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Time-series data

15 February, 2016 - 09:58

Data come in several forms. One form is time-series, which reflects a set of measurements made in sequence at different points in time. Table 2.1 reports the annual time series values for several price series. Such information may also be presented in charts or graphs. Figure 2.1 plots the data from column 2, and each point represents the data observed for a specific time period. The horizontal axis reflects time in years, the vertical axis price in dollars.

\mid  Time-series: a set of measurements made sequentially at different points in time.

Table 2.1 House prices and price indexes
1 2 3 4 5
Date   Price of detached bungalows, N. Vancouver House price index CPI   Real house price index
1999Q1 330,000 100.0 100.00 100.00
2000Q1 345,000 104.55 101.29 103.21
2001Q1 350,000 106.06 104.63 101.37
2002Q1 360,000 109.09 105.49 103.41
2003Q1 395,000 119.70 108.61 110.21
2004Q1 434,000 131.52 110.01 119.55
2005Q1 477,000 144.55 112.81 128.13
2006Q1 580,000 175.76 114.32 153.75
2007Q1 630,000 190.91 117.33 162.71
2008Q1 710,000 215.15 118.62 181.38
2009Q1 605,000 183.33 120.56 152.07
2010Q1 740,000 224.24 125.40 178.96
2011Q1 800,000 242.42 129.06 187.83
2012Q1 870,000 263.33 131.00 210.02

Source: Prices for North Vancouver houses come from Royal Le Page; CPI from Statistics Canada, CANSIM II, V41692930 and author’s calculations.

Annual data report one observation per year. We could, alternatively, have presented them in quarterly, monthly, or even weekly form. The frequency we use depends on the purpose: If we are interested in the longer-term trend in house prices, then the annual form suffices. In contrast, financial economists, who study the behaviour of stock prices, might not be content with daily or even hourly prices; they may need prices minute-by-minute. Such data are called high-frequency data, whereas annual data are low-frequency data.

\mid  High (low) frequency data: series with short (long) intervals between observations.

When data are presented in charts or when using diagrams the scales on the axes have important visual effects. Different scales on either or both axes alter the perception of patterns in the data. To illustrate this, the data from columns 1 and 2 of Table 2.1 are plotted in Figure 2.2 and Figure 2.3, but with a change in the scale of the vertical axis.

Figure 2.2 House prices in dollars North Vancouver 1999-2012
 
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Figure 2.3 House prices in dollars North Vancouver 1999-2012 
 

The greater apparent slope in Figure 2.2 might easily be interpreted to mean that prices increased more steeply than suggested in Figure 2.3. But a careful reading of the axes reveals that this is not so; using different scales when plotting data or constructing diagrams can mislead the unaware viewer.