<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Alex Martin | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/alex-martin/</link><description>Alex Martin</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/alex-martin/index.xml" rel="self" type="application/rss+xml"/><item><title>The Role of US Monetary Policy in Banking Crises Across the World</title><link>https://macropaperwarehouse.com/papers/the-role-of-us-monetary-policy-in-banking-crises-across-the-world/</link><guid>https://macropaperwarehouse.com/papers/the-role-of-us-monetary-policy-in-banking-crises-across-the-world/</guid><description>&lt;p&gt;The historical record suggests US monetary tightening is dangerous for banks elsewhere &amp;ndash; the early-1980s international debt crises followed the 1980-82 Volcker tightening, the Mexican Peso Crisis followed the 1994 Greenspan tightening &amp;ndash; and this paper asks whether that danger is uniform or conditional. Its answer is that it is conditional, and on a specific thing: whether a country&amp;rsquo;s exposure to the United States is &lt;em&gt;direct&lt;/em&gt;. Using an annual unbalanced panel of 69 countries (24 developed, 45 emerging) spanning 1870 to 2010, with systemic banking crises taken from Reinhart and Rogoff (2009) and yielding 239 distinct crisis starts, the authors estimate panel logit regressions in which the change in US short-term interest rates enters only through interactions with exposure measures &amp;ndash; necessarily so, since a US variable that does not vary by country would be collinear with the time fixed effects. Direct exposure is measured by a country&amp;rsquo;s bilateral trade intensity with the United States, and for the post-1990 sample by its dollar-denominated debt liabilities net of assets; indirect exposure by overall trade openness and the Chinn-Ito capital account openness index. Both trade measures are also instrumented with gravity estimates built from distance, population, common language, borders, land area, landlocked status and colonial history, following Frankel and Romer (1999). For directly exposed countries the interaction is positive and significant, and economically meaningful: &amp;ldquo;a 1 % tightening in monetary policy increases the probability of a crisis by 1.0-6.8% for a given level of direct exposure to the United States.&amp;rdquo; For countries that are merely globally integrated the effect is ambiguous &amp;ndash; the contemporaneous trade-openness interaction is actually negative and significant, which the authors read as openness providing diversification, those countries receiving funds flowing out of the directly exposed ones, or a more orderly reversal helping to correct accumulated imbalances &amp;ndash; and &amp;ldquo;the impact diminishes when we correct for the endogeneity.&amp;rdquo; The channel is capital flows, and the paper adjudicates between two opposing possibilities: a tightening might lean against the wind and curb credit booms that would otherwise end in crisis, or it might trigger a sudden reversal of flows. &amp;ldquo;We find evidence that the latter effect dominates&amp;rdquo;: tightening significantly reduces portfolio flows to countries with direct US exposure but not to merely open ones, and where the adjustment is disorderly the crisis probability rises. Splitting the sample, the effect &amp;ldquo;is mainly an emerging market phenomena&amp;rdquo; &amp;ndash; the interaction stays positive and significant in every subsample except the developed-country one. Results survive replacing the rate change with Gertler-Karadi, Rogers-Scotti-Wright and Romer-Romer shock series on the 1990-2010 window, OLS and probit estimation, adding local monetary policy and exchange rate changes, an alternative merged crisis database, and dropping the winsorization. The scope conditions are substantial: the exposure measures are themselves slow-moving country characteristics interacted with a common time-series shock, crises are rare events, and the baseline omits local monetary policy and exchange rates because including them shrinks the sample by three-quarters.&lt;/p&gt;</description></item></channel></rss>