This is the first in a series of blog posts analysing and discussing Serbian quarterly construction time series.
Aims
The aims of these blog posts are the following:
- To describe main features of quarterly construction time series
- To model series using popular time series models
- To forecast future construction 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/SBRS03.xls). It shows three quarterly construction time series (base = 2016): effective hours of work, value of construction work performed and number of completed apartments. All three series cover the same period: 2002Q1 to 2018Q2.
Dataset description
Dataset is available for download in two formats: csv and RData.
Column names in csv file are: Conhou (effective hours of work), Conval (value of construction work performed) and Conapa (number of completed apartments).
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 three 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 quarterly construction time series will be presented and discussed.
