on the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations (replication data)

This folder contains the data set used in "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations". The data set includes 430 monthly time series from 10 European countries (Denmark, Finland, France, Germany, Italy, Netherlands, Portugal, Spain, Sweden, United Kingdom) that can be categorized into the following five groups of variables: industrial production indices, financial variables, unemployment rates, producer prices, and consumer prices. The majority of series span the period between January 1996 and July 2014.

The folder includes the following txt-files:

1) cpi.txt -> consumer price indices (all items; food and non-alcoholic beverages; alocoholic beverages, tobacco and narcotis; clothing and footwear; housing, water, electricity, gas and other fuels; furnishings, household, equipment and routine household maintenance; health; transport; communications; recreation and culture; education; restaurants and culture; education; restaurants and hotels; miscellaneous goods and services) 2) emp.txt -> unemployment rates (total, persons under 25, persons between 25 and 74, women, men) 3) ip.txt -> industrial production indices (total, consumer goods, capital goods, durable goods, non-durable goods, intermediate goods, manufacturing, minign and quarrying) 4) money1.txt -> money supply (M1-M3), share price index, nominal effective exchange rate (broad, narrow), real effective exchange rate (broad, narrow) 5) money2.txt -> long term government bond yield 6) ppi.txt -> producer price indices (total, capital goods, durable goods, consumer goods, intermediate goods, non-durable goods, manufacturing goods, mining and quarrying)

Data and Resources

Suggested Citation

Rossen, Anja (2016): On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations (Replication data). Version: 1. Journal of Economics and Statistics. Dataset. http://dx.doi.org/10.15456/jbnst.2016127.062352