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This is the second chapter of a forthcoming monograph entitled "On Implementing Full-Fledged Inflation-Targeting Regimes: Saying What You Do and Doing What You Say." We begin by discussing the costs of inflation, including their role in generating boom-bust cycles. Following a general discussion of the need for a nominal anchor, we describe a specific type of monetary anchor, the inflation-targeting regime, and its two key intellectual roots-the absence of long-run trade-offs and the time-inconsistency problem. We conclude by providing a brief introduction to the way in which inflation targeting works.
This paper presents the theoretical structure of MAPMOD, a new IMF model designed to study vulnerabilities associated with excessive credit expansions, and to support macroprudential policy analysis. In MAPMOD, bank loans create purchasing power that facilitates adjustments in the real economy. But excessively large and risky loans can impair balance sheets and sow the seeds of a financial crisis. Banks respond to losses through higher spreads and rapid credit cutbacks, with adverse effects for the real economy. These features allow the model to capture the basic facts of financial cycles. A companion paper studies the simulation properties of MAPMOD.
Contributors working at the International Monetary Fund present 14 chapters on the development of monetary policy over the past quarter century through the lens of the evolution of inflation-forecast targeting. They describe the principles and practices of inflation-forecast targeting, including managing expectations, the implementation of a forecasting and policy analysis system, monetary operations, monetary policy and financial stability, financial conditions, and transparency and communications; aspects of inflation-forecast targeting in Canada, the Czech Republic, India, and the US; and monetary policy challenges faced by low-income countries and how inflation-forecast targeting can provide an anchor in countries with different economic structures and circumstances.
This paper presents a new version of MAPMOD (Mark II) to study the effectiveness of macroprudential regulations. We extend the original model by explicitly modeling the housing market. We show how household demand for housing, house prices, and bank mortgages are intertwined in what we call a deadly embrace. Without macroprudential policies, this deadly embrace naturally leads to housing boom and bust cycles, which can be very costly for the economy, as shown by the Global Financial Crisis of 2008-09.
This note provides guidance to facilitate the staff’s advice on macroprudential policy in Fund surveillance. It elaborates on the principles set out in the “Key Aspects of Macroprudential Policy,” taking into account the work of international standard setters as well as the evolving country experience with macroprudential policy. The main note is accompanied by supplements offering Detailed Guidance on Instruments and Considerations for Low Income Countries
Many central banks in emerging and advanced economies have adopted an inflation-forecast targeting (IFT) approach to monetary policy, in order to successfully establish a stable, low-inflation environment. To support policy making, each has developed a structured system of forecasting and policy analysis appropriate to its needs. A common component is a model-based forecast with an endogenous policy interest rate path. The approach is characterized, among other things, by transparent communications—some IFT central banks go so far as to publish their policy interest rate projection. Some elements of this regime, although a work still in progress, are worthy of consideration by central banks that have not yet officially adopted full-fledged inflation targeting.
Inflation targeting (IT) serves as monetary policy framework in several advanced economies, where it has enhanced policy transparency and accountability. The paper considers its wider applicability to developing countries. The prerequisites for a successful IT framework are identified as an ability to carry out an independent monetary policy (free of fiscal dominance or commitment to another nominal anchor, like the exchange rate) and a quantitative framework linking policy instruments to inflation. These prerequisites are largely absent among developing countries, though several of them could with some further institutional changes and an overriding commitment to low inflation make use of an IT framework.
Yes, it makes a lot of sense. This paper studies how to design simple loss functions for central banks, as parsimonious approximations to social welfare. We show, both analytically and quantitatively, that simple loss functions should feature a high weight on measures of economic activity, sometimes even larger than the weight on inflation. Two main factors drive our result. First, stabilizing economic activity also stabilizes other welfare relevant variables. Second, the estimated model features mitigated inflation distortions due to a low elasticity of substitution between monopolistic goods and a low interest rate sensitivity of demand. The result holds up in the presence of measurement errors, with large shocks that generate a trade-off between stabilizing inflation and resource utilization, and also when ensuring a low probability of hitting the zero lower bound on interest rates.
Governments issue debt for good and bad reasons. While the good reasons—intertemporal tax-smoothing, fiscal stimulus, and asset management—can explain some of the increases in public debt in recent years, they cannot account for all of the observed changes. Bad reasons for borrowing are driven by political failures associated with intergenerational transfers, strategic manipulation, and common pool problems. These political failures are a major cause of overborrowing though budgetary institutions and fiscal rules can play a role in mitigating governments’ tendencies to overborrow. While it is difficult to establish a clear causal link from high public debt to low output growth, it is likely that some countries pay a price—in terms of lower growth and greater output volatility—for excessive debt accumulation.