We built different financial cycle measures, also applied recently in Comunale and Hessel (2014).
Our aim is to provide a comprehensive database with definitions of variables that may be of use for crosscountry comparative analysis.
The database includes 41 countries (EU28 and OECD members) from 1994 to 2014 with both annual and quarterly frequency.
The main contributions of our database are that: i) it is publicly available and freely downloadable from the website of the Bank of Lithuania and it can be used subject to a clear reference; ii) the data are updated to the most recent year/quarter available; ii) considers not only the EU members as of 2014 (Croatia is therefore included in the sample), but also other non-EU countries part of the OECD (including both advanced and developing economies); iii) is built using both HP filtering techniques and the Principal Component Analysis (PCA), the latter are used to compute synthetic indices, to come up to different applicable indicators; iv) we added also some business cycle measures for comparison reason.
Ultimately, we show an application of our data, checking whether the financial cycle can influence the estimation of inflation in the euro area and what is the difference between adding a business or a financial cycle measure for the exchange rate pass-through (ERPT). We find that the ERPT can be higher in the presence of house price fluctuations at the frequency of the financial cycle.
JEL Codes: E32, E44, F36.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
house prices, Mariarosaria Comunale, Exchange rate pass-through, inflation, Dynamic Panel Data, European Union, financial cycle, business cycle, OECD, HP filter, Principal Component Analysis, domestic demand, real GDP, credit