The COVID-19 crisis induced an unprecedented launch of unconventional monetary policy through asset purchase programs (APPs) by emerging market and developing economies. This paper presents a new dataset of APP announcements and implementation from March until August 2020 for 27 emerging markets and 8 small advanced economies. APPs' effects on bond yields, exchange rates, equities, and debt spreads are estimated using different methodologies. The results confirm that APPs were successful in

more »

... ificantly reducing bond yields in EMDEs, and these effects were stronger than those of policy rate cuts, suggesting that such UMP could be important tools for EMDEs during financial market stress. JEL Classification Numbers: E52, E58, E65, G12, G15 comments from the ED offices representing the countries in the sample. 2 All programs for EMs were newly announced during the COVID-19 crisis, except Indonesia, where it was an expansion of a pre-existing program. During and after the GFC, AEs introduced four main types of unconventional measures: (i) negative interest rate policies, (ii) lending operations or credit policies, where central banks expand their liquidity facilities to support credit flows to the private sector, (iii) large-scale asset purchase programs to address market dysfunctionalities that impaired the transmission channels of monetary policy and/or lower long term bond yields and ease broad financial conditions, and (iv) forward guidance. ©International Monetary Fund. Not for Redistribution sovereign bond yields than in AEs (Hartley and Rebucci (2020)), and that the effect on the exchange rate is relatively small or insignificant (International Monetary Fund (2020) ). Against this background, this paper first develops a novel and extensive database of APP announcements and implementation in EMDEs. The database aims at illustrating the recent experience with such UMP schemes in EMDEs, including their objectives and modalities, and at helping to draw some initial lessons from these policy experiments. Specifically, the database contains recent COVID19-related UMP measures for 27 EMDEs, highlighting different characteristics including: (i) the nature of the program-purpose, size, targeted market, etc.; (ii) whether the announcement were made jointly with other authorities or coincided with other central bank policy announcements; and (iii) transactions data where publicly available. The same information is also collected for 8 small AEs, for comparison. The information collected in the database on UMP suggests that a number of countries carried out several APPs during the period under consideration (January-August 2020), or tweaked their programs, with programs exhibiting different characteristics depending on the objective. Most of the interventions aimed at boosting confidence and improving market functioning, and targeted the government bond market, although a few countries (BEAC, Brazil, Chile, Ethiopia, Hungary, Israel, Korea, Mauritius, and Norway) aimed at the corporate or bank bond market. Egypt is the only country that purchased equities. The size of the programs in EMDEs was comparable to that of AEs in our sample. About two thirds of these programs were quantity-based (fixed or maximum amount of purchases). Examples and Thailand. Other programs were also quantity-based, but more flexible, with purchase amounts calibrated to market conditions and/or the economic and inflation outlook (e.g., Angola, Canada, Colombia, Costa Rica, and Hungary). Except for Chile (price-based APP targeting bank bonds), none of the programs were price-based. Building and expanding on existing studies, we use the database to empirically analyze the effects of these APPs on financial market variables for 15 emerging markets and 8 small AEs. First, we look at the distribution of sovereign bond yields and exchange rates, following previous studies; and also at the distribution of equity prices, corporate bond yields, and EMBI spreads. For each variable and country, we investigate whether there is a different impact response one, two, and three days following announcements. These effects are also estimated for conventional monetary policy actions for comparison. Second, we use countryspecific regressions to investigate whether other policies announced at the same time as the APP, external factors, and the COVID-19 pandemic's impact on activity alter the impact of the announcements. The results help us identify the main channels of impact as well as whether the effect of UMP is different from that of conventional policy easing. Finally, we test whether the main findings hold when we employ a panel regression, controlling for various factors. The analysis covers the