Research

So-called “connector” countries have been argued to bridge trade between China and the United States. We distinguish trade reallocation—domestic production substituting for Chinese exports to the United States—from trade rerouting—Chinese exports transiting with minimal domestic processing—and show in a conceptual framework that the two leave opposite signatures in the domestic and Chinese valueadded shares of a country’s exports. Taking this framework to the data through a synthetic control approach applied to six Asian economies, we find evidence of trade reallocation in Vietnam: domestic value added in its strategic-sector exports to the United States rose over 2018–23, with no evidence of significant rerouting. The reallocation also coincided with increased greenfield FDI by firms from China, consistent with the relocation of production capacity to Vietnam.

Using a small open economy overlapping generations model, this paper examines how AI can drive economic divergence across and within Asian economies. While AI adoption may promise sizable productivity gains, it could create temporary but potentially longlasting divergence across countries. Structurally-prepared advanced economies tend to adopt AI earlier and see immediate growth gains while emerging markets and developing economies (EMDEs) face delayed adoption and initial growth headwinds from rising costs of capital. Structural reforms that boost productivity and strengthen human capital not only accelerate adoption in EMDEs but also amplify the growth gains. Within countries, AI adoption could widen inequality along multiple dimensions: across skill groups, as high-skilled workers benefit disproportionately from complementarity with the more capital-intensive technology, and across generation, as the shift of national income toward capital favors asset-rich older households relative to younger workers who rely primarily on labor income. Redistributive policies can help mitigate these distributional pressures, though they entail equity efficiency trade-offs that vary with country-specific fiscal and demographic conditions.

This paper provides a first comprehensive assessment of industrial policy (IP) across Asia‑Pacific and its potential to enable structural transformation. Building an IP database for 2009–2024, paired with a rich dataset, the paper documents a large wave of IP interventions. Subsidies dominate, followed by import-limiting measures. Novel applications of machine‑learning and clustering approaches to assess IP targeting suggest that, ex-ante, about three-quarters of IP could align with structural transformation strategies, including relatively safe (“safe-bets”) and risky (“moonshots”) strategies promoting technological upgrading and diversification, and strategies to alleviate market‑frictions and distortions in key sectoral nodes. IP’s ex-post linkages to trade, competitiveness, and domestic firms’ indicators are small and short‑lived; sustained gains that could lead into structural transformation appear only sporadically. Our findings underscore the need for a more parsimonious and carefully‑designed IP—anchored to targeting clear market‑failure rationales and complemented by ambitious structural reforms—potentially enhancing effectiveness and lowering net costs.

This paper investigates the role of cross-border investments, including by Sovereign Wealth Funds (SWFs), in driving economic growth and diversification of Gulf Cooperation Council (GCC) countries. Utilizing novel deal-level datasets, we analyze GCC cross-border investment portfolios across various dimensions such as time, geography, and industry. We show that recent years have witnessed an increase in GCC cross-border investments. While the geographic distribution of these investments remains diverse and balanced across different regions, both inward and outward investments are increasingly directed towards the services sector. The empirical results demonstrate a significant positive relationship between both cross-border inward and domestic investments on GCC real non-hydrocarbon GDP. Notably, the medium-term increase in real non-hydrocarbon GDP resulting from inward investments is three times larger than that from domestic investments. This amplification could be explained by increased inward investments in high-growth services sectors. Although domestic investments, including by SWFs, are contributing to the GCC economic transformation, their efficiency could be further enhanced by focusing on strategic partnerships with international investors and fostering a more transparent and competitive business environment. Recent shift in GCC investments in renewable and clean energy projects will further support diversification efforts.

The Middle East (ME) is often perceived as region with rentier economies and uncompetitive markets. Evidence of market power in the region however is scant. In this paper, we ask the following three questions: Is the ME uniquely uncompetitive? Has the evolution of market power in the region traced the global rise in market power? What government policies and actions influenced the market power in the region and can taxes be a way to even the playing field? To answer these questions, we utilize comprehensive firm-level data from Compustat between 2004 and 2022 and employ two methods for estimating markups (production function and cost-share approach). We document that market power among listed firms in the ME is higher than in the US, but on a downward trend. We find that the value-added tax (VAT) reforms introduced by some Gulf states from 2018 to 2022 resulted in a reduction of market power, an additional benefit beyond increasing fiscal space. While policymakers should continue to use available regulatory levers to achieve economic efficiency and a level playing field, VAT could be considered as an alternative instrument.

This paper explores Asia-Pacific's medium-term growth prospects using two approaches. First, growth accounting analysis and machine-learning estimation reveal how demographics, capital deepening, productivity, and human capital shaped Asia's growth. Second, an innovative algorithm forecasts growth by matching countries' current conditions with historically analogous periods using Dynamic Time Warping (DTW). Comparing pattern-based forecasts with traditional projections highlights economic convergence and demographic headwinds. Results show that without ambitious reforms, Asia's growth will likely moderate, though remaining the world's fastest growing region. The paper offers data-driven tools for policymakers to identify growth drivers and generate robust forecasts.

​The paper explores the drivers of political fragility by focusing on coups d’état as symptomatic of such fragility. It uses event studies to identify factors that exhibit significantly different dynamics in the runup to coups, and machine learning to identify these stressors and more structural determinants of fragility—as well as their nonlinear interactions—that create an environment propitious to coups. The paper finds that the destabilization of a country’s economic, political or security environment—such as low growth, high inflation, weak external positions, political instability and conflict—set the stage for a higher likelihood of coups, with overlapping stressors amplifying each other. These stressors are more likely to lead to breakdowns in political systems when demographic pressures and underlying structural weaknesses (especially poverty, exclusion, and weak governance) are present or when policies are weaker, through complex interactions. Conversely, strengthened fundamentals and macropolicies have higher returns in structurally fragile environments in terms of staving off political breakdowns, suggesting that continued engagement by multilateral institutions and donors in fragile situations is likely to yield particularly high dividends. The model performs well in predicting coups out of sample, having predicted a high probability of most 2020-23 coups, including in the Sahel region. 

We empirically examine U.S. monetary policy spillovers to the Middle East and Central Asia (ME & CA) region by decomposing U.S. interest rates changes into two orthogonal shocks: the pure monetary policy shock and the information news shock. Using a sample of 16 ME & CA countries, we find that when interest rates increase, the two shocks have opposite spillovers on the region. Tightening driven by contractionary monetary policy shocks hinders growth, while tightening driven by positive information news shocks boosts growth despite higher interest rates. Countries with weaker fundamentals face more negative spillovers from contractionary monetary policy shocks but may sometimes benefit more from positive information news shocks. Moreover, high oil prices mitigate both spillovers for oil exporters while global risk appetite amplifies both spillovers. Finally, we estimate a large degree of heterogeneity in the impact of the 2022 U.S. tightening cycle on ME & CA countries, with oil exporters with stronger fundamentals withstanding well the shock and oil importers with weaker fundamentals being hit the most. 

This paper investigates the link between crisis risk estimation and crisis prevention policy in the context of sudden stops with growth impacts. We propose a two-stage framework that embeds an early-warning problem into a policy-making problem, and conduct a welfare analysis of crisis risk estimation based on subsequent policy responses. Building upon this two-stage framework, we show that there is welfare cost asymmetry between two types of errors: the welfare-maximizing weight on the missed crises is greater than that on the  false alarms. This paper introduces a constrained optimization problem under the Neyman-Pearson paradigm to solve this error-asymmetry problem, and conducts backtesting with multiple algorithms under this paradigm with asymmetry-warranted evaluation metric. Bringing this welfare-based two-stage framework to emerging market countries' data, we uncover the time-varying risk tolerance of policymakers.