The Leading Indicator: Lessons from Trends in Credit & Household Debt Accumulation

The Leading Indicator:

Lessons from Trends in Credit & Household Debt Accumulation

Justin Sherwood

California State University, Chico

I wrote this essay during my final semester of college in April and May of 2021. My computer hard drive crashed shortly after I had finished it. Fortunately there was a not too old draft that was saved to my Onedrive and I was able to retain what you see below.

There are likely to be a few errors because I have not bothered to go through and re-proof read it since I won’t be turning it in again. Nonetheless, the information that remains in the document should be useful to economically curious readers.

I hope you enjoy the read I think you will find that its contents show an increasing need to re-evaluate the current structure of the American economy. The information analyzed by this essay should serve to increase the sense of urgency among policymakers to make appropriate adjustments to their decision making process.


             When the housing bubble burst between 2006 and 2008, it sent shockwaves throughout the economy and caused a financial crisis. Policymakers had to begin using extensive and, in some cases, novel monetary and fiscal policy tools in order to protect the system from breaking itself.

            The problem started when a few highly influential financial institutions became overleveraged starting with a series of loan defaults. These defaults were on loans held within financial instruments called mortgage-backed securities along with other collateralized debt obligations. Simply put, both mortgage-backed securities and collateralized debt obligations are packages of separate loans that are sold as a group. The simultaneous default on many of these loans created a liquidity crisis for United States banks which rippled throughout the entire U.S. economy.

            Packaged loans were analyzed by private rating agencies which judged the entire package as a group. Ratings agencies allowed banks to buy loans based on the aggregate rating of the package and save money on individual appraisal costs. If one loan within the package was rated as being high risk, even if the borrower defaulted, a bank still expected profits from the low-risk loans within the package. The crisis occurred when bad mortgages began to default. Banks were trapped in a liquidity squeeze where many institutions needed to borrow short term funds. Simultaneously none of the U.S.’s financial institutions were willing to lend the necessary funds to banks in need of immediate assistance.  

            Using extensive fiscal stimulus and active monetary policy, the federal government alongside the Federal Reserve stopped the bleeding of the financial system. They did this through what was called the Troubled Asset Relief Program, or TARP which gave the treasury a hidden “bazooka” as Hank Paulson, then Treasury Secretary liked to call it. Congress granted him essentially unlimited funds by the end of all related hearings. Concurrently the Federal Reserve implemented policies like Quantitative easing which allowed it to purchase bad assets like delinquent home mortgages directly from banks to keep the prices of homes from falling.

            The United States economy has been back on a path of GDP growth for most of the years since the recovery from the financial crisis began as shown in Figure 2. However, this growth has been unimpressive and slow which is a leading indicator for a phase change in the long-term business cycle as I will discuss in the results of this research paper.

            All of the actions I mentioned above taken by policymakers have kept borrowing costs low and asset prices high while the economy recovered from the previous crisis before the pandemic. These actions also stimulated circulation in the economy which supported growing incomes. As shown in Figure 1, household debt to GDP followed a general downward trend beginning in 2009 after the fallout of the financial crisis. That downward trend appeared to be ending in 2019. When the Coronavirus pandemic hit, the downward trend fully reversed and skyrocketed upward within a single quarter.          

            Recovery was feasible in the wake of the financial crisis in large part because of the federal reserve’s ability to lower interest rates. Prior to the crisis, rates were above 5% during that business cycle. Due to the severity of the crisis, they dropped almost instantly to near 0% reaching a trough at just .07%! Record low interest rates increased access to credit throughout the economy. Massive government deficits were also a factor in the recovery. The government had to run these deficits in order to curb inflation. If they sell a bond, they can spend money while taking money out of the economy in order to prevent inflation. Keeping inflation low and returning GDP to an upward trend were the goals and monetary and fiscal policy tools worked for us in 2008.


            The Coronavirus pandemic caused a severe and immediate reduction in GDP that far exceeded the loss of GDP which occurred during the financial crisis during the last recession. If GDP growth is meant to be the primary indicator of a healthy economy, then why did the financial crisis seem more economically catastrophic than the shocks caused by the Coronavirus? Monetary policy tools were already reaching their maximum capacity to affect the economy prior to pandemic hovering consistently just above 0% and not exceeding 2.42 percent since before the financial crisis hit full swing in 2008. Further, the federal government has continued to sustain deficits year after year since the financial crisis and is far more overleveraged than it has ever been. So, to restate my question. What made this version of our economy seem less in danger of collapse than the one we witnessed during the financial crisis? After I answer this question, I further explore whether or not policy interventions successfully averted the long-term dangers to the U.S. economy that were uncovered during the financial crisis.

            This paper contributes to economic literature in two ways. First, the research draws insights into the changing nature of economic outcomes based on unprecedented fiscal and monetary policy interventions. Second, the research offers evidence to support the related literature which tends to suggest that debt cycles follow predictable long-term patterns.

            Examining credit card and household debt is an important element of this economic analysis. This acts as a proxy for the “rational decision maker” assumption underlying much of the established economic theory. If individuals are rational decision makers, then presumably individuals and households will not choose to take on more debt than they are able to pay back in the long run. After the financial crisis the rational-decision-maker framework was brought into question, and I want to discover just how irrational we have become as a society.

            I cite three authors; Barlevy, Jennings, and Kim to show the linkage between household debt proliferation and severe contractions in GDP. I juxtapose their assessments of household debt with the response by policy officials to the financial crisis of 2006-2008 to show that despite monetary and fiscal policies best efforts, the crisis was not truly avoided. Instead, it was perturbed, fixing the short-term liquidity problem at the time, but leaving the U.S. economy vulnerable to undesirably high inflation or a significant drag on GDP growth over the next few business cycles.

Literature Review:

            In the Crisis and The Asset Driven Household, Jake Jennings finds credit supply has been kept up by an asset driven wealth effect. Jake shows that “Increased access to credit from asset price inflation, even if they do not own the assets, are sustaining lower and middle-income households” (Jennings). The piece starts by pointing to the flaws in Freidman’s theory on the relationship between household consumption and spending.

            Established economic literature suggests increases in access to credit is made possible by increases in household net worth. Jennings draws a correlation between rising household net worth and declining savings rates. Since the 1980s the ratio of household savings to disposable income has followed a general downward trend.

            Notably, as savings rates have declined, we have also seen a decline in household financial obligations as a percentage of disposable income as shown in Figure 4. Households are earning more in comparison to their debt load, therefore there is still some degree of truth to Friedman’s Permanent Income Hypothesis (PIH) and Modigliani’s Life Cycle Income Hypothesis (LCIH). This indicates that low borrowing costs are attracting individuals with sufficient incomes to service increased household debt loads.

            Jake properly criticizes the rational decision maker assumption that these economists held. Specifically, their assumptions were that households would tend to save enough of their income to be proportionate with their “lifetime spending and utility” (Jennings 2018). This criticism is valid, as Jake points out since household debt to income ratios have been rising for all of the past 64 years since the PIH for example was first hypothesized up until the Financial Crisis appeared to shock some sense into people.

            The author cites Mian et. Al. to show that household net worth can also rise when the assets that a household owns go up. The wage share of income ratio has dropped precipitously since the 1970s. Meanwhile the consumption to income ratio has tracked upward. In other words, people are relying increasingly on debt to consume. However, as mentioned earlier, incomes have risen compared to household financial obligations to somewhat justify this phenomenon when viewing it through a macroeconomic lens.

            Jake concludes his paper by reaffirming its views of the puzzling state of household debt to income ratios in the U.S. Concluding that, “the relationship is simply an artificial effect from excluding asset price revaluation in household saving.” He shows a relatively flat line in net household savings to income rate compared to a declining net worth to disposable incomes top drive his point home.

            From the University of Massachusetts, in a paper titled Macroeconomic Effects of Household Debt Y.K. Kim shows the connection between increases in household debt burdens and the severity of economic downturns.

            He posits that increased access to credit does drive growth but eventually the debt service payments get high enough to require borrowers to spend less on consumption and thus output level decreases as well. Kim notes that the problem lies with how the debt burden is shared. In times when household debt accumulates faster than normal, rentiers also end up with a higher distribution of income and these individuals tend to have a higher propensity to save.

            Kim along with many other economists became interested in this topic as a result of Hyman Minsky’s Financial Instability Hypothesis. Minsky’s idea was that debt financed spending proliferates during boom periods, but eventually debt to income ratios become too high and leave the system vulnerable to economic shocks. Kim cites previous research into Minsky’s ideas by Cynamon and Fazzari who find that debt financed household spending provides additional economic stimulus during certain periods, but eventual excesses negatively affect consumption and outputs level in the long run, staying in line with Kim’s initial assertions.

            Kim approaches his research with the theoretical framework of debt-driven business cycles. Which is a largely acknowledged economic framework by economists as it increases circulation and incomes and tends to cause market actors to offer lower prices to reach more customers. His goal is to empirically differentiate the short run and long run impacts of debt on GDP. He starts by defining his terms and expressing the individual data points the research uses to analyze the problem. Like Jake’s research, Kim focuses on the three variables of GDP, debt, and net worth. He separates the data out a bit to see if he can determine if certain areas of debt composition results in different outcomes.

            Through a series of regression tables the author, the author shows that for consumer, household, and mortgage debt, rate shocks are associated with an increased growth rate of GDP. Looking from the other direction, GDP is associated with an increase in all of the specific debt measurements I just named. This seems to suggest upon first look that they are coexisting phenomena. Meaning that for GDP to go up, debt statistics must go up, and for debt statistics to go up, GDP has to go up.

            Kim’s findings are in line with previous research mentioned earlier which shows that there is a credit driven cyclical process by which GDP goes up in the short run but creates a long-term risk factor for growth in the long run. The specific variable of household debt appears to be most significant according to the author. Stating, “we observe a bidirectional positive feedback process between aggregate income and debt accumulation” (Kim 131).

            Kim adds consumption as a fourth variable for his tests. Consumption should be the element of GDP which would suffer as a result of lowered long run output, so it is an important consideration in the model. He also considers mortgage debt as an individual variable to make the point that particular elements of household debt are more significant than others.

            The author finds a problem with one cointegration test in his model (Kim 139). The model finds that consumer debt does not show a statistically significant positive effects on growth rates within shorter lag periods even though it does show negative effects at the third lag as the author anticipated. When Kim tried to use multiple cointegrating relationships there was a further complication. He notes that because household debt is already considered in the calculation of net worth, it needs to be measured with identification restrictions on every cointegrated vector. However, this is accounted for as the paper progresses and when net worth and household debt were measured as separate cointegrating vectors the long-run relationship in the model is preserved.

            One limitation of the study is the significance value for net worth determined by the author. This was one of his three primary variables if you remember. He uses a 10 percent statistical significance framework which I consider to be unsatisfactory for an empirically analyzed data set. However, in terms of economics, the observed effects are human behaviors which are difficult to calculate with true accuracy mathematically. So, it is easy to forgive this writer for choosing that level of significance. In the sixth data set there is also a weak exogenous relationship that may cause a statistical error in some areas. Specifically, when measuring consumption, the author notes that all variables other than consumption don’t significantly adjust to short-run variations from the equilibrium.

            This research is significant because as opposed to previous models, the author assumes a constant relationship between the variables rather than a linear one. Meaning that the variables follow significant interrelated trends but may not occur simultaneously. This is an important consideration for my findings later in the paper regarding the long-term debt cycle. Across multiple measurements, including replacing net worth with total household assets, the results are consistent. GDP is correlated with household debt in the long run.

            The authors results are not meant to suggest any truth to Minsky’s financial instability hypothesis though they are in line with its assumptions. Kim argues that in order to prove Minsky’s hypothesis, much more complex and diversified relationships must be analyzed on a broader scale than his work does in this paper. Overall, this paper does well for its goals. It shows a strong interrelationship between household debt and GDP. It does not prove empirically its chronological implications, however. It would be more helpful to my research if it did show chronological significance since I am attempting to form chronologically based predictions.     Kim’s research shows that there is a strong relationship between household debt and short-term growth. The research had hoped to show some evidence could be used to support Minsky’s financial instability hypothesis, but the author believes the results are insufficient to do so. The author points out that the problem with empirically proving Minsky’s financial instability hypothesis stating, “There are other factors that may work to contain the effect of household debt explosion (for example, central bank monetary policy or financial sector regulation)”(Kim 141).

            The third author I am going to analyze is Gadi Barlevy. His paper is called Economic Theory and Asset Bubbles. The author paints a picture wherein policymaking efforts seem to be strictly redistributive. Unless policy provides a market efficiency this author believes it is antithetical to the goals of policymaking bodies in the U.S to involve themselves in market functions. He notes that policy is typically aimed at curbing the catastrophic side effects of asset bubbles being created and quickly losing value over a short period of time. Given this fact, the author wants to know how policymaking actually effects the creation of the phenomenon we call asset bubbles.

            He starts by providing background into historical asset price rises. He first points to the large downturn in the stock market following the bursting of the dotcom bubble. This bubble built up during the 1990s and crashed at the end of the decade. Technology stocks surged as some people began to believe in the future of an internet economy. They quickly fell once people began to look for where they could create actual profit streams within these companies. This was written in 2007 and he also notes the downturn in housing growth starting in 2006 as a possible cause for concern. Just one year after this paper was published housing prices were proven a worthy issue to consider.

            The paper begins by the author clarifying the definition of an asset bubble. The press typically overuses the phrase, so the public often misunderstands the definition. A bubble must eventually burst in order to be a bubble after all. The author quotes an economist named Kindleberger who defines the phenomenon as “an upward price movement over an extended range that then implodes.” The author argues that the fundamental value of money “should be zero”(Barlevy 49). The idea is that money itself is a bubble. He understands this is going to be a strange definition to many people and recognizes that money does offer a capital gain. Instead of a financial capital gain however, the author argues the gain is in the utility of the money. Money plays a useful role so he is not arguing that money is literally valueless but that the paper itself has an inherent value of zero.

            For the sake of clarity, the rest of the article specifically defines its use of the word “bubble”. From here on the author means, “an asset whose price cannot be justified by the value of the dividends that society expects to earn from this asset class collectively” to define the word “bubble” (Barlevy 49).

            In order to prevent these significant asset price corrections from occurring the author notes public calls for regulation. However, previous studies have shown that these kinds of policies can be more harmful than the problems they intend to mitigate. One problem is that misevaluation by policy makers could lead to asset prices being problematically suppressed. In other words, they may suppress an asset value that was actually properly priced. Furthermore, He cites a 1999 paper by the previous federal reserve chairman Ben Bernanke and his colleague Gertler which points to the effects such regulations could have on the ability of the federal reserve to properly shape inflation.

            A problem arises in terms of appraisal. When one person sells an asset, they are anticipating that its future value will be less than what it is now, and the buyer is assuming it will have greater value in the future. Obviously, this is not inherently true as some people buy cars and intend to sell them later for some value but do not anticipate receiving the full price, they paid for it in return for its future sale. It is also somewhat of a truism though when talking about specific assets like stocks which someone is expected only to buy as an investment. Speculation is one of the primary problems in determining the seriousness of an asset bubble. If investors are always fully informed and understand their holdings’ value, they would not sell an undervalued asset nor buy an overvalued one.

            The author criticizes three traditional views of bubbles in economics. He challenges three major assumptions: Infinitely many traders, differences in initial beliefs and the possibility of irrational traders, and inefficiency. Infinitely many traders assumes that all players in the game are essentially playing a game of hot potato. In order for there to be a bubble we would assume that someone is always expecting to sell something based on its value to someone else. Meaning that an overvalued asset would always be liquidated by a statistically significant number of owners of that asset if its market value drops. So, every owner would have to assume that they are selling something to someone who will get less value out of it in the future than it is worth today. Coincidentally every buyer would have to assume that they are buying something from someone who could have gotten more personal value from it later.

            The author’s second criticism of bubbles is differences in initial beliefs and the possibility of irrational traders. Here he describes a study which involved college undergraduate students with perfect information about a market and an incentive to trade responsibly. The students still created a bubble where they appraised an asset higher than its fundamental value. The incentive of the experiment was that each student would be able to keep whatever net profit their trading strategies provided. He cites many examples, and in each there are catastrophic mistakes by individuals in a given study. One study by Harrison and Kreps (1978) found that “One of their results shows that an asset can trade for more than what any one trader in the economy believes the fundamental value should be, even the trader with the most optimistic view of dividends” (Barlevy 51).

            The final criticism he makes is about the inefficiency element of bubbles. When traders inefficiently allocate resources, this means they are willingly buying something today that they know will be worth less in the future. The author believes policymakers to understand the inefficiencies underlying a bubble in order to properly combat its dangers.

            One major limitation of this paper is in the way the argument is framed. The author essentially argues that for policy to make sense it must be on the basis of being good for the whole society rather than for one particular group or individual. This means that policy interventions must benefit everyone. What he fails to consider is if policy interventions, despite hurting some groups for the benefit of others in the short run, could potentially benefit everyone in the long run. This is a particularly important consideration since the author is discussing U.S. policymaking.

            Franklin D. Roosevelt famously wrote, “The liberty of a democracy is not safe if the people tolerated the growth of private power to a point where it becomes stronger than the democratic state itself. That in its essence is fascism: ownership of government by an individual, by a group, or any controlling private power.” He has since been said by many to have saved capitalism. I am not agreeing or disagreeing with this belief, but it should be considered. Afterall this is a man who enforced one of the greatest wealth redistributions of all time. The author makes unperfect policymaking efforts out to be fundamentally redistributive and beneficial strictly to those who resources are redistributed to.


            The household debt to GDP ratio followed a general downward trend since the onset of the financial crisis until the coronavirus pandemic broke everything as shown in Figure 3. Shortly after its assent during the initial lockdowns, the data appeared as though it might have already returned to its regular downward trend between Q2 & Q3 of 2020. This correlates with the implementation of massive fiscal stimulus between March and May of 2020. Since the money takes time to spend, there is some natural lag time between the implementation of stimulus packages and their effects on the economy. At the conclusion of Q4, that flat slightly upward sloping line indicates that households will most likely remain dependent on fiscal stimulus for the household debt burden to return to its general downward trend going forward unless removing lockdown restrictions causes incomes to go up or debt burdens to fall. The government has not indicated recently that it is planning on implementing any new stimulus packages. It is important to note that not all of the money has been spent from the previous ones. However, much of it has been spent and the primary effects of the package on households has likely already played out as direct payments to households and individuals have already gone through.

            Government spending is “G” in the equation for calculating GDP. In other words, the more the government spends, the higher the economy’s income will be. That is unless rampant government spending signals to households that they should reduce personal spending or investment expenditures. This could happen for several reasons. Fear over potential inflation as a result of too much government spending is one factor that can be linked to reduced investment and consumption expenditures. Contrarily, expenditures in these areas could also be spurred by the government reducing its spending because reduced future earnings expectations are also linked to reduced consumption and investment expenditures and much of the incomes in the United States are made possible by G in GDP, AKA government spending.

            Government spending was already on a continual incline leading up to last year’s shock to GDP which means the primary contributors of the most recent decline must be attributed to slowing investment and consumption expenditures. GDP quickly returned above previous highs within the same year of the Coronavirus crash as shown by the FRED chart in Figure 1. Monetary and fiscal policy officials showed that the same tools used during the financial crisis, seemed to have averted a persistent recession once again.  However, it is this researcher’s belief that we are not out of the woods yet.

            As you can see in Figure 3, nonfinancial credit liability levels have been on a steady incline since the 1970s and the line is only growing steeper in recent years. As a big part of that as shown in Figure 4, households and nonprofit organizations have seen increasing credit liability levels over the same time period. There was a significant reversal immediately following the financial crisis causing consumers and nonprofits to reduce their overall liability levels slightly every quarter until Q1 of 2013 (Figure 5). The upward trend has otherwise roughly kept its course since. When there is an increased demand for credit, households are considered to be optimistic about their future earning potential or are taking advantage of low borrowing costs (Zabai, Anna. 2017).

            Households may have cause to assume increasing incomes. Certain government policies, like the gigantic fiscal stimulus packages that have already been passed in response to the pandemic, but not been fully spent will likely raise wages. There has also been a lot of talking between politicians about proposing legislation to increase minimum wage rates at the federal level. Alongside near 0% interest rates keeping borrowing costs low, wages will necessarily rise. If wages increase, borrowers will have a greater ability to pay off their debts. However, this simplification of the problems we face does not take into consideration the inflationary effects such actions will have.

            Back in March, the Federal Reserve estimated a 6.5% growth rate for the United States economy in 2021. Why would they maintain low interest rates when the economy is on this kind of a growth trajectory? They also estimated just barely above 2% inflation for the year, which is just above its targeted rate. If Jerome Powell is following his predecessor’s knowledge, I can only assume that the Federal Reserve is still trying to prevent deflation by keeping interest rates low (Bernanke 2002). This would mean that the federal reserve is concerned about prices in the economy decreasing. The concern stems from what can be boiled down to the association between price deflation and extended periods of slow GDP growth (Bernanke 2002). 

            If the federal reserve is only assuming 2% inflation while projecting 6.5% growth, they are assuming that producers and service providers whose products and services are included in the Consumer Price Index’s basket of goods are not going to factor in increases to the money supply to the final sale price of their products and services. At least not sufficiently to match the increase in circulation that such policies are projected to generate to justify the higher than usual GDP growth rate.

            When the inflation and growth projections I just mentioned were formulated, the economy was still suffering under government lockdown policies. Those policies are in large part still in place today. As we approach herd immunity, government officials are signaling that lockdown procedures will be significantly reduced in the coming few months. What happens when all of that pent up demand which was temporarily stifled by lockdowns gets released back into the economy? Won’t producers be able to increase prices on their final products when a flood of buyers hit the market with low interest rates and government money still generating massive cash flows all around the economy?

            Consider the M1 Money Supply measurement, which the Federal Reserve conveniently discontinued during the initial months of the Coronavirus pandemic. In Figure 4 we can see that the M1 Money Supply has skyrocketed since the onset of the pandemic. This is in large part due to the way that the Federal Reserve changed this measurement when they discontinued it in May of last year. Since then, they take into account “other liquid deposits” on top of the traditional measurements (“M1 Money Stock (DISCONTINUED)” 2021). However, this seems to have provided a simple way to cover for the fact that M1 was already on a significant upward trajectory in April following the initial government stimulus which gave M1 measured cash to millions of Americans.

            Legendary investor Warren Buffet has already warned that his companies are experiencing significant price increases in the cost of production. He adds that they are passing these costs right along to the final buyer and raising the prices of their products (Polumbo 2021). If many producers share Buffet’s sentiments, the Federal Reserve’s 2% inflation target may not meet its mark. It is important to note however, that the goods Mr. Buffet is referring to largely involve housing which the federal reserve likely wants to bolster, since rising asset prices create increases in access to credit, and thus stimulate the economy.

            Jerome Powell has signaled time and time again that the central bank of the United States will not implement negative interest rates. He has also signaled that monetary policy is expected to remain active until 2023 (Robb 2021). This implies the possibility of more quantitative easing over the next few years. Additionally, the Powell’s statements imply that interest rates will remain low but not fall below 0%.

            If the federal reserve does find itself with a higher than intended inflation rate in the next few years, then it will likely have to raise interest rates to uphold the value of the dollar. When interest rates rise, asset prices tend to drop as lenders reduce credit to the market and thus demand to the market as less borrowers can afford to enter. So, if they raise interest rates then borrowers could get squeezed and this could reduce GDP as less credit circulates through the economy.

            For new homeowners, high interest rates typically coincide with higher initial down payment requirements and always coincide with higher long term interest payments. This reduces demand in the housing market. For existing homeowners, the effect on credit is roughly the same. Reduced asset prices during rate hikes make current asset holders and homeowners less creditworthy since the value of their collateral tends to drop. If interest rates are increased to curb inflationary pressures, many barrowers will be denied access to credit or will not want it because of the high cost of borrowing. If this occurs, even more downward pressure will be placed on the economy as households are forced to reduce spending.

            Zabai and Anna point out that the level of savings a household has as well as its level of outstanding debt contributes to a banks willingness to lend. When interest rates are higher, banks have to be more pragmatic about who they give loans to. As Jake Jennings notes, household savings rates have been on a general decline since the 1970s, being replaced by rising asset prices. Declining savings rates reached a trough at just 2.2% in 2005. Between 2005 and 2012 savings rates trended upward until they reached a peak of 12% in December of 2012. In the beginning of 2013 savings rates dropped off significantly and the upward trend leveled off until the Coronavirus pandemic seemingly gave households a financial epiphany. Households massively increased their savings rate following the pandemic reaching a high of 33.7% in April of 2020 (Figure 8). Since the peak in April of 2020, savings rates began declining again until November of the same year at which time the rate jumped up again and has yet to show a decline as far as current data is concerned. Since 2005 we have seen massive increases in fiscal stimulus as well as continued low interest rate policies by the federal reserve. Juxtapose roughly 30 years of declining savings rates with increasing levels of household debt and a real problem appears. When monetary and fiscal policy tools are rendered ineffective or are removed from the economy. Who will hold up the house when households find themselves drowning in unrepayable debts?

            This paper focuses on growing household debt to GDP ratios as the primary indicator of long-term economic turmoil because without monetary and fiscal policy this measurement appears to follow a trend that is outside of the rational decision makers framework. Household debt to GDP skyrocketed during the initial phase of the Coronavirus pandemic. Even with the help of fiscal stimulus note that household debt to GDP has yet to return to below pre-pandemic levels. If households are assuming to be able to pay back what they borrow, why would the household debt to GDP measurement skyrocket at the onset of a pandemic? What about the pandemic could have caused borrowers to expect rising incomes? If we answer this question from a rational decision makers point of view, we will have to say that households were assuming fiscal stimulus would uplift incomes enough to assist households in paying off their debts. Perhaps they were correct. Fiscal stimulus did seem to correlate with an immediate reduction in the household debt to GDP ratio as shown in Figure 5. However, the federal government has to pay off its debts too.

            Consider that the federal debt to GDP ratio has not been as high as it is today since the WWII era (Figure 6). This is the only time period which economists have data available to reference similar levels of federal debt. If we can learn anything from the significant debt proliferation leading up to and during the referenced time period, it is that following the debt proliferation was a substantial period of deleveraging. Consider that in conjunction with monetary policy tools reaching their maximum capacity as shown by the Effective Federal Funds rate chart in Figure 8. If the Federal Reserve is unwilling to go below 0%, there is little room left to maneuver for the United States’ central bank.

            If households are continually increasing their liabilities, monetary policy tools are reaching their maximum capacity to shape markets, and the federal government needs to begin deleveraging then what institution is left to save us next time households reach an overleveraged breaking point again?


            Though many government officials propagated the unpredictability of the financial crisis at the onset of the downturn, in fact many people raised concerns about it beforehand. In truth, economists have been warning for years about the long-term threats I address here, but none have been able to paint a compelling enough picture to prepare the public for how their expectations should change when we enter the contractionary phase of the long-term debt cycle.

            Interconnected historical trends in different sectors of the economy show how the contractionary phase of the long-term debt cycle shifts certain economic inputs in predictable ways that could help to improve investment strategies.

            Despite the apparent ability of policy intervention to influence short term outcomes, certain long term downward trends are endogenous to the basic functions of our economic system and must reoccur eventually in order to prevent the system from breaking itself. The contributions of our financial system to the incredible productivity growth of the last century will not sustain themselves in America unless the financial system goes through a serious correction in the degree of economic leverage held by institutions and individuals.



Figure 1

Figure 2

Figure  3

Figure 4


Barlevy, Gadi. “Economic Theory and Asset Bubbles.” SSRN, Federal Reserve Bank of Chicago, 11 Sept. 2007,

“Federal Debt: Total Public Debt as Percent of Gross Domestic Product.” 2021. 2021.

Francisco. 2009. “How Has the Percentage of Consumer Debt Compared to Household Income Changed over the Last Few Decades? What Is Driving These Changes?” Federal Reserve Bank of San Francisco. Federal Reserve Bank of San Francisco. July 2009.

“M1 Money Stock (DISCONTINUED).” 2021. 2021.

Polumbo, Brad. 2021. “‘The Costs Are Up, Up, Up’: Warren Buffett Just Issued Grave Inflation Warning.” Foundation for Economic Education. May 3, 2021.

Robb, Greg. 2021. “Fed Recommits to Keeping Interest Rates Low despite Some Inflation Overshoot.” MarketWatch. MarketWatch. March 17, 2021.

“Shares of Gross Domestic Income: Compensation of Employees, Paid: Wage and Salary Accruals: Disbursements: To Persons.” 2019. 2019.

“Speech, Bernanke –Deflation– November 21, 2002.” 2021. 2021.

“United States Households Debt to GDP | 1950-2020 Data | 2021-2023 Forecast.” 2020. 2020.

“U.S. Government COVID-19 Economic Stimulus and Relief Measures.” 2021. Investopedia. 2021.

‌ Zabai, Anna. 2017. “Household Debt: Recent Developments and Challenges.” December 3, 2017.


Low Interest rates in a period of growth?

Central Focus, is the failure of monetary and fiscal policy to stimulate proper redistribution channels the cause of our boom-and-bust cycle? What follows each consecutive bust? An even higher boom. Until it doesn’t. What can data about household debt teach us about the effects and defects of monetary and fiscal policy?

Figure 5: Household Debt to GDP (Longest Data Set Available)


Screen Shot 2021-05-15 at 12.46.26 AM
Screen Shot 2021-05-15 at 12.47.07 AM
Screen Shot 2021-05-15 at 12.48.34 AM
Screen Shot 2021-05-15 at 12.48.52 AM
Screen Shot 2021-05-15 at 12.49.17 AM
Screen Shot 2021-05-15 at 12.49.33 AM
Screen Shot 2021-05-15 at 12.46.55 AM
Screen Shot 2021-05-15 at 12.53.52 AM
Screen Shot 2021-05-15 at 12.55.11 AM
Screen Shot 2021-05-15 at 12.56.57 AM
Screen Shot 2021-05-15 at 12.57.24 AM
Screen Shot 2021-05-15 at 12.57.39 AM