First, the illiquid and long-term nature of the private equity asset class, significant dispersion in returns across funds, as well as bilateral and relationship-driven fundraising, creates scarcity in access to individual funds, giving private equity funds the bargaining power when splitting the returns. As the industry’s growth deaccelerates, the pendulum of bargaining power will start to shift to limited partners, but more permanently than what we saw during the GFC.
Second, we will see larger scrutiny of the cost structure and the industry’s value-add. Put simply, it is an expensive asset class, with the net returns to limited partners lacking consistency in beating public benchmarks (e.g. Harris et al. 2014).3 A central tension is large funds’ management fees, which typically run at 1.5% to 2% of committed capital already in the first five years of the fund life.4 This structure is lucrative for managers but underscores the disconnect between the private equity firm’s income stream and its fund performance, especially for large funds.
Third, such pressures would make new and smaller funds particularly vulnerable. The proliferation of new funds, especially generalists’ funds, in the past decade was partly explained by the strength of capital flow and investment managers’ desire to capture a more significant share of fund economics. These funds have a higher embedded cost structure. Larger funds, therefore, have more room to compress the fees and have a higher ability to experiment in the investment space. All this gives larger-scale firms a better chance to withstand adverse pressures, resulting in market consolidation.
The premise of my recent paper (Taylor 2021) is that the rapid decline in British agricultural prices in the last quarter of the 19th century, which shrank not only the income of aristocratic landed estates but also the income of ‘commoner’ (i.e. non-aristocratic) families who owned land, led to a significant proportion of male aristocrats marrying American heiresses with rich dowries as substitutes for the traditional source – namely, brides from British families with landed estates but no titles.
British agricultural prices began their drop in the mid-1870s for several reasons, from the development of US railroads and prairies to the advent of steamships, all of which led to the UK market being flooded with cheap prairie wheat. Meanwhile, in the US, high society shunned the families of the newly rich businessmen making their fortunes during the Gilded Age. East Coast high society was the jealously guarded preserve of families who could trace their ancestry back to the earliest Dutch or English settlers, and who socially ostracised the nouveau riche business magnates and their families. So, what were these newly rich families to do? They married into the British aristocracy as a means of establishing a social pedigree, whatever the cost.
Figure 1 shows the percentage of marriages between British aristocrats and non-aristocrats (‘out-marriages’) for British males born in 20-year cohorts between 1700 and 1899, as well as the 20-year average real price of wheat in London 33 years later (33 being the average age at which British aristocrats married during the 18th and 19th centuries). The positive correlation between the decline in the price of wheat and the percentage of brides from landed families marrying into the aristocracy is striking, as is the rise in the percentage of ‘out-marriages’ to foreigners as wheat prices fell.
Mortality in 2020 significantly exceeds what would have occurred if official COVID-19 deaths were combined with a normal number of deaths from other causes. The demographic and time patterns of the non-COVID-19 excess deaths (NCEDs) point to deaths of despair rather than an undercount of COVID-19 deaths. The flow of NCEDs increased steadily from March to June and then plateaued. They were disproportionately experienced by working-age men, including men as young as 15 to 24. The chart below, reproduced from Mulligan (2020b), shows these results for men aged 15–54. To compare the weekly timing of their excess deaths to a weekly measure of economic conditions, Figure 1 also includes continued state unemployment claims scaled by a factor of 25,000, shown together with deaths.
First, we compute the differences between the output paths for 2020–2030 projected before and after the pandemic (the shaded area in Figure 1) and estimate its present value discounting at a 0% real interest rate (a reasonably conservative assumption in a context where real rates are negative for most developed countries). This yields a total loss of about half of global GDP.
Next, there is the question of the fiscal stimulus (equivalent to 15% of GDP, according to the IMF fiscal monitor) without which the output loss in 2020 would have been much steeper. How much of the economic impact of the fiscal unwinding is properly accounted for in the revised growth projections (Beck et al. 2021), particularly given that a big part of the stimulus (6% of the 15%) was below the line (loans, equity stakes, guarantees) with a cost that is contingent on the speed and composition of economic recovery in each country? There is no simple answer here. Moreover, we are ignoring potential bouts of financial stress or debt restructurings in heavily indebted countries (Persaud 2021), as well as the second wave of stimulus already in line for 2021 in many advanced economies. All things considered, adding the full 15% of GDP as an indicative measure of the cost of fiscal support does not look unreasonable.
Third, there is the value of the excess deaths due to Covid-19. There is, of course, no uncontroversial way to put a value on human life. For the sake of argument, we follow a recent estimation for the US by Cutler and Summers (2020) that uses the ‘statistical lives’ value to place it between $10 million and $7 million per life. If we take the considerably more conservative $5 million per life, acknowledging that the statistical value may vary across countries, the cost related to the global cumulative deaths registered so far amounts to 16.9% of global GDP.
Author(s): Eduardo Levy Yeyati, Federico Filippini
Our first set of results concern the effects of monetary policy on disposable income. We show that softer monetary policy increases disposable income at all income levels, but that the gains are highly heterogeneous and monotonically increasing in the income level. As shown in Figure 1, a decrease in the policy rate of one percentage point raises disposable income by less than 0.5% at the bottom of the income distribution, by around 1.5% at the median income level, and by more than 5% for the top 1% over a two-year horizon.
Author(s): Asger Lau Andersen, Niels Johannesen, Mia Jørgensen, José-Luis Peydró
Calculating ‘excess savings’ is simple: they are the cumulative amount by which personal saving during the pandemic exceeded a counterfactual path without COVID-19. As shown in blue in Figure 1, personal saving has been elevated since last March. The red line represents one plausible counterfactual scenario, in which the saving rate out of disposable income is constant at its pre-pandemic level (7.3%), while disposable personal income grows at its average rate over the previous twenty years (3.5%). ‘Excess savings’ are the area between the two lines. According to this calculation, they amount to $1.6 trillion. Different plausible assumptions on the counterfactual evolution of personal saving in the absence of the pandemic lead to relatively small differences in this headline number.
Author(s): Florin Bilbiie, Gauti Eggertsson, Giorgio Primiceri
In a week when bitcoin is setting records with a market value exceeding a trillion dollars, what would it mean if cryptocurrencies succeed?
The only reason all the bitcoins are worth a trillion dollars is the expectation of success, as they are not very useful today. Cryptocurrencies must provide some valuable service if they are to justify their high valuation, otherwise holding bitcoin is just like collecting stamps or beanie babies – a minority activity that does not justify the current $51,000 price.
But what is the valuable service that makes bitcoin successful?
The gap between the income and wealth of black and white households in the US is large and persistent. According to the 2019 Survey of Consumer Finances (SCF), the median wealth of a white household is almost nine times higher than that of a black household. The income gap is smaller (1.7 times) but still large. Moreover, these gaps are as large as they were 50 years ago (Kuhn et al. 2020). Concern about racial inequality has increased recently with evidence that the COVID-19 pandemic is having a disproportionate effect on the black community (Bertocchi and Dimico 2020). These stark facts have attracted the attention of economists (e.g. Mayhew and Wills 2020, Chetty et al. 2018) and policymakers. For instance, Raphael Bostic, president of the Federal Reserve Bank of Atlanta, recently stated that the Federal Reserve “can play an important role in helping to reduce racial inequities and bring about a more inclusive economy”.1
A prominent line of thinking is that an accommodative monetary policy lowers unemployment rates and increases labour income for marginal workers, who are oftentimes low-income and minority households. This is what Coibion et al. (2014) call the earnings channel of monetary policy. More specifically, Carpenter and Rodgers (2004) show that a monetary policy accommodation reduces the gap between the unemployment rates of black and white households.
Author(s): By Alina Kristin Bartscher, PhD candidate, University of Bonn, Moritz Kuhn, Professor at the Department of Economics, University of Bon, Moritz Schularick, Professor of Economics, University of Bonn, CEPR Research Fellow, Member of the Academy of Sciences of Berlin-Brandenburg and Paul Wachtel, Professor of Economics, New York University Stern School of Business. Originally published at VoxEU