Economic Data Sources on the Internet

Su, Chapter 3

Data on Paper - A Thing of the Past

• As recently as five years ago economic data were primarily available on paper

• Made analysis difficult• Past few years has seen an explosion of

publicly available data on the internet• Browser/Spreadsheet/Database Program has

become a powerful tool

Main Problems with Economic Data on the Internet

• Knowing where to look– Decentralized US system not user friendly

• Finding most recent or appropriate data available

• Getting data into convenient form• Data Overload

How to find data on the Internet

• Think about what you want to accomplish• Then think about what data you need• Then think about what government agency

publishes the data you need• Go to the appropriate Web site

What if you only have a general idea about the data you need?

• Important Starting points– Resources for Economists on the Internet(RFE) http://rfe.wustl.edu/sc.html– Economic Report of the President

What if you need specialized data that is not readily available?

• Contact information• Find the section closest to your area of

interest

Case Study: IIP Retrieval and Analysis

• Goals:– Provide practical experience locating and

manipulating economic data available on the internet

– Provide understanding of the cyclical and seasonal behavior of production in the US economy

Motor Vehicle Production since WWII

• In this exercise we will collect and analyze data on the production of motor vehicles in the US since the end of the second World War.

• Motor vehicle production is and has been an important part of the manufacturing sector of the US economy. The economic data from this sector exhibit interesting behavior.

Activities

• Locate monthly data on production of motor vehicles and parts and capacity utilization in this sector, both seasonally adjusted and unadjusted

• Read this data into a spreadsheet• Analyze this data

Data Analysis

• Estimate and interpret the secular trend in motor vehicle production

• Discuss the implications of this trend for the future of the industry

• Estimate and interpret seasonal variation in motor vehicle production

• Examine the capacity utilization data and analyze the relationship between utilization and production

Data Location

• Source of monthly production data?

Data Location

• Source of monthly production data?• Identification of needed data and

documentation– What format are the data in? ASCII Text with

coded identifiers– Series are in multiple files: Recent data files and

Historical data files– Also split up by seasonal adjustment

Series Identification Codes

• Documentation is in Table 2a for these variables

TABLE 2AINDUSTRIAL PRODUCTION: INDUSTRY GROUPS SICGroup and Series CODE CODE

Motor vehicles and parts B37100 371

Data Record Format

• A “record” is one line of data in a data file• Understanding the format of records and

files is important when manipulating data• In this case, each record is a years worth of

monthly data. The series ID and year are on each record

• Each file has many records.

Industrial Production and Capacity Utilization Data Retrieval

The data have various start dates. The earliest date is 1919. Data are written with three decimal places, twelve months of data per line.

Data Format

Column 1-8 : series code in double quotes Column 9 : blank Column 10-13 : date, in YYYY format Column 14-15 : blank Column 16-121: data, 7 positions including decimal and 3 decimal places, separated by two blanks.

Data Retrieval

• For now, we’ll work with the seasonally adjusted (SA) and unadjusted (NSA) Index of Industrial Production data for Motor Vehicles and Parts (B37100).

• In the web browser, highlight the region with the Motor Vehicle IIP series and hit control-c (for copy)

• Switch to Excel (I use alt-tab) and hit control-v (paste). This copies each row of data from the browser into one cell in the spreadsheet

• Use the pull-down “data” menu to convert this into cells, using the “Text to Columns” feature.

Data Manipulation

• Now these data need to be put into a single column. There are several ways to do this, including the “brute force” method. I used Excel

• The “Copy” “Paste Special” with the “Transpose” option will work for one year at a time.

• When done, should have two columns of data.• Add dates in Column A, and graph

Series Component: Seasonal

• Seasonal Variations are easily identified in the NSA series.

• In this case, there is a month where motor Vehicle and Parts production is significantly lower.

Original SA and NSA Series

Jan-47 Jan-52 Jan-57 Jan-62 Jan-67 Jan-72 Jan-77 Jan-82 Jan-87 Jan-92 Jan-97

Series Component: Cyclical

• Timing of Recessions:– July ‘53 - May ‘54– August ‘57 - May ‘58– April ‘60 - February ‘61– December ‘69 - November ‘70– November ‘73 - March ‘75– January ‘80 - July ‘80 and July ‘81 - November ‘82

• Can clearly see many of the recessions in this sample

Index of Industrial Production - SA

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Jan-47 Jan-52 Jan-57 Jan-62 Jan-67 Jan-72 Jan-77 Jan-82 Jan-87 Jan-92 Jan-97

‘74 ‘80-’82‘90

‘69‘60

Series Component: Irregular

• Note that there are some downturns not associated with business cycles

• These are Irregular components• !966-1967 period

Index of Industrial Production - SA

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Jan-47 Jan-52 Jan-57 Jan-62 Jan-67 Jan-72 Jan-77 Jan-82 Jan-87 Jan-92 Jan-97

?

1966-1967Jan-66 63.18Feb-66 63.32Mar-66 63.27Apr-66 63.32May-66 60.72Jun-66 60.39Jul-66 56.36Aug-66 54.9Sep-66 58.64Oct-66 63.04Nov-66 60.81Dec-66 59.53Jan-67 54.78Feb-67 52.2Mar-67 53.05Apr-67 53.99May-67 54.44Jun-67 53.53Jul-67 52.89Aug-67 52.38Sep-67 49.78

• Note that the series falls significantly during this period

• Jan-66 63.19• Sep-67 49.78

• Over 13% decline in 21 months

• Need more industry-specific details

Series Component: Secular Trend

• While cyclical (and to some extent irregular) components can be identified by inspection, the secular trend must be estimated

• Many different trend lines can be fitted to a single series– Linear, exponential, logarithmic

Linear Trend

IIP = 0.167t - 76.535

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Jan-47 Jan-52 Jan-57 Jan-62 Jan-67 Jan-72 Jan-77 Jan-82 Jan-87 Jan-92 Jan-97

How to easily draw trend lines in Excel

1. On chart, right click series, select “Add Trendline”

Select Type

Select Options, including forecast period

Lessons Learned

• Data manipulation and analysis takes a lot of time

• The “Trendline” tool in Excel can be used as a simple forecasting tool to quickly generate n-period ahead projections

• Before getting excited about that 6th Order polynomial regression forecast, note that it fails to track any historical downturn.

(continued)

• There are many ways to remove seasonal components. Each produces different SA series with different properties

• There are many ways to estimate the secular trend component

• We need some way to compare and evaluate each of these methods