Reconstructing the Real-Time View

One of the most common real-time data questions is: what did this series look like at the time? Macrotrace provides an as_of() method to reconstruct the vintage available on any historical date. This is a critical starting point for replication work, as it allows researchers to understand what data was actually available to forecasters, policymakers, and analysts at the time they were making decisions.

Load the Series

We will use the FRED PAYEMS series, which tracks total nonfarm payroll employment in the United States.

from macrotrace import MTTimeSeries

payems = MTTimeSeries(
    dataset_id="PAYEMS",
    source="fred",
)

Recover the Vintage Available on a Historical Date

The as_of() method returns the most recent vintage available on or before the date you choose.

from datetime import datetime, timezone

realtime_payems = payems.as_of(
    datetime(2020, 7, 15, tzinfo=timezone.utc)
)
print(realtime_payems)

Time Series: PAYEMS (All Employees, Total Nonfarm)
Source: FRED
Units: Thousands of Persons
Latest Vintage Date: 2020-07-02
Vintages: 785 available from 1955-05-06 to 2020-07-02
+------------+----------+
| Timestamp  |  Value   |
+------------+----------+
| 2019-09-01 | 151368.0 |
| 2019-10-01 | 151553.0 |
| 2019-11-01 | 151814.0 |
| 2019-12-01 | 151998.0 |
| 2020-01-01 | 152212.0 |
| 2020-02-01 | 152463.0 |
| 2020-03-01 | 151090.0 |
| 2020-04-01 | 130303.0 |
| 2020-05-01 | 133002.0 |
| 2020-06-01 | 137802.0 |
+------------+----------+