Essay 1

Author

Ryan Showman

Key Findings

Compared to Regular ETFs, there are fewer ESG ETFs on the market and they tend to have smaller net assets, but ESG ETF inception dates do not make much of a difference on the net assets of the fund.
Since 2013, ESG ETFs have seen an increasing new fund growth rate until the COVID-19 pandemic, which has caused the growth rate to fall until now.
ESG ETFs have lower Net Expense Ratios and Gross Expense Ratios than Regular ETFs.

Introduction

ESG ETFs are a new trend in investing that takes into account environmental, social, and governance risks when choosing what firms to invest in. This trend is especially rising in younger generations that will have to deal with the impacts of climate change in their lifetimes and want to do good while still making money. In spite of this, there are many that question the profitability and realistic future of ESG ETFs. This report compares ESG and Regular ETFs at Blackrock, finding that while ESG ETFs are less popular, smaller in size, and have little difference in net asset based on their inception date compared to the Regular ETFs, they were growing at a high rate up until the COVID-19 pandemic and have much lower expenses than regular ETFs .

Body

The ESG ETF market is still relatively small when compared to traditional ETF’s. Figure 1 shows a comparison of ESG ETFs and Regular ETFs in terms of net assets (in millions of USD). It can be seen that there are still far more Regular ETFs than ESG ETFs at blackrock. This makes sense, since ESG ETFs are a relatively new concept while Regular ETFs have been around for decades. It can also be seen that there are far larger Regular ETFs than ESG ETFs. This could be for a number of reasons. On one hand, the larger scale of Regular ETFs existing could mean that it should statistically have more outliers. On the other hand, this could reflect the newness of ESG ETFs and how they have not yet caught on to the same extent of Regular ETFs. It could also reflect risk aversion to ESG ETFs out of fear that they will not yield as high of returns as Regular ETFs, which include profitable commodities such as oil and weapons.

Code

library(tidyverse) 
library(dplyr)
github_raw_csv_url <- "https://raw.githubusercontent.com/t-emery/sais-susfin_data/main/datasets/blackrock_etf_screener_2022-08-30.csv"
blackrock_etf_data <- read_csv(github_raw_csv_url)

Code

blackrock_etf_data <- blackrock_etf_data |> 
  # we are transforming both date columns (currently character strings) into date objects
  # so we can work with them.
  # this syntax is a bit confusing, but selects all columns containing `date` and applies
  # lubridate::mdy() function to them to turn them into date objects. 
  mutate(across(contains("date"), lubridate::mdy)) |>
  # Billions is a more useful magnitude than millions, so we'll create a column with 
  # the assets in billions by dividing by `net_assets_millions` by 1,000 (10^3)
  # If we wanted trillions, we could divide by 1,000,000 (10^6)
  mutate(net_assets_usd_bn = net_assets_usd_mn/10^3) |> 
  # this column doesn't add anything to our analysis - it says that the data is from 8/30/22
  select(-net_assets_as_of)

Code

mini_blackrock_data <- blackrock_etf_data |> 
  group_by(is_esg) |> 
  # take the top 5 from each group, by net assets
  slice_max(order_by = net_assets_usd_bn, n = 5) |> 
  # select the following columns 
  select(ticker, fund_name = name_wo_ishares_etf, asset_class, sub_asset_class, region, incept_date, net_assets_usd_bn,
         msci_weighted_average_carbon_intensity_tons_co2e_m_sales) |> 
  # rename to `co2_intensity` because the full name is a mouthful, if descriptive.
  rename(co2_intensity = msci_weighted_average_carbon_intensity_tons_co2e_m_sales) |> 
  # always good to ungroup() if you've used a group_by().  We'll discuss later.
  ungroup()

Code

blackrock_etf_data |> 
  ggplot(aes(x = is_esg, y = net_assets_usd_mn, color = region)) +
  geom_point(position = "jitter") +
  labs(title = "Figure 1: Net Assets of ESG v. Regular ETFs",
       subtitle = str_wrap("The regular ETF market is much larger and has larger funds than ESG ETFs.", width = 70),
       x = "",
       y = "Net Assets", 
       caption = "Source: Blackrock | Latest Data: 08/30/2022 | Calculations by Ryan Showman"
       ) +
    scale_y_continuous(labels = scales::label_dollar(suffix = "M"), expand = c(0,0)) +
      theme_minimal()

New ESG ETFs are growing but growth peaked around 2020 and new ESG ETF growth rate has been declining ever since. Figure 2, demonstrating new ESG ETFs vs. Regular ETFs over time, shows that new ESG ETFs started to consistently appear in around 2013. Following this, new ESG ETF growth rates increased until 2020, where their growth started to decline. In comparison, Regular ETFs have been relatively consistent with their growth rate over the past 30 years. The decline in new ESG ETF rates in 2020 could be due to the COVID-19 pandemic, which slowed down the entire financial system. However, it is interesting to note that growth rates have not risen again since the economy reopened. It could be that there is some delay in response to the economy reopening or that there is less of an interest in ESG ETFs, which is probably unlikely.

Code

blackrock_etf_data |> 
  ggplot(aes(x = incept_date)) +
   facet_wrap(~is_esg, ncol = 1) +
  geom_density(fill = "cadetblue1") +
  labs(title = "Figure 2: ESG vs. Regular ETFs Inception Date Density",
       subtitle = str_wrap("New ETFs have grown over the past 10 years, but growth has recently declined.", width = 70),
       x = "Inception Date",
       y = "Density", 
       caption = "Source: Blackrock | Latest Data: 08/30/2022 | Calculations by Ryan Showman"
       )  +
        theme_minimal()

The size of ESG ETFs based on their inception date has been relatively the same. Figure 3 shows the net assets (in million of USD) of ESG ETFs vs. Regular ETFs based on their inception date. This graph shows that ESG ETFs started in 2016 or 2017 may have slightly larger net assets, but there is not a strong trend of older ESG ETFs being necessarily better. Newer ESG ETFs may have been able to keep up because it is such a new evolving field, or because when the ETF was created just does not make much of a difference. In contrast, Regular ETFs with older inception dates seem to have considerably larger net assets on average. This could demonstrate that ESG ETFs do not always act like Regular ETFs, or that it is too soon to determine the net assets of ESG ETFs in the long run.

Code

blackrock_etf_data |> 
   ggplot(aes(x = incept_date, y = net_assets_usd_mn)) +
   geom_point() +
     geom_smooth() +
   facet_wrap(~is_esg, ncol = 1) +
   labs(title = "Figure 3: Net Assets of ESG vs. Regular ETFs by Inception Date",
        subtitle = str_wrap("Inception date seems to have little impact of ETF size.", width = 70),
        x = "Inception Date",
        y = "Net Assets", 
       caption = "Source: Blackrock | Latest Data: 08/30/2022 | Calculations by Ryan Showman"
       ) +
  scale_y_continuous(labels = scales::label_dollar(suffix = "M"), expand = c(0,0)) +
      theme_minimal()

`geom_smooth()` using method = 'loess' and formula 'y ~ x'

When looking at expenses alone, ESG ETFs are more profitable than Regular ETFs. Because ESG ETFs are relatively new, it is difficult to determine their profitability yet. However, expenses are an important factor to consider. Figure 4 shows that ESG ETFs have a median Net Expense Ratio of around .19%, while Regular ETFs have a median Net Expense Ratio of around .35%. Meanwhile, Figure 5 shows the median of ESG ETF and Regular ETF Gross Expense Ratios to be around .19% and around .35% respectively, as well. This means that on average, ESG ETFs have lower expenses than Regular ETFs. This could make ESG ETFs more profitable and even if they are less profitable, lower expenses could offset a higher risk.

Code

blackrock_etf_data |> 
  ggplot(aes(y = net_expense_ratio_percent)) +
  geom_boxplot() +
    facet_wrap(~is_esg, ncol = 1) +
  labs(title = "Figure 4: ESG vs. Regular ETF Net Expense Ratio",
        subtitle = str_wrap("ESG ETFS show lower average Net Expense Ratios than Regular ETFs.", width = 70),
        x = "",
        y = "Net Expense Ratio", 
       caption = "Source: Blackrock | Latest Data: 08/30/2022 | Calculations by Ryan Showman") +
        theme_minimal()

Code

blackrock_etf_data |> 
  ggplot(aes(y = gross_expense_ratio_percent)) +
  geom_boxplot() +
    facet_wrap(~is_esg, ncol = 1) +
   labs(title = "Figure 5: ESG vs. Regular ETF Gross Expense Ratio",
        subtitle = str_wrap("ESG ETFS show lower average Gross Expense Ratios than Regular ETFs.", width = 70),
        x = "",
        y = "Gross Expense Ratio", 
       caption = "Source: Blackrock | Latest Data: 08/30/2022 | Calculations by Ryan Showman") +
        theme_minimal()

Conclusion

In spite of their recent development and criticisms, the future of ESG ETFs looks like it should be somewhat bright. Under normal economic circumstances ( excluding the pandemic and its economic impacts), new ESG ETFs have seen large growth rates. On top of this, their lower Gross and Net Expense Ratios could make them more attractive and profitable to investors. However, it is worth noting that the inception date of ESG ETFs does not seem to have much of an impact on their net assets and that the ESG ETF market is still relatively smaller in quantity of funds and net assets compared to Regular ETFs. In spite of this, the data presented in this report and worse climate change impacts should signify a growth in the popularity and profitability of ESG ETFs in the future.