Published Book Chapter

• Yu, J. and Cao, W. (2024) ‘China’s strategic interest in Guyana’s oil: Present engagement and future outlook’. In: Mair, J. and Beck, A. (eds.) Oil Dorado, Edition 7 (2025 Edition). 

Publication

• Yu, J. (2022) ‘The effects of COVID-19 on the labor market’, Journal of Economics, Business and Management, 10(1), pp. 65–71. doi:10.18178/joebm.2022.10.1.675. 

Work in Progress 

• Pre-Grant Patents and Innovation Diffusion [Working Paper] [Slides]

  • Abstract: Are pre-grant patents effective forward-looking signals of global innovation diffusion? Patent grants are important legal milestones, but information diffusion about the underlying technologies occurs at the time patents are published. As the innovation literature rarely studies this distinction, I address this question using pre-grant patent flows across countries, sectors, and industries over time. This allows me to separately identify timing effects on diffusion and those that are running through either innovation or trade channels. At country level, results show that the innovation channel creates larger and more persistent total factor productivity (TFP) gains and stock price responses. This confirms that international technology spillovers originate from the expansion of the global stock of knowledge rather than strategic changes in trade intensity between home countries and their partners. A one–standard-deviation foreign pre-grant patent shock raises manufacturing-sector TFP by about 0.28%, and the R&D capital stock rises by roughly 0.18% with a one-year delay. This reflects their forward-looking nature, which prompts resource reallocation in anticipation of future productivity gains. These gains are especially pronounced in countries which manufacturing sectors that are more R&D-intensive. At the industry level, countries with more value-added–intensive industries are more capable of generating internationally influential frontier innovations and exhibit larger labour productivity gains. 

  • Presented at: ESCoE Conference on Economic Measurement (2026); IEA World Congress (2026); 32nd Conference on Computing in Economics and Finance (2026) ; 33rd Symposium of the Society for Nonlinear Dynamics and Econometrics (2026); Annual Conference of Scottich Economic Society (2026); European Regional Science Association (ERSA) British & Irish Section, 4th annual Online Early Career Colloquium (2026); CMA-Durham Workshop (2025); RSA Regional Futures Conference (2025); National Institute of Economic and Social Research Brown Bag Seminar (2025); Lancaster University Macro Reading Group (2025); PhD-Economic Virtual Seminar Job Market Paper Series (2025); Lancaster University Department of Economics Internal Seminar (2025); Macroeconomics Research Unit Seminar Series, University of Kwazulu-Natal (2025); NWSSDTP PhD Conference, University of Manchester (2025); 

• Global Tehnology Shocks and Labor Dynamics: Aggregate and Sectoral Evidence from OECD Countries [Slides] [Presentation - from 1:31:34]

  • Abstract: To what extent does trade facilitate gains from technology diffusion and productivity gains across countries? Using panel local projection, this study examines the aggregate and sectoral diffusion of global technology shocks across 18 OECD countries from 1971 to 2015. To capture the diffusion of global technology shocks beyond traditional domestic TFP measures, I construct World Total Factor Productivity (WTFP)  as an exogenous measure through import-weighted average of trade partners' utilization-adjusted TFP changes. In the short run, global technology shocks diffuse through traded sectors and boost foreign demand and prices for domestic traded goods. This incentivizes firms to expand output and hire more workers along with increase in total hours worked and TFP for long term productivity growth. Over time, global technology shocks create more jobs along with permanent increase in output, domestic TFP with lower hours worked. Borrowing capacity and labor mobility reflects the cross-country heterogeneity in the global technology diffusion: countries with greater external borrowing capacity rely more on imports to meet rising demand while those with higher mobility of labor forces facilitate faster sectoral reallocation and more efficient uptake of productivity gains. In light of recent trade tensions, these findings highlight the importance of maintaining open trade networks to make the most of the global technology diffusion for future productivity growth and labor market resilience. 

  • Presented at: LSE-Miguel Dols Fellows' Workshop Spring 2024-5; Durham University Business School Doctoral Conference: AI and Digital Technologies in Business (2025); MMF PhD Conference (2025); Lancaster Workshop on Empirical and Theoretical Macroeconomics (2025); Lancaster University Graduate College PGR Seminar (2024, 2025); Lancaster University PhD Economics Seminar series (2025); PhD-EVS seminar series (2023, 2024); RGS Doctoral Conference in Economics (2024); RES Easter Training School (2024); NWSSDTP PhD Conference (2024); Lancaster University Macro Reading Group (2023).

• Selecting Relevant Factors in Stock Option Returns — with Boen Liang (University of York)

  • Abstract: This paper investigates which characteristics and option-based factors are most relevant in explaining the cross-section of delta-hedged equity option returns. Motivated by the growing literature on the "factor zoo" in asset pricing, we extend the inquiry to the stock options market, which remains under-explored due to complexities such as short maturities, dynamic moneyness, and limited data availability. Using a large panel of U.S. equity options from 1996 to 2022, we construct 10x10 double-sorted option portfolios based on 19 option characteristics. To identify relevant factors, we employ the sequential elimination method (SEM), informed by the RBIC rank estimator, which can select option factors when N ≤  T/2. Our results highlight a small set of robust factors— particularly idiosyncratic volatility (IVOL) and cash-flow variance (CFV)-that consistently explain option return variation across specifications and time periods. IVOL emerges as the most relevant factor overall.