FRED Dataset
Our group chose the Federal Reserve Economic Data (FRED) data source, with the link: https://fred.stlouisfed.org/. There are a lot of different data sets under different sections, including: macroeconomic analysis, energy prices and consumption, labor market dynamics, and education spending and outcomes.
Context of the FRED Dataset for Macroeconomic Analysis
The Federal Reserve Economic Data (FRED) is a database maintained by the Research division of the Federal Reserve Bank of St. Louis that has more than 816,000 economic time series from various sources.
Who uses the data?
Economists, policy makers, business leaders/owners, researchers, financial market analysts, and students can use the FRED data.
What does the FRED offer?
FRED contains frequently updated US macro and regional economic time series at annual, quarterly, monthly, weekly, and daily frequencies. The FRED data source has time series data from mid 1900s and up to the most recent days in 2024. FRED aggregates economic data from a variety of sources, most of which are US government agencies.
Where is the data from?
The data is taken from reputable organizations such as the U.S. Bureau of Labor Statistics (BLS), Bureau of Economic Analysis (BEA), Federal Reserve Board, World Bank, and other national and global reputable organizations.
The FRED offers reliable, intensive, and broad database for analyzing and visualizing key economic indicators, which can help make data-driven and more informed decisions regarding business strategies, investment, and monetary/public policy.
Inflation affects purchasing power of consumers, interest rates, wages, and more. Analyzing inflation can help to anticipate inflationary pressures, which would affect the whole economy in various industries. Secondly, the national income measures the overall health of a country financially by providing insight onto the citizen’s economic well-being. Additionally, the fiscal policy variables influence stability and growth by affecting tax income, debt level, government spending, investments, and more. Furthermore, employment levels are a key indicator of the economic health, as it influences consumer spending and business investments. Lastly, international trade shows the country’s global economic imports and exports and helps to understand a country’s competitiveness.
10-Year Breakeven Inflation Rate: Represents the market’s expectation for the average annual inflation over the next ten years.
Nominal Gross Domestic Product (GPD): to track the total market value of all finished goods and services produced within a country’s borders in a specific period.
Real Personal Income: adjusted for inflation, it measures the purchasing power of individuals.
International trade
Trade Balance: Goods and Services, Balance of Payments Basis: the difference between a country’s value of exports and imports of goods and services over a specific period of time.
Consumer Opinion Surveys: Consumer Prices: Future Tendency for United States: reflects consumers’ level of optimism about the performance of the economy.
Federal Debt: Total Public Debt as Percent of Gross Domestic Product: tracks the government’s debt level in relation to the GDP (economic output).
Federal Government Current Receipts: tracks the total money the federal government obtains from taxes.
Employment levels
Unemployment Rate: the unemployment rate represents the number of unemployed as a percentage of the labor force.
The first step would be loading the required libraries and the dataset. Then, I proceed to rename the variables to simplify them and convert ‘Year’ column from character to numeric
# A tibble: 6 × 9
Year Inflation_Rate GDP Consumer_Prices Unemployment_Rate Trade_Balance
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 2003 1.96 2864112. 2.91 5.99 -41354.
2 2004 2.44 3054299. 3.43 5.54 -50903.
3 2005 2.47 3259799. 4.09 5.08 -59712.
4 2006 2.48 3453896. 3.93 4.61 -63628.
5 2007 2.35 3618557. 3.99 4.62 -59250.
6 2008 1.89 3692465. 4.73 5.8 -59362.
# ℹ 3 more variables: Personal_Income <dbl>, Government_Receips <dbl>,
# Federal_Debt_Ratio <dbl>tibble [22 × 9] (S3: tbl_df/tbl/data.frame)
$ Year : num [1:22] 2003 2004 2005 2006 2007 ...
$ Inflation_Rate : num [1:22] 1.96 2.44 2.47 2.48 2.35 ...
$ GDP : num [1:22] 2864112 3054299 3259799 3453896 3618557 ...
$ Consumer_Prices : num [1:22] 2.91 3.43 4.09 3.93 3.99 ...
$ Unemployment_Rate : num [1:22] 5.99 5.54 5.08 4.61 4.62 ...
$ Trade_Balance : num [1:22] -41354 -50903 -59712 -63628 -59250 ...
$ Personal_Income : num [1:22] 10884 11233 11365 11778 12054 ...
$ Government_Receips: num [1:22] 1896 2028 2305 2539 2668 ...
$ Federal_Debt_Ratio: num [1:22] 58.7 60.1 60.8 61.5 62.1 ...
The overall trend of the U.S. GDP shows an upward trend, showing that the economy has been growing significantly throughout the past two decades. The graph shows the periods of expansion and minor dips in GDP, but the overall growth appears steady.
There are two shaded areas around 2008 and 2019. The first shaded area around 2008 marks the global financial crisis. During this period, the GDP dipped, but by 2010, it started to recover. The other shaded area around 2019 shows the impact of the COVID-19 pandemic. There was a downturn in GDP, however quickly bounced back in the following years.
The scatterplot does not seem to show a strong clear pattern between GDP and inflation rate. The points spread across different GDP values, without a clear upward or downward trend. This could suggest that GDP and inflation are not strongly correlated as they don’t have a direct, simple relationship.
However, it is noticable that the points with higher inflation rates are scattered across both high and low GDP values, which may indicate that even as GDP changes, the inflation does not necessarily flow a predictable path. In other words, high GDP does not directly align with high inflation rates, and vice versa.
Steady Increase in Disposable Personal Income
The disposable personal income shows a generally stead upward trend, which indicates that people’s purchasing power in the U.S. generally increased in the last 20 years. This could be attributed to economic growth, inflation, wage increases, and other adjustments over the years. However, there is a significant dip in the disposable personal income after 2020, which is most likely attributable to the economic shock caused by the COVID-19 pandemic that disrupted earnings and employment for many households.
The green line, which represents the percentage of consumer optimism regarding prices, reflects hoow the prices have changed over the past 20 years, likely due to inflation, supply-demand imbalances, and other economic disruptions. There’s a significant spike after 2020, during the same time time disposable personal income decreased. This could correspond to the economic effects of the COVID-19 pandemic that caused shortages, inflation, and widespread disruptions to supply chains and consumer markets globally.
Consecutively Low Consumer Confidence is Followed by High Consumer Confidence in 2021-2024
The heatmap shows varying shades of blue, with darker shades indicating higher levels of Consumer Confidence in Prices. There are lighter colros in earlier years, which may suggest that consumer confidence level in those periods were relatively low. On the other hand, there are some darker blue bands towards the more recent years, indicating periods of higher consumer confidence.
Notable Dip Around 2008 and Signficant Spike After 2020 in Consumer Confidence in Prices
There is a noticable dip from 2008 to 2009, with the color changing from darker blue to lighter blue, which may correlate with the global financial crisis affecting consumer confidence in prices. This may be due to economic instability, which caused consumers to have low confidence levels in prices, especially due to the overall decline in economic activity after the housing market crisis. The dark blue for the years 2022-2024 may imply that consumer confidence in prices has been quite strong recently and quite consistently, potentially due to post-pandemic recovery measures, which include economic policies, stimulus packages, or other factors affecting consumer confidence.