Final project

AUTHOR

SHIYU LIAO

library(dplyr)

Attaching package: 'dplyr'
The following objects are masked from 'package:stats':

    filter, lag
The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union
library(ggplot2)
library(tidyverse)
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ lubridate 1.9.3     ✔ tibble    3.2.1
✔ purrr     1.0.2     ✔ tidyr     1.3.0
✔ readr     2.1.5     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(janitor)

Attaching package: 'janitor'

The following objects are masked from 'package:stats':

    chisq.test, fisher.test
library(esquisse)
library(tidyr)
library(readxl)




file_path <- "/Users/liaoshiyu/Desktop/sustainable/Sustainable finance final project.xlsx"
data <- read_excel(file_path)
head(data)
# A tibble: 6 × 115
  COUNTRY  PRODUCT   FLOW  UNIT  `42005` `42036` `42064` `42095` `42125` `42156`
  <chr>    <chr>     <chr> <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 Austria  Gasoline… Tota… US d…    1.31    1.31    1.31    1.35    1.41    1.44
2 Belgium  Gasoline… Tota… US d…    1.5     1.49    1.5     1.54    1.62    1.64
3 Bulgaria Gasoline… Tota… US d…    1.19    1.14    1.2     1.21    1.29    1.31
4 Canada   Gasoline… Tota… US d…    0.77    0.81    0.86    0.89    0.94    0.98
5 Croatia  Gasoline… Tota… US d…    1.32    1.33    1.37    1.39    1.52    1.54
6 Cyprus   Gasoline… Tota… US d…    1.33    1.31    1.33    1.35    1.45    1.48
# ℹ 105 more variables: `42186` <dbl>, `42217` <dbl>, `42248` <dbl>,
#   `42278` <dbl>, `42309` <dbl>, `42339` <dbl>, `42370` <dbl>, `42401` <dbl>,
#   `42430` <dbl>, `42461` <dbl>, `42491` <dbl>, `42522` <dbl>, `42552` <dbl>,
#   `42583` <dbl>, `42614` <dbl>, `42644` <dbl>, `42675` <dbl>, `42705` <dbl>,
#   `42736` <dbl>, `42767` <dbl>, `42795` <dbl>, `42826` <dbl>, `42856` <dbl>,
#   `42887` <dbl>, `42917` <dbl>, `42948` <dbl>, `42979` <dbl>, `43009` <dbl>,
#   `43040` <dbl>, `43070` <dbl>, `43101` <dbl>, `43132` <dbl>, …
data <- data %>%
  mutate(COUNTRY = substr(COUNTRY, 1, 3))
head(data)
# A tibble: 6 × 115
  COUNTRY PRODUCT    FLOW  UNIT  `42005` `42036` `42064` `42095` `42125` `42156`
  <chr>   <chr>      <chr> <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 Aus     Gasoline … Tota… US d…    1.31    1.31    1.31    1.35    1.41    1.44
2 Bel     Gasoline … Tota… US d…    1.5     1.49    1.5     1.54    1.62    1.64
3 Bul     Gasoline … Tota… US d…    1.19    1.14    1.2     1.21    1.29    1.31
4 Can     Gasoline … Tota… US d…    0.77    0.81    0.86    0.89    0.94    0.98
5 Cro     Gasoline … Tota… US d…    1.32    1.33    1.37    1.39    1.52    1.54
6 Cyp     Gasoline … Tota… US d…    1.33    1.31    1.33    1.35    1.45    1.48
# ℹ 105 more variables: `42186` <dbl>, `42217` <dbl>, `42248` <dbl>,
#   `42278` <dbl>, `42309` <dbl>, `42339` <dbl>, `42370` <dbl>, `42401` <dbl>,
#   `42430` <dbl>, `42461` <dbl>, `42491` <dbl>, `42522` <dbl>, `42552` <dbl>,
#   `42583` <dbl>, `42614` <dbl>, `42644` <dbl>, `42675` <dbl>, `42705` <dbl>,
#   `42736` <dbl>, `42767` <dbl>, `42795` <dbl>, `42826` <dbl>, `42856` <dbl>,
#   `42887` <dbl>, `42917` <dbl>, `42948` <dbl>, `42979` <dbl>, `43009` <dbl>,
#   `43040` <dbl>, `43070` <dbl>, `43101` <dbl>, `43132` <dbl>, …
data <- data %>%
  mutate(PRODUCT= substr(PRODUCT, 1, 3))
head(data)
# A tibble: 6 × 115
  COUNTRY PRODUCT FLOW     UNIT  `42005` `42036` `42064` `42095` `42125` `42156`
  <chr>   <chr>   <chr>    <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 Aus     Gas     Total p… US d…    1.31    1.31    1.31    1.35    1.41    1.44
2 Bel     Gas     Total p… US d…    1.5     1.49    1.5     1.54    1.62    1.64
3 Bul     Gas     Total p… US d…    1.19    1.14    1.2     1.21    1.29    1.31
4 Can     Gas     Total p… US d…    0.77    0.81    0.86    0.89    0.94    0.98
5 Cro     Gas     Total p… US d…    1.32    1.33    1.37    1.39    1.52    1.54
6 Cyp     Gas     Total p… US d…    1.33    1.31    1.33    1.35    1.45    1.48
# ℹ 105 more variables: `42186` <dbl>, `42217` <dbl>, `42248` <dbl>,
#   `42278` <dbl>, `42309` <dbl>, `42339` <dbl>, `42370` <dbl>, `42401` <dbl>,
#   `42430` <dbl>, `42461` <dbl>, `42491` <dbl>, `42522` <dbl>, `42552` <dbl>,
#   `42583` <dbl>, `42614` <dbl>, `42644` <dbl>, `42675` <dbl>, `42705` <dbl>,
#   `42736` <dbl>, `42767` <dbl>, `42795` <dbl>, `42826` <dbl>, `42856` <dbl>,
#   `42887` <dbl>, `42917` <dbl>, `42948` <dbl>, `42979` <dbl>, `43009` <dbl>,
#   `43040` <dbl>, `43070` <dbl>, `43101` <dbl>, `43132` <dbl>, …
data <- data %>%
  mutate(UNIT = 'USDollars')
head(data)
# A tibble: 6 × 115
  COUNTRY PRODUCT FLOW     UNIT  `42005` `42036` `42064` `42095` `42125` `42156`
  <chr>   <chr>   <chr>    <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
1 Aus     Gas     Total p… USDo…    1.31    1.31    1.31    1.35    1.41    1.44
2 Bel     Gas     Total p… USDo…    1.5     1.49    1.5     1.54    1.62    1.64
3 Bul     Gas     Total p… USDo…    1.19    1.14    1.2     1.21    1.29    1.31
4 Can     Gas     Total p… USDo…    0.77    0.81    0.86    0.89    0.94    0.98
5 Cro     Gas     Total p… USDo…    1.32    1.33    1.37    1.39    1.52    1.54
6 Cyp     Gas     Total p… USDo…    1.33    1.31    1.33    1.35    1.45    1.48
# ℹ 105 more variables: `42186` <dbl>, `42217` <dbl>, `42248` <dbl>,
#   `42278` <dbl>, `42309` <dbl>, `42339` <dbl>, `42370` <dbl>, `42401` <dbl>,
#   `42430` <dbl>, `42461` <dbl>, `42491` <dbl>, `42522` <dbl>, `42552` <dbl>,
#   `42583` <dbl>, `42614` <dbl>, `42644` <dbl>, `42675` <dbl>, `42705` <dbl>,
#   `42736` <dbl>, `42767` <dbl>, `42795` <dbl>, `42826` <dbl>, `42856` <dbl>,
#   `42887` <dbl>, `42917` <dbl>, `42948` <dbl>, `42979` <dbl>, `43009` <dbl>,
#   `43040` <dbl>, `43070` <dbl>, `43101` <dbl>, `43132` <dbl>, …
ggplot(data, aes(x = COUNTRY)) + 
  geom_bar() + 
  theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
  labs(x = "Country", y = "Count", title = "Number of Entries per Country")

data <- data %>%
  mutate(across(5:ncol(data), as.numeric, .names = "num_{.col}"))
Warning: There was 1 warning in `mutate()`.
ℹ In argument: `across(5:ncol(data), as.numeric, .names = "num_{.col}")`.
Caused by warning:
! NAs introduced by coercion
long_data <- data %>%
  pivot_longer(
    cols = starts_with("num_"),
    names_to = "Time",
    values_to = "Price"
  ) %>%
  mutate(
    
    Time = str_replace(Time, "^num_", ""),
    
    Time = as.Date(paste0("01-", Time), format="%d-%b-%y")
  )

Research Question:

ESG issues caused by the impact of the Russia-Ukraine war on oil prices

Introduction:

As the world’s second-largest oil producer, Russia plays a key role in the global oil supply chain. After the war broke out, the international community imposed a series of economic sanctions on Russia, including restrictions on its oil exports. These sanctions not only directly reduce global oil supply, but also increase market uncertainty and risks. In the short term, this resulted in a significant increase in global oil prices. The rise in oil prices has led to the urgent need for many countries to invest resources in industries that are beneficial to crude oil prices rather than ESG-related energy industries.

OPEC countries import oil from Russia significantly reduced:

After the outbreak of the Russia-Ukraine war in 2022, the international community’s economic sanctions on Russia caused members of the Organization of the Petroleum Exporting Countries (OPEC) to reduce oil imports from Russia. OPEC’s main members include countries such as Saudi Arabia, Iraq, the United Arab Emirates, Kuwait and Iran, which play an important role in the global oil market. In the context of sanctions, these countries have to seek other oil-producing countries to ensure domestic energy security and economic stability. According to the above chart, starting from February 2022, the proportion of OPEC countries’ oil imports from Russia has shown a significant downward trend. Among them, the decrease in some countries such as Estonia is particularly significant, which shows the profound impact of the war and the international political fluctuations it brings on the global oil supply chain.

At the same time, these countries’ decision to reduce their dependence on Russian oil has also accelerated the reshuffling of the global oil market. As imports of Russian oil decline, OPEC countries must increase their reliance on oil from other countries, such as Nigeria, Angola and even non-OPEC countries such as the United States and Brazil, to make up for the supply gap. This change in supply sources not only affects the pattern of global oil trade, but may also cause a new round of adjustment in oil prices.

Crude oil Price increase significantly:

As shown in the chart above, the average oil price in OPEC countries has increased significantly since the outbreak of the Russia-Ukraine war in 2022. The initial price spike reflected the immediate impact of international sanctions on Russian oil exports. Subsequently, despite the fluctuations, the overall trend shows that prices have been rising. This trend suggests that the strategy of reducing Russian oil imports not only affects the oil market in the short term, but may also lead to long-term market restructuring.

Rising oil prices have had a knock-on effect on global commodity markets. Rising prices for oil, a raw material and key input in the production process, have pushed up costs across the manufacturing industry. This has a direct impact on the prices of consumer goods, thereby exacerbating global inflationary pressures. Without supplies from Russia, the world’s second-largest oil producer, rising oil prices will have a particularly profound impact on various economies.

In addition, continued price increases are forcing governments and companies to re-examine energy strategies. As an important source of energy, oil price fluctuations have a huge impact on energy policy formulation. For example, the development of the ESG-related energy industry, which was originally actively promoted, may be challenged by the high price of crude oil, and some investments may be forced to flow back to the traditional energy industry.

Texas Argument About ESG Caused by Traditional Energy Development:

The popularity of ESG investing fell to its lowest level since 2018 in early 2024, amid rising global energy prices triggered by the Russia-Ukraine conflict. Rising energy prices and continued demand for fossil fuels are driving a reassessment of ESG investment strategies. Especially in large energy-producing states like Texas, the challenges to ESG strategies from governments and investors are even more significant. A Texas public school fund is pulling $8.5 billion from BlackRock, the world’s largest investment manager, a move that reflects dissatisfaction with the company’s ESG investing practices, particularly in its investment policies for energy companies. Texas has accused BlackRock of having a strategy that is inconsistent with Texas’ support for fossil fuel companies, and BlackRock has countered that it has significant investments in Texas energy companies, pointing to the strong long-term performance of its investments. The incident illustrates the challenges ESG investment strategies face in energy-rich states such as Texas, while also illustrating the complexity and tensions of political and economic issues in an era of high oil prices. This trend is reflected in energy security. and economic growth pressure, some politicians may be more inclined to support the traditional energy industry rather than ESG investments.

Conclusion:

The rise in oil prices triggered by the Russia-Ukraine war had a major impact on the global economy, including turmoil in the international environment and commodity markets. This conflict not only increases energy prices, but also increases market concerns about energy supply security, which in turn affects raw material costs and production. At the same time, investment attitudes toward ESG have also changed, especially in resource-rich areas such as Texas. The era of high oil prices has prompted some governments and investors to rethink the degree of support for traditional energy sources, which may have an impact on long-term ESG development trends and sustainable investment strategies.

Reference:

Aloui D, Benkraiem R, Guesmi K, Mzoughi H (2023) Managing natural resource prices in a geopolitical risk environment. Resour Policy 83:103628. https://doi.org/10.1016/j.resourpol.2023.103628

International Energy Agency. (n.d.). Monthly Oil Price Statistics. Retrieved April 24, 2024, from https://www.iea.org/data-and-statistics/data-product/monthly-oil-price-statistics-2#monthly-oil-product-prices

International Energy Agency. (n.d.). Reliance on Russian Fossil Fuels in OECD and EU Countries. Retrieved April 24, 2024, from https://www.iea.org/data-and-statistics/data-product/reliance-on-russian-fossil-fuels-in-oecd-and-eu-countries

International Energy Agency. (n.d.). Monthly Oil Statistics. Retrieved April 24, 2024, from https://www.iea.org/data-and-statistics/data-product/monthly-oil-statistics

Klar, R. (2023, July 25). Texas schools pull billions in investment from BlackRock over fossil fuel boycott, ESG. The Hill. Retrieved April 24, 2024, from https://thehill.com/homenews/state-watch/4543054-texas-schools-pull-billions-investment-blackrock-fossil-fuel-boycott-esg/