What Are Base Effects?
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It is a very important consideration when you're looking at any incoming data. It's important because the base effect can skew the current or incoming reading that you get.
So, base effects in our videos or reports you will from time to time hear or see us referring to base effects and its implications for incoming data. And it's actually a very simple concept to understand but it is a very important consideration when you're looking at any incoming data. So, economic data is often measured as expressed as a month over month figure or a 1/4 on 1/4 figure or a year on year figure.
When you look at a data point let's say it's monthly CPI data, and like we have on this chart your month on month or your month over month, data measures how much higher or how much lower CPI is in the current bundle the whatever month you're tracking compared to the prior month, so, if you're tracking May CPI data you comparing that to the CPI in April, basically seeing whether it came in higher or lower compared to the prior month.
Similarly, when you're looking at quarterly data you're comparing the prior 1/4 to the current one you're looking at. When you're looking at year over year, you're obviously looking at the prior year's data compared to the current data that you're looking at. Now, why are the base effects important? It's important because the base effect can skew the current or incoming reading that you get.
Let's take a recent example, like Texas where we had all of that bad weather the blizzard hitting Texas with large parts of it shutting down. There was obviously... That was an unforeseen event where something that nobody saw coming. But as a result of that you saw a big disruption in business coming out of Texas. And that means that the growth data, the CPI data all of the data that we got from Texas for that month will obviously be much lower than they usually are.
So, when you get the next month data like we had this month comparing back to last month once business has resumed and it's back to normal the month on month or data of the next month will obviously look much better than it actually is, just because the prior month's data was skewed by whatever event it was. Sometimes it might be seasonal factors.
A very good example of this has been the pandemic in 2020 which has distorted so many of our year over year and 1/4 over 1/4 data points over the past couple of months. And now that we are going into 1/4 two of 2021, the base effects are going to potentially give us some grating numbers coming out. So, let's take CPI while we're on the screen, US Core PCE, as an example, it has been distorted obviously by 1/4 to the massive lock-downs that we have had coming out across the globe, not only in the US of course across the globe, but looking at US data, we had a huge drop to the downside in Core PCE in the second 1/4 of the year. And the main reason for that, like we said was the pandemic, was the economy shutting down.
Having this as a super low base, obviously comparative to where we coming from having this as our base for the year over year numbers, once we get to May, 2021 or June, 2021 and July, 2021 there's a very good chance that we'll see upside surprises in the year-over-year numbers purely just based on the base effects alone because you're coming from such a low base.
Now that the economy is running a lot stronger, businesses are running much higher and much stronger than we were running back in May, June and July, because of that, because of incoming fiscal stimulus, etc, there's a lot of anticipation that not only based on the base effects, but based on other measures we gonna see some potential upside surprises in something like CPI data.
Now, it's this base effect which causes some data points to be released with seasonally adjusted figures to basically try and counteract any drastic skews which might pop up in the data from prior months or quarters with seasonal factors like the festive period could drastically affect the outcome.
Because a very low base effect can make the incoming data look much better than it really is, and a very high base can make the incoming data look a lot worse than it really is, it's very important for us to always consider whether we are coming from a very low base or very high base when comparing incoming data.
Any other questions don't hesitate to let us know.
-----
If you find this content helpful, you’ll love Financial Source.
There’s a link below were you can learn more about it
https://financialsource.co
Why Professional Traders Use A Forex News Feed To Trade - https://youtu.be/EQnphXBffBQ
Always stay on the right side of the market and know what to trade every day. Sign up for a FREE TRIAL:
https://financialsource.co
------------------------
It is a very important consideration when you're looking at any incoming data. It's important because the base effect can skew the current or incoming reading that you get.
So, base effects in our videos or reports you will from time to time hear or see us referring to base effects and its implications for incoming data. And it's actually a very simple concept to understand but it is a very important consideration when you're looking at any incoming data. So, economic data is often measured as expressed as a month over month figure or a 1/4 on 1/4 figure or a year on year figure.
When you look at a data point let's say it's monthly CPI data, and like we have on this chart your month on month or your month over month, data measures how much higher or how much lower CPI is in the current bundle the whatever month you're tracking compared to the prior month, so, if you're tracking May CPI data you comparing that to the CPI in April, basically seeing whether it came in higher or lower compared to the prior month.
Similarly, when you're looking at quarterly data you're comparing the prior 1/4 to the current one you're looking at. When you're looking at year over year, you're obviously looking at the prior year's data compared to the current data that you're looking at. Now, why are the base effects important? It's important because the base effect can skew the current or incoming reading that you get.
Let's take a recent example, like Texas where we had all of that bad weather the blizzard hitting Texas with large parts of it shutting down. There was obviously... That was an unforeseen event where something that nobody saw coming. But as a result of that you saw a big disruption in business coming out of Texas. And that means that the growth data, the CPI data all of the data that we got from Texas for that month will obviously be much lower than they usually are.
So, when you get the next month data like we had this month comparing back to last month once business has resumed and it's back to normal the month on month or data of the next month will obviously look much better than it actually is, just because the prior month's data was skewed by whatever event it was. Sometimes it might be seasonal factors.
A very good example of this has been the pandemic in 2020 which has distorted so many of our year over year and 1/4 over 1/4 data points over the past couple of months. And now that we are going into 1/4 two of 2021, the base effects are going to potentially give us some grating numbers coming out. So, let's take CPI while we're on the screen, US Core PCE, as an example, it has been distorted obviously by 1/4 to the massive lock-downs that we have had coming out across the globe, not only in the US of course across the globe, but looking at US data, we had a huge drop to the downside in Core PCE in the second 1/4 of the year. And the main reason for that, like we said was the pandemic, was the economy shutting down.
Having this as a super low base, obviously comparative to where we coming from having this as our base for the year over year numbers, once we get to May, 2021 or June, 2021 and July, 2021 there's a very good chance that we'll see upside surprises in the year-over-year numbers purely just based on the base effects alone because you're coming from such a low base.
Now that the economy is running a lot stronger, businesses are running much higher and much stronger than we were running back in May, June and July, because of that, because of incoming fiscal stimulus, etc, there's a lot of anticipation that not only based on the base effects, but based on other measures we gonna see some potential upside surprises in something like CPI data.
Now, it's this base effect which causes some data points to be released with seasonally adjusted figures to basically try and counteract any drastic skews which might pop up in the data from prior months or quarters with seasonal factors like the festive period could drastically affect the outcome.
Because a very low base effect can make the incoming data look much better than it really is, and a very high base can make the incoming data look a lot worse than it really is, it's very important for us to always consider whether we are coming from a very low base or very high base when comparing incoming data.
Any other questions don't hesitate to let us know.
-----
If you find this content helpful, you’ll love Financial Source.
There’s a link below were you can learn more about it
https://financialsource.co
