Do industrial policies that promote clean energy offer a "ray of hope", increasing a country's growth and welfare, whilst simultaneously reducing carbon emissions? We study the impact of Chinese solar subsidies whose implementation by city-regions went alongside massive expansion of the sector and a dramatic fall in global solar prices. We construct new city and firm panel data on solar policies, patenting and output. Using synthetic-difference-in-differences 2004-2020, we find production and innovation subsidies were more effective than demand-side (installation) subsidies in generating large and persistent increases in local innovation, net entry, production and exports. Demand policies did, however, reduce local pollution. To examine aggregate effects, we build and structurally estimate a quantitative spatial model with endogenous innovation and heterogeneous productivity across firms and cities, which accounts for business stealing and knowledge spillovers. Counterfactual analysis shows that: (i) local effects remain substantial at the macro level explaining 40%–50% of the aggregate changes in solar innovation, prices and revenues; (ii) social benefits to Chinese citizens exceed subsidy costs by 65% (and double this when environmental benefits are included); and (iii) although all subsidy types increase welfare, innovation subsidies are the most cost-effective.

Disasters cost billions each year in damage and recovery spending. Governments have little evidence on how to target this spending, and typically direct resources based on whether an area was physically exposed and how much was destroyed. This makes sense during the initial emergency, but as recovery unfolds, disaster incidence — who bears the welfare cost — may diverge from physical exposure. When your neighbours are unaffected, you can access assistance and labour markets nearby; when they are also flooded, there is nowhere to go. This paper asks how a government with a limited budget should target recovery spending in space to minimise the welfare cost of a disaster, accounting for these indirect effects. We formalise the idea of disaster incidence using a simple spatial general equilibrium model in which flooding elsewhere enters welfare in a market access form familiar from trade models. The model yields an optimal targeting rule that accounts for both direct and indirect flood exposure. We test whether spillovers matter in practice using original panel data on 5,100 rural households surveyed one and two years after Pakistan's 2022 floods, and a recentered IV (Borusyak and Hull, 2023) leveraging hydrological simulations. Our findings are consistent with the model: labour market disruption and asset sales are driven primarily by flooding in the surrounding area rather than by direct exposure. We calibrate the model to Pakistan and compare targeting rules under uncertainty — asking not just which performs best on average, but which holds up best when the planner is wrong about the world.

IGC · STEG · Harvard University

When cities face water scarcity, policymakers must decide how to allocate the burden of saving water between households and firms. We study Cape Town's 2016-2018 water crisis during which water prices rose sharply. Using administrative tax records covering all formal employment in South Africa we document two facts. First water-intensive sectors in Cape Town experienced persistent establishment and employment declines. This divergence did not occur in control metros. Second the effects are spatial: within Cape Town locations with higher water intensity remain even after prices return to lower levels. We propose a mechanism: when firms exit they historical accumulated productive capital that took years to build. If enough exits occur the local economy crosses a tipping point to a permanently lower equilibrium. To formalise this we develop a dynamic spatial model that distinguishes contemporaneous agglomeration from historical agglomeration. The model allows for temporary resource shocks to permanently alter the equilibrium output of locations within a city. We discuss identification of the key agglomeration parameters and the policy implications for how scarce resources should be allocated between households and firms during crises.

IGC · Water, Air and Energy (WAE) Lab

Heatwaves, intensified by climate change, hit the poorest the hardest. Many are exposed to dangerous temperatures through outdoor or factory-based work, and have limited access to adaptive resources. How can social protection evolve to address the growing losses caused by extreme heat? We conduct a randomized controlled trial among low-income workers in Delhi, India, comparing the effects of temperature-indexed heat alerts, anticipatory daily wage payments delivered before heat events, and same-day daily wage payments delivered during heatwaves. We measure impacts on labour supply, adaptive behaviours, health, and financial wellbeing. The design separately identifies the value of information, the value of cash, and the value of acting ahead of heatwaves.

JPAL K-CAI

Psychologists have long argued that human needs are met in order of priority: until basic needs such as shelter are secured, attention and effort remain focused on them, delaying higher-order pursuits. This idea has implications for a range of economic outcomes — shaping, for instance, how much background risk a household bears and, thus, how willing it is to make high-risk, high-reward investments in the future. Despite its influence, the idea that needs follow a hierarchy has rarely been tested using credible causal evidence on economic behaviour. We provide such a test using the reconstruction of flood-destroyed homes in Sindh, Pakistan. Exploiting staggered disbursements of home-reconstruction grants, we compare otherwise-similar households that received funding just before and just after a program expansion. Combining administrative records with a survey of 6,000 households, we estimate the effects of home security on risk-taking, migration, health, schooling, and productive investment.

Hub for Equal Representation (LSE)