Monetary Policy and Data Uncertainty: A Case Study of Distribution, Hotels and Catering Growth

This paper is a case study of the real world monetary policy data uncertainty problem. The initial and the latest release for growth rates of the distribution, hotels and catering sector are combined with official data on household income and two surveys in a state-space model. Though important to the UK economy, the distribution, hotels and catering sector is apparently difficult to measure. One finding is that the initial release data is not important in predicting the latest release. It could be that the statistical office develop the initial release as a building block towards the final release rather than an estimate of it. Indeed, there is multicollinearity between the initial release and the retail sales survey, which would then contain the same early available information. A second finding is that the estimate of the later release is sensitive to the estimate of the average historical growth rate. This means that establishing priors for this parameter and testing for shift structural breaks should be very important.Data Uncertainty; Distribution Sector; Kalman Filter; Monetary Policy

Inflation Targets as a Stabilisation Device

Over 80% of countries using explicit inflation targets in 2000 were doing so either as part of a disinflation strategy, or when inflation was neither low nor stable. Our illustrative theoretical model suggests annual revisions to short-run targets are endogenous to inflation outcomes during disinflation as long as the policymaker cares about misses from both the short-run target and a long-run target. Furthermore, target revisions will are larger when the target is undershot compared to when the target is overshot. We confirm the result using cross-country panel estimates from a unique data-set of inflation target misses in 60 countries in the 1990s. During disinflation it is therefore relatively difficult to separate decisions about target-setting from implementation. Short-term targets on a disinflation path may be more akin to conditional forecasts than policy rules, but their publication may nevertheless increase transparency and hence help policymakers to achieve lower inflation.

Unit Root Testing in a Central Bank

Central bank economists have to understand and forecast macroeconomic time series. A serious problem that they face is that those series are often trended or a.ected by persistent innovations to the process. To try to get round this problem, or at least to understand its possible e.ects, it is common to test whether series are stationary. These tests are often called unit-root tests.1 In this handbook we discuss such testing. A model-builder should use appropriate econometric techniques. In order to choose between alternative estimators, the model-builder needs to think carefully about the relevant theory and the available data. But economic theory is rarely unambiguous in its implications for the data generating process. Subjecting the data to pre-estimation testing can help to gauge the relevance of different theories and possible data problems.Unit, Root, Testing, Central Bank

Testing a DSGE model and its partner database

There is now an impetus to apply dynamic stochastic general equilibrium models to forecasting. But these models typically rely on purpose-built data, for example on tradable and nontradable sector outputs. How then do we know that the model will forecast well, in advance? We develop an early warning test of the database-model match and apply that to a Colombian model. Our test reveals where the combination should work (consumption) and where not (in investment). The test can be adapted to look at many likely sources of DSGE model failure.Monetary Policy, Sectoral Model, DSGE, Forecast Performance, Kalman Filter. Classification JEL: F47; E01; C61

Policy Analysis Tool Applied to Colombian Needs: PATACON Model Description

In this document we lay out the microeconomic foundations of a dynamic stochastic general equilibrium model designed to forecast and to advice monetary policy authorities in Colombia. The model is called Policy Analysis Tool Applied to Colombian Needs (PATACON). In companion documents we present other aspects of the model and its platform, including the estimation of the parameters that affect the dynamics and the impulse responses functions.Monetary Policy, DSGE, Small open economy. Classification JEL: E32, E52, F41.

Monetary Policy Forecasting in a DSGE Model with Data that is Uncertain, Unbalanced and About the Future

If theory-consistent models can ever hope to forecast well and to be useful for policy, they have to relate to data which though rich in information is uncertain, unbalanced and sometimes forecasts from external sources about the future path of other variables. One example from many is financial market data, which can help but only after smoothing out irrelevant short-term volatility. In this paper we propose combining different types of useful but awkward data set with a linearised forward-looking DSGE model through a Kalman Filter fixed-interval smoother to improve the utility of these models as policy tools. We apply this scheme to a model for Colombia.Monetary Policy, DSGE, Forecast, Kalman Filter Classification JEL: F47, E01, C61.

Modelling transmission mechanism of monetary policy in the Czech Republic

In December 1997, the Czech Republic became the first transitional economy to adopt an inflation-targeting (IT) framework. This paper addresses two important topics: optimal inflation-targeting horizon and optimal speed of disinflation. A small, aggregate, forward-looking model of the Czech monetary transmission was calibrated and estimated. Stochastic simulations were used to compare consequences of different forecast horizons and different targeted disinflation paths. Our first conclusion is that the optimal targeting horizon is probably less than a year. Secondly, postponing the initial disinflation does not imply significant gains in terms of lower output volatility or a smaller external imbalance.Inflation targeting, Transmission, transition, Simulations

The views are not necessarily those of the Bank of England or the interim Financial Policy Committee.

Peter Zimmerman for comments and contributions. All speeches are available online at www.bankofengland.co.uk/publications/speeches2 1

The Sectoral Effects of Exchange Rate Fluctuations – A Case Study of Colombia: OIES paper: SP 31

Nearly all countries whose exports are highly concentrated in fuel products fix their nominal exchange rate in order to protect the livelihoods of vulnerable workers in other sectors from exchange rate changes that could be caused by variations in international fuel prices. In this paper, we assess the impact that fuel price-induced exchange rate variability has on the different sectors of fuel-exporting countries, taking Colombia as a case-study. We document the rich variety of sectoral responses to an oil-price induced appreciation in Colombia and assess different solutions to underperforming sectors. Our analysis points to policies that improve the options available to workers in exposed sectors. We also suggest that there may be an additional need for sectoral countercyclical macroprudential tools – those that can be used to reduce lending only to non-tradable sectors – in times of fuel price-induced exchange rate appreciation. Examples of these tools are higher loan-to-value ratios and risk weights on mortgages, on the commercial retail sector, and on personal loans, together with regulatory capital ratios, sectoral liquidity buffers, or taxes on housing sales.</p