The Nature of econometrics and Economic data ttable 1.2 A Data Set on Economic Growth Rates and Country Characteristics obsno country gpcrgap ovcon seconds Argentina 0.89 32 Austria 3.32 16 3 2.56 Bolivia 1.24 Zimbabwe 2.30 The variable gpcrgdp represents average growth in real per capita GDP over the period 1960 to 1985. The fact that govcons60(government consumption as a percentage of GDP) and second60(percent of adult population with a secondary education) corre spond to the year 1960, while gpcrgdp is the average growth over the period from 1960 to 1985, does not lead to any special problems in treating this information as a cross- sectional data set. The order of the observations is listed alphabetically by country, but there is nothing about this ordering that affects any subsequent analysis Time series data a time series data set consists of observations on a variable or several variables over time. Examples of time series data include stock prices, money supply, consumer price index, gross domestic product, annual homicide rates, and automobile sales figure Because past events can influence future events and lags in behavior are prevalent in the social sciences, time is an important dimension in a time series data set. Unlike the arrangement of cross-sectional data, the chronological ordering of observations in a time series conveys potentially important information a key feature of time series data that makes it more difficult to analyze than cross- sectional data is the fact that economic observations can rarely, if ever, be assumed to be independent across time. Most economic and other time series are related, often strongly related, to their recent histories. For example, knowing something about the ross domestic product from last quarter tells us quite a bit about the likely range GDP during this quarter, since GDP tends to remain fairly stable from one quarter toThe variable gpcrgdp represents average growth in real per capita GDP over the period 1960 to 1985. The fact that govcons60 (government consumption as a percentage of GDP) and second60 (percent of adult population with a secondary education) corre￾spond to the year 1960, while gpcrgdp is the average growth over the period from 1960 to 1985, does not lead to any special problems in treating this information as a cross￾sectional data set. The order of the observations is listed alphabetically by country, but there is nothing about this ordering that affects any subsequent analysis. Time Series Data A time series data set consists of observations on a variable or several variables over time. Examples of time series data include stock prices, money supply, consumer price index, gross domestic product, annual homicide rates, and automobile sales figures. Because past events can influence future events and lags in behavior are prevalent in the social sciences, time is an important dimension in a time series data set. Unlike the arrangement of cross-sectional data, the chronological ordering of observations in a time series conveys potentially important information. A key feature of time series data that makes it more difficult to analyze than cross￾sectional data is the fact that economic observations can rarely, if ever, be assumed to be independent across time. Most economic and other time series are related, often strongly related, to their recent histories. For example, knowing something about the gross domestic product from last quarter tells us quite a bit about the likely range of the GDP during this quarter, since GDP tends to remain fairly stable from one quarter to Chapter 1 The Nature of Econometrics and Economic Data 8 Table 1.2 A Data Set on Economic Growth Rates and Country Characteristics obsno country gpcrgdp govcons60 second60 1 Argentina 0.89 9 32 2 Austria 3.32 16 50 3 Belgium 2.56 13 69 4 Bolivia 1.24 18 12 61 Zimbabwe 2.30 17 6 14/99 4:34 PM Page 8