study first analyzes administrative Facebook Marketplace data, then launches a large-scale randomized audit experiment in Pakistan. Funded by PEDL, CEPR, and LUMS, our ongoing research will generate rigorous evidence to guide targeted interventions and platform policies that promote gender equity in online entrepreneurship.

Consumer receipt lotteries — programs that reward shoppers with entry into prize draws for submitting formal sales invoices — have been adopted in many countries to promote formal receipts and boost tax compliance. We conduct the first randomized field experiment of a consumer lottery in the hospitality sector of Khyber Pakhtunkhwa, Pakistan, assessing the impact on formal invoice issuance, reported revenues, and potential spillovers to non-participating firms.