Question for mailbag post: What risk metrics are you tracking for the possible hard landing scenario?
For example, policy makers and investors use different sets of tools in which they identify and measure risk.
The NBER uses its six indicators: real personal income less transfers, nonfarm payrolls, real personal consumption expenditures, real manufacturing and trade sales, household employment, and the index of industrial production.
Fundamental analysts might track inter-market relationships (like high beta/low vol, copper/gold, HY/TSY), credit spreads, credit card spending, mortgage data (defaults, ARMs), unemployment claims.
Technical analysts track metrics like breadth (new lows, A/D line, % above 10-DMA, 20-DMA, 50-DMA), momentum (RSI), sentiment, etc.
Corporations run VaR tests, banks run liquidity and stress tests, and large institutional investors like pensions and endownments run scenrio tests on their ALM and surplus.
I.e., did you come across some of these metrics elsewhere and decide to explore them more in-depth, did you hypothesize that they'd be informative because of reports you'd been reading, or something else? How much exploration do you do that doesn't lead to something tangible or interesting (i.e., how many charts do you create that don't make it into the post)? Is there a stock set of datasets that you know to turn to or do you also have to search for those pretty much from scratch?
For context, my research background is Cognitive Science, but I've gotten interested in the kinds of analyses/datasets used in Economics so I'm wondering how one even goes about coming up with a "question" to answer.
Given how high mortgage rates are and low levels of housing sales, the Fed is obviously not going to be close to their balance sheet reduction goals on the MBS front. Do you think they'll opt to sell MBS, allow more Treasuries to roll off to hit the overall target, admit that they just aren't going to hit the target and be fine with it or something else entirely?
You (or at least your publication via Alan) made the claim a while back that low inflation is here to stay for the long-term, even if not for the short-term. All manner of other prognosticators are now baking in the opposite prediction: that we’re in for a decade of high inflation. Do you think you were wrong then or that the other prognosticators are wrong now?
Question: I have a hypothesis that states that the continued manipulation of energy prices (oil) and the conversion of all currencies back to the dollar in the currency market means that there is no such thing as a “free market”. We operate within a rigged, highly geopolitical, hegemonic construct where there is no such thing as “true value”, just traded hegemonic economic war games.
Mailbag Q: What's a framework for thinking about how far we will get into a reduced or recession economy before unemployment starts to rise in a meaningful way?
1. How long a period should reporters use when talking about a company's profits (or losses)? I am tired of reading about record profits with no context of what period those apply to or any idea of what the last 5-10 years have looked like.
2. It seems to me that the 2010's were a period of pretty stable prices for many things. Yet, inflation seems to be calculated just based on comparisons to a year back, at most. What does inflation, particularly of specific things, look like now if done over a longer period? I remember thinking that real gas prices over much of the last decade were possibly lower than in the 1970's and 80's but I don't know. I have always struggled with putting things in 'real' (without regard to inflation) terms. Your insights on this would be much appreciated. This also applies ot 'record' profits.
There has been a lot of conversation about the excess savings that consumers built up during the pandemic, but not a ton about the savings "burn rate" by income level. From what I've read, it seems pretty clear that most of these savings were accumulated by higher income households, and that lower income households have already spent most of this excess (which makes sense given their MPC is higher).
How does this play out across higher income households (ie, if/when do their excess savings dry up)?
At what point do people stop thinking about the excess savings as "excess"?
Do recession expectations push consumers to hold more savings across all brackets?
I apologize for asking this out of the blue, but do you think it would be detrimental to tax automation and datamining? I know that many of the companies which use these practices have colossal profit margins, however would such taxation shift costs to the consumer, and if so, how much? I am also aware of the current negative externalities caused by automation (job loss) and datamining (infringement on privacy and reducing the ability of small businesses to start up) so I am curious what an economist would have to say about such things.
To put a little more focus on the term 'taxes', what I am asking about for Automation is to take the percentage of "work done by machines which have replaced humans which require little to no human oversight" and multiply it by 15%, which then would be the tax rate which would be applied to gross earnings. An example would be a company which has half of its work done through automation paying 7.5% of it's gross revenue in automation taxes.
Datamining would be a profit-based tax of 10% for engaging in the practice while increasing on a month-by-month rate of 0.333%. A company which engages in dataming for two years would pay a datamining tax rate of 18% ((10%+(24*0.333)), stacking with the corporate tax rate for a total of 39% (21+18).
What do you think about the topic of AI safety? A seemingly growing number of prominent people are worried that AI poses a massive risk to humanity's future--not just because of biased algorithms or technology-induced unemployment but because they worry AI will take over / run amok / turn us all into paperclips. Do you share these concerns?
Question for mailbag post: What risk metrics are you tracking for the possible hard landing scenario?
For example, policy makers and investors use different sets of tools in which they identify and measure risk.
The NBER uses its six indicators: real personal income less transfers, nonfarm payrolls, real personal consumption expenditures, real manufacturing and trade sales, household employment, and the index of industrial production.
Fundamental analysts might track inter-market relationships (like high beta/low vol, copper/gold, HY/TSY), credit spreads, credit card spending, mortgage data (defaults, ARMs), unemployment claims.
Technical analysts track metrics like breadth (new lows, A/D line, % above 10-DMA, 20-DMA, 50-DMA), momentum (RSI), sentiment, etc.
Corporations run VaR tests, banks run liquidity and stress tests, and large institutional investors like pensions and endownments run scenrio tests on their ALM and surplus.
So, what does Full Stack Economics look at?
Medicine is impotent in so many ways still. Are we spending enough on government-funded research? Maybe it should be doubled? X10?
How do I find a doctor wife to support my stay-at-home Substack writer lifestyle? It seems rather comfy
This might be way too broad of a question, but: how do you go about the early stages of research and planning for a quantitative post (like the 14 charts one: https://www.fullstackeconomics.com/p/14-charts-that-explain-americas-inflation)? The charts in that article (and in others you've written, e.g., https://www.fullstackeconomics.com/p/24-charts-that-show-were-mostly-living-better-than-our-parents) are really informative and to me, show the power of a great visualization.
I.e., did you come across some of these metrics elsewhere and decide to explore them more in-depth, did you hypothesize that they'd be informative because of reports you'd been reading, or something else? How much exploration do you do that doesn't lead to something tangible or interesting (i.e., how many charts do you create that don't make it into the post)? Is there a stock set of datasets that you know to turn to or do you also have to search for those pretty much from scratch?
For context, my research background is Cognitive Science, but I've gotten interested in the kinds of analyses/datasets used in Economics so I'm wondering how one even goes about coming up with a "question" to answer.
What do you make of canada's plan to self-immolate? https://twitter.com/HoCStaffer/status/1575208419115794432?s=20&t=bXx0WiC1rmlGBng0zhu5-g
What are the distributional effects of inflation?
I've been seeing a lot of memes like this: https://twitter.com/maiamindel/status/1575160972234280965?s=20&t=1l2RiVd1yLPWUc32ERDF5w
What do you think of big-picture history/economics books, or GG&S specifically? Are they over-rated?
Given how high mortgage rates are and low levels of housing sales, the Fed is obviously not going to be close to their balance sheet reduction goals on the MBS front. Do you think they'll opt to sell MBS, allow more Treasuries to roll off to hit the overall target, admit that they just aren't going to hit the target and be fine with it or something else entirely?
You (or at least your publication via Alan) made the claim a while back that low inflation is here to stay for the long-term, even if not for the short-term. All manner of other prognosticators are now baking in the opposite prediction: that we’re in for a decade of high inflation. Do you think you were wrong then or that the other prognosticators are wrong now?
Question: I have a hypothesis that states that the continued manipulation of energy prices (oil) and the conversion of all currencies back to the dollar in the currency market means that there is no such thing as a “free market”. We operate within a rigged, highly geopolitical, hegemonic construct where there is no such thing as “true value”, just traded hegemonic economic war games.
Hi. Check this out and happy to chat if it fits the bill.
https://albellenchia.substack.com/p/to-serve-man
Mailbag Q: What's a framework for thinking about how far we will get into a reduced or recession economy before unemployment starts to rise in a meaningful way?
Here's a couple of topic ideas for you:
1. How long a period should reporters use when talking about a company's profits (or losses)? I am tired of reading about record profits with no context of what period those apply to or any idea of what the last 5-10 years have looked like.
2. It seems to me that the 2010's were a period of pretty stable prices for many things. Yet, inflation seems to be calculated just based on comparisons to a year back, at most. What does inflation, particularly of specific things, look like now if done over a longer period? I remember thinking that real gas prices over much of the last decade were possibly lower than in the 1970's and 80's but I don't know. I have always struggled with putting things in 'real' (without regard to inflation) terms. Your insights on this would be much appreciated. This also applies ot 'record' profits.
There has been a lot of conversation about the excess savings that consumers built up during the pandemic, but not a ton about the savings "burn rate" by income level. From what I've read, it seems pretty clear that most of these savings were accumulated by higher income households, and that lower income households have already spent most of this excess (which makes sense given their MPC is higher).
How does this play out across higher income households (ie, if/when do their excess savings dry up)?
At what point do people stop thinking about the excess savings as "excess"?
Do recession expectations push consumers to hold more savings across all brackets?
I apologize for asking this out of the blue, but do you think it would be detrimental to tax automation and datamining? I know that many of the companies which use these practices have colossal profit margins, however would such taxation shift costs to the consumer, and if so, how much? I am also aware of the current negative externalities caused by automation (job loss) and datamining (infringement on privacy and reducing the ability of small businesses to start up) so I am curious what an economist would have to say about such things.
To put a little more focus on the term 'taxes', what I am asking about for Automation is to take the percentage of "work done by machines which have replaced humans which require little to no human oversight" and multiply it by 15%, which then would be the tax rate which would be applied to gross earnings. An example would be a company which has half of its work done through automation paying 7.5% of it's gross revenue in automation taxes.
Datamining would be a profit-based tax of 10% for engaging in the practice while increasing on a month-by-month rate of 0.333%. A company which engages in dataming for two years would pay a datamining tax rate of 18% ((10%+(24*0.333)), stacking with the corporate tax rate for a total of 39% (21+18).
What do you think about the topic of AI safety? A seemingly growing number of prominent people are worried that AI poses a massive risk to humanity's future--not just because of biased algorithms or technology-induced unemployment but because they worry AI will take over / run amok / turn us all into paperclips. Do you share these concerns?