Claims, Payroll, and Unemployment: Reasons for Popularity of These Datasets Analysis
This article continues on the discussion of the widespread use of the data on unemployment claims, total nonfarm payrolls, and unemployment levels. Major definitions are available here.
The main reasons for the popularity of the time series mentioned are threefold: their release schedule, their availability and reliability, as well as their close relationship with economic activity and hence the stock market. So let us go through these reasons in turn.
Release schedule
The weekly updates on unemployment claims make this series virtually the most popular data item in the world. This level of regularity is quite high by the economic statistics standards as the numbers on most non-financial activity indicators come out only monthly, quarterly, or yearly (the Bank of international settlements' Triannual Survey on Currency Use comes to mind as an example of an even less frequent data). When combined with financial data, which usually have a much higher frequency, the releases on unemployment claims allow to better understand and align the events in the financial sector and the broader economy. Analysis, research, and especially short-term forecasting are also made a lot easier as there are more data points.
The data on total nonfarm payrolls and unemployment comes out on the monthly basis. It is certainly less convenient to converge with the financial indicators or use for short-term market forecasting. Nevertheless, these indicators provide a look at the behavior of the fundamental parameters of the economy, so they serve as indispensable inputs for any macroeconomic or broader market analysis.
One particular issue with the data indicators discussed here is the need to align their varying frequencies. Usually, there are 3 ways of doing this:
- taking the first week of the month as the claims data point corresponding to the monthly value in the other series - this approach is especially useful for forecasting;
- taking the average value of the weeks in every month - on many occasions this allows to find the best fit model;
- using the sum of all weekly claims - this can provide some insights into how the total claims transform to the actually recorded unemployment.
Availability and reliability
All of the data series mentioned are freely available on the US Department of Labor's Employment and Training Administration (ETA) and US Bureau of Labor Statistics (BLS) websites (the links available at my piece on the series definitions [link to the Definitions article]. Furthermore, many researchers consider the access to data in the Federal Reserve Economic Data (FRED) online database provided by the St. Louis Fed (available here) easier to use as the series are already pre-formatted and can be bundled together even if the sources vary.
The major adjustments in the data are related to the high seasonality of the employment patterns. Hence, all the series can be accessed in the seasonally adjusted and non-adjusted raw variants. At the same time, with updates on the data happen, in general, the data itself is pretty reliable and not subject to constant high-magnitude revisions.
Relationship with economic activity
The importance of all the series discussed here comes from the high connection of all these datasets with the economic activity. There are 3 main links:
- both unemployment and employment data dynamics reflect the rate with which the economy is creating or destroying jobs, and this indicates the level of the current sentiment of consumers and companies as well as their outlook and thinking about the future;
- more importantly, unemployment plays a crucial role in the Federal Reserve's reaction function, i.e. the way the US central bank directs monetary policy to influence the situation in the economy;
- finally, somewhat obviously, the weekly claims data allows making judgments on how both employment and unemployment are behaving at the moment or will be moving to in the future.
Consequently, in the most simple schematic way the data researchers' and financial analysts' thinking goes like this: the weekly news releases on unemployment claims show what is happening to the labor market → the analyst evaluates how the Federal Reserve is most likely to react to these new data → this thinking is applied to the financial or economic forecast.
All in all, the unemployment-related datasets play a very important role in the understanding of the current situation in the labor market for researchers, policy-makers, and analysts.