There’s a common joke that a financial or economic analyst’s forecast is about as useful as trying to predict the weather. While that’s a bit of an oversimplification, the latest jobs report from the U.S. Department of Labor reinforced that stereotype in spades. The results were bad — so bad, in fact, that not a single economist came close to predicting the fallout.

Only 38,000 jobs were added to the U.S. economy, well off the average consensus estimate of 161,000. The National Bank of Canada came closest to the mark, forecasting 90,000 jobs. Strangely, the best guesses came from foreign institutions. On the other hand — and perhaps unsurprisingly — the major American banking and financial firms put up an average forecast of 146,000 new positions added. Lower the total consensus, yes, but still, way off the actual figures.

Why did so many miss, and glaringly so? There are of course a multitude of reasons, but in my opinion, the primary ones focus on normalcy bias and monetary incentive.

First, most economists were likely making a linear calculation based on prior jobs data. In other words, they assumed that momentum begets momentum. That’s typically true among studies of several disciplines unrelated to the economy. It’s not necessarily bad, but it is a biased assumption. Momentum doesn’t last indefinitely — at some point, all bullish trajectories undergo a correction or even a permanent reversal.

Second, we have to acknowledge the monetary incentive of those that provide high-level, highly publicized forecasts. Note that foreign institutions were the decidedly more bearish forecasters. American firms, in contrast, saw the situation as a glass half-full. Again, being bullish is no moral defect per say. But in this specific circumstance, there’s an element of a conflict of interest. American firms would absolutely benefit if they were to “talk up” the markets, even if it wasn’t fundamentally sound.

But a third reason could be chalked up to plain ol’ laziness. A vast proportion of economists are fiscal historians. They operate under the aphorism “history repeats itself.” That is true, but on a grand scale. Against a more detailed scale, the aphorism falls flat. For example, we know that in casino gambling, the games are set up so that the house has an advantage. But on any given play, that broader understanding bears no guidance to the probability of winning or losing right now. To get that detailed probability would require detailed work. But why do that when you are given a public platform based on market capitalization rather than the actual validity of your work?

One easy statistic to point to could have been the stock market. The benchmark S&P 500 is flat over the trailing 52-weeks. If the labor market is so hot as the current administration claims, why doesn’t Wall Street buy into it? Another statistic is consumer sentiment. Why is it that the index is negative against where we were in the year-ago period? Shouldn’t the consumer be especially confident if the labor market is doing so well?

For American institutions, such discrepancies in data is no cause for concern. Sadly, we have to rely on foreign research firms to tell us a more accurate story.