| data.spurious {desk} | R Documentation |
Non-Stationary Time Series Data
Description
The variables in this data set are non-stationary and help to understand spurious regression in the context of time series analysis.
Usage
data.spurious
Format
A data frame with yearly observations from 1880 to 2022 on the following five variables:
year | year of the observation. |
temp | deviation of the pre-industrial average global temperature. |
elements | number of discovered elements in chemistry (periodic table). |
gold | price for 1 ounce of fine gold in US-Dollar (not inflation-adjusted) starting in 1968. |
cpi | consumer price index: total all items for the United States (index 2015 = 100) starting in 1968. |
Details
In Auer et al. (2023, Chap. 22) these data are used to illustrate the estimation of dynamic regression models.
Source
NASA (GISTEMP Team, 2023: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2023-05-11 at https://data.giss.nasa.gov/gistemp/).
IUPAC (https://iupac.org/what-we-do/periodic-table-of-elements/).
LBMA (retrieved from Deutsche Bundesbank Zeitreihen-Datenbanken, BBEX3.A.XAU.USD.EA.AC.C08).
OECD (retrieved from FRED, https://fred.stlouisfed.org/series/CPALTT01USA661S).
References
Auer, L.v., Hoffmann, S. & Kranz, T. (2023): Ökonometrie - Das R-Arbeitsbuch, 2nd ed., Springer-Gabler (https://www.oekonometrie-lernen.de).
Lenssen, N., Schmidt, G., Hansen, J., Menne, M., Persin, A., Ruedy, R., & Zyss, D. (2019): Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.