We estimate the impact of distinct types of slowdowns in China on countries and firms globally. We combine a structural vector autoregression framework with a broad-based measure of domestic economic activity in China to distinguish supply versus demand components of Chinese growth. We then use local projection models to assess the responses to such shocks of GDP growth (revenue) in other countries (firms). We find that both supply and demand slowdowns are associated with substantial declines in partner GDP and firm revenue, which are larger in countries and firms with stronger trade links to China, but the relative magnitudes depend on the level of aggregation.

We investigate the role of digitalization in mitigating post-recession scarring. Using balance sheet data from 24,000 firms in 75 countries, we find that firms in industries that are one standard deviation more digitalized than average experience 2% less scarring across recessions since 2001. Early data since the outbreak of the COVID-19 pandemic suggest an even larger mitigation effect during the resulting recessions. Using information from LinkedIn profiles, we also find that more digitalized industries experienced 4% higher hiring rates and higher net inflows. These results are robust across a wide range of digitalization measures – drawing on ICT input and employment shares, robot usage, online sales, intangible assets and digital skills listed on online profiles – and several alternative specifications.

This paper studies variation in crypto markets globally, their interaction with equity markets, and their response to US monetary policy. We first identify a single “crypto factor” that explains 80% of variation in crypto prices. Second, we show that the increasing correlation between crypto and global equity markets can be explained by the entry of institutional investors into crypto markets. Third, we find that a monetary contraction reduces the crypto factor, and by substantially more than for global equities, possibly due to the increased cost of leverage reducing the risk appetite of the marginal investor. We formalize our findings in a model with heterogeneous agents and time-varying aggregate effective risk aversion.

We document near-exponential growth in the demand for artificial intelligence (AI)-related skills in India’s services sector since 2016, using a new dataset of online vacancies from its largest jobs website. This coincides with the take-off in developed countries, and is driven by the largest firms and high-tech clusters. We evaluate the impact of demand for AI skills on establishment-level non-AI postings, using a shift-share design that exploits variation in exposure to new AI inventions. We find negative effects on posting volumes and wage offers, particularly for highly skilled managerial and professional occupations, non-routine work, and analytical and communication tasks.

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.

We construct daily databases of crypto bans and policy statements concerning central bank digital currencies (CBDCs) to estimate their effects on crypto trading volumes for an unbalanced panel of 116 countries from November 2016 to December 2021. We find that trading volume falls by up to 55% in the week after the announcement of a ban, and by up to 25% after a CBDC-supportive speech by senior central bank officials. For the strictest bans, this reduction persists over the subsequent quarter, driven by a reduction in trading by institutional investors. The results suggest that crypto market participants pay significant attention to government policy on digital assets.

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.