The staff report for the Second Review Under the Stand-By Arrangement on the Former Yugoslav Republic (FYR) of Macedonia highlights economic developments and policies. FYR of Macedonia’s economic performance since independence has been marked by notable achievements in macroeconomic management, as well as some disappointments in the area of structural reforms. Inflation was brought down from hyperinflation levels to the low single digits by the de facto exchange rate peg, which was sustained in spite of sometimes challenging circumstances.
This paper quantifies the economic impact of uncertainty shocks in the UK using data that span the recent Great Recession. We find that uncertainty shocks have a significant impact on economic activity in the UK, depressing industrial production and GDP. The peak impact is felt fairly quickly at around 6-12 months after the shock, and becomes statistically negligible after 18 months. Interestingly, the impact of uncertainty shocks on industrial production in the UK is strikingly similar to that of the US both in terms of the shape and magnitude of the response. However, unemployment in the UK is less affected by uncertainty shocks. Finally, we find that uncertainty shocks can account for about a quarter of the decline in industrial production during the Great Recession.
Statistical offices have often recourse to benchmarking methods for compiling quarterly national accounts (QNA). Benchmarking methods employ quarterly indicator series (i) to distribute annual, more reliable series of national accounts and (ii) to extrapolate the most recent quarters not yet covered by annual benchmarks. The Proportional First Differences (PFD) benchmarking method proposed by Denton (1971) is a widely used solution for distribution, but in extrapolation it may suffer when the movements in the indicator series do not match consistently the movements in the target annual benchmarks. For this reason, an enhanced formula for extrapolation was recommended by the IMF’s Quarterly National Accounts Manual: Concepts, Data Sources, and Compilation (2001). We discuss the rationale behind this technique, and propose a matrix formulation of it. In addition, we present applications of the enhanced formula to artificial and real-life benchmarking examples showing how the extrapolations for the most recent quarters can be improved.
This paper presents a "bridge model" for short-run (one or two quarters ahead) forecasting of Italian GDP, relying on industrial production and survey indicators as key variables that can help in providing a real-time first GDP estimate. For a one- to two-year horizon, it formulates and estimates a Bayesian VAR (BVAR) model of the Italian economy. Both the "bridge" and the BVAR model can be of great help in supplementing traditional judgmental or structural econometric forecasts. Given their simplicity and their good forecasting power, the framework may be usefully extended to other variables as well as to other countries
IN EXAMINING, with the help of such statistical material as is available, the behavior of imports into India during the five post-partition years 1948–49 to 1952–53,1 it is possible to trace the relationship of imports to developments in the rest of the economy and, in particular, to national income movements. The ratio of import prices to the domestic cost of living is also commonly regarded as an important factor in determining the level of imports.