Amen Jalal

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Hello! I am a 5th year PhD student in economics at the London School of Economics. I have a Bachelors in economics from Yale University. Before starting the PhD, I worked at the World Bank as a research assistant in the DIME and ID4D teams.

I work on labor, gender and environmental issues in low income countries.

Works in progress

Salary Range Disclosure in Job Ads

Experiment ongoing

Supported by G2LMLIC

AEA registry

Click for abstract Salary is a central characteristic of jobs, and varies considerably across firms for similar positions. However, globally, salary information is scarce at the hiring stage, making it difficult for workers to direct search. This study assesses how salary disclosure in job ads affects workers’ sorting and firms’ wage setting behavior. Using firm surveys and administrative data from Pakistan’s largest online job search platform—where I see salary ranges even when they are hidden from jobseekers—I find that better paying firms are more likely to hide salary information. In particular, such firms use salary non-disclosure as a ‘self-screening' tool to exclusively attract ‘suitable’ workers. This practice may disadvantage women, who tend to have lower labor market exposure and thus may be less able to extract wage signals from job descriptions, or may prefer to know the bargaining space before negotiating. To study these issues, I partner with the job platform to run an experiment in which treated ads are induced to post salary ranges while control ads can choose whether to disclose this information. The experiment uses a saturation design that randomly exposes some labor markets to high (75%) and others to low (25%) treatment intensity.


Coping with Catastrophe: Pakistan’s 2022 Floods

(with Pol Simpson)

Second annual follow-up survey ongoing

Supported by the IGC, STEG and Harvard University

IGC Blog Post

Click for abstract Extreme weather events are becoming more frequent due to climate change, yet we know little about how unprecedented climate shocks impact the most vulnerable populations. In this project, we investigate the effects of the 2022 floods in Pakistan, which affected 33 million households and left one third of the country under water. Using a pre-flood census, we draw a random sample of 5,100 low-income, rural households across 6 districts of Sindh, whom we track and survey one and two years after the floods. These households vary in their local exposure to the 2022 floods. We study (i) the impact of the floods on these households, (ii) how they cope with these impacts and make forward-looking adaptations, and (iii) how flood impacts evolve over time. We exploit plausibly random local variation in flood water inundation – i.e., precipitation interacted with topography – conditional on historical rain and flood risk. Our outcomes include flood damages (e.g. loss of income or assets, health impacts, and disruption of social networks and trade), coping strategies (e.g. drawdown of savings, sale of assets, new loans, increased labour supply, changes to educational or nuturitional investments) and adaptation (e.g. diversification of networks or assets, and migration).


The Illusion of Time: Job Search and Female Labor Force Participation

(with Oriana Bandiera and Nina Roussille)

Draft available soon

Supported by Gates Foundation, STICERD (LSE), and RISF (LSE)

AEA registry

Click for abstract This paper documents a large gap between college-graduating women’s intended and realized labor force participation, and proposes an explanation. To do so, we field a panel survey and an experiment on >1,500 college students in Pakistan. A month before graduation, women believe they have about the same likelihood as their male peers of working six months later (~75%). By contrast, we uncover large employment gaps: only 37.9% of women were employed six months later, compared to 64.4% of men. Traditional supply-side (e.g. GPA, major, job preferences, search effort) and demand-side factors (e.g. interviews, wage and job offers) leave this gap virtually unchanged. However, we find that women’s employment is much more sensitive to the timing of their applications than men’s. We provide a theoretical framework and empirical evidence on why timing matters: the unexpected increase in women's reservation wages over time. To causally estimate the effect of timing, we experimentally shift students' job applications closer to graduation. We find that this treatment increases women's employment by 22.3% (7.5 ppt) six months later, and has no effect on men. Finally, we explore behavioral and cultural mechanisms through which the treatment operates.


Can Market Competition Reduce Corruption?

(with Muhammad Haseeb and Kate Vyborny)

Draft available soon

Supported by the World Bank’s ID4D and the Gates Foundation

Policy brief

Click for abstract We study whether market competition can reduce corruption in the public sector. We exploit exogenous changes to the market structure of payment agents responsible for the delivery of government cash transfers in Pakistan. We find that a payment reform that increased the market power of these agents resulted in a 29.1 percentage point increase in the likelihood that bribes were paid involuntarily to access the cash transfers. However, higher competition between payment agents reduces the likelihood of bribe payment by 18.4 percentage points. We rule out the possibility that these effects are driven by teething problems of a new technology, or strategic entry of payment agents.


What Happens When Cash Transfers Suddenly Stop?

(with Nasir Iqbal, Mahreen Mahmud, Kate Vyborny)

Draft available soon

Supported by IFPRI and IPA

Click for abstract Cash transfers are the most popular form of social protection globally. However, they may not pay out indefinitely due to budget cuts, changes to program design, or graduation of recipients from the program. How do low-income households cope after long-running cash transfers suddenly stop? Using a regression discontinuity-in-differences design around a revised eligibility threshold, we investigate the effect of being exited from Pakistan's largest cash transfer program. One year after discontinuation, we find no significant impacts on households' economic outcomes or well-being. Two years later, we find a 5% drop in consumption (40% of the value of the transfer) and a 6 pp (12.5%) decrease in women's mobility (p<0.1), defined as market visits unaccompanied by family.


Equilibrium Effects of a Billion Trees: Evidence from Pakistan

(with Veronica Salazar-Restrepo)

Analysis ongoing

Supported by the IGC

Click for abstract Several countries are investing large sums of money in nation-wide tree planting programs for climate mitigation and adaptation. However, there is limited evidence on the impacts of such programs. They may disrupt ecosystems and agriculture, displace local communities, and lead to more deforestation in other areas. Conversely, planting the right species of trees at the right place can sequester carbon, regenerate forests, and provide ecosystem services like flood prevention. In this project, we focus on Pakistan's Billion Tree Tsunami Afforestation Programme (BTTAP), which planted 1 billion trees in the province of Khyber Pakhtunkhwa. First, we process high-resolution satellite imagery using a cutting-edge, context-specific remote-sensing algorithm. Second, we gather environmental data on wind, fires, temperature, precipitation, and pollution to measure spillovers of the program in down-wind areas. Finally, we incorporate these spillovers in a theoretical framework to analyze whether the program displaced existing economic activities like agriculture.


Teaching