Understanding Economic Data: Types, Variables, and Analysis

1. Econ 299Quantitative Methods in Economics Economic Data Calculus and Economics Basics of Economic Models Advanced Calculus and Economics Statistics and Economics Econometric Introduction Lorne Priemaza, M.A. Lorne.priemaza@ualberta.ca

2. 1. Data Description, Presentation, and Manipulation 1.1 Data Types and Presentations 1.2 Real and Nominal Variables 1.3 Price Indexes 1.4 Growth Rates and Inflation 1.5 Interest Rates 1.6 Aggregating Data: Stocks and Flows 1.7 Seasonal Adjustment Appendix 1.1 Exponentials and Logarithms

3. Why do economists need data? • 1) Describe Economy • Current and past data • Increases and decreases • This information can influence decisions ie: GDP, interest rate, unemployment, price, debt, etc. • 2) Test Theory • Does variable A affect variable B? ie: Smokers and the cost to healthcare ie: Married couples and health

4. 1 Data Types Data is essential for economists. Data can be categorized by: 1) How it is collected: • time series data • cross-sectional data • panel data 2) How it is measured: • nominal data • real data

5. Time Series Data -Collects data on one economic agent (city/person/firm/etc.) over time -Frequency can vary (yearly/monthly/ quarterly/weekly/daily/etc.) -ie: Canadian GDP, GMC stock value, your height, U of A tuition, world population

6. Alberta’s Tuition – Time Series

7. China GDP – Time Series Source: World Development Indicators, The World Bank, www.worldbank.org

8. Final Fantasy Quality - Time Series Data Source: www.thefinalfantasy.com Source: the truth Time Series: One Agent Many Time Periods

9. Cross Sectional Data -Collects data on multiple economic agents (locations/persons/firms/etc) at one time -Taken at one specific point in time (September report, January report, etc.) -ie: current stock portfolio, hockey player stats, provincial GDP comparison, last year’s grades

10. 99/00 Tuition – Cross Sectional

11. Canadian Provincial Corporate Tax 2015- Cross Sectional Data Source: Canada Revenue Agency (http://www.cra-arc.gc.ca/tx/bsnss/tpcs/crprtns/prv/menu-eng.html), NDP platform (Alberta) *Refers to the higher rate; not applicable to small business

12. Timothy A. Student’s Weekly Time Spent Studying for Midterms - Cross Sectional Data Cross Sectional: Many Agents One Time Period

13. Panel Data -Combination of Time Series and Cross-sectional Data -Many economic agents -Many time periods -More difficult to use -Often required due to data restrictions -also referred to as pooled data

14. Pooled Tuition

15. 1.1 Data Types • Exercise: What kind of data is: 1) Election Predictions 10 days before an election? 2) MacLean’s University Rankings? 3) Yearly bank account summary? 4) University Transcript after your 4th year?

16. 1.2 Real and Nominal Variables • 1. Nominal variables • Measured using current prices • Provides a measure of current value Ie: a movie today costs $12.

17. 1.2 Real and Nominal Variables • 2. Real variables • Measured using base year prices • Provides a measure of quantity (removing the effects of price change over time) Ie: a movie today costs $4.00 in 1970 dollars

18. A Movie in 1970 In 1970, a movie cost $0.50 BUT $0.50 then was a lot more than $0.50 now. Nominal Comparison: Movie prices have increased by a factor of 24 ($0.50 -> $12) Real Comparison: Movie prices have increased by a factor of 8 ($0.50 -> $4)

19. GDP example • Gross Domestic Product -Monetary value of all goods and services produced in an economy How do nominal and real GDP differ?

20. Nominal GDP -Current monetary value of all goods produced: ∑ quantities X prices -changes when prices change -changes when quantities change

21. The Problem with Nominal GDP Assume: prices quadruple (x4) production is cut in half (x 1/2) Nominal GDP (year 1) = 1 X 1 = 1 Nominal GDP (year 2) = 0.5 X 4 = 2 -although production has been devastated, GDP reflects extreme growth

22. Real GDP -Base year value of all goods currently produced: ∑ quantities X prices baseyear -doesn’t change when prices change -changes when quantities change

23. The Solution of Real GDP Assume: prices quadruple (x4) production is cut in half (x 1/2) Real GDP (year 1) = 1 X 1 = 1 Real GDP (year 2) = 0.5 X 1 = 0.5 -real GDP accurately reflects the economy

24. Price Indexes (Indices) -Used to convert between real and nominal terms -different indexes for different variables or groups of variables Ie: GDP Deflator 2002 = 100 (base year) 2010 = 125 (World Bank) The “price” of GDP has risen 25% between 2002 and 2010

25. GDP – Converting Between Real and Nominal

26. General Conversion Equations

27. Example: Tuition *Based on 3% yearly inflation typical to years listed

28. 1.3 Math Review – Summation Notation X – variable you are adding s – starting observation n – last observation In this class, often simplified to:

29. 1.3 Math Review – Summation Notation Add up each good’s (1, 2…n) product of its price today times its quantity last term. For example, if you were in charge of food for a convention:

30. 1.3 Price Indexes Price indexes summarize how the cost of baskets (collections of goods or services) changes over time. The total cost of a basket is:

31. Example #1 John is constructing a price index to reflect his entertainment spending John values two activities equally: seeing movies and eating hot dogs The prices of movies and hot dogs have moved as follows:

32. Example #1 Simple Price Index = ∑price X weight Exercise: If John valued hot dogs three times as much as movies, what would the price indexes become?

33. 1.3.1 Normalizing Price Indexes -price indexes themselves are meaningless “The price of GDP was 78.9 this year” -price indexes help us: • Compare between years • Convert between real and nominal -to compare more easily, we normalize to make the index equal 100 in the base year

34. Normalizing the price index: = 100 in base year For example, if GDP was 310 in 1982, dividing every year’s GDP by 310 and then multiplying by 100 normalizes GDP to be 100 in 1982.

35. Example #1a - Normalized Take 2000 as the base year: Does the base year chosen affect the outcome?

36. Example #1b - Normalized Take 2002 as the base year: Note:Raw and normalized PI’s WORK the same, normalized PI’s are just easier to visually interpret

37. Example #2 – Tuition If instead of using inflation for our tuition deflator, we use the education deflator, we can first normalize it to 1999/2000: *Cansim series V735564, January Data

38. Example: Tuition – Converting from real to nominal

39. 1.3.1.1 Changing Base Years -base years can be changed using the same formula learned earlier -in the formula, always use the price indexes from the SAME SERIES (same base year)

40. 1.3.2 Common Price Indexes -Up until this point, price index weights have been arbitrary -Arbitrary weights leads to bias, difficulty in recreating data, and difficulty in interpreting and comparing data -One common price index (which the Consumer Price Index uses) is the Laspeyres Price Index (The Paasche Price Index is the other common index used)

41. 1.3.2 Laspeyres Price Index -uses base year quantities as weights -still = 100 in base year (automatically normalized LPIt = ∑ pricest X quantitiesbase year ---------------------------------- X 100 ∑ pricesbase year X quantitiesbase year -tracks cost of buying a fixed (base year) basket of goods (ie: CPI)

42. Example: Movies and Karaoke

43. Example: Laspeyres (Base year 1)

44. 2 Price Index Calculation Methods • Using individual prices and quantities -Same as before 2) Using basket costs PaQb Price of basket b in year a P2012Q1997 Price in 2012 of what was bought in 1997

45. Method 1 – Individual Prices and Quantities

46. Method 2 – Basket Costs

47. Method 2 Example Every year, Lillian Pigeau likes to travel. The first year, she went to Maraket, the second year to Ohm, and the third year to Moose Jaw. The costs of those trips are as follows:

48. Method 2 – Laspeyres (Year 1 Base Year)

49. Method 2 – Laspeyres (Year 1 Base Year)

50. Method 2 – Laspeyres (Year 1 Base Year)