Moody's makes statement on US debt and it is not good

 

Moody's rating agency lowered its US debt rating to negative from stable. It is still triple-A although S&P has rated the US as AA+ since 2011 and Fitch downgraded the US to AA+ in August.  In its view, downside fiscal weakness has increased from continued political polarization. Deficits have continued and the interest costs now exceed $1 trillion annually, so there is less room to maneuver. With the continued debt ceiling cap, the political process will continue to have uncertainty. Eliminating the debt ceiling cap will not solve anything other than causing any debt management to be pushed further into the future without any fiscal responsibility.

Moody's expects federal interest payments relative to revenue and GDP to rise to around 26% and 4.5% by 2033, respectively, from 9.7% and 1.9% in 2022. These projections factor in Moody's expectation of higher-for-longer interest rates, with the average annual 10-year Treasury yield peaking at around 4.5% in 2024 and ultimately settling at around 4% over the medium term. The debt affordability forecasts also take into account Moody's expectations that, absent significant policy changes, the federal government will continue to run wide fiscal deficits of around 6% of GDP near term and to around 8% by 2033, the widening being driven by higher interest payments and aging-related entitlement spending. By comparison, deficits averaged around 3.5% of GDP from 2015-2019. Such deficits will raise the US federal government's debt burden to around 120% of GDP by 2033 from 96% in 2022. In turn, a higher debt burden will inflate the interest bill.

Of course, there is still the fundamental question - do deficits matter? The answer is that they do, except we don't know when or at what level. We may not know it until we hit that critical level but at that time it will be clearly too late. We do know that we are on a path that will take us to that critical level. Just because it has not mattered, does not mean it will not matter.

The divergence between economic expectations and reality - which is right?

 

Economists are failing with their forecasts and one of the reasons is that what is expected form the data is not matching consumer sentiment from surveys. Usually, pre-pandemic, the survey data gave us a good look at what might happen in the future. Now, we have more pessimism from surveys. The correlation or direction seems right but there is a level of caution that suggests something is wrong with consumer thinking. There is spending but it has not caused a sense of optimism. You could say that this is a carryover from the pandemic, which is true. However, saying this does not help explain the root cause or how this gap may be closed. The survey to hard data gap is something that is adding to market uncertainty. Who is to say which is right?

The Kolb Learning Model and Investments

 

The Kolb Learning model is a simple four-point approach to improving the learning experience. Start with some specific experience, which should lead to some reflective observations. What did you feel? Then, what did you see? 

The observing must be then placed in context which is conceptualized thinking. The thinking finally must be converted into action, or active experimentation which will, of course, lead to a new experiences. This is often referred to as Experiential Learning Theory (ELT). People learn by direct experience and is an effective way to teach young students. It is a learning style.

This is not different from following any scientific hypothesis testing. See, observe, conceptualize or hypothesize, and then test. Yet, it is useful to form simple frameworks for thinking based on our direct experience. 

The Kolb learning model or ELT can also be used with making investment decisions through linking a specific observation or experience to forming a hypothesis. 

Turning wrong into right

 

Investing is about failure. You are more likely to be wrong than right. Some will say that a great investor is one who is at most 60% right. It seems natural that we should spend more time on faults, errors, and failure. Change failure into success or at least a learning opportunity may make all the difference in the world. 

This topic is addressed in Amy Edmondson's Right Kind of Wrong: The Science of Failing. Written by an HBS professor, there are a lot of good stories of failure and what can be learned, but the core work is based on the serious research that all failures are not the same. Classify failure and we can do a better job of avoiding.

Failure is an outcome that deviates from desired results. Errors or mistakes are unintended deviations from prespecified standards. Violations are intentional deviations from rules.  We want to avoid violations, minimize errors, and learn from failure.

All failures are not the same. There can be good and bad failures. Good failures are necessary for progress. From good failures come discoveries. Basic failures are caused by mistakes that can be avoided, but there are also complex failures that are driven by multiple causes. 

Because we have aversion to failure and mistakes we try to avoid them and hide them under the rug. Let's not talk about mistakes. Hence, there is little opportunity for learning. 

Effective teams may see more mistakes because they are more willing to report failures and learn from them. They are open to learning from mistakes. The important point is to try and classify failures and focus on the why and how it can be avoided in the future. Is the failure systemic to the procedure used? Failures occur because rules are not followed, or the wrong rules are in place. Other failures can be associated unexpected events, which require a different mindset. There are also failures associated with new discovery, intelligent failure from dealing with high uncertainty allows for strong learning. 

We will all make mistakes. The question is whether we can stop basic failures and learning from complex and intelligent failures.