We examine the impact of artificial intelligence (AI) on hiring and wages in service sector firms, using a novel dataset of vacancy posts from India’s largest jobs website. We first document a rapid rise in demand for machine learning (ML) skills since 2016, particularly in the IT, finance and professional services industries. Vacancies requiring ML skills list substantially higher wages, but require more education and are highly concentrated both geographically and in the largest firms. Exploiting plausibly exogenous variation in exposure to advances in AI capabilities, we then examine the impacts of establishment demand for ML skills, as a proxy for AI adoption. We find that growth in the demand for ML skills has a direct negative impact on the total number of vacancies posted by incumbent firms. Drawing on rich data on wage offers, we further find that growth in ML demand reduces wage offers for all but the lowest-paid roles.

We examine the role of market characteristics and timing in explaining observed heterogeneity in VAT pass-through. We first extend existing theory to characterize the roles of imperfect competition and product differentiation, then investigate these relationships empirically using a panel of 14 Eurozone countries between 1999 and 2013. We find important roles for product market regulation and product quality, and little impact of advance announcement of reforms. Our findings have important implications for policy-makers considering VAT rate adjustments, by illuminating which of the consumers or the producers would experience the brunt of a reform across different settings.

This paper exploits China’s accession to the WTO to investigate the propagation of a supply shock across the Indian production network. Consistent with a model of multi-product manufacturers gaining access to higher-quality components, a fall in input tariffs raises revenue, quality and prices whilst lowering quality-adjusted prices and the probability of product exit. Upgrading persists for at least ten years; at the peak in 2010, products with a 10% higher pre-accession input tariff, and hence a larger post-accession fall in tariffs, have 5.3% higher quality. This in turn raises quality further down the supply chain, with input-output linkages amplifying the one-step effect by up to 75%. These results highlight a potential beneficial impact of the ‘China shock’ in developing countries, namely supply-driven quality upgrading.

We examine the effects of robotization on developing countries, using a Ricardian framework and new firm-level robotization data from eleven developing countries. We find that robot adoption in advanced economies can benefit workers in developing countries through lower prices and increased demand for inputs – though with potential adverse effects in the transition, particularly for the least mobile workers. Continued Chinese subsidization of robots is likely to reduce China’s trade with OECD countries, while increasing that with developing countries – as China’s profile of comparative advantage increasingly aligns with the former. Larger and more globally-connected firms in developing countries are more likely to adopt robots, as they can afford the fixed costs of upgrading and value the resulting precision more highly. These firms expand post-adoption, increasing the competitive pressure on the smaller, less international firms in which those workers most vulnerable to replacement by robots are also more likely to work.