New York – The BLS Nonfarm Employment numbers released today have, as they often do, had a significant impact on the market. Until recently, WANTED Analytics, a firm which uses online job ad data to forecast monthly changes in employment, had offered their forecasts as a free service on their blog. These monthly forecasts will now be made available as an offline service to new or existing WANTED Analytics subscribers.
WANTED outlines three major reasons for this change:
Most professional forecasters already maintain models of their own. An additional forecast or model output is of little use to practitioners. Instead, WANTED’s services have focused on integrating Hiring Demand into existing forecasting equations. Particularly relevant is the specification of Hiring Demand autoregressive terms (AR terms), as well as their interaction with other labor market variables. What’s more, WANTED provides both weekly and monthly data, so forecasters can use either datasets depending on their preferences. Only a separate subscription service can allow sufficient technical support to properly incorporate Hiring Demand data into sophisticated econometric models. BLS revisions to Nonfarm Employment counts are a fact of life in the employment forecasting world. “What the forecast would have been” under revised data is different than what is produced given the preliminary data. As such, the same Hiring Demand data produces different forecasts as the BLS revises its data once, twice, and finally thrice. This is because most models include previous values of employment. In other words, monthly Nonfarm Employment counts are a moving target. Providing a public forecast, once and only once, does not adequately accommodate the fact that the same forecasting model produces different results as the BLS revises its data. Once integrated into forecasting models, however, the marginal impact of Hiring Demand can be quantified even as the BLS revises its data. Hiring Demand is so closely related to published measures of economic activity that providing derived output free of charge is not a sustainable long-term business practice. Hiring Demand explains 94% of future changes in Canadian Employment levels, explains 80% of future changes in new Unemployment Insurance Claims, and explains 78% of S&P 500 index returns.
In addition to the valid statistical considerations outlined in the first two points, we think the third point is especially important. WANTED says that their hiring demand data has proven to be a valuable tool in predicting changes in employment, unemployment claims, and even stock market returns. If WANTED’s models are really useful at helping to predict employment and economic activity, it makes little sense to give this away for free, when they could build a viable business line around their data. It now remains to be seen whether investors, consultants, analysts, and others are willing to pay for access to this data.