Research

I study how industrial policy shapes innovation by examining China's Strategic and Emerging Industries (SEI) initiative (2010-2018), a large-scale fiscal intervention targeting frontier technology sectors. Employing a staggered difference-in-differences design with city-industry-level patent data, I uncover three key findings: (1) While patent quantity surged by 184%, quality metrics showed minimal improvement; (2) The quantity gains came at a 14% decrease in patent output from untreated sectors, revealing sectoral displacement instead of crowd-in effects; (3) Cities that adopted path-dependent targeting (selecting sectors with pre-existing innovation advantages) achieved over twice the patent growth rates of their counterparts, yet the persistent stagnation in quality metrics exposes its scaling trap. These findings reveal a paradox in China's development model: while achieving unprecedented success in scaling innovation quantity, the nation has yet to realize comparable quality gains - a critical gap as it transitions from 'made' to 'created in China'.

Presented at: NIE Symposium 2025 (Nottingham); RES 2025 Annual Conference (University of Birmingham); EAYE Annual Meeting 2025 (KCL); Asian Economic Development Conference (Peking University); 58th ADB Annual Meeting (Milan); BOFIT Seminar (Bank of Finland); 2024 Junior Research Day (UCL); SSEES Seminar (UCL); 2024 CJRSE (Cambridge University); 2024 Chinese Economist Society Annual Conference (Zhejiang University); 2024 Chinese Economic Association Conference (London); CSAE Research Workshop (Oxford University); 2024 RECA Conference (London); Sapienza University PhD Seminar

This study examines the role of multinational firms and global value chain linkages in the cross-country diffusion of emerging technologies. The analysis combines detailed information on the near-universe of online job postings in 17 countries with data on multinational networks and firm-to-firm linkages from 2014 to 2022. Online job postings are utilized to investigate how jobs related to emerging technologies spread through firm networks. The findings show that emerging technology jobs are highly concentrated within multinational firms and their supply chains. Approximately one third of all emerging technology job postings during this period come from Fortune 500 firms, their affiliates, buyers, suppliers, or innovation partners. Although the locations where these technologies originate exhibit a higher prevalence of technology job openings, this advantage diminishes over time as diffusion accelerates in wealthier and geographically closer countries and regions. The study highlights the significant role of firm-to-firm linkages in technology diffusion, with some linkages proving more influential than others. Firms that were previously buyers or innovation partners of establishments in technology-originating locations experienced faster growth in jobs related to these technologies. Moreover, relationships outside corporate boundaries play a particularly critical role, and these connections are influential beyond the factor of geographical distance.

Presented at: 2024 Jobs and Development Conference (Cairo); 2024 Trade and Uneven Development Conference* (Washington DC); 2024 CatChain Symposium* (Maastricht)

(* presented by coauthor)

We investigate whether turmoil in the oil market leads to gender-differentiated labor market outcomes. Acknowledging the persistent and pervasive gender gaps in the labor market, we argue that male and female workers might bear the cost of higher oil prices differently. Exploiting data on employment, unemployment, and labor force participation rates by gender, we use a panel of 101 countries from 1975 to 2022, high-frequency oil shock identification, and local projections to test our hypothesis. We reveal a complex picture: while men tend to experience more immediate job losses in response to oil market fluctuations, they also exhibit a faster recovery. In contrast, women endure a sustained drop in employment, emphasizing the persistent challenges they face. We then uncover two primary factors driving the heterogeneity of the shock impact. First, female workers from oil-importing countries face more prolonged job loss compared to male workers. Second, oil-dependent industries such as mining and construction see growing gender inequality, while the more energy-efficient industries such as agriculture and retail manifest narrowing gender gaps. These nuanced findings have significant distributional ramifications, particularly in light of the recent, excruciating rise in energy prices. Our empirical validation survives a broad set of robustness checks. 

Presented at: IMF Gender Working Group Seminar; IMF Working Paper Series Seminar (Washington DC)

China’s green transition is among the most ambitious state-led attempts to align climate goals with technological leadership. This paper first catalogs major green policy initiatives launched since the early 2000s, including emissions targets, financing mechanisms, and industrial subsidies that elevated China into a green innovation powerhouse. Building on this overview, I then examine the effects of the Strategic Emerging Industries (SEI) initiative on green innovation through an event study with city-industry level patent data. I uncover two critical divergences: first, while targeted green sectors experienced explosive growth in innovation scale, equally prioritized non-green sectors gained only half as much. Second, innovation quality stagnated across all sectors despite quantity surges. While existing literature credits China’s green innovation boom to infrastructure and global value chains, this study calls for policy recalibration toward rewarding innovation quality for sustained green transformation.

We investigate the effect of intra-firm gender disparities on innovation using a unique longitudinal dataset of UK companies from 1996 to 2019. Utilizing within-industry and within-firm variation, we examine the relationship between gender pay gaps and diversity and patenting activities. Our findings indicate that gender parity does not negatively impact innovation. Moreover, in some specifications, we uncover evidence suggesting that a wider gender pay gap adversely affects both the quantity and quality of patents. However, the impact of gender imbalance is nuanced, varying according to the pay grade positions occupied by female employees.

Presented at:  2024 SITES-GLO (Naples); 2023 EALE*(Prague)

(* presented by coauthor)

Artificial Intelligence (AI) is widely viewed as the defining technology of our time, but its diffusion remains uneven and poorly understood. This paper examines how AI diffuses differently from other frontier technologies. Using job posting data from 17 countries between 2014 and 2022, we compare AI to 28 emerging technologies tracked by Bastos et al. (2024), and infer AI diffusion when firms post jobs containing AI-related keywords. We identify four key departures from typical technology diffusion patterns. First, AI adoption has been more spatially dispersed from the outset, particularly within countries. Second, national income explains more of the cross-country variation in AI adoption than it does for other technologies. Third, distance to AI pioneers poses less of a barrier for AI diffusion across countries but matters more across firms. Finally, multinational firm linkages appear less effective in spreading AI than for other technologies. These patterns reflect features of AI highlighted in the literature - its open-source foundations, relatively recent emergence, and reliance on tacit capabilities rather than tradable inputs.