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This entry pertains to the 7th IMF Annual Macro-Financial Research Conference. I was only able to attend the first day, and I summarize my reactions to each of the papers followed by some outstanding questions at the end.
Introduction
It was my first time back in DC since last year’s flyouts, and the contrast with New York was striking—DC feels calm in a way that makes you realize just how hectic NYC really is. (That said, the traffic lights in DC are far too long for my taste.)
I was there to discuss Divya Kirti’s paper, “The Insurer Channel of Monetary Policy,” which is squarely in my area of interest: the intersection of asset prices and insurance. You can find my discussion slides here, and below I detail some of other presentations that I could attend.
Session I: Restrictions to the Global Financial System
- Ken Teoh (IMF) presented “Redrawing the Landscape of Cross-Border Flow Restrictions: Modern Tools and Historical Perspectives,” co-authored with Katharina Bergant, Andres Fernandez, and Martin Uribe. They use machine learning and IMF’s comprehensive AREAER database to construct a granular historical dataset of cross-border restrictions since 1950, revealing five new stylized facts. Notably, high-income countries liberalized earlier and more extensively, suggesting potential benefits from early liberalization. They document a shift from quantity-based to persistent administrative controls, with outflow restrictions liberalizing faster than inflows—despite greater policy emphasis on inflow controls. Discussant Dennis Quinn (Georgetown) particularly praised the innovative use of data.
- William Witheridge (U of Maryland) presented “The Exchange Rate as an Industrial Policy,” examining how exchange rates can promote economic development. Discussant Martin Uribe (Columbia University) argued the paper is more accurately about capital controls, noting the exchange rate itself doesn't explicitly appear in the model equations. Witheridge clarified that exchange rates emerge endogenously, and the original title indeed reflected capital controls rather than exchange rates.
- Roberto Chang (Rutgers University) presented “Controls on Capital Outflows: New Evidence and a Theoretical Framework,” co-authored with Andrés Fernández and Humberto Martínez. The paper argues that capital controls on outflows (CCOs), when implemented during financial distress, can serve as beneficial coordination tools to prevent self-fulfilling crises caused by foreign investor panics. Discussant Kristin Forbes (MIT) connected this analysis to an older debate on this topic. There was one question from the audience, which I resonated with, on whether the paper's negative stance toward macroprudential policies was somewhat exaggerated given the static nature of their model.
Session II: Financial Globalization and Growth: Historical Lessons and Future Challenges
- Damien Capelle (IMF) presented “Unbalanced Financial Globalization,” co-authored with Bruno Pellegrino. The paper quantifies how financial globalization has unfolded unevenly—rich countries liberalized capital accounts much faster than poorer ones, exacerbating global capital misallocation. Contrary to standard models predicting efficiency gains, they show this imbalance has decreased global GDP by nearly 3%, widened income disparities between rich and poor countries, and shifted capital from lower-income to already capital-rich nations. Discussant Ernest Liu (Princeton) emphasized the delicate micro-foundations behind their rational-inattention-based logit demand system, arguing that obtaining their precise specification requires restrictive assumptions on priors.
- Ernest Liu (Princeton) presented “Neoclassical Growth in an Interdependent World,” co-authored with Benny Kleinman, Stephen Redding, and Motohiro Yogo. The paper generalizes the neoclassical growth model by incorporating frictions in trade and capital markets and imperfect substitutability across international goods and investments, making it quantitatively tractable and realistic. Discussant Tomas Williams (GWU) highlighted discrepancies between the model’s estimated elasticities and empirical estimates, questioning the model’s fit with real-world data.