Crude Oil Market Functioning and Sustainable Development Goals: Case of OPEC++-Participating Countries

Abstract

This article aims to substantiate the factors by which the oil industry influences the sustainable development of OPEC++-participating countries under conditions of uncertainty. The impact of the price parameters of the world oil market and the tools of its regulation on the sustainability of OPEC++-participating countries was assessed using panel regression analysis. The sustainable development level of OPEC++-participating countries was analyzed by the integrated estimation method, focusing on crude oil market functioning features. Undoubtedly, we can testify that there is a direct correlation between the country’s level of socio-economic development and sustainable development. In resource economies, a reduction in oil production and exports cannot have the same effect on sustainable development as in countries that do not produce oil, or are characterized by a higher level of economic development. With an appropriate level of economic diversification and the effectiveness of the institutional framework for managing the oil market, sustainable development can be achieved. Based on the model of the integrated assessment of the sustainable development of oil-exporting countries, the impact of statistically significant financial investors’ panic factor on the imbalance of oil prices due to the uncertainty of economic development was determined. Key indicators that create a panic factor in the oil market were identified. These include the indicators of the number of countries enforcing lockdown and the pandemic’s duration. We argue for the need to develop an effective strategy for achieving the sustainable development goals (SDGs) in OPEC++-participating countries, based on the management of crude oil supply and demand forces and by considering the effect of financial investors’ panic factor on the oil market.

1. Introduction

1.1. Crude Oil Price Imbalance as a Threat to the Economic Development of OPEC Countries

Since 1950, crude oil has remained the most important strategic resource in the world economy, accounting for about 31% of global energy consumption, exceeding coal, gas, and renewable energy consumption [1]. Since crude oil prices on the world market began to decline rapidly, due to its active production and the development of new fields, an urgent need to regulate its supply volume in order to reduce production and stabilize the price level has arisen. In order to solve this problem, the Organization of the Petroleum Exporting Countries (OPEC) was created, whose members are the world leaders in oil production and account for about 80% of the world’s oil reserves [2]. In addition to the constant problem of balancing the price of crude oil, OPEC countries face a steady decline in demand for oil as the world develops on a green trajectory, which also necessitates a decrease in oil production. The awareness of the scale of the negative consequences of the current economic development model has stimulated many countries worldwide to transition towards a model of socio-economic development based on the balance of economic, social, and environmental interests; the so-called green economy model. The commitment by numerous countries in 2015 [3] to develop clean technologies in the energy sector and significantly reduce investments in oil and gas production to limit global warming to a level less than 2 °C determines reaching the maximum level of oil demand by 2025 (97 million barrels per day), according to the forecasts of world-leading experts. After the world economy’s recovery from the COVID-19 pandemic, oil demand is expected to decline steadily by 21% per day by 2050 [4]. Due to recent global trends, it is possible to talk about the diversification of the energy resources business, both within the oil and gas segments (from conventional oil to the dynamically growing market of shale oil and gas and liquefied natural gas) [5] and in its cross-branch configuration (from refined oil to alternative energy sources) [6].

In today’s world, almost every country is a consumer of oil, but not every one is a producer. The feature of oil-producing countries is that OPEC members are resource economies; an oversupply of crude oil leads to a depreciation of crude oil and a sharp decline in sales revenue. Oversupply, in turn, against the background of the low level of diversification of the economies in OPEC countries, threatens economic development, social welfare, and sustainable development in the long run [7,8,9]. On the other hand, modern research has proven that an increase in the average quarterly price of USD 6 per barrel of crude oil reduces the growth rate of industrial countries and the global economy as a whole by 0.3% [10].

Therefore, the dependence on resource wealth of OPEC countries is a fatal problem for their economic and sustainable development under current conditions.

1.2. The COVID-19 Pandemic and the Risks to the Development of the OPEC Oil Industry

In addition to the persistent imbalance in crude oil prices and the reorientation of energy business investments toward the diversification of energy resources, a significant threat to the development of the OPEC oil industry has become the spread and duration of the COVID-19 pandemic [11,12,13]. The adverse effects of the pandemic on the global economy have exacerbated the risks of reduced demand for crude oil due to reduced production resulting from the implementation of a regime of forced social distancing [14,15]. However, it should be noted that Shaikh [16] presents contradictory points of view regarding the impact of the pandemic on the level of demand for crude oil [16]. The controversy about this approach is caused, first, by the ambiguous interpretation concerning the changes in labor productivity during the transition to remote work. Along with the view of Vasiljeva et al. [17] about the decrease in its level during the quarantine period, Maghlaperidze et al. [18] proved the possibility of achieving higher labor productivity in distance employment [17,18]. Second, scientists increasingly use the number of disease cases, labor force mortality and vaccination rates, the duration of a pandemic, and other factors as disincentives when studying energy and other markets of goods and services, and predicting trends during the pandemic [11,19]. The results of many scientific studies confirm that the COVID-19 pandemic was the main reason for falling global oil prices [13,20,21], and the level of socio-economic development in OPEC members and oil-exporting countries in general [20]. Throughout 2020, the Brent Spot Price FOB level has fallen by 33.3% relative to 2019, reaching its lowest level since 2004, of 41.76 dollars per barrel (USD/bbl). Oil prices stabilized in the first nine months of 2021, rising to 61.85 USD/bbl, but this price level is lower than the pre-crisis period (2018–2019) [22].

Following these conclusions, it can be argued that changes in COVID-19 spread rates directly and proportionally determine oil market trends, and consequently, transformations in resource economies. For example, the January–April 2021 global number of infections was 20.8 times higher than in January–April 2020; the number of deaths increased 5.9-fold [23], which preceded the record fall in global oil prices on 21 April 2020 (to a value of 9.12 USD/bbl).

1.3. The Sustainable Development of OPEC Economies as a Factor of Oil Industry Sustainability

As the data show, economic growth rates over a long time have been characterized for the majority of OPEC member countries by significant jumps in GDP reduction over the last 12 years, and a typical slowdown in economic growth due to the volatility and uncertainty of the oil market’s prices and the inability to reach an agreement within the OPEC+ format. From 2009 to 2020, only three countries, Iran, Iraq, and Saudi Arabia, had average economic growth rates above 3%, considered the minimum necessary to ensure healthy national economic development [24] (Appendix A,

Table A1. Dynamics of the economy of OPEC countries (annual GDP growth rate, %) [24].

	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	Average Increase
Algeria	−20	17	24	4	0	2	−22	−5	8	3	−2	−17	−1
Angola	−21	19	33	15	7	7	−29	−2	21	−17	−17	−26	−1
Congo	−17	35	19	13	1	0	−34	−15	9	21	−6	−18	1
Equatorial Guinea	−24	8	31	5	−2	−2	−39	−15	9	9	−17	−14	−4
Gabon	−22	18	27	−6	2	3	−21	−3	4	18	−2	−7	1
Iran	2	18	20	3	−22	−5	−13	9	7	2	27	9	5 *
Iraq	−15	25	34	17	8	−3	−27	0	13	21	3	−29	4 *
Kuwait	−28	9	33	13	0	−7	−30	−4	10	17	−4	−20	−1
Libya	−28	10	−57	151	−16	−47	−52	8	63	37	−4	−45	2
Nigeria	−19	118	11	15	10	10	−13	−17	−7	12	−4	6	10 *
Saudi Arabia	−17	23	27	10	1	1	−13	−1	7	14	1	−12	3
United Arab Emirates	−20	14	21	7	4	3	−11	0	8	9	0	−15	2
Venezuela	−18	24	14	−1	−29	−9	52	−14	−48	−32	−35	−26	−10
OPEC	−16	27	19	9	−4	0	−13	−4	1	8	2	−9	2

* Growth rate values above 3%.

). Recognizing the detrimental effects of Groningen on economic development, many OPEC member countries have attempted to diversify economic development through industry, the nuclear program, tourism, agriculture, and more, but oil rents continue to account for the lion’s share of these countries’ GDP [25]. Therefore, the optimal combination of national absolute and comparative advantages (economic pragmatism) becomes the main way for governments to achieve competitiveness in modern world trade, and sustainable economic growth [26]. As noted by Alzubair [27], the International Monetary Fund [28] using economic diversification to eliminate the “resource curse” in current conditions is achievable for oil-exporting countries only when they preserve a stable high level of crude oil prices, the income from which will be redirected to developing alternative stable income in the economy.

Most scientists point out that the most effective solution is the formation of cartel agreements to influence global energy markets [29]—a solution that has caused Venezuela’s economic situation to be relatively stable for a long time [30]. However, conditions of increased uncertainty, as in the case of the COVID-19 pandemic, show that the cartel form of integration does not offer a guarantee of maintaining high oil prices, and thus of eternal economic prosperity through oil exports, for OPEC countries, Russia, and other participants in oil-exporting agreements [13].

Although there is more research on the relationship between economic growth and sustainability, it should be noted that the roles of oil production and refining, and their impact on the environment, are still unclear. Moreover, few studies consider the case of oil-dependent resource economies, particularly countries with developing economies, such as members of OPEC, characterized by high levels of investments in the oil industry alone, the absence of rigid legislative norms of environmental protection, and the total dependence of economic growth on the level of oil production, oil prices and export volumes [31,32].

The scientific priority of our study is the justification and systematization of the oil market’s development factors, determining the achievement of SDGs in the medium term in oil-exporting countries (the member countries of the OPEC++ deal), and the empirical analysis of practical management tools for resource-dependent economies by determining the relationship between sustainable development and the oil market’s conditions under the uncertainty of COVID-19. Furthermore, this study will help determine whether the measures implemented to balance crude oil prices by the OPEC++ countries will affect their countries’ economic growth and achievement of the SDGs.

2. Literature Review

The strategy aimed at reducing the production and consumption of traditional energy sources, mainly crude oil; according to scientists such as Shahbaz et al. [33], Shahbaz et al. [34], Sarkodie and Strezov [35], Bekun et al. [36], Usman, Iorember and Olanipekun [37], Usman, Elsalih and Koshadh [38], Rafindadi and Usman [39], and leading research organizations such as International Energy Agency, Enerdata, S&P Global Platts, Intergovernmental Panel on Climate Change and others, this should facilitate the decarbonization of the socio-economic system, and sustainable development not only in OPEC countries, but also at the level of global development [33,34,35,36,37,38,39,40,41,42,43,44,45]. These statements are based on such leading concepts about the relationship between economic growth, trade, and sustainable development as the environmental Kuznets curve [46,47], the composition effect [48], the technique effect [49], the scale effect [50], the pollution haven hypothesis [51], and the depression hypothesis [52]. These theories are based on the rationale of a non-linear and linear relationship between trade (as an indicator of economic growth) and sustainability indicators. As a country’s economic growth rate and the openness of trade networks increase, the degradation of the ecological system due to increasing levels of emissions into the environment intensifies, and vice versa. As the consumption of hydrocarbons decreases due to the transition to alternative energy sources, there is a decrease in the energy intensity of industrial production, and an increase in business activity based on innovation and informatization [53,54].

On the other hand, a different point of view suggests that the relationship between sustainable development and economic growth can be either negative or positive, depending on changing circumstances.

The Laffer curve of trade [52] states the non-linear nature of the relationship between trade and economic growth at the development stages of different countries. It interprets the dependence of the country’s financial stability, the activity of innovation, the quality of human potential, and the institutional structure of the differential impact on the quality of the ecological environment. The higher the level of development in these factors, the more there is a directly proportional impact of trade openness and economic growth on sustainable development, and vice versa.

The growth hypothesis [55] reflects a positive relationship between economic growth and sustainable development. Alesina et al. [56], Zahonogo [57], Baldwin et al. [58], Bond et al. [59], Almeida and Fernandes [60], and Guncavdi and Ulengin [61] in their studies empirically substantiated the positive impacts of economic openness and its growth due to the deepening specification of economic activity, returns from the scale of production, the redistribution of knowledge and the intensity of its dissemination, increasing the quality of intellectual capital, and other factors [56,57,58,59,60,61].

Looking at this dependence in terms of the economic growth concept (as one of the critical pillars of sustainability theory), the intensity of oil production and its export increases the openness of OPEC+++ economies, and determines the increased innovation of the energy industry’s infrastructure and other sectors of the economy, which in turn should affect the sustainable development of these countries [52]. However, as mentioned above, the openness of the economy is achieved at the expense of such commodities as oil. Therefore, it is possible to assume that this statement can be confirmed only under the condition of the institutional effectiveness of the country, for example, ensuring the priority of the use of oil income in infrastructural sectors of the country’s economy for the diversification and creation of an alternative permanent income, introducing advanced technologies to ensure the sustainability of oil production and refining processes, etc.

According to Ponkratov et al. [11], a drop in output leads to increased oil prices. On the other hand, a drop in output and sales with prices remaining unchanged leads to a lower GDP in oil-exporting countries [62]. Due to the multidirectional nature of the effects of changes in oil production volumes on the sustainability of oil-exporting countries, the study has formulated the following hypothesis:

H1: 

Changes in physical volumes of oil production and export (reduction) have a mixed effect on the sustainable development of oil-exporting countries.

According to Vasiljeva et al. [17], the pandemic’s duration also reduces sustainable development and destabilizes oil market and the OPEC economies. However, official data show that oil prices rose to 67.73 USD/bbl at the end of April 2021 [22]. Consequently, we can cite the contradictory results of the scientific studies of Ponkratov et al. [11] and Shaikh [16] about the nature of the destructive impact of the pandemic on the level of crude oil prices in the medium and long terms [11,16]. At the same time, all of these factors undoubtedly serve as fundamental causes of an imbalance in oil price levels, but each of them is insufficient as a stand-alone explanation. Given the uncertainty due to the pandemic in the consumer market and the inability of resource economies to agree on an effective price-balancing strategy, it can be argued that price levels are significantly influenced by irrational investor behavior in the oil market. The International Organization of Securities Commissions (IOSCO), while making recommendations to improve transparency in the derivatives market, concluded that there was no convincing evidence of a systematic influence of financial speculators on oil price movements [63]. Subsequent studies have empirically confirmed that financial speculators do not systematically contribute to the volatility of primary and, particularly, oil prices, but do play a determining role in times of uncertainty and panic [16,64,65]. The financial investors’ panic in April 2020 was caused by uncertainty in the demand for oil futures contracts. This uncertainty resulted from both objective factors (declining production, transportation, unfavorable forecasts of global economic development) and subjective ones (unfavorable expectations associated with psychological tension due to the growing number of infections, deaths, and social isolation). Therefore, it can be assumed that financial investors, although they do not determine the general trend of oil prices, can strengthen or destabilize these prices at some moments. This panic manifests itself as the risk of the non-realization of oil futures contracts and others, which reduces oil prices [66]. Therefore, our study formulated the following hypothesis:

H2: 

Along with traditional fundamental factors such as reductions in business activity, the imbalance in world oil prices during the COVID-19 pandemic is caused by consumer financial investors’ panic.

High oil prices can positively impact the sustainable development of oil-producing countries, since the costs of production, refining, and transportation are reduced due to the reduction in oil production [52]. As a result, this money can be redirected to support other sectors of the national economy, or improve the oil industry’s sustainability. For example, the reduction in oil production under OPEC+ and OPEC++ deals contributed to three medium oil spills only (7–700 tons), without large oil spills (>700 tons) occurring in 2020. These are the lowest oil spill rates since 1970 [67]. Additionally, high oil prices increase state budget revenues, and consequently the incomes of citizens, and provide economic growth in the country, whose impact on sustainability we have considered in the formulation of Hypothesis 1.

There is also an opinion that the increase in oil prices causes deindustrialization in oil-exporting countries, and the gradual displacement by the oil industry of other industries with significant emissions into the atmosphere [68]. Therefore, in the long term, the country’s economy will function based on the import of goods and services and the export of oil, and other polluting productions can be moved to countries with cheaper labor, providing cheaper production and reductions in emissions into the atmosphere [69].

On the other hand, the proponents of the “resource curse” theory (or “oil needle”, or “Dutch disease”) consider that high oil prices cause oil-exporting countries to lag in their economic development [70]. However, the availability of natural resources is not the curse, rather it is their domination in the GDP formation of the country’s economy: when the price of crude oil rises as a resource sector commodity for a long time, under the influence of the factor of wage growth in the oil-industrial complex, labor force outflows from the tradable sector [71]. Additionally, an increase in crude oil prices intensifies foreign investment in the oil industry, which raises the cost of the country’s national currency and reduces the competitiveness of domestic producers’ goods compared to imports. In other words, the resource and non-tradable sectors suppress the development of the tradable goods sector. Consequently, economic growth rates are constantly decreasing, the number of unemployed people is increasing, and, as a result, a recession in social and economic sectors in the country may occur, which will only exacerbate the situation with the environment [70]. Nevertheless, there is no convincing systematic evidence of a causal relationship between income from resource exports and the decline in industrial production. As shown in the work of Hutchison [72], stagnation in Norway, the Netherlands, and Britain could also be explained by other factors.

It should be noted that it is quite difficult to apply the “Dutch disease” theory to the analysis of the reasons for stagnation in OPEC+++ countries, since most countries, in particular OPEC members, are characterized only by the resource and service sectors. The consequences of the prevailing raw material export economic development model are related to the low level of SDGs achievement by the OPEC member countries, the level of which, except for in Angola, Equatorial Guinea, Libya, and Iran, in 2020, averaged 62% [73]. In this case, it can be said that there has been no progress in this direction over the past 20 years, as the average level of SDGs achievement in OPEC countries compared to 2000 has changed only by 4%, mainly due to the progress of four countries: United Arab Emirates, Algeria, Gabon and Congo [73]. Based on the above, we formulated the hypothesis:

H3: 

The increase in crude oil prices had a negative impact on the sustainable development of oil-exporting countries.

3. Data

Among the sustainable development indicators, the standardized values of the economic, social, and environmental development indicators—the components of sustainable development [74,75]—were used. The list of indicators is based on studies [15,74,75,76,77,78] and is presented in

Table 1. Indicators for assessing the impact of the oil market on the sustainable development of OPEC++-participating countries.

Notation	Indicators
Sustainability indicators (SUS)
Inv	Foreign direct investment (equity value, accumulative saving, and other capital), net inflows, USD
GDP	Real GDP per capita, USD
Cap	Gross capital formation, % of GDP. Gross capital formation consists of the cost of fixed assets and net changes in inventory levels.
Imp	Imports of goods and services, % of GDP
Exp	Exports of goods and services, % of GDP
S-deb	Short-term debt, % of total reserves
Ser-deb	Total debt service, % of exports of goods, services and primary income
T-deb	Total external debt stocks, USD
Man	Medium and high-tech manufacturing value added, % manufacturing value added
Intel	Charges for the use of intellectual property, payments, USD. This indicator refers to payments and receipts between residents and non-residents for the use of property rights (such as patents, trademarks, copyrights, industrial processes, and designs, including trade secrets and franchises) and for use under licensing agreements
Tech	Export of high-tech goods, USD
Inf	Inflation, consumer prices, %. It is the annual percentage change in the cost of purchasing a basket of goods and services for the average consumer.
Gin	Gini index
Pov	Poverty rate at the national poverty line, % of population
Un	Unemployment, % of the total labor force according to the methodology of the International Labor Organization
Liter	Adult literacy rate, % of people aged 15 and older
Nit	Nitrous oxide emissions, thousand metric tons of CO2 equivalent. These are emissions from burning biomass in agriculture, industrial activities, and cattle breeding
Met	Methane emissions, kt of CO2 equivalent. These are methane emissions associated with human activities, such as agriculture and industrial methane production.
Gas	Total greenhouse gas emissions, kt of CO2 equivalent. This indicator characterizes the total CO2 emissions, excluding short-cycle biomass combustion.
Indicators of global oil market conditions (OIL)
Spot	Brent oil spot prices, USD 100/bbl
Fut	Brent oil futures prices, USD 100/bbl
Var	Indicator of Brent oil spot price variation based on daily price
Var-Fut	Indicator of Brent oil futures price variation based on daily price
Spot-gr	Chain-weighted growth rate of Brent oil spot prices
Fut-gr	Chain-weighted growth rates of Brent futures prices
Indicators forming the financial investors’ panic on the oil market (PANIC)
Cas	Number of new cases of COVID-19 infection, persons per total population
Dea	Number of deaths from COVID-19 infections, persons per total population
Cas.gr	Growth rate of new COVID-19 infections
Dea.gr	Growth rate of COVID-19 deaths
Dur	Pandemic duration (weeks) (on the study date)
Lock	Number of countries with lockdown. These are countries with a regime of isolation, which does not allow people to leave the territory of their country.
Cas.coun	Number of countries where cases of COVID-19 infection have been recorded
Dea.coun	Number of countries with COVID-19 deaths (on the study date)
Tools of supranational regulation of global market development parameters (REG)
POil	Oil production volumes by OPEC++-participating countries, billion barrels per year
EOil	Oil exports from OPEC++-participating countries, billion barrels per year
POil-gr	The growth rate of oil production by OPEC++-participating countries relative to the previous period
EOil-gr	The growth rate of oil exports from OPEC++-participating countries relative to the previous period
Ren	Renewable energy consumption, % of total final energy consumption

. These indicators reflect the macroeconomic situation of countries and their investment activity, which, on the one hand, is an indicator of the efficiency and level of development of countries, and on the other hand, determines the development potential of the country and the oil industry. They are also indicators of the imports and exports of goods and services as components of the calculation of national accounts indicators. With the digitalization of the economy, the role of the production and export of high-tech goods and the development of intellectual property increases, which in this study is considered through relevant indicators. This study also used debt indicators to assess sustainable development: short-term debt, debt service, and the amount of external debt. The economic development of countries at the expense of borrowed funds is risky from the point of view of financial security, and as a result, national security. Therefore, it is necessary to consider not only indicators of economic development, but also the measurement of financial sources of development. Among the indicators of social development, we used the inflation rate (as a factor of the depreciation of the population’s incomes, and reductions in the population’s purchasing power), the unemployment rate (as a factor of social tension and reductions in purchasing power), and the literacy rate (indicating potential for social and economic development). The poverty rate reflects the population’s income level. In addition to the income level, income distribution in society is essential. A widening gap in the wealth of the rich and the poor cannot indicate sustainable growth. The Gini index has been used to take into account the evenness of income distribution in the population. Nitrogen, methane, and greenhouse gas emissions are indicators that describe the environmental components of sustainable development.

The statistical data sources include [22,23,79,80,81]. Values of the indicators for OPEC member countries (Algeria, Angola, Congo, Equatorial Guinea, Gabon, Iran, Iraq, Kuwait, Libya, Nigeria, Saudi Arabia, United Arab Emirates, Venezuela [82]), observer states (Russia, Kazakhstan, and Azerbaijan), and the USA and Canada (which joined the OPEC++ deal) were used.

Among the world oil market’s condition indicators, we used Brent oil spot prices [22], oil futures prices [80], variations in Brent oil price, and indicators of the chain-weighted growth rates of the respective types of prices. In addition, the impact of these indicators on the sustainability of oil-exporting countries was investigated. Spot prices primarily reflect market demand for oil and futures prices (speculative demand) [83].

As tools of the supranational regulation of the world oil market’s development parameters, the factors influencing the demand and/or supply of oil are controlled at the supranational level. Consequently, such tools limit oil production volumes, oil exports, and the stimulation of developing renewable energy sources.

Using these variables (Table 1) for modeling was possible due to their stationarity. The extended Dickey–Fuller test was performed in the EViews 10 program to check the stationarity of the time series, which results are shown in

Table 2. Stationarity test results using indicators for assessing the impact of the oil market on the sustainable development of OPEC++-participating countries.

Indicator	Integration Level	Prob	Indicator	Integration Level	Prob	Indicator	Integration Level	Prob
Inv	1	0.01	Pov	0	0.00	Dea	1	0.02
GDP	1	0.02	Un	0	0.00	Cas.gr	0	0.01
Cap	0	0.00	Liter	1	0.04	Dea.gr	1	0.04
Imp	1	0.00	Nit	1	0.02	Dur	1	0.02
Exp	1	0.04	Met	0	0.01	Lock	1	0.04
S-deb	0	0.01	Gas	1	0.04	Cas.coun	1	0.01
Ser-deb	0	0.01	Spot	1	0.00	Dea.coun	1	0.04
T-deb	0	0.01	Fut	1	0.00	POil	1	0.00
Man	1	0.01	Var	1	0.04	EOil	1	0.03
Intel	0	0.01	Var-Fut	1	0.02	POil-gr	1	0.03
Tech	1	0.04	Spot-gr	1	0.02	EOil-gr	1	0.02
Inf	0	0.00	Fut-gr	1	0.02	Ren	1	0.01
Gin	0	0.04	Cas	1	0.02

Notes: Prob—the probability that the time series is non-stationary.

.

The indicator values of the probability do not exceed 0.05, which indicates the stationarity of the time series at the 0-th and 1st integration levels.

To test Hypotheses H1 and H3, we used annual statistical data of the relevant groups of indicators: sustainable development (SUS), oil market conditions (OIL), and regulatory tools (REG), for the period 1992–2020. Sustainable development indicators (SUS) were used in OPEC++-participating countries. Price indices of the oil market (OIL) were used globally without detailing by country. As regards the indicators of the regulatory tools used in the study of their impact on the price characteristics of the oil market (REG→OIL), the values were derived from around the world. However, when studying their impact on the sustainability of the countries (REG→SUS), the values for countries were used.

The study of the impact of financial investors’ panic (PANIC) is limited to the duration of the COVID-19 pandemic. To realize this purpose of the study and test Hypothesis H2, we used weekly global data of PANIC and OIL indicators from March 2020 to October 2021.

The annual and weekly indicator values used in this study were not combined in the same model. The results obtained from the annual data were not used in modeling the weekly data, and vice versa. These data were used to test different hypotheses. Therefore, annual and weekly data had no adverse effects on the adequacy of the simulation results.

4. Methodology

In order to test the hypotheses, the following econometric models were developed as part of our research:

(1)

Model of integrated assessment of the sustainable development of oil-exporting countries used in testing Hypotheses H1 and H3. The principal components analysis was used to determine the values of partial indicators of the integrated model and their weighting coefficients;

(2)

Panel regression models, linear regression models of the impacts of changes in physical volumes of oil production and exports, as well as oil prices, on the sustainable development of OPEC++-participating countries (Hypotheses H1 and H3);

(3)

Non-linear regression models to assess the financial investors’ panic factor impact caused by the COVID-19 pandemic on the price parameters of the development of the world oil market (Hypothesis H2).

The methodological approach to assessing the sustainable development of OPEC++-participating countries under the impact of changes in the characteristics of the crude oil market is shown in Figure 1.

A principal component analysis was performed in the STATISTICA 12.0 program to determine sustainable development components and factors affecting the sustainable development of the OPEC++-participating countries. Standardized values of the indicators were used for the analysis. Standardized values were calculated as the difference ratio between the actual indicator and minimum in the sample to the difference between maximum and minimum values. The composition of the principal components was determined based on factor loadings ≥ |0.7| [84]. The number of principal components was determined according to the Kaiser criterion, which is significant for those whose Eigenvalues are at least “1”. Finally, the principal component analysis was applied to the data sample for all the countries under study, based on the annual values of the indicators. The adequacy of its use was confirmed in 504 observations [85] which exceeded the cumulative variance percentage of 80% [84] (89.35% for principal components).

The model of the integrated assessment of the sustainable development of oil-exporting countries, taking into account the results of the principal component analysis, is presented as:

$$I_S={{\displaystyle \sum }}^{ }d{S}_i\times F{S}_i,$$

(1)

where I_S—integrated indicator of sustainable development;

dS_i—variance of the i-th component of sustainable development;

FS_i—the value of the i-th component of sustainable development.

The values of dS_i and FS_i were calculated using principal component analysis.

The integrated indicator of sustainable development must be calculated since sustainable development is described by many indicators (Table 1), which have different levels and dynamics, thus complicating the assessment.

In order to determine the coefficients of the significance of particular indicators when building an integrated additive model with no retrospective data, the expert method [86] and the informational entropy indicator [87,88] are usually used, or alternatively, particular indicators can be taken as equal in significance [75,89]. The disadvantages of such methods are:

(1)

For expert methods, the subjectivity of expert judgments;

(2)

Using the indicator of informational entropy considers the variability of variables, but does not reflect their significance. The method of building an integrated model, wherein partial indicators are taken to be of equal significance, also does not reflect the significance of the indicators.

Determining the coefficients of the significance of particular indicators proposed in this study made it possible to avoid subjectivity, because a statistical method was used. The significance of particular indicators was determined based on the percentages of variance, which describe the variability of the sustainable development of countries under the impact of groups of indicators (factors). This approach is applicable in the absence of the dependent variable values in retrospect, which is necessary, for example, for regression and discriminant models [11,17].

In addition, using all the intercorrelated indicators (Table 1) would lead to multicollinearity in the model. The exclusion of some indicators from the model would lead to a loss of informativeness. The integrated model (Formula (1)) made it possible to reflect all partial sustainable development indicators and avoid multicollinearity by using the principal components, which are not intercorrelated.

Due to the data panel’s nature, panel regression analysis was used to model the impact of changes in physical volumes of oil production, oil exports, and oil prices on the sustainable development of OPEC++-participating countries. In the EViews 10 program models, random panel effects were built. The model parameters were determined using the least squares method.

To determine the indicators of the world oil market’s conditions and the tools for its regulation, as specified in Table 1, we used indicators with statistically significant correlation coefficients, with the integrated indicator of sustainable development according to the Pearson criterion. The statistical significance of correlation coefficients was estimated at the significance level of p = 0.05.

Based on the correlation indicators, it has been determined that the following indicators were significant: Brent oil price, variation index of Brent oil spot price (based on daily price values), the growth rate of oil production by OPEC++-participating countries, and the growth rate of oil export volumes from OPEC++-participating countries. These indicators were used as independent variables in the models and the principal component analysis. The dependent variables of the regression model are the integrated indicator of sustainable development in OPEC++ countries and the values of sustainable development components of the countries. The components of sustainable development were determined by the principal component analysis, and used as dependent variables to determine the causes of changes in the integrated indicator of sustainable development under the impact of regressors.

Using principal components as dependent variables resulted in small confidence intervals, which might have reduced the reliability of the results obtained. Despite this, the adequacy of the regression models built for assessing the impact of world oil market indicators on the sustainable development of OPEC++-participating countries is confirmed by the following characteristics:

(1)

The impact of independent variables on the dependent variable established by the panel Granger causality test and confirmed by the t-Statistic for independent variables. The probability given by the Granger test that the independent variables have no impact on the dependent variable does not exceed 0.05. The empirical t-Statistic values exceed the critical value at a significance level of p = 0.05;

(2)

The F-statistic and the Durbin–Watson statistic criteria for models based on the comparison of their empirical values, with critical values at a significance level of p = 0.05;

(3)

Normally distributed model residuals.

The study of the impact of financial investors’ panic on the dynamics of world oil prices, based on weekly data from March 2020 to October 2021, did not reveal a linear function of the relationship between these indicators. To test Hypothesis H2, non-linear assessment methods in the program EViews 10 were used. We have established the variables that form panic in the oil market and their relationship with its price characteristics. The assessment model of the impact of panic of financial investors caused by the COVID-19 pandemic on the price parameters of the world oil market has the form:

$$Spot{\left(Var\right)}_t=a_1\times Loc{k}_t{}^2+a_2\times Loc{k}_t+a_3\times 1/Du{r}_t{}^2+a_4\times 1/Du{r}_t+a_0,$$

(2)

where Spot(Var) is the Brent oil spot price indicator (USD 100/bbl) and the Brent oil spot price variation indicator, respectively (weekly data);

Lock—the number of countries in lockdown;

Dur—the duration of the pandemic for the period of the study (weeks);

a₁–a₄—significance coefficients of the variables affecting the dynamics and variations of Brent oil prices;

a₀—intercept term.

The independent variables of model (2) were derived from the composition of the indicators (Table 1) based on their statistical significance. Statistical significance was established according to t-statistics, F-statistic, and the p-value, which does not exceed 0.05 for these variables.

5. Results

The application of principal component analysis made it possible to establish the model component composition of the impact of oil market conditions on the sustainable development of the OPEC++-participating countries (

Table 3. Components of the model for assessing the impact of oil market conditions, and the tools of its regulation, on the sustainable development of OPEC++ member participating countries.

Principal Components of the Model	Variable Structure	Eigenvalue	Variance, %
Macroeconomic development factor (Investment)	Inv, GDP, Cap, Imp, Exp, Man, S-deb, Ser-deb, T-deb, Inf *, Un *	7.37	43.70
The factor of innovative intellectual potential (Innovation)	Intel, Tech, Liter	2.72	16.12
The factor of social development (Social)	Gin, Pov, Inf *, Un *	1.98	11.74
Environmental factor (Environmental)	Nit, Met, Gas	1.71	10.14
Factor of oil production and export intensity (Production)	POil-gr, EOil-gr	1.29	7.65
Cumulative variance, %	-	-	89.35

* Indicators that are attributed to more than one principal component based on the values of factor loadings.

).

The results confirm the representativeness of the established groups of indicators when studying the impact of the oil market’s conditions on the sustainable development of the OPEC++-participating countries (Table 1). The indicators of consumer price inflation and the unemployment rate were not reflected unambiguously in the composition of the principal components, which indicates their wide-ranging impact on the sustainability of the crude oil-exporting countries. These indicators can be considered in the context of macroeconomic and social development.

Factors of macroeconomic development, innovative intellectual potential, social development, and the environment are formed from sustainable development indicators, as shown in Table 1. The factor of macroeconomic development characterizes the level of economic development of the countries under study, the volume of exports and imports, investment attractiveness, and the debt burden. The factor of innovative intellectual potential characterizes countries’ innovative and intellectual development (through the indicators of revenues derived from the use of intellectual property, the volume of exports of high-tech goods, and the literacy level of the population). The factor of social development describes the standard of living and the evenness of income distribution in society. Finally, the environmental factor describes the environmental component of countries’ sustainable development through indicators of emissions of harmful substances into the environment.

The factor of the intensity of oil production and export is formed from the tools of the supranational regulation of the development parameters of the world oil market: indicators of the growth rates of oil production and export from OPEC++ countries.

The Brent oil spot price indicators and variations in Brent oil global prices are not included in the factors due to the lack of statistically significant factor loadings. These indicators were used in building a model of the impact of the oil market’s conditions on the sustainable development of the OPEC++-participating countries without data reduction.

Based on macroeconomic and social development factors, innovation and intellectual potential, and environmental conditions, the integrated indicator of the sustainable development of OPEC++-participating countries was calculated. The variance in oil production and export intensity was not considered, as this factor is not a component of sustainable development. The dynamics of the integrated indicator of sustainable development for the countries are presented in Figure 2.

When calculating the integrated indicator of sustainable development, we used partial indicators–stimulants, whose growth indicates an increase in sustainability (for example, foreign direct investment, real GDP per capita, exports of high-tech goods, and others), and indicators–disincentives, whose growth harms sustainable development (for example, inflation, unemployment, poverty rate, nitrous oxides emissions, and others). Furthermore, the analysis of factor loadings verified that the indicators–stimulants have positive factor loadings with allocated factors, while the indicators–disincentives have negative ones, meaning that the macroeconomic development factor, the factor of innovative intellectual potential, the factor of social development, and the environmental factor are stimulants—their growth indicates a higher level of sustainable development in countries.

In order to assess the impacts of oil production and export volumes on the dynamics of the integrated indicator of sustainable development, panel regression models were built (

Table 4. Panel regression models for assessing the impact of oil production and export volumes on the sustainable development of OPEC++-participating countries.

Countries for Which IS ≥ 0.48				Countries for Which IS ≤ 0.31
Dependent Variable: integrated indicator of sustainable development (Investment)				Dependent Variable: integrated indicator of sustainable development (Investment)
Total panel (balanced) observations: 449		F-statistic: 11.9475		Total panel (balanced) observations: 45		F-statistic: 19.0654
Durbin–Watson statistic: 1.7793		Prob (F-statistic): 0.0000		Durbin–Watson statistic: 1.7890		Prob (F-statistic): 0.0000
Variable	Coefficient	t-Statistic	Prob.	Variable	Coefficient	t-Statistic	Prob.
Production	−0.7734	−2.8453	0.0195	Production	0.5942	3.3944	0.0106
Intercept term	2.4434	3.0532	0.0027	Intercept term	−1.7945	−4.0917	0.0013
Dependent Variable: integrated indicator of sustainable development (Innovation)				Dependent Variable: integrated indicator of sustainable development (Innovation)
Total panel (balanced) observations: 449		F-statistic: 27.2453		Total panel (balanced) observations: 504		F-statistic: 24.0987
Durbin–Watson statistic: 1.8007		Prob (F-statistic): 0.0000		Durbin–Watson statistic: 1.8019		Prob (F-statistic): 0.0000
Variable	Coefficient	t-Statistic	Prob.	Variable	Coefficient	t-Statistic	Prob.
Production	−1.2467	−3.8912	0.0004	Production	0.5035	3.9053	0.0019
Intercept term	3.7064	4.9818	0.0000	Intercept term	−1.564	−5.1092	0.0000
Dependent Variable: integrated indicator of sustainable development (Social)				Dependent Variable: integrated indicator of sustainable development (Social)
Total panel (balanced) observations: 449		F-statistic: 49.1193		Total panel (balanced) observations: 45		F-statistic: 42.1313
Durbin–Watson statistic: 1.7935		Prob (F-statistic): 0.0000		Durbin–Watson statistic: 1.8175		Prob (F-statistic): 0.0000
Variable	Coefficient	t-Statistic	Prob.	Variable	Coefficient	t-Statistic	Prob.
Production	−0.8396	−4.0115	0.0000	Production	0.9206	4.1761	0.0000
Intercept term	2.5047	7.1318	0.0000	Intercept term	−2.8045	−5.8990	0.0000
Dependent Variable: integrated indicator of sustainable development (Environmental)
Total panel (balanced) observations: 504				F-statistic: 31.2640
Durbin–Watson statistic: 1.8092				Prob (F-statistic): 0.0000
Variable		Coefficient		t-Statistic		Prob.
Production		0.7179		3.7890		0.0000
Production 2		−0.6846		−3.1509		0.0004
Intercept term		0.8468		4.1638		0.0000
Dependent Variable: integrated indicator of sustainable development (IS)				Dependent Variable: integrated indicator of sustainable development (IS)
Total panel (balanced) observations: 449		F-statistic: 29.1218		Total panel (balanced) observations: 45		F-statistic: 30.0060
Durbin–Watson statistic: 1.7925		Prob (F-statistic): 0.0000		Durbin–Watson statistic: 1.7905		Prob (F-statistic): 0.0000
Variable	Coefficient	t-Statistic	Prob.	Variable	Coefficient	t-Statistic	Prob.
Production	−1.2924	−4.1509	0.0000	Production	−0.9011	−5.0118	0.0000
Production 2	0.0516	2.9899	0.0217	Production2	0.1919	3.6703	0.0005
Intercept term	3.7543	6.1154	0.0000	Intercept term	−0.7778	−4.8912	0.0000

Notes: F-statistic—empirical values of F-criterion; t-Statistic—empirical values of t-criterion; Prob (F-statistic)—the probability that the empirical F-criterion value is not statistically significant; Prob—the probability that the empirical t-criterion value is not statistically significant; Durbin–Watson statistic—empirical value of the criterion; I_S—an integrated indicator of sustainable development; Production—factor value of oil production and export intensity; Investment—macroeconomic development factor value; Innovation—factor of innovative intellectual potential value; Social—factor of social development value; Environmental—environmental factor value; Production ²—factor 2 value of oil production and export intensity

).

We determined causal relationships between model variables using the panel Granger causality test. The results of the Granger test establish the statistically significant impact of the oil production and export intensity factor on the integrated indicator of sustainable development and its components. The probability that the oil production and export volumes do not affect the integrated indicator of sustainable development was 0.02.

The oil production and export intensity values, calculated during principal component analysis in the STATISTICA 12.0 program, were used as independent variables. The partial indicators that formed the factor were not used since they were intercorrelated, and their inclusion in the model would lead to multicollinearity. On the other hand, excluding these indicators would lead to lower informativeness.

To determine the levels of sustainable development in the countries under study, we performed Student’s t-tests for independent samples. As a result, it was determined that the first group of observations was formed by countries with the values of the integrated indicator of sustainable development ≥ 0.48, and the second group ≤ 0.31. For these groups, the criterion empirical value 27.33 exceeds the critical 1.97 [90] at a significance level of 0.05, indicating statistically significant differences in the integrated indicators of sustainable development for the countries of these groups.

The adequacy of the built regression models confirms the differential impact of oil production and export intensity on the sustainable development of countries, depending on the level of their development.

The probability that the empirical F-criterion values of the model and the t-criterion of the independent variables are not statistically significant tends to zero, indicating that the model and all independent variables are statistically significant. Adequacy is also confirmed by:

• The absence of autocorrelation, since the empirical value of the Durbin–Watson criterion (1.7793–1.8175) is greater than the critical level of 1.704 [91];
• Normally distributed model residuals, since they are based on the Jarque–Bera statistics at the significance level of p = 0.05 [92].

For the more developed countries, the growth of the factor of the intensity of oil production and export has a negative impact on sustainable development. An increase in opportunity costs causes a decrease in the rate of socio-economic development. Increasing oil production requires capital investment in the oil industry, which automatically reduces the amount of investment directed towards developing other more technological, efficient, promising sectors of the economy, which constrains economic and social development.

For less developed countries, high-tech industries require increased investment in their development. The growth of oil production and export leads to economic and social development; therefore, it is advisable to increase capital investment to increase the technological effectiveness of this industry.

The reverse effect of oil production and export intensity on environmental development (environmental factor) is explained by the growth of emissions of pollutants from oil production into the environment, which is relevant for all countries under study, regardless of the development level.

The impact of the oil production and export intensity on the environmental factor does not differ depending on the sustainable development level (

Table 5. Graphs of the impact of the oil production and export volumes on the sustainable development of OPEC++-participating countries.

Dependent Variable	Macroeconomic Development Factor	The Factor of Innovative Intellectual Potential	The Factor of Social Development
Graph of the dependence on the factor of oil production and export intensity
Dependent variable	Environmental Factor	Integrated Indicator of Sustainable Development	for more developed countries with an integrated indicator of sustainable development ≥ 0.48; for less developed countries with an integral indicator of sustainable development ≤ 0.31; for all countries, regardless of sustainable development level
Graph of the dependence on the factor of oil production and export intensity

Notes: IS—an integrated indicator of sustainable development; Production—factor value of oil production and export intensity; Investment—macroeconomic development factor value; Innovation—factor of innovative intellectual potential value; Social—factor of social development value; Environmental—environmental factor value.

).

The impact of the financial investors’ panic factor caused by the COVID-19 pandemic on the development of the world oil market is interpreted using regression models of a non-linear type (

Table 6. Regression models for assessing the impact of the financial investors’ panic factor on the global oil market.

Model	t-Statistic	p	F-Statistic	Prob(F-Statistic)	E, %
Spot = −0.0019 × Lock2 + 13.9353/Dur2 − 13.8256/Dur + 0.6082	t(Lock2) = −12.57 t(Dur2) = 7.69 t(Dur) = −8.20	0.00	38.42	0.00	E (Lock) = −0.48 E (Dur) = 0.28
Var = 0.0001 × Lock2 + 0.0037 × Lock − 1.7373/Dur2 + 1.6088/Dur	t(Lock2) = 6.11 t(Lock) = 8.64 t(Dur2) = −6.04 t(Dur) = 7.10	0.00	20.15	0.00	E (Lock) = 0.57 E (Dur) = −0.50

Notes: t-statistic—empirical values of t-criterion; p—significance level; F-statistic—empirical values of F-criterion; Prob (F-statistic)—the probability that the empirical F-criterion value is not statistically significant; E—values of the dependent variable elasticity, characterizing the percentage change in the resultant indicator when the independent variable grows by 1% compared to its average value for the period under study; Spot—indicator of spot prices for Brent oil, USD 100/bbl (weekly data); Var—variation in spot prices for Brent oil (annual values); Lock—the number of countries in lockdown; Dur—the pandemic’s duration on the date of analysis, in weeks.

).

The built models testify to the statistical significance (at p = 0.05) of the dependence of price indicators of the world oil market situation (spot prices and indicators of their variation) on the number of countries in lockdown and the pandemic’s duration.

Expansion of the pandemic scale (the number of countries with a quarantine on the territory) destabilizes the situation in the oil market—it provokes a decrease in prices and increases volatility, because of uncertainty in the market and panic among investors, caused by uncertainty in the stability of demand for oil and the possibility of the realization of futures for purchase of oil. However, at the same time, the prolonged nature of the pandemic’s spread over time helps to reduce the negative impacts (and may lead to zeroing the threats outlined), since investors are adapting to instability and reducing instances of financial investors’ panic. The statistical significance of these indicators is confirmed by empirical values of the t-Statistic exceeding the critical 2.0 and those of the F-statistic exceeding the critical 2.71 [90] at a significance level of 0.05, with a p-level→0. These indicators point to the adequacy of the built models.

In order to assess the impact of oil prices on the sustainable development of OPEC++-participating countries, the following panel regression model was built (

Table 7. Regression model for assessing the impact of oil prices on the sustainable development of OPEC++-participating countries.

Dependent Variable: Integrated Indicator of Sustainable Development (IS) Total Panel (Balanced) Observations: 504		F-Statistic: 17.0964 Prob (F-Statistic): 0.0000 Durbin–Watson Statistic: 1.7094
Variable	Coefficient	t-Statistic	Prob.
Spot	−1.1646	−5.0521	0.0000
Var	−0.9708	−4.1632	0.0000
Intercept term	0.0891	2.7325	0.0229

Notes: F-statistic—empirical values of F-criterion; t-Statistic—empirical values of t-criterion; Prob (F-statistic)—the probability that the empirical F-criterion value is not statistically significant; Durbin–Watson statistic—empirical value of the criterion; I_S—integrated indicator of sustainable development; Spot—indicator of spot prices for Brent oil, USD 100/bbl; Var—variation in spot prices for Brent oil (annual values).

).

The built model has demonstrated the statistically significant impact of spot prices for Brent oil and variations in these spot prices on the integrated indicator of sustainable development. Rising crude oil prices and their volatility have a negative impact on the sustainable development of oil-exporting countries due to the manifestation of the “resource curse”, and a decline in the investment attractiveness of the industry and the country.

The representativeness of the obtained results is ensured by the following:

• The probability that the empirical F-criterion and t-criterion values are not statistically significant tends to be zero;
• Autocorrelation is absent, because the empirical value of the Durbin–Watson statistic (1.7094) is greater than the critical level of 1.69 [91];
• The model residuals are normally distributed, since they are confirmed at the significance level of p = 0.05 [92].

6. Discussion

Our empirical research allowed us to make several important statements, such as that, among the traditional factors in the high volatility of oil prices, such as reductions in demand for crude oil due to the slowdown of the world economy, reductions in the business activity of national economies, and the diversification of investments in energy resources with the priority of developing alternative energy sources, financial investors’ panic should also be included. Undoubtedly, this factor is particularly acute given the risk of uncertainty related to socio-economic development. As the results have shown, financial investor panic was the most significant factor at the beginning of the COVID-19 pandemic, during which countries imposed lockdowns, leading to a record fall in global oil prices. When the number of countries with lockdown grows by 1%, oil spot prices fall by 0.48%, and price variations increase by 0.57%. The above allows us to confirm the formulated Hypothesis H2. Further information about new pandemic waves, new surges of infection, and mortality did not lead to changes in the price characteristics of the world oil market, despite the continued decline in business activity around the world, and in the OPEC++-participating countries. Based on the results obtained, it can be concluded that further waves of the COVID-19 pandemic, unless a massive hard lockdown is introduced, will not lead to significant falls in oil prices, since, during this period, financial investors’ panic has the most significant impact on price volatility—much greater than the reduction in business activity around the world.

The findings do not refute the results of studies by Ponkratov et al. [11], Le et al. [12], and Shaikh [16]. Higher elasticities in the price characteristics of the oil market’s development are implied by the indicator of the number of countries with lockdown than by the indicator of the COVID-19 pandemic’s duration. Undoubtedly, this can be explained by the impact of not only the financial investors’ panic factor, but also by the decline in demand for oil as a result of the reduction in production and services during the lockdown. The pandemic’s duration impacts the effects of financial investors’ panic on the oil market. Meanwhile, the effect of the number of locked-down countries on the price characteristics of the oil market manifests itself without a time lag. This impact does not provide the time lag needed to mitigate the adverse effects of financial investors’ panic on the oil market. Uncertainty, which depends on the pandemic’s duration, also significantly impacts the oil price dynamics and their variation: the longer the pandemic duration, the lower its impact on the oil market.

Model building made it possible to establish the different impact of oil production and export intensity on the integrated indicators of sustainable development, macroeconomic development, innovative intellectual potential, and social development factors, depending on the development level of the countries. For countries with a higher level of development (with the integrated indicator of sustainable development higher than 0.48), a decrease in oil production and export leads to an increase in the macroeconomic development factor. In less developed countries (with the same indicator’s value less than 0.31), it decreases the values of these factors. The revealed regularity is explained by the fact that, on the one hand, a decrease in oil production and exports contributes to the diversification of the economy, and the development of more advanced industries with greater added value, which is characteristic of more developed countries and agrees with the point of view of Khodaparast Shirazi et al. [52]. On the other hand, a decrease in the volume of oil production and exports reduces companies’ profits, the volume of budget revenues, and funds allocated for innovative development and social payments. In less developed countries, this decrease is more tangible, and the opportunity to diversify the economy becomes more limited due to the reduction in funds that could be invested in the development of other industries.

The impact of oil production and export intensity on the environmental factor is identical for countries with any level of sustainable development. A reduction in production volumes leads to growth in environmental factor values, improving the country’s environmental situation. For less sustainably developed countries, a decrease in oil production and exports has a more significant positive effect on the environment, while in more developed countries, a less significant effect is seen. This regularity confirms the possibility of applying the Laffer hypothesis to explain the relationship between trade, economic growth, and sustainability for oil-producing countries [52]. We used the environmental Kuznets curve hypothesis [46] to interpret the results. Developed countries are characterized by high-tech, resource-saving, efficient oil production facilities that are less harmful to the environment. In less developed countries, oil production is more harmful to the environment. Consequently, reducing the production volume has a more significant positive effect. By considering the changes in the components of sustainable development, it can be determined that reducing oil production and exports has a positive effect on the sustainable development of OPEC++-participating countries. For more developed countries, the positive effect is more significant; for less developed countries, it is less significant.

The identified patterns indicate an ambiguous impact of reducing oil production and exports on sustainable development, confirming Hypothesis H1. This ambiguity manifests in different impacts on:

(1)

The components of sustainable development (the growth of environmental factors, the growth and decline of macroeconomic development innovative intellectual potential, social development factors);

(2)

Countries depend on their level of macroeconomic development, their innovative intellectual potential, and their social development factors (growth in more developed countries, reduction in less developed ones).

It has been empirically proven that an increase in the spot price of oil harms the sustainable development of OPEC++-participating countries, although higher oil prices should lead to higher corporate earnings and higher budget revenues. The resulting negative impact can be explained within the “resource curse” theory framework. Rising oil prices stimulate the oil industry’s development, while other more high-tech industries with higher value-added come second, thus hindering economic development. The development of the oil industry means an increase in the production volume, which, as was proven within the framework of Hypothesis H1, leads to a deterioration in the environmental component of sustainable development, and a decrease in the macroeconomic development, innovative intellectual potential, and social development for more developed countries. The results confirm Hypothesis H3, according to which an increase in the level of crude oil prices has a negative impact on the sustainable development of oil-exporting countries.

A disincentive to sustainable development is also the growing volatility of oil prices. Increased volatility reduces the investment attractiveness of the industry and the country, and, accordingly, reduces the financial resources channeled into the development of oil and other industries.

In general, based on the results of our study, we can state that with the uncertainty of the pandemic and the developing trend of green growth in OPEC++ countries, for developing economies in particular, sustainability in the current environment cannot be achieved by reducing oil production and exports or by increasing the level of spot prices. The priority should be countercyclical government policies that aim to reduce government spending (spending less than earning). The introduction of a flexible fiscal policy and medium-heavy taxation would create incentives to invest and counter the threat of the nationalization of the extractive industry at a time of high volatility in oil prices.

7. Conclusions and Recommendations

According to the integrated assessment results among OPEC++-participating countries, the USA, Canada, the United Arab Emirates, and Kuwait demonstrated the highest level of sustainable development. Nigeria, Congo, and Angola showed the lowest levels of all components of sustainable development. Throughout the period under study, most countries observed growth in the integrated indicator of sustainable development. The USA has demonstrated the most stable growth dynamics in this indicator.

Thus, based on these findings, it is advisable to develop an effective strategy for managing the crude oil market in OPEC++-participating countries in order to achieve SDGs. In forecasting oil prices, it is necessary to consider the financial investors’ panic factor. This factor is difficult to assess via the scientific approach only because, as a psychological factor, it cannot be confirmed or refuted empirically, since there will always be market participants who benefit from one or another investment strategy, which means that it is possible to adjust the panic theory to any price dynamics. Today, oil has been transformed into a financial asset because trading in financial derivatives (futures) greatly exceeds physical oil’s global production and consumption. Sellers and buyers of this virtual oil need information about the actual and future market conditions in order to make rational decisions about the prices and volumes of transactions. The primary source of this information remains the market of the basic asset, i.e., physical oil. That means that supply level adjustments can impact prices even in times of financial investors’ panic. According to the results obtained, a reduction in oil production volumes, as suggested by the terms of the OPEC+ and OPEC++ deals, will lead to the stabilization of oil market prices, but will negatively affect the sustainability of the countries’ development. Frequent violations of the terms of the agreement by the OPEC++-participating countries also jeopardize the effectiveness of the regulatory tools discussed above. However, efforts to reduce production are no longer enough to balance the market in its current conditions. Building an energy business based on digital platforms, pools of intellectual property rights, big data, digital algorithms and targeted marketing technologies on the one hand, with the exponential growth of information (related to the thinking, psychology, and perception of consumers) and technological transformations on the other hand, can help to create fundamentally new conditions for balancing supply and demand in the oil market.

Reductions in oil production and exports generally positively affect the sustainable development of OPEC++-participating countries. For more developed countries, the positive effect is more significant; for less developed countries, it is less significant. Therefore, this study shows that in resource economies, a reduction in oil production and exports does not have the same effect on sustainable development as in countries that do not produce oil or are characterized by a higher level of economic development. This point is confirmed by the empirical validation of the long-term adverse effect of rising crude oil prices on SDG implementation. This effect is explained by the low level of economic diversification and the concept of the Dutch disease, as scholars have noted extensively. However, in our view, these factors are secondary and generated by institutional weaknesses in the OPEC+++ countries, particularly those characterized by emerging economies.

Undoubtedly, economic diversification will provide a basis for sustainable development in long-term GDP growth, reduce the volatility of oil prices, and stimulate employment. However, diversification of the economy requires appropriate conditions, which cannot be achieved—as studies have shown so far—by reducing oil production and exports and increasing oil prices. Moreover, weak institutions preclude overcoming the “resource curse”, and discourage SDG achievement. The result is a vicious circle, by which it is impossible to achieve sustainability without creating effective political and economic institutions in the OPEC+++ countries.

A country with any level of economic development, given the political will, can create institutions, and implement policies and instruments, that promote economic growth and economic diversification. Unfortunately, the means to generate this will are unknown. However, in our view, democracy, countercyclical fiscal policy, strong property rights protection, an open economy, low levels of corruption, government accountability, contract guarantees, and other factors can provide a solid foundation for SDG achievement in resource economies. Moreover, since the decline in demand for oil is the primary trend of the world economy in the short term, it seems advisable to reorient petrodollars towards promising high-tech market segments, which will act as drivers of economic growth in oil-exporting countries.

The results obtained here are practical, but their implementation is limited to the short- and medium-term, since the oil market is highly volatile with a pronounced cyclicality. At the same time, the SDGs and related targets are global, and are implemented in the long term. Therefore, the compatibility of OPEC countries’ sustainable development objectives with the oil market’s prospects has not been studied in this article, but will be considered in our future works. Also of particular interest to us is the study of the institutional framework’s impact on achieving sustainable development, economic openness, and economic growth in oil-exporting countries. Finally, the impact of the financial investors’ panic on the oil market’s ability to achieve the SDGs is of particular interest to us. This factor is characterized by the versatility and complexity of potential impacts, and deserves a devoted study.