Data Exercise Data Collection Collect the following data

Data Exercise

1. Data Collection

Collect the following data:

(a) Quarterly data on real GDP and its main expenditure components (i.e. C, I, G, EX, IM) for Canada.

Note: If you get this data from Statistics Canada, be aware that they might report a bunch of sub-components alongside each component. It’s not always clear which sub-components have been included in the head- line component and which have not. One way to check that you have the correct components is that your expenditure components sum up to GDP (though this only works with the nominal data).

(b) Quarterly data on the employment level and unemployment rate for working age people (15-64 years old, for example).

Employment, unemployment, and inﬂation are often reported monthly. If you download monthly data, you will have to convert this into quarterly data when you come to question 4. You can do this by taking the average of the three monthly data points corresponding to each quarter.

Your data should cover at least the last 30 years. On each graph, indicate exactly what each series is (e.g. is your data seasonally adjusted? how are prices measured for your inﬂation data? what approach was taken to generate real GDP from the nominal data? etc...). List the data source on each graph. Acceptable sources are the central bank, a governmental statistical agency (e.g. Statistics Canada), or a major non-governmental agency (e.g the OECD or the IMF).

2. Output and its components

(a) Plot Y, and all of the expenditure components, along with their trends. Note: if you are going to use the polynomial time trend approach, start with a cubic polynomial. If that is too rigid to track the data, you can try increasing the order. You will probably be better oﬀ not including the 2020 data when you estimate the equation of the trend. Large outliers at the end of the series can skew the estimation of the trend component.