Discover more macro-related work here:
The UK Business Cycle – Dating and Implications
The Institute is at the centre of the National debate on the measurement and understanding of business cycle fluctuations. We start this process at the fundamental level. The UK has some excellent long run data on economic progress and some of the basic facts of business cycle peak and troughs have been explored in earlier work at the Institute. Chadha and Nolan (2002) explored the long run of the UK business cycle and presented some stylised facts on duration and the cyclical behaviour of macroeconomic aggregates. We present a Table from Appendix A from their working paper with some basic business cycle dates.
Database of Bank of England operations in the gilt-edged market, 1928 – 1972
Compiled by William A. Allen
This note introduces a new set of data which are now available on the National Institute of Economic and Social Research website.
Mapping the Monetary and Financial Sectors, 1790-1850
British Academy/Leverhulme Small Grant: SG150907
Principal Investigator: Professor Jagjit S. Chadha (NIESR)
Co-Investigator: Mr Ryland Thomas (Bank of England)
The main purpose of this small pilot grant was to start exploring the microfiche data from the Gayer-Rostow-Schwartz volumes on the Growth and Fluctuations in the British Economy, 1790-1850. We have transcribed the series from Section III and from Section IV of the microfiche, which collected data in the 1930s and 1940s from a number of published sources. We have plotted the series and are making the series available to economic historians for research purposes.
Real time forecast combinations for the oil price
Baumeister and Kilian (2015) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real-time variables. Mindful of the importance of Brent crude oil as a global price benchmark, we extend consideration to the North Sea based measure and update the evaluation sample to 2017:12. We model the oil price futures curve using a factor-based Nelson-Siegel specification estimated in real time to fill in missing values for oil price futures in the raw data. We find that the combined forecasts for Brent are as effective as for other oil price measures. The extended sample using the oil price measures adopted by Baumeister and Kilian (2015) yields similar results to those reported in their paper. And the futures-based model improves forecast accuracy at longer horizons.