This is the first in a series of blog posts analysing and discussing Serbian monthly retail trade time series.
Aims
The aims of these blog posts are the following:
- To describe main features of monthly retail trade time series
- To model series using popular time series models
- To forecast future retail trade time series values
- To compare forecasting performance of different time series models
Dataset
The dataset under examination comes from the National Bank of Serbia database (http://nbs.rs/export/sites/default/internet/latinica/80/realni_sektor/SBRS04.xls). It shows two monthly retail trade indices (2017=100) in current and constant prices. The first series covers period 2001M1 to 2018M8 and the second series: 2002M1 to 2018M8.
Dataset description
Dataset is available for download in two formats: csv and RData.
Column names in csv file are: Retcur (retail trade in current prices, 2017=100) and Retcon (retail trade in constant prices, 2017=100). Those familiar with R could download and use RData file. This file contains time series in different formats, but the time series used directly in the next blog posts are in the multivariate time series object Bts.name containing two above listed time series. This RData file contains also a few other time series objects in different format (a, Ats, Azoo, Azoo.name and Bts).
In the next blog post line graphs for each monthly retail trade time series will be presented and discussed.
