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Keynes Fund

 

Summary of Project Results


To improve on existing data sets and develop new historical data sets

Although there are a number of available data sets that will be very useful to the project, an examination of existing data sets reveals that improvements can be made, including to national income series and real credit series, both at the annual and quarterly frequency. These improvements will provide new data sources to economists and economic historians using historical data.

To identify national credit cycles

Wavelet methods will be used to decompose the (real) credit time-series into components of various frequencies this will provide a description (and potentially a new data set) of national credit cycles since c.1870. Given data availability the analysis of the pre-WWII period will be limited to approximately 20-countries. For the post-WWII period it will be possible to consider much wider country coverage, although the 20-country data set will provide useful long-run comparisons.

To investigate the international linkages between national credit cycles

A number of modern statistical tools will be used to identify the changing temporal pattern of international synchronisation of credit cycles:

  1. Dynamic Factor Models will be used to isolate latent common (global) factors that drive the evolution of the national credit series and their cyclical components;

  2. GVAR methodology will be used to explore the spill-over effects of global shocks on a set of inter-related economies;

  3. The Local Projections method with be combined with spatial econometrics to estimate Impulse Response Functions of shocks (such as banking crises) that happened in linked economies.

To analyse the relationship between credit cycles and real economic activity

Credit cycles are often seen as a separate type of fluctuations to business cycles. The starting point of this project differs in that credit cycles and economic fluctuations are seen to display relationships across a number of timescales. The proposed project will examine the connection between credit cycles and a broad set of real variables, including GDP, industrial production, construction, investment, employment and total factor productivity.

 

 

Dr. Solomos Solomou

 

Dr Solomos Solomou is University Reader at the Faculty of Economics and Fellow of Peterhouse College, University of Cambridge. His research interests are in Historical Perspective, Long Cycles; Business Cycles; Trade Policy; Exchange Rate Regimes and Economic Performance; Weather and Sectoral Fluctuations.

 

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