This paper uses the Growth-at-Risk (GaR) methodology to examine how macrofinancial conditions affect the growth outlook and its probability distribution. Using this approach, we evaluate risks to GDP growth in the Dominican Republic using quarterly data for 1996-2018. We group macrofinancial conditions in five principal determinants, based on 32 indicators. The Dominican Republic’s growth distribution appears most vulnerable to negative shocks to domestic financial conditions, domestic leverage, domestic demand, and external demand, with additional repercussions from the external cost of borrowing in the longer run. Our findings show that domestic monetary policy plays a particularly important role in reducing growth vulnerabilities when the economy is weak.
Mr. Tobias Adrian, Mr. Dong He, Nellie Liang, and Mr. Fabio M Natalucci
This paper describes the conceptual framework that guides assessments of financial stability risks for multilateral surveillance, as currently presented in the Global Financial Stability Report (GFSR). The framework emphasizes consistency in measuring financial vulnerabilities across countries and over time and offers a summary statistic to quantify aggregate financial stability risks. The two parts of the empirical approach—a matrix of specific vulnerabilities and a summary measure of financial stability risks—are distinct but highly complementary for monitoring and policymaking.
Mr. Ananthakrishnan Prasad, Mr. Selim A Elekdag, Mr. Phakawa Jeasakul, Romain Lafarguette, Mr. Adrian Alter, Alan Xiaochen Feng, and Changchun Wang
The growth-at-risk (GaR) framework links current macrofinancial conditions to the distribution of future growth. Its main strength is its ability to assess the entire distribution of future GDP growth (in contrast to point forecasts), quantify macrofinancial risks in terms of growth, and monitor the evolution of risks to economic activity over time. By using GaR analysis, policymakers can quantify the likelihood of risk scenarios, which would serve as a basis for preemptive action. This paper offers practical guidance on how to conduct GaR analysis and draws lessons from country case studies. It also discusses an Excel-based GaR tool developed to support the IMF’s bilateral surveillance efforts.
Mr. Tobias Adrian, Federico Grinberg, Nellie Liang, and Sheheryar Malik
Using panel quantile regressions for 11 advanced and 10 emerging market economies, we show that the conditional distribution of GDP growth depends on financial conditions, with growth-at-risk (GaR)—defined as growth at the lower 5th percentile—more responsive than the median or upper percentiles. In addition, the term structure of GaR features an intertemporal tradeoff: GaR is higher in the short run; but lower in the medium run when initial financial conditions are loose relative to typical levels, and the tradeoff is amplified by a credit boom. This shift in the growth distribution generally is not incorporated when solving dynamic stochastic general equilibrium models with macrofinancial linkages, which suggests downside risks to GDP growth are systematically underestimated.
Mr. John C Bluedorn, Rupa Duttagupta, Mr. Jaime Guajardo, and Miss Nkunde Mwase
Growth takeoffs in developing economies have rebounded in the past two decades. Although recent takeoffs have lasted longer than takeoffs before the 1990s, a key question is whether they could unravel like some did in the past. This paper finds that recent takeoffs are associated with stronger economic conditions, such as lower post-takeoff debt and inflation levels; more competitive real exchange rates; and better structural reforms and institutions. The chances of starting a takeoff in the 2000s was triple that before the 1990s, with domestic conditions accounting for most of the increase. The findings suggest that if today’s dynamic developing economies sustain their improved policies; they are more likely to stay on course compared to many of their predecessors.
This paper investigates the relationship between inflation and long-run growth. It presents an endogenous growth model that illustrates the channels through which inflation affects growth. The model highlights the effects of inflation on the productivity of capital and the rate of capital accumulation. The reduction in growth is caused by a diversion of resources away from activities that lead to faster rates of growth toward activities associated with reducing the costs of inflation. The negative association between inflation and growth is assessed empirically for a sample group of Latin American countries.