FRED Macro Dashboard Starter Kit: Track Inflation, Jobs, Rates
Quick answer: the FRED macro dashboard is a calmer monthly data workflow
A FRED macro dashboard is a repeatable way to monitor official economic indicators without turning every headline into a market prediction. Instead of doom-scrolling CPI, jobs, Fed rates, mortgage rates, yield-curve headlines, and recession chatter, the dashboard pulls selected time series from FRED and turns them into a monthly “what changed?” review.
The FRED Macro Dashboard Starter Kit is a free educational download from Jivaro. It includes a Google Sheets-ready workbook, a Google Apps Script refresh function, a Python notebook, and a prompt table for writing a short human-reviewed macro note. It is built for finance-curious readers, beginner and intermediate investors, students, researchers, writers, and analysts who want a cleaner monthly routine.
Educational note: This dashboard is not investment advice, trading advice, recession prediction, or a buy/sell/hold signal. It organizes official macro data so readers can ask better questions. It does not tell anyone what to buy, sell, hold, short, borrow, or avoid.
Download the FRED Macro Dashboard Starter Kit
Start with the zip kit if using Google Sheets. Use the Python notebook if the goal is to work locally, export files, or build charts from the same FRED series.
The kit is positioned as a free educational resource. For other Jivaro tools, browse the Jivaro Apps hub. For broader digital products and resources, the Jivaro Store is separate from this free dashboard download.
What is included in the starter kit?
Google Sheets-ready workbook
The workbook is designed around a simple monthly review: raw monthly data, dashboard summaries, and a prompt-driven note-writing tab. It keeps the workflow readable for people who do not want to live inside a terminal.
Google Apps Script refresh function
The Apps Script fetches official FRED CSV data and refreshes the workbook. The key function is refreshFredMacroDashboard(). Review any script before authorizing it in a Google account.
Python notebook
The notebook pulls the same series and exports CSV, XLSX, and chart files. It fits readers who want versioned research folders, reproducible data pulls, or chart images for monthly notes.
What_Changed prompt table
The prompt table keeps the final step human. Instead of asking a model to “predict the market,” it asks the reader to describe what changed, what stayed noisy, and what needs a later update.
Why use FRED data instead of headline panic?
FRED, short for Federal Reserve Economic Data, is an economic-data database created and maintained by the Research Department at the Federal Reserve Bank of St. Louis. It brings together time series from national, international, public, and private sources and provides tools for downloading, charting, transforming, and aggregating data.
That matters because macro headlines usually compress a lot of uncertainty into one sentence. “Inflation rose,” “jobs cooled,” “the yield curve inverted,” or “mortgage rates jumped” can all be directionally true while still being incomplete. A dashboard helps separate the data point from the interpretation.
The starter kit uses the public FRED graph CSV pattern for simple spreadsheet refreshes. For example, the CPI series can be pulled through the graph CSV route:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=CPIAUCSL
That CSV approach is different from using the official FRED API. FRED’s API documentation is useful for readers who want to customize the workflow, but official web service requests require an API key. The kit’s Google Sheets workflow assumes CSV-based refreshes, not an API-key setup.
FRED macro dashboard series: what each indicator is supposed to do
The dashboard uses a compact set of inflation, labor, rates, housing, production, and recession-context indicators. The goal is not to include every possible macro series. The goal is to keep a monthly review focused enough to repeat.
| FRED series | What it tracks | Why it matters | How the dashboard reads it | Mistake to avoid |
|---|---|---|---|---|
| CPIAUCSL | Headline Consumer Price Index for All Urban Consumers. | It is one of the most watched gauges of broad consumer-price inflation. | Read as a year-over-year change, not just the latest index level. | Treating one hot or cool month as a complete inflation story. |
| CPILFESL | Core CPI, excluding food and energy. | It helps smooth two volatile categories so underlying inflation pressure is easier to compare. | Read as a year-over-year change alongside headline CPI. | Thinking “core” means households do not care about food and energy. It is an analytical filter, not a household budget. |
| UNRATE | U.S. unemployment rate. | It gives a simple labor-market temperature check, especially when compared with recent movement. | Read as a level and recent change. | Assuming the unemployment rate captures every labor-market stress point by itself. |
| PAYEMS | Total nonfarm payroll employment. | It shows whether payroll employment is expanding or contracting month to month. | Read as monthly change. | Ignoring revisions or focusing only on the first release. |
| FEDFUNDS | Effective federal funds rate. | It summarizes where overnight bank funding is trading relative to monetary policy conditions. | Read as a monthly level and change. | Assuming it directly predicts stocks, mortgages, or personal borrowing costs. |
| DGS10 | 10-year Treasury constant maturity yield. | It is a benchmark long-term rate used in many market and valuation discussions. | Daily data are converted to monthly using the latest observation in each calendar month. | Explaining every move with one cause. Long yields can move for growth, inflation, policy, liquidity, and term-premium reasons. |
| T10Y2Y | 10-year Treasury yield minus 2-year Treasury yield. | It shows the slope of a widely watched part of the yield curve. | Daily data are converted to monthly using the latest observation in each calendar month. | Treating an inversion as a precise recession countdown timer. |
| DFII10 | 10-year inflation-indexed Treasury yield. | It is commonly used as a market-based real-rate proxy. | Daily data are converted to monthly using the latest observation in each calendar month. | Calling it a pure growth forecast. Real yields can also reflect liquidity, risk appetite, and term structure. |
| T10YIE | 10-year breakeven inflation rate. | It gives a market-implied inflation measure derived from nominal and inflation-indexed Treasury yields. | Daily data are converted to monthly using the latest observation in each calendar month. | Confusing breakevens with guaranteed future inflation. |
| MORTGAGE30US | 30-year fixed mortgage average in the United States. | It connects the rates conversation to housing affordability and financing conditions. | Weekly data are converted to monthly using the latest observation in each calendar month. | Assuming the average is the rate every borrower can get. |
| INDPRO | Industrial Production: Total Index. | It gives a read on real production activity across manufacturing, mining, and utilities. | Read as a year-over-year change. | Overreacting to one month or ignoring revisions. |
| USREC | NBER-based U.S. recession indicator. | It provides historical recession shading and context. | Read as historical context only. | Using it as an early-warning recession model. It is not a forecast signal. |
Because the dashboard mixes monthly, daily, and weekly series, the kit standardizes the view to a monthly rhythm. Daily and weekly indicators are converted to monthly by using the latest observation in each calendar month. That keeps the review repeatable, but it also means the dashboard is not meant for intraday trading or daily market timing.
How to set up the Google Sheet version
The spreadsheet workflow is designed for readers who want a practical dashboard without building a data pipeline from scratch.
- Download the starter kit zip and copy the Google Sheets-ready template into a working Google Sheet.
- Open the sheet and go to Extensions > Apps Script.
- Paste the included Apps Script into the script editor.
- Run
refreshFredMacroDashboard(). - Review the Monthly_Data tab for the cleaned monthly values.
- Review the Dashboard tab for the summarized indicator view.
- Use the What_Changed prompts to write a short monthly note in plain English.
Readers who prefer local analysis can use the Python notebook download instead. The notebook is better suited for exporting CSV files, XLSX workbooks, and chart images into a research folder.
The 15-minute monthly FRED macro dashboard workflow
The point of the dashboard is not to stare at macro data all day. The point is to build a monthly habit that is calm enough to repeat.
- Refresh the sheet or notebook. Run the Google Apps Script refresh or rerun the Python notebook.
- Scan inflation. Compare headline CPI and core CPI year-over-year. Ask whether both moved in the same direction or diverged.
- Scan labor. Check the unemployment-rate level, recent unemployment change, and the monthly change in payroll employment.
- Scan rates and the yield curve. Review the federal funds rate, 10-year Treasury yield, 10-year minus 2-year spread, 10-year real yield, and breakeven inflation.
- Scan housing and production. Check the 30-year mortgage average and industrial production year-over-year.
- Write the “what changed?” note. Summarize what changed, what did not change, what looks noisy, and what needs confirmation next month.
For readers connecting macro notes to investing research, keep the boundary clear. A macro dashboard can provide background context for articles such as Top 10 Stocks for 2026, but it does not turn a watchlist into a personal recommendation. For active-market behavior and risk, Jivaro’s Range Trading Strategy guide is a useful reminder that clean-looking charts can hide messy execution, costs, taxes, and emotional sizing.
How to read the dashboard without overreacting
Inflation: look for direction and persistence
Headline CPI and core CPI should be read as year-over-year changes in this kit. The question is not “Did one release beat a headline?” The better question is whether the trend looks broad, persistent, or mixed.
Labor: separate the level from the change
The unemployment rate is a level. Payrolls are read as monthly change. A single payroll print can be revised, and a low unemployment rate can still hide stress in hours, wages, participation, or sector-level weakness.
Rates: connect policy, markets, and expectations carefully
The federal funds rate, 10-year Treasury yield, 10-year minus 2-year spread, real yield, and breakeven inflation each answer a different question. The dashboard is strongest when it compares them, not when it tries to crown one “the” signal.
Housing and production: watch pressure points
Mortgage rates affect housing affordability and financing conditions. Industrial production gives a window into real activity. Neither series is a standalone market forecast, but both add useful context to inflation, labor, and rate trends.
Recession context: use USREC as history, not prophecy
USREC is included to show historical recession periods. It helps readers see how indicators behaved around past cycles. It should not be treated as a live recession predictor or early-warning model.
Common mistakes when using macro dashboards
Treating one print as a forecast
One CPI release, jobs report, mortgage-rate update, or yield-curve move can matter. It still needs confirmation from later data and related indicators.
Confusing breakevens with guaranteed inflation
Breakeven inflation is market-implied and useful, but it is not a promise of future inflation. It can be affected by liquidity, risk premiums, and market structure.
Using USREC as a prediction model
USREC is historical recession context. It is useful for shading past recessions and comparing cycles, not for predicting the next recession date.
Ignoring revisions
Many economic series can be revised. A monthly note should leave room for the phrase “initially reported” when a release is fresh.
Mixing frequencies without resampling
Daily yields, weekly mortgage rates, and monthly CPI data should not be compared casually unless the time frequency is standardized.
Overreacting to headlines
A dashboard should slow the reader down. If it creates more panic, the workflow is being used like a news feed instead of a review system.
Who the FRED Macro Dashboard Starter Kit fits — and who should skip it
Good fit
The kit fits readers who want a repeatable monthly review, students learning economic indicators, writers building macro notes, researchers who want a starter workflow, and investors who want context without turning every release into a trade.
Not ideal
The kit is not ideal for day trading, real-time market alerts, automated trading signals, recession prediction, portfolio optimization, or personalized investment decisions.
Readers building broader money systems can pair the dashboard with Jivaro’s Cashflow Catalyst guide for cash-flow thinking and the Jivaro finance archive for more finance explainers. The macro dashboard should remain a research habit, not a pressure machine.
FAQ
What is a FRED macro dashboard?
It is a dashboard that pulls selected FRED economic time series into a repeatable view for tracking inflation, labor, rates, housing, production, and recession context.
Does the starter kit require a FRED API key?
The Google Sheets workflow is written around public FRED CSV refreshes. Readers who rewrite the kit to use the official FRED API should review FRED’s API-key documentation.
Can this dashboard predict recessions?
No. USREC is included for historical recession context. The dashboard is not a recession model and should not be used as a prediction tool.
Why use a monthly workflow?
A monthly rhythm keeps the review calm and repeatable. It also makes it easier to compare monthly CPI, monthly labor data, and resampled daily or weekly series.
Is the Python notebook necessary?
No. The sheet is the simpler starting point. The notebook is optional for readers who want local exports, reproducible files, XLSX output, CSV output, or charts.
Can investors use this as a buy or sell signal?
No. The dashboard is for educational monitoring and research context. It does not recommend buying, selling, holding, shorting, or timing any asset.
Sources and notes
This article is educational and uses simplified workflow language to describe the starter kit. It does not provide personalized investing, trading, legal, tax, or financial advice.
- FRED homepage — official Federal Reserve Economic Data site.
- What is FRED? — FRED help page explaining the database, tools, revisions, transformations, and frequency aggregation.
- Downloading Data from FRED — official FRED help page on Excel and CSV downloads.
- FRED CSV pattern using CPIAUCSL — example graph CSV export pattern used to explain the spreadsheet refresh approach.
- FRED API documentation and FRED API key documentation — official API context for users who want to customize beyond the CSV workflow.
- Federal Reserve DDP/FRED information page — Federal Reserve Board information on the Data Download Program and FRED partnership.
- FRED series pages used in the dashboard table: CPIAUCSL, CPILFESL, UNRATE, PAYEMS, FEDFUNDS, DGS10, T10Y2Y, DFII10, T10YIE, MORTGAGE30US, INDPRO, and USREC.