We apply a range of models to the U.K. data to obtain estimates of the output gap. A structural VAR with an appropriate identification strategy provides improved estimates of output gap with better real time properties and lower sensitivity to temporary shocks than the usual filtering techniques. It also produces smaller out-of-sample forecast errors for inflation. At the same time, however, our results suggest caution in basing policy decisions on output gap estimates.
We revisit the conventional view that output fluctuates around a stable trend by analyzing professional long-term forecasts for 38 advanced and emerging market economies. If transitory deviations around a trend dominate output fluctuations, then forecasters should not change their long-term output level forecasts following an unexpected change in current period output. By contrast, an analysis of Consensus Economics forecasts since 1989 suggest that output forecasts are super-persistent—an unexpected 1 percent upward revision in current period output typically translates into a revision of ten year-ahead forecasted output by about 2 percent in both advanced and emerging markets. Drawing upon evidence from the behavior of forecast errors, the persistence of actual output is typically weaker than forecasters expect, but still consistent with output shocks normally having large and permanent level effects.
Bin Grace Li, Mr. Stephen A. O'Connell, Mr. Christopher S Adam, Mr. Andrew Berg, and Mr. Peter J Montiel
VAR methods suggest that the monetary transmission mechanism may be weak and unreliable in
low-income countries (LICs). But are structural VARs identified via short-run restrictions capable
of detecting a transmission mechanism when one exists, under research conditions typical of these
countries? Using small DSGEs as data-generating processes, we assess the impact on VAR-based
inference of short data samples, measurement error, high-frequency supply shocks, and other
features of the LIC environment. The impact of these features on finite-sample bias appears to be
relatively modest when identification is valid—a strong caveat, especially in LICs. However,
many of these features undermine the precision of estimated impulse responses to monetary policy
shocks, and cumulatively they suggest that “insignificant” results can be expected even when the
underlying transmission mechanism is strong.
Anh D. M. Nguyen, Mr. Jemma Dridi, Ms. Filiz D Unsal, and Mr. Oral Williams
The perception that inflation dynamics in Sub-Saharan Africa (SSA) are driven by supply shocks
implies a limited role for monetary policy in influencing inflation in the short run. SSA’s rapid
growth, its integration with the global economy, changes in the policy frameworks, among others,
in the last decade suggest that the drivers of inflation may have changed. We quantitatively
analyze inflation dynamics in SSA using a Global VAR model, which incorporates trade and
financial linkages among economies, as well as the role of regional and global demand and
inflationary spillovers. We find that in the past 25 years, the main drivers of inflation have been
domestic supply shocks and shocks to exchange rate and monetary variables; but that, in recent
years, the contribution of these shocks to inflation has fallen. Domestic demand pressures as well
as global shocks, and particularly shocks to output, however, have played a larger role in driving
inflation over the last decade. We also show that country characteristics matter—the extent of oil
and food imports, vulnerability to weather shocks, economic importance of agriculture, trade
openness and policy regime, among others, help in explaining the role of shocks.
In the United States and a few European countries, inventory behavior is mainly the outcome of demand shocks: a standard buffer-stock model best characterizes these economies. But most European countries are described by a modified buffer-stock model where supply shocks dominate. In contrast to the United States, inventories boost growth with a one-year lag in Europe. Moreover, inventories provide limited information to improve growth forecasts particularly when a modified buffer-stock model characterizes inventory behavior.