Investment decision of fdi firms in vietnam under uncertainty of carbon taxation

OVERVIEW OF RESEARCH

Research setting and motivations

Three critical financial decisions for firms include investment, dividend, and financing decisions, with investment decisions in foreign countries being the most challenging due to uncertainties related to differing political systems, cultures, laws, and customer behaviors The academic exploration of "investment decision under uncertainty" began with Hirshleifer in the 1960s and has since been expanded by scholars like Lucas Jr & Prescott, Abel, and Dixit & Pindyck, making it a significant topic of interest in contemporary research This ongoing development reflects the complexities and importance of making informed investment choices in an unpredictable global landscape.

Investing in large fixed asset projects, often deemed irreversible, is expected to yield significant profits in the medium to long term, driving substantial growth for firms However, such investments carry considerable risks due to uncertainties in both internal and external environments External factors contributing to this uncertainty include market fluctuations, potential technological advancements that could render existing projects obsolete, and changes in regulations, laws, and political stability in the project's intended location.

Uncertainties can significantly raise project investment costs during both the investment and commercial production phases, ultimately increasing production expenses and reducing competition, which diminishes profitability As rational investors, firms remain vigilant regarding these uncertainties Consequently, companies and their consulting experts strive to quantify and manage these uncertainties, converting them into more manageable risks.

11 bring it into project financial appraisal, increasing the likelihood of project success (Munns & Bjeirmi, 1996).

Following World War II, Western multinational enterprises experienced significant market expansion, fueled by rapid economic growth in many Western nations This growth enabled large corporations to invest heavily in overseas projects for greater profits, shifting their focus from domestic production and exports Consequently, fierce investment competition emerged among multinational corporations, particularly as strong economies sought to exert influence in potential investment countries for competitive advantages This competitive landscape forced these enterprises to make swift investment decisions, often under conditions of limited information and high uncertainty, thereby necessitating a willingness to embrace increased risks in their investment strategies.

Many countries advocate for international economic integration while simultaneously imposing trade and investment barriers to protect domestic firms These barriers manifest as technical obstacles, complex regulations, and a lack of transparency in the investment environment, often accompanied by ambiguous interpretations of policies Additionally, restrictions influenced by local cultures, religions, and environmental concerns further hinder foreign investment and trade Such policies create significant uncertainty, negatively impacting foreign firms' willingness to invest and engage in international trade.

The increasing uncertainties faced by firms pose significant challenges to their investment decisions This rise in uncertainty has spurred extensive research aimed at understanding its implications.

Investment decisions under uncertainty are increasingly significant, particularly as multilateral and bilateral trade and investment policies evolve, presenting prime opportunities for firms within member countries To effectively attract foreign investment, host governments must comprehend the behaviors and decision-making processes of these firms Vietnam, actively engaging in global economic integration through international trade and investment agreements, is experiencing shifts in its external business environment Consequently, the factors influencing investment decisions are growing in both quantity and complexity, highlighting the rising levels of uncertainty that firms must navigate.

Since the United Nations Climate Change Declaration in 1992 and the Kyoto Convention in 1997, many countries have committed to reducing greenhouse gas emissions, with carbon taxation being a key measure Although developing nations like Vietnam have not yet adopted mandatory carbon emission reductions, the possibility remains for future implementation Consequently, Vietnam's investment landscape may face uncertainties regarding potential carbon taxes on projects that generate emissions and rely heavily on fossil fuels Research by Fuss et al (2008) highlights that climate change policies are significant systematic risks in the 21st century.

(2008), after the year 2012, the risk of carbon taxation is getting bigger.

Vietnam serves as a compelling case study for understanding the investment decisions of foreign direct investment (FDI) firms amidst the uncertainties of carbon taxation As a developing country, Vietnam prioritizes attracting FDI, particularly for large, irreversible projects like power plants and chemical factories According to forecasts by the Global Infrastructure Hub and Oxford Economics, Vietnam requires approximately $608 billion for infrastructure investments from 2016 to 2040, with $265 billion allocated for large-scale fossil fuel energy projects This substantial investment necessitates collaboration between local governments and both domestic and foreign companies Additionally, the absence of carbon taxation has led to an influx of carbon leakage projects, where investors from carbon-taxed countries seek to avoid such taxes by investing in Vietnam Consequently, these investors must navigate carbon-related uncertainties when making investment decisions Furthermore, Vietnam's status as a transitional economy, characterized by an imperfect legal system, may attract foreign firms seeking to capitalize on weaker environmental regulations, allowing them to minimize environmental costs and taxes.

Academic research on investment decisions under uncertainty can be categorized into two primary strands: theoretical studies that explore the principles of investment decision-making amidst uncertainty, and empirical investigations that analyze significant uncertainties such as price volatility, rising costs, exchange rate fluctuations, and tax implications on investment choices.

In theoretical research, notable authors such as Lucas & Prescott (1971), Hartman (1972), Abel (1983), and Dixit & Pindyck (1994) have established that an increase in a firm's marginal profit function due to heightened uncertainty incentivizes greater investment and production levels Additionally, Pindyck (1991) and Dixit & Pindyck (1994) highlighted the critical aspect of investment irreversibility in large-scale asset projects, indicating that investors often postpone investment decisions in response to increased uncertainty, opting to wait for clearer information to ensure future profitability.

Increased uncertainty can generate an option value of waiting, suggesting that valuable information may emerge in the future Theoretical research on the interplay between uncertainty and investment identifies two primary types: timing uncertainty, which influences when to invest, and uncertainty regarding the level of investment itself.

The theoretical research on "investment decisions under uncertainty" indicates that uncertainties related to taxation significantly lower foreign direct investment (FDI) levels Pindyck (1986) demonstrated that tax policy uncertainty reduces firm investment, a finding echoed by Hassett & Gilbert (1999) through the use of a randomized continuous-time algorithm Additionally, Alvarez et al (1998) found that investors are likely to accelerate investment when anticipating tax rate decreases, while Hassett & Metcalf (1999) and Agliardi (2001) confirmed that uncertainties in tax policy can delay investment projects.

Theoretical research utilizing simulation methods examines how future uncertainties impact current investment decision-making Although these uncertainties have yet to materialize, they significantly influence investors' choices today.

This article examines five irreversible investment projects, focusing on coal-fired power plants and iron and steel plants Utilizing net present value (NPV) calculations and advanced algorithms, the research analyzes potential outcomes amid future uncertainties related to carbon taxation.

2013) which are very close research to the thesis.

In Vietnam, there are quite a few researches on the factors affecting FDI inflows in general The typical researches should be referred to Nguyen Thi Lien Hoa

Research targets and research questions

This thesis aims to develop a novel mathematical economic model that analyzes the profit function of firms engaged in investment projects, incorporating the uncertain impacts of carbon taxation The model will elucidate the intricate relationship between investment decisions and environmental regulations, providing valuable insights for businesses navigating the complexities of carbon pricing.

This article explores the relationship between a firm's profit levels and the impact of carbon taxation on investment decisions, utilizing Varian's (1992) profit function By employing an optimization algorithm, the study analyzes how carbon tax influences key elements in the profit function, including capital stock (K) and labor level (L) The findings will be interpreted to formulate relevant theoretical proposals.

This thesis aims to identify research gaps by reviewing theoretical and empirical studies, with a focus on developing a mathematical model to address these gaps It will investigate how uncertainties related to carbon taxation affect the investment decisions of investors from developed, carbon-taxed countries when investing in irreversible projects in developing countries, particularly those similar to Vietnam By creating mathematical models and conducting calculations, the research will analyze investment decision-making and the selection of capital, technology, and labor levels in irreversible foreign direct investment (FDI) projects in Vietnam amidst carbon tax uncertainties.

In order to fulfill the research objectives of the thesis, the following two research questions were studied and answered by the thesis.

(1) What are effects of carbon taxation uncertainties on investors’ investment decision in irreversible FDI projects?

(2) What are the levels of capital per labor selected by the investors in irreversible FDI projects under uncertainties of carbon taxation?

Research objectives and scope of research

This thesis focuses on how foreign firms make investment decisions in irreversible projects amidst uncertainties linked to carbon taxation, which is increasingly adopted in developed countries for sustainable development and is anticipated to be implemented in Vietnam soon The study will analyze the effects of these uncertainties on foreign investors' behavior, particularly regarding their optimal choices of capital, technology, and labor in their investment initiatives in Vietnam.

This article presents managerial and policy recommendations aimed at attracting higher-quality foreign direct investment (FDI) projects These strategies focus on minimizing environmental impacts while simultaneously enhancing the quality of technology and labor associated with these investments.

The research focuses on large fixed assets owned by foreign companies in Vietnam that contribute to carbon emissions, highlighting the associated risks of carbon taxes in these investments Known in academia as irreversible investment projects (McDonald & Siegel, 1986), these significant ventures typically involve essential commodities or infrastructure in sectors such as transportation, telecommunications, energy, and oil and gas Investors are predominantly large multinational enterprises (MNEs/MNCs) from developed nations, where carbon tax avoidance is a prevalent issue.

1 MNEs/MNCs (Multinational Enterprises/Companies)

19 applied or about to apply, to non-carbon taxation developing countries, therefore, this study in Vietnam context can be generalized to other developing countries.

Methodology

This thesis employs a quantitative approach, utilizing mathematical modeling and simulation techniques based on reasonable assumptions and available empirical data The selection of the research method is guided by the research's nature, relevant studies, and the accessibility of actual data.

This thesis introduces a novel research direction focusing on investment decisions under uncertainty related to future carbon taxation in Vietnam, an area lacking prior studies Utilizing qualitative methods, such as in-depth interviews with experts, may yield significant bias due to the absence of current carbon tax-related uncertainties, making discussions about future implications challenging Consequently, the reliability of the information gathered through interviews for analysis is questionable On the other hand, employing quantitative research to collect empirical data for hypothesis testing is also impractical, as carbon taxation has yet to be implemented, rendering empirical data ineffective in reflecting the potential impacts of carbon tax uncertainty Thus, both qualitative and quantitative research methods face substantial limitations in this context.

This thesis employs quantitative methods through algorithmic modeling and computational simulations to analyze the profit function of a firm in relation to uncertainties surrounding carbon taxation By utilizing mathematical techniques to develop this model, the research aims to assess how these uncertainties influence the firm's investment decisions regarding capital, technology, and labor levels.

The profit function model proposed by Varian (1992) has been selected for its advantages over the traditional net present value (NPV) approach This model, as outlined by Varian (1992, p 23), provides a comprehensive framework for analyzing firm profitability, making it a valuable tool for decision-making in economic contexts.

- � : is profit function of the firm.

- F (K, L): is the production volume of the firm depending on capital level (K) and labor level (L).

- C (r, w): is the cost of the business operation depending on the cost of capital (r) and labor wage (w), not including the cost of carbon tax.

- T (τ): is the cost of carbon tax that the firm needs to pay when the government imposes carbon tax on the volume of carbon emission.

- p is average selling price of products

The function operates under the fundamental assumption that the firm consistently invests when the return is positive, aiming to maximize profits as a rational investor Consequently, the firm selects the optimal input levels of capital (K), labor (L), rental rate (r), and wage rate (w) to achieve this profit maximization A comprehensive discussion of the research methodology and the chosen research model is provided in Chapter 3 of the thesis.

Expected outcomes of the thesis

The thesis aims to enhance academic knowledge and research methodologies in project appraisal, focusing on uncertainties in investment decisions related to irreversible projects, particularly carbon taxation Chapter 2 will present a theoretical framework and empirical evidence, emphasizing the impact of carbon taxation on low-tech investors Furthermore, the mathematical model developed in the thesis is anticipated to yield new theoretical insights, suggesting that carbon taxation could serve as a significant adjustment tool for government policies.

21 develop carbon tax related policies to increase the quality level of FDI projects This theoretical discovery is a clearly novelty of the thesis.

This thesis introduces innovative research methods and tools to Vietnam's academic community, specifically through the use of mathematical modeling and simulation techniques These advancements contribute to diversifying the research methodologies employed in Vietnam, enhancing the overall research practice.

This thesis examines various methods of project appraisal, specifically Discounted Cash Flow (DCF) and Return on Investment (RO), for large asset projects crucial to industrial and economic development It serves as a valuable reference for applied research in investment project appraisal while enhancing students' understanding of project finance, appraisal techniques, and project management.

Structure of the thesis

The thesis is structured into five chapters, with Chapter 1 offering a comprehensive overview of the research This chapter outlines key components including the research context, motivation, targets and objectives, as well as the scope of the study Additionally, it highlights the anticipated academic contributions and practical applications of the thesis outcomes.

Chapter 2 - Theoretical framework and empirical evidence, focusing on the analysis of previously theoretical researches in the world and developing the framework related to the main research direction of the thesis is the relationship between the firm’s investment decision and uncertainties in the irreversible project A number of relevant empirical studies will also be analyzed and commented to identify research gaps The final part of Chapter 2 is to analyze and select the basic research model which is the profit function of firm for further modeling and simulation of the thesis.

Chapter 3 - Research Method is to focus on comparative analysis for selection of research method on the given research settings, research targets, research questions, objectives and scope of research Chapter 3 also discusses the basic assumptions in the research model and simulation data to ensure both the convenient development of the model, but such the assumptions do not distort the research results.

Chapter 4 - Research results is to focus on the development of investment decision model of the firm to invest in the investment project in different cases such as

The application of a carbon tax varies, with expectations for its implementation throughout the project life cycle This affects the investment decision-making of two distinct firms as they choose their capital, technology, and labor levels under the same carbon tax rate The theoretical insights gained from each scenario will serve as a foundation for subsequent simulation analyses.

Chapter 5 - Conclusions and managerial/policy implications are developed on the basis of research results in Chapter 4 This chapter will summarize and interpret the results of theoretical findings Based on these findings, a number of policies and managerial implications are proposed Chapter 5 will also discuss some further research directions to better deepen the researches on the relationship between carbon taxes and the firm’s investment decision.

Research on the interplay between a firm's investment decisions and uncertainties in irreversible investment projects is a prominent area of study globally This field often begins with the broader examination of "investment decision under uncertainty," particularly focusing on tax-related uncertainties The thesis is closely linked to various aspects of investment operations, including the characteristics of irreversible projects, project appraisal, project finance, and the associated risks and uncertainties Chapter 2 will provide a comprehensive summary of these related studies, establishing a theoretical framework for the thesis's research model.

2.1 The firm and investment operation.

2.1.1 The rationality of the firm’s investment decision.

A firm is fundamentally defined as a legal entity established for profit, operating under the law with the primary goal of generating income (Chandler, 1992) Its activities are strategically designed to achieve profits in the short, medium, and long term Initially, firms primarily focused on trading goods, which encompassed buying, storing, sorting, preliminary processing, packaging, and transportation.

The evolution of firms has transitioned from artisanal and industrial production to a focus on service and industrialization, with machinery and equipment becoming essential components Key factors driving this development include the ongoing learning and experiences of managers and employees, advancements in production equipment and technology, and the availability of capital.

The emergence of the multinational company model coincided with the expansion of firms into manufacturing establishments across various countries Established in 1600, the East India Company is recognized as the world's first multinational corporation, engaging in the purchase, transportation, stockpiling, and sale of agricultural products, as well as the exploitation of colonial resources and investment in agriculture within the colonies for importation back to the United Kingdom (Sen, 1998).

The contemporary industrial enterprise, which began to take shape in the 1880s, has evolved significantly and continues to thrive today These modern enterprises are defined by a combination of highly skilled labor and advanced machinery, enabling capital-intensive production This approach optimizes production inputs, leading to economies of scale, where increasing production volume results in lower unit costs.

Modern industrial enterprises primarily operate in sectors requiring advanced technology and equipment, such as automobile assembly, transportation, energy, oil and gas, chemicals, and pharmaceuticals Recently, new players have emerged, focusing on digital services and information-communication technology, with companies like Intel, Google, Microsoft, Apple, and Samsung leading the way Most firms in the S&P 500 are categorized as large industrial or technology enterprises, with their investments typically directed towards large-scale projects that involve significant capital, complex technology, and a demand for highly skilled labor, ultimately producing and supplying high-tech products and services.

The firm not only serves as a producer and supplier of goods but also functions as an investor, continually seeking investment opportunities to sustain its established market position while exploring new potential markets.

In 2015, industrial enterprises increasingly prioritized the identification, assessment, and decision-making processes related to substantial industrial projects Consequently, large industrial projects have emerged as strategic investments for contemporary industrial firms.

The general profit function of an enterprise is denoted as Л calculated as turnover minus production cost.

In profit maximization, the relationship between the average selling price (p), total quantity produced or sold (q), and production cost (C) is crucial, as production costs increase with higher output levels To achieve maximum profit, firms strategically determine the optimal production level (q) that maximizes profit (Л) at the established price (p) This leads to the formulation of the profit maximization function.

The Cobb-Douglas production function (q = AK α L β) illustrates the relationship between a firm's output (q) and its inputs, namely capital (K) and labor (L) This function serves as a foundation for understanding how project or firm profits relate to these inputs Furthermore, the profit function can be expanded to incorporate additional production costs, including potential future expenses such as new taxes that may impact operational costs.

The firm and investment operation

2.1.1 The rationality of the firm’s investment decision.

A firm is fundamentally defined as a legal entity created for profit, operating under the law with profit maximization as its primary objective (Chandler, 1992) Every activity undertaken by a firm is strategically aimed at generating profits in the short, medium, and long term Historically, firms primarily engaged in trading goods, which involved activities such as buying, storing, sorting, preliminary processing, packaging, and transportation.

The evolution of firms has transitioned from artisanal to industrial production, where machinery and equipment play a crucial role This shift marks the beginning of a service-oriented era in business According to the author, the development of a firm hinges on three key factors: continuous learning and experience among managers and employees, advanced production equipment and technology, and sufficient capital.

The concept of the multinational company emerged as firms expanded their manufacturing operations across various countries Established in 1600, the East India Company is recognized as the first multinational corporation, engaging in the purchase, transportation, storage, and sale of agricultural products while exploiting colonial resources and investing in agriculture within the colonies for importation back to the United Kingdom (Sen, 1998).

The modern industrial enterprise, which began to emerge in the 1880s, is characterized by a combination of highly educated labor and advanced machinery, leading to capital-intensive production This integration allows for the optimization of production inputs, resulting in economies of scale where increased production lowers the unit cost.

Modern industrial enterprises primarily operate in sectors that require advanced technology and equipment, including automobile assembly, transportation, energy, oil and gas, chemicals, and pharmaceuticals Recently, a new wave of firms has emerged, emphasizing digital services and information-communication technology, with notable examples being Intel, Google, Microsoft, Apple, and Samsung Most companies within the S&P 500 are classified as large industrial or technology enterprises, often channeling their investments into large-scale projects that involve significant capital, complex technologies, and a demand for highly skilled labor, ultimately producing and supplying high-tech products and services.

The firm not only serves as a producer and supplier of goods but also functions as an investor, consistently seeking investment opportunities to uphold its established market position while exploring new potential markets.

In 2015, industrial enterprises increasingly prioritized the search, evaluation, and decision-making processes for investing in large industrial projects These significant investments are viewed as strategic opportunities for modern industrial companies.

The general profit function of an enterprise is denoted as Л calculated as turnover minus production cost.

To maximize profit, a firm determines the optimal production level (q) by analyzing the relationship between average selling price (p), total quantity produced/sold, and production costs (C), which increase with higher production volumes The profit maximization function is established to ensure that the profit (Л) reaches its maximum value at the chosen output level, given the set price.

The Cobb-Douglas production function, represented as q = AK^α L^β, illustrates the relationship between a firm's output (q) and its inputs, capital (K) and labor (L) This foundational equation establishes a framework for analyzing how profit is influenced by these factors Furthermore, the profit function can be expanded to incorporate additional production costs, including potential future expenses such as new taxes that may affect operational costs.

Modern businesses, including large family-owned enterprises, are generally overseen by a team of well-regulated managers who adhere to stringent internal governance policies These policies are designed to align all business operations with the goal of maximizing profits or dividends for shareholders, as agreed upon and strictly followed by board members.

Internal governance policies are adaptable to the current production and business landscape, aiming to optimize profits Consequently, firms, acting as investors, focus on making rational decisions grounded in reliable information and sound evidence, while minimizing emotional biases (Carlton & Perloff, 2015).

Rational investors prioritize target profit as the key criterion in their investment decisions, focusing on expected financial returns In contrast, social investors and social enterprises often opt for projects that may yield lower financial returns but offer greater social impact, highlighting a different set of values in investment choices.

To thrive in a competitive landscape and maximize profits, firms must adopt effective governance practices while minimizing operational costs In addition to retaining existing customers and expanding their market reach, businesses should continuously conduct research and make strategic investment decisions in new projects that offer promising medium- to long-term returns.

Investment involves reallocating capital from a low-risk state to a higher-risk state with the aim of achieving greater future profits However, investments are inherently subject to market uncertainty and potential risks, with the exception of certain low-risk options like government bonds from stable economies, which are regarded as safe investments.

According to Reilly & Brown (2002), investments possess three key characteristics: a commitment to allocate capital over time, exposure to inflation, and susceptibility to uncertainty or risk regarding future returns Investment activities encompass a range of actions, including purchasing and holding materials, commodities, stocks, bonds, financing struggling companies, lending, and injecting capital into new projects From an economic standpoint, under perfect competition conditions, enterprises play a crucial role in the investment landscape, as noted by Marshall (Bridel, 1987).

Irreversible project

Foreign Direct Investment (FDI) prioritizes large and irreversible projects, which are crucial for a robust economy These capital-intensive projects demand extensive preparation, often requiring firms to allocate about 10% of the total investment for essential activities such as surveys, market research, and feasibility studies before making an investment decision Such projects encompass design, equipment procurement, and construction phases According to Archibald & Voropaev's survey (2004), irreversible projects fall into specific classifications, including group 3 (3.1 and 3.2).

5 (5.1 to 5.4), and group 7 (7.7) These projects can be named as follows: (1) transport

Investment in infrastructure projects, including telecommunications, energy (such as refineries and power plants), and basic commodity production (like steel and chemicals), is crucial for the growth of strong economies Developing countries, like Vietnam, have a pressing need for substantial investments in these irreversible fixed asset projects Consequently, prioritizing such investments is essential for the economic development of these nations.

New weapon system; major system upgrade Satellite development/launch; space station mod Task force invasion

Acquire and integrate competing company Major improvement in project management Form and launch new company.

Consolidate divisions and downsize company Major litigation case.

Microwave communications network 3rd generation wireless communication system.

4 Event Projects 2004 Summer Olympics; 2006 World Cup

5.4Facility, design, procurement, construction in Civil, Energy,

Closure of nuclear power station

Demolition of high rise building

Process plant maintenance turnaround Conversion of plant for new products/markets.

Flood control dam; highway interchange New gas-fired power generation plant; pipeline Chemical waste cleanup.

New shopping center; office building New housing sub-division.

New tanker, container, or passenger ship

New project management information system (Information system hardware is considered to be in the product development category.)

People and process intensive projects in developing countries funded by The World Bank, regional development banks,

US AID, UNIDO, other UN, and government agencies; and

Capital/civil works intensive projects—

7.7Infrastructure: energy (oil, gas, coal, power generation and distribution), industrial, telecommunications, transportation, urbanization, water supply and sewage, irrigation)

Projects often involve establishing an organizational entity responsible for the operation and maintenance of the facility, while lending agencies enforce specific project lifecycle and reporting requirements.

8.2 Live play or music event

New motion picture (film or digital) New

TV episode New opera premiere

New automobile, new food product

New life insurance/annuity offering.

Measure changes in the ozone layer How to reduce pollutant emission.

Determine best crop for sub-Sahara Africa Test new treatment for breast cancer.

Determine the possibility of life on Mars

An important characteristic associated with the investment decision in the large asset project is the project’s irreversibility which was first mentioned in 1986 by

McDonald and Siegel (1986) initiated a research focus on investment decisions in large-scale projects, further explored by Bertola (1998) Pindyck (1990) emphasized that significant investments, such as those in refineries, power plants, and chemical facilities, typically involve multiple design stages and substantial preparation costs Large asset projects are characterized by two key features: first, irreversibility, where any investment costs incurred prior to project cancellation become sunk costs, as the outcomes cannot be repurposed; second, these projects can be temporarily halted to await more favorable conditions, enabling investors to make informed decisions based on factors like rising product prices, reduced initial costs, or improved project policies.

Irreversible investment projects, such as high-value production, infrastructure development, power plants, and oil refineries, often have extended life cycles lasting 20-30 years or more These projects share common characteristics, including their significant duration and substantial financial commitment.

Investment projects often require substantial initial capital and extensive preparation time, including design, equipment procurement, and construction The decision-making process for these investments can be lengthy and fraught with uncertainties, necessitating careful consideration of various information factors Typically, such projects are executed in multiple phases, as illustrated in the accompanying diagram.

Cost & Human efforts for project

Diagram 2.1: Typical Project Life Cycle (Burke, 2003)

Phase 1, known as the Concept or Initial Phase, involves essential preliminary research and investment preparation During this stage, the project is assessed from multiple perspectives to determine its alignment with the firm’s strategic goals Various analyses are conducted, typically documented in a pre-feasibility study (Pre-F/S), which aids in decision-making regarding whether the project should advance to the next stage, the detailed feasibility study (Detailed F/S).

Phase 2 (Intermediate/Development) is crucial in the investment preparation period, as it centers on the feasibility study that quantifies project evaluation inputs with precision During this phase, financial analyses, including key indicators like NPV, IRR, and B/C, are calculated to inform investment decisions Once the feasibility study is complete and project costs are accurately assessed based on reasonable assumptions, investors may still encounter uncertainties This may lead them to adopt a "wait and see" approach, pausing the investment decision until more favorable information emerges or uncertainties are reduced to an acceptable level This cautious strategy is particularly relevant for irreversible projects, emphasizing the need for thorough analysis before committing to investment.

Strategic financial decisions, such as project investment preparation, play a crucial role alongside other key financial choices like dividend policy and financing decisions (Pindyck, 1994) When firms invest early in project preparation, particularly with effective public relations, they can enhance the market value of the project This proactive approach ultimately contributes to increased corporate value and higher stock prices (Vermeulen & Fuss, 2008).

In Phase 3 (Intermediate - Execution), investors commit substantial resources to detailed design, consulting services, advance payments to equipment suppliers and contractors, and construction costs At this stage, the project becomes largely irreversible; cancellation would result in significant financial losses, as the total expenditures have escalated into sunk costs.

Phase 4, known as the Final Phase or Transfer, occurs after the execution phase (Phase 3) is completed During this phase, the project transitions into a trial and commercial operation period, where it begins to produce and sell its product or service in the market.

By the end of the second phase, investors typically allocate 5-10% of the total project cost towards market surveys, research, project design, and feasibility studies (Burke, 2003) If the project is canceled, this expenditure is completely lost, as the feasibility study cannot be repurposed for other projects During the feasibility study phase, if significant uncertainties arise, investors may choose to pause and seek more favorable information before proceeding with their investment decisions, leading to a "wait-and-see" approach.

The author’s review of existing literature reveals a lack of empirical studies differentiating between reversible and irreversible projects based on quantitative metrics like capital or labor scale The primary distinction lies in the sunk costs incurred by investors, which represent the non-recoverable expenses if a project is abandoned; higher sunk costs correlate with greater project irreversibility Numerous real-world examples illustrate the characteristics of both irreversible and reversible projects, impacting investment decision-making in these contexts.

The Nghi Son refinery and petrochemical project, a significant initiative backed by a joint venture of the Vietnam Oil and Gas Group (PVN), Idemitsu Group, Mitsui Chemical, and Kuwait National Oil and Gas Group, represents an irreversible investment of approximately $9 billion Approved by the Vietnamese government and included in the master plan since 2003, the project underwent extensive preliminary design and cost estimation before moving forward Following the master plan's approval, investors dedicated five years to conducting detailed feasibility studies and preparing for the investment decision made in 2008, resulting in sunk costs amounting to several hundred million dollars.

By 2008, investors received investment licenses and a capital construction period exceeding 10 years During the project preparation phase, if uncertainties arise that could impact the feasibility of a project over its expected 40-year operation, investors often adopt a "wait and see" approach This strategy allows them to clarify uncertainties, assess risks, and recalculate financial indicators to enhance the chances of recovering substantial sunk costs, potentially in the hundreds of millions of USD, once the project becomes operational In the case of the Nghi Son Refinery and Petrochemical Project, the investor highlighted the need for compensation for import taxes on wholesale prices to remain competitive against imported products from companies like Petrolimex This significant uncertainty was mitigated by securing a government guarantee, transforming the uncertainty into a manageable risk and thereby improving the project's feasibility.

Reversible project : Also in this big project, Nghi Son Refinery and

Investment decision under uncertainties

According to McMenamin (2002), investment decisions can be categorized into tactical and strategic types Tactical investment decisions involve a firm's investment in financial instruments like stocks, bonds, and intangible assets, including intellectual property, patents, copyrights, and trademarks These decisions can be made rapidly based on current market conditions, particularly the status of the stock and financial markets Firms may choose to either hold these highly liquid financial assets for the long term or sell them quickly, depending on their investment strategy.

Strategic investment decisions involve significant, irreversible projects that require substantial capital and are aimed at maintaining a firm's market position over the medium to long term According to Al-Ajmi et al (2011), these decisions are crucial for effective firm management, fostering long-term growth and increasing overall firm value However, such irreversible projects are often subject to various uncertainties that can impact expected returns, prompting extensive theoretical and empirical research on how firms navigate investment decisions in uncertain environments.

2.4.1 Theorectical studies of investment decision under uncertainty

Lucas (1971) pioneered the mathematical modeling of firm value (V), which is influenced by factors such as product price (p), production output (q), investment level (x), and discount rate (β) over time (t), under the assumption that firms aim to maximize their value Abel (1983) further explored the effects of price volatility on the investment levels of risk-neutral investors, utilizing mathematical techniques to create relevant models.

Abel (1983) utilized a Cobb-Douglas production function to analyze the impact of price volatility on capital stock (K) and labor (L) as primary inputs His findings aligned with Hartman (1972), indicating that an increase in selling price raises the marginal value of capital, prompting firms to invest more Subsequently, Abel & Eberly (1994) enhanced this model by introducing firm value (V), defined as the expected total operating profit minus total operating costs over the project lifecycle, while accounting for the uncertainty of the shadow price (q) of installed capital.

Eberly (1994) found that firms consistently strive to maximize their value by optimizing their capital stock (K) and technology (ɛ), which are essential inputs in their production process.

Caballero (1991) summarizes the researches of Hartman's (1972) study, Abel

Between 1983 and 1985, studies explored the relationship between uncertainties and investment in building a firm's value model (V), which is influenced by profit (�), capital (K), labor (L), and various costs in both perfect and imperfect competition markets Caballero (1991) found that the adjusted investment cost due to asymmetric or symmetric information has a minimal impact on the uncertainties-investment relationship, while the cost of investment capital and marginal profit from increased investment capital are significant factors Dixit and Pindyck (1994) utilized a net present value (NPV) formula to assess how product price, interest rates, and construction costs affect NPV, thereby influencing firm value (V) Although their findings provide illustrative insights, they lack generalizability due to the NPV function not being developed in a general form, unlike the works of Abel (1983), Abel & Eberly (1994), or Caballero (1991).

In 2016, Stonkey proposed a theoretical model addressing how tax policy uncertainty influences a firm's investment decisions The study demonstrated that firms tend to delay investment projects, opting for a "wait & see" approach in response to such uncertainties.

Recent research, with the exception of Dixit & Pindyck (1994), shares common characteristics Firstly, these studies utilize firm value (V) and profit functions (π), focusing on gross or operating profit, which are influenced by key inputs such as capital stock (K) and labor (L) Additionally, the models incorporate uncertainties like product selling prices and capital costs, operating under the assumption that firms aim to maximize their value or project profitability Secondly, the profit function typically follows a Cobb-Douglas form, emphasizing the roles of capital stock (K) and labor (L) as primary inputs.

Research on investment decisions in uncertain environments has focused on irreversible projects, such as steel plants, coal-fired power plants, and real estate developments, which are significantly influenced by future government policies For instance, a coal-fired power plant's revenue can be adversely affected by carbon taxation policies Studies utilizing the Real Options Approach (ROA), including those by Sekar (2005), Reedman et al (2006), Herbelot (1992), Titman (1985), Wang & Zhou (2006), and Zhang et al (2014), highlight that the feasibility of such projects hinges on the chosen appraisal method ROA has proven effective in addressing uncertainties that may arise in the future Sekar (2005) conducted a case study on a coal-fired power plant employing two technologies with varying carbon emissions, illustrating that uncertainties related to carbon taxation significantly impact operating costs and demonstrate that traditional Net Present Value (NPV) calculations may underestimate input costs compared to ROA.

2.4.2 Empirical studies of investment decision under uncertainty

Empirical research reveals a diverse range of influences that uncertainty has on firm investment decisions at the sector level Studies have examined how fluctuations in inflation and US sales prices affect investment levels, utilizing Citibank data from 1954 to 1989 (Huizinga, 1993) Additionally, the impact of price fluctuations on both current and future investments of US manufacturing firms has been analyzed (Ghosal & Loungani, 1996) Other research highlights the relationship between price volatility, product demand, and business investment (Peters, 2001), as well as the effects of stock market volatility on firm investments in developed economies (Lensink, 2002) Furthermore, exchange rate fluctuations have been shown to significantly impact investment decisions (Byrne & Davis, 2005).

An analysis of theoretical and empirical studies on "investment decision under uncertainty" reveals a diverse landscape of research Theoretical frameworks establish the firm's value function (V) as the difference between its profit function and a cost function that accounts for uncertainty The profit function is typically modeled using a Cobb-Douglas approach with capital (K) and labor (L) as inputs Notable contributions from researchers such as Abel (1983), Caballero (1991), Pindyck (1990), and Abel & Eberly (1994, 1998) have further developed these theoretical models Key uncertainty factors examined include product selling prices, capital investment costs in competitive markets, and asymmetric or proportional information These studies operate under the fundamental assumption that firms strive to maximize profits and enhance business value.

Table 2.4 highlights essential publications that underpin the foundational principles of this thesis, including the model structure, key variables, and assumptions from these works, which will be utilized to construct and enhance the research model presented in this study.

Table 2.4: Summary of related theoretical/empirical studies on investment decisions under uncertainties.

Authors Model & forms of function

Lucas (1971) Value of the firm

(V) Cobb-Douglas production function with K and L are two main variables

Product price (p), production volume (q), investment level (x), discount rate (β), according to time (t)

(1)Firm always maximize their profit; (2)production function is constant returns to scale.

Abel (1983) Cobb-Douglas production function

Capital stock (K) and labor level (L), price fluctuation,

Firm always maximize their profit; Competitive market, risk neutral firm;

Caballero Value of firm (V) in Profit function ( � ) (1) Perfect and (1991); perfect competition capital stock (K); imperfect competition Hartman and imperfect labor level (L), cost market; (2) Constant

(1972), Abel competition market of capital and other economy of scale; (3)

Abel & Eberly Value of firm (V) is Capital stock (K), Firm always

In 1994, the firm value (V) is maximized by optimizing the expected present value of operating profit (�) while subtracting operational costs, considering key variables such as labor level (L), the shadow price (q) of installed capital, product price (p), and technology (ɛ).

Sekar (2005) Case study of project appraisal for coal fired power project with different technology.

NPV/RO in explicit form (numerical function instead of variable function.

Explicit number of initial investment capital, carbon emission volumeand cost of carbon taxes.

Author using explicit data to calculate and compare three investmet plans, using the basic assumption as of NPV.

Investment decisions under carbon taxation uncertainties

2.5.1 Carbon taxes and carbon leakages

The Earth's rising temperature is primarily caused by the accumulation of greenhouse gas emissions, particularly carbon dioxide, in the ozone layer, leading to greenhouse effects and global climate change These carbon emissions primarily originate from electricity production using fossil fuels like coal, oil, and gas, as well as from human activities such as fossil fuel-based transportation and agriculture Many initiatives aimed at reducing global emissions are being endorsed to combat climate change effectively.

Since the 1997 Protocol, numerous countries have committed to implementing measures aimed at reducing carbon emissions By 2011, 36 developed nations had pledged to lower their carbon output, with Europe, comprising 29 countries, counted as a single entity These nations belong to Annex I, which primarily includes developed countries, while 137 developing countries, categorized as Non-Annex I, agreed to future emission reductions without specific commitments The Annex I countries have gradually adopted various emission reduction strategies, including emission quotas, carbon taxation, and the promotion of renewable energy production.

Carbon taxes are implemented to hold producers accountable for their carbon emissions, typically based on the amount of carbon released or the electricity generation capacity of fossil fuel power plants By increasing production costs, these taxes incentivize high-emission producers to adopt greener technologies, often referred to as green investments Research, such as that by Speck (1999) and others, has shown that carbon taxation can effectively reduce corporate emissions and encourage technological advancements for lower emissions These taxes can be applied at various points in the production chain, either directly on carbon emitters or on suppliers of carbon-intensive materials, a method known as vertical targeting (Bushnell & Mansur, 2011) For instance, a coal producer may be taxed upstream, while the electricity generation plant, which uses the coal, is taxed directly for its emissions, ultimately impacting electricity consumers through final product pricing.

According to Bushnell & Mansur (2011), direct carbon taxation on firms, particularly coal-fired power plants, may lead to "carbon leakage," where investors shift to non-carbon taxed countries to avoid taxes (Babiker, 2005) This phenomenon occurs when carbon-emitting firms relocate investments to regions without carbon taxes, subsequently importing goods to evade taxation Consequently, foreign investors are drawn to high carbon-emission industries, such as steel and electricity, in developing nations that lack carbon tax regulations Research indicates that imposing carbon taxes on upstream manufacturing processes is more effective than taxing downstream products, as the latter increases the risk of investment shifts to non-taxed countries For instance, applying carbon taxes on coal rather than on power plants can better mitigate carbon leakage Additionally, implementing carbon-related measures like border adjustment taxes, export carbon taxes, or carbon trading mechanisms can further help reduce carbon leakage (Bushnell et al., 2011).

In response to the carbon taxation policies in a country, the producers in carbon-taxed country will have several options as follow.

Carbon leakage refers to the relocation of production from countries with carbon taxes to those without, leading to an increase in total carbon emissions due to the extended transportation of imported goods This phenomenon highlights the unintended consequences of carbon taxation policies, as it can result in higher overall emissions rather than the intended reduction (Wei et al., 2016).

Companies facing carbon taxes may choose to invest in greener technologies to reduce their carbon emissions However, this shift requires significant initial investment, resulting in higher costs for green products compared to those made with traditional methods Consequently, products from green technology may struggle to compete on price with those produced using older technologies, and the transition to greener solutions can be a lengthy process.

The firm plans to retain its old technology while separating its production segment by outsourcing the manufacturing of high carbon-emission components to firms in non-carbon taxed countries, subsequently importing these parts for assembly on the mainland (Wei et al., 2016) This approach allows for quicker decision-making and execution compared to other strategies, enabling the firm to reduce production costs in the short to medium term However, it will require restructuring the assembly operations in the carbon-taxed country to align with the order-making processes in the non-carbon taxed regions, posing challenges in maintaining production quality abroad.

In the medium to long term, firms may consider relocating their production equipment to countries without carbon taxes, as highlighted by Branger & Quirion (2014) Alternatively, they might choose to invest in new projects while retaining old technology that maintains the same carbon emission levels This practice leads to carbon leakage, where non-carbon taxed products are imported back into carbon-taxed countries, ultimately increasing total carbon emissions due to the extended transportation distances Consequently, the effectiveness of carbon taxation measures is compromised.

Many developing countries, such as Vietnam, do not implement carbon taxation, allowing investors to benefit from lower input costs and various investment incentives This lack of carbon taxes enables firms to maintain competitive pricing for their products Since the Kyoto Protocol in 1997, there has been a notable rise in investments aimed at avoiding carbon taxes Additionally, the significant decline in global freight rates since the 1990s has further fueled this trend A study by Peters et al (2011) reveals that between 1992 and 2008, carbon emissions in developing countries doubled, while emissions in developed nations remained relatively stable.

In the past 16 years, developed countries have significantly increased their imports from developing nations, nearly doubling the volume This trend has led to greater carbon emissions, as highlighted by Peters et al (2011), who concluded that higher consumption in developed countries indirectly contributes to increased carbon footprints Additionally, Peters et al (2009) noted that international trade facilitates the transfer of carbon emissions from countries with carbon taxes, specifically Annex-I countries under the Kyoto Protocol 1997, to those without such taxes, namely non-Annex I countries.

Empirical studies by various authors indicate that the value of carbon leakage associated with investments varies across different industries Research focusing on carbon leakage investments by geographic region and sector, as conducted by Paltsev, highlights these disparities.

Research on carbon leakage related investments shows significant variability in estimated values, with findings ranging from 5% to 130% Notably, while a 2001 study reported a 10% value, Babiker (2005) found a much higher estimate of 130% when analyzing the displacement of energy-intensive production subject to carbon taxation Babiker attributed the discrepancies in these studies to the use of different methodologies; many studies relied on similar paradigmatic structures, whereas his research employed a comprehensive computational model that incorporated a broader range of variables, leading to divergent results.

Elliott et al (2010) estimated the carbon leakage rate from Annex B countries of the Kyoto Agreement to be 20%, highlighting concerns about carbon tax avoidance investments While some researchers, such as Barker et al (2007) and Harstad (2010), acknowledge the uncertainty surrounding carbon leakage rates, many empirical studies indicate a clear trend of increased carbon leakage-related investments shifting from carbon-taxed countries to non-carbon-taxed developing nations.

Investing in non-carbon taxed countries to evade carbon taxation involves navigating various uncertainties, particularly regarding the timing and rate of potential carbon taxes Key questions for investors include when these taxes might be implemented and what the specific rates will be Rational investors must factor these uncertainties into their project appraisals to enhance the reliability of financial indicators, ultimately enabling them to make more confident investment decisions.

2.5.2 Taxpayers and rates of carbon tax.

Carbon taxes target emissions from sources like coal-fired power plants and fossil fuels, which are significant contributors to carbon emissions in various industries According to the US-based Center for Energy and Climate Change Solutions, as of 2013, approximately 72% of carbon emissions originated from energy-intensive sectors such as steel and construction materials, while agriculture accounted for 11%, land development and deforestation for 6%, and transportation for 2.2% This highlights that projects involving coal, oil, and gas, particularly in electricity production and heavy industries like cement and steel manufacturing, are among the largest emitters Such projects often entail extensive preparation, high costs, and irreversible impacts on the environment.

Research gaps

Research on the impact of carbon taxation uncertainties on Foreign Direct Investment (FDI) firms' decisions regarding irreversible projects is limited globally, with existing studies often focusing on a single type of project These studies typically employ NPV/ROA methods to assess the expected value of projects under varying carbon price scenarios, raising questions about the generalizability of their findings to other irrevocable projects Consequently, it is essential to explore the effects of carbon taxation uncertainties on investment in a broader context that can be applied across different project types, highlighting a significant research gap in this area.

A comprehensive literature review reveals that research on investment decisions under uncertainty is a crucial area for academics, business leaders, and investment advisors Key uncertainties, particularly those related to taxation, significantly impact foreign direct investment (FDI) decisions Both theoretical and empirical studies consistently indicate that the imposition of taxes adversely affects and reduces the investment levels of firms.

Research on the impact of carbon taxation uncertainties on firms' investment decisions in irreversible projects is limited Notable studies, such as those by Sekar (2005), Zhang et al (2014), and Shahnazari et al (2014), focus on coal-fired power projects in Australia, while Reedman et al (2006) utilized real options analysis to explore technology selection under carbon taxation uncertainties in the Australian power generation sector These studies are specific to particular project types and technologies, leading to significant variations in carbon emissions and associated tax costs While these findings may apply to similar projects, they are insufficient for generalizing macro policies across different investment projects and sectors.

Carbon taxation is anticipated to be implemented soon, attracting significant interest from investors (Barradale, 2014) This aligns with the findings of the ACCA's 2012 report on Carbon Taxation and Corporate Behavior, which suggests that carbon tax rates are expected to rise in the coming years However, the specific rates and growth levels remain uncertain.

Research on the impact of carbon taxation uncertainties on firms' investment decisions in irreversible projects remains limited, highlighting a significant research gap that this thesis aims to address.

Current research lacks an exploration of how carbon taxation impacts investors' decisions regarding capital, technology, and labor levels in their projects Most studies on investment decisions under uncertainty primarily examine the effects of uncertainties on firm value or project profitability This gap presents an opportunity for further investigation into the influence of carbon taxation on investor choices in these critical areas.

The analysis of theoretical research highlights the impact of general and tax-related uncertainties on firms' investment decisions in irreversible projects, focusing on capital stock (K) and labor level (L) as key inputs These elements represent the size of investment capital and domestic labor utilized in projects The capital-labor ratio (K/L) serves as a crucial indicator of a firm's technological development; a higher ratio suggests greater worker efficiency per unit of capital, indicating the use of advanced technology This relationship is supported by Sollow (1957) and recent empirical findings by Kim (1997) Additionally, Broersma & Oosterhaven (2004) emphasize that variations in this ratio significantly influence firm productivity, with increases in the ratio correlating with enhanced productivity outcomes.

The existing theoretical research primarily examines the impact of uncertainties on corporate value and net present value, rather than exploring how these uncertainties influence the selection of capital (K) and labor (L) to maximize profits This highlights a significant research gap that this thesis aims to address, providing valuable insights for policy development to enhance capital and technology levels, as well as labor quality in investment projects, particularly foreign direct investment (FDI) Additionally, China is considering implementing an export carbon tax on energy-intensive exports to reduce carbon emissions and promote energy-efficient production, which serves as an important indicator of technological advancement in manufacturing (Li et al., 2012).

The current state of technology and labor in Foreign Direct Investment (FDI) projects in Vietnam is concerning, highlighting the need for improved measures and policies to enhance technology and labor quality In many FDI projects, the foreign investors dictate production technology due to their significant investment share and superior technological and market knowledge Consequently, there are instances where foreign parties introduce outdated technologies or refurbished equipment, which may have been economically unviable in developed nations but can still be profitable in Vietnam due to lower input costs, government incentives, and the ability to bypass environmental regulations Notably, existing research lacks a focus on policies aimed at improving these conditions.

The lack of academic research on capital, technology, and labor levels in Foreign Direct Investment (FDI) projects in Vietnam hampers the development of effective policies This deficiency results in inadequate technological appraisal by authorities and administrative restrictions on outdated equipment, which can negatively impact environmental sustainability Consequently, it is essential to conduct research aimed at enhancing the capital, technology, and labor standards in FDI projects within Vietnam.

Conclusion of Chapter 2

Foreign firms' investment decisions in FDI projects are influenced by various uncertainties, which can be categorized into quantitative factors—such as exchange rates, market prices, capital costs, inflation, and taxes—and qualitative factors, including institutional quality, investment location, legal stability, political stability, diplomatic relations, and investment protection commitments It is crucial for investors to account for these uncertainties, as they can escalate into significant risks within their investment decision models Rational investors prioritize profit maximization while navigating these uncertainties, ensuring that all potential risks are thoroughly assessed during the investment appraisal process.

Firms are increasingly concerned about the uncertainties surrounding carbon taxation, anticipating its future implementation and potential increases in tax rates in countries where it is already applied However, research on the impact of carbon taxation on investment decisions has primarily been limited to case studies of specific projects, making it challenging to generalize findings across entire sectors or economies, as well as for other types of irreversible investment projects.

This thesis addresses the research gap in the theoretical model concerning firms' investment decisions amid uncertainties related to carbon taxation for irreversible projects Additionally, it aims to provide a scientific foundation for policy recommendations that enhance technology and labor quality, which are pressing issues in Vietnam.

As described in Chapter 1, Section 1.4, the quantitative approach is selected to apply in this thesis to find the answers the following two research questions.

(1) What are effects of carbon taxation uncertainties on investors’ investment decision in irreversible FDI projects?

(2) What are the levels of capital per labor selected by the investors in irreversible FDI projects under uncertainties of carbon taxation?

A recent study highlights the lack of existing research in Vietnam regarding the future uncertainties of carbon taxation and its impact on investment decisions for irreversible projects To address this gap, various research methods, including qualitative and quantitative approaches, can be employed It is essential to evaluate practical conditions and research settings to determine the most suitable method for effectively answering the research questions.

Utilizing qualitative research methods, such as in-depth interviews with CEOs and investment consultants regarding the impacts of carbon taxation on investment decisions, may lead to significant bias due to the uncertainties surrounding carbon taxation Since these uncertainties have yet to materialize, predicting expert opinions on future scenarios becomes increasingly complex, resulting in unreliable data for analysis Consequently, this thesis will not employ qualitative methods like in-depth and focus interviews.

The second option involves utilizing quantitative methods by developing econometric models to hypothesize the effects of carbon tax uncertainties on investment decisions, treating these decisions as the dependent variable We would create a regression function that includes firm profits as well as independent variables related to carbon tax uncertainties However, gathering quantitative data, such as firms' investment levels, to test these hypotheses is currently impractical, as carbon taxes have not yet been implemented, and their effects are not reflected in available data Additionally, empirical research summarized in Chapter 2 indicates that investment data in developed countries is highly specialized and typically sourced from banks, lenders, and investment funds, which is not yet accessible in Vietnam, particularly concerning irreversible projects.

There is currently a lack of empirical studies addressing the uncertainties that influence investment decisions in irreversible projects in Vietnam Consequently, there are no tested econometric models to verify the consistency of empirical frameworks, making it challenging to ascertain the feasibility of such research Successful empirical research using econometric models requires reliable research frameworks and robust datasets that are extensive and cover multiple years to ensure dependable regression outcomes Pindyck (1990) noted that econometric models often struggle to accurately predict investment fluctuations, particularly for irreversible projects characterized by high levels of irreversibility Thus, it is reasonable to conclude that employing quantitative empirical research methods may not be appropriate in this context.

To address the existing constraints, a quantitative research approach utilizing mathematical modeling is viable By establishing a mathematical research model, it can be enhanced through algorithmic techniques, enabling result calculation and simulations using hypothetical data This method is deemed suitable for theoretical research.

Mathematical modeling is an essential tool for economists across different research levels, as highlighted by 1994 studies Lawson & Marion (2008) emphasize the strengths of algorithmic modeling, noting that algorithms provide the appropriate language for formulating research elements and assumptions They also point out that algorithms offer a concise framework with clear rules for detailed development and computation Furthermore, mathematical calculation techniques have a long history of validation, and the advancement of computational software today enables the execution of complex calculations with exceptional accuracy.

Numerous studies, including those by Lucas et al (1971), Abel (1983), and Majd & Pindyck (1987), have employed quantitative methods and algorithmic modeling relevant to this thesis Milne & Whalley (1999) proposed a model for firm valuation based on the premise that firms invest whenever their value increases or maximizes Additionally, Agliardi (2011) and Kauffman et al (2015) utilized Return on Assets (ROA) and algorithm development to evaluate the effects of taxes and investment decisions on firms Other notable contributions in this area include the work of Hartman (1972) and Abel.

(1983, 1984, 1985); Caballero (1991); Dixit & Pindyck (1994), and Abel & Eberly

In the 1990s, researchers utilized mathematical modeling to analyze firms' investment decisions, focusing on the profit function as a foundational model They argued that rational firms aim to maximize profits, leading them to invest in projects with positive profitability To optimize their production operations, these firms select the ideal levels of capital (K) and labor (L).

This article outlines key statements derived from research relevant to the thesis presented in Chapter 2, forming the foundation for selecting the research model for future steps Firms consistently make rational investment decisions with the primary goal of maximizing returns on investment To effectively attract foreign direct investment (FDI), policies must be developed based on a comprehensive model to enhance the generalizability of research findings This thesis adopts the economic profit function proposed by Varian (1992), aligning with the works of Hartman (1972) and Abel (1983, 1984, 1985), as well as Dixit & Pindyck (1994) The fundamental profit function of a firm is defined as the revenue function minus the cost function, where the revenue function is calculated by multiplying the average price by the production function, representing the firm's output.

The profit function utilized in research by Abel & Eberly (1993, 1997) and Caballero (1991) is based on the Cobb-Douglas production function This model is chosen as the foundational framework for this thesis for several reasons: Firstly, it is featured in the highly regarded book "Microeconomic Analysis," widely adopted in esteemed universities and boasting over 9,000 citations since its first edition in 1992, according to Google Scholar Secondly, the development and calculation of this model are expected to yield significant theoretical and scholarly insights.

The profit function incorporates capital stock (K) and labor (L) as key production inputs, highlighting the significance of investment quality By integrating carbon tax-related uncertainties into the model, we can analyze the interplay between K, L, and these uncertainties, thereby addressing the second research question effectively.

Based on the above discussion, the profit function model according to Varian

(1992) was constructed in general and put into development, calculated as follows:

- � : the profit function of the firm.

- F (K, L): is the production volume of the firm depending on capital level (K) and labor level (L).

- C (r, w): is the cost of the business operation depending on the cost of capital (r) and labor wage (w), not including the cost of carbon tax.

- T (τ): is the cost of carbon tax that the firm needs to pay when the government imposes carbon tax on the volume of carbon emission.

- p is average selling price of products

The function assumes that a firm consistently invests when Л > 0, aiming to maximize profits as a rational investor Consequently, the firm selects optimal levels of inputs, including K, L, r, and w, to achieve this profit maximization The model, under reasonable assumptions outlined in Chapter 4 - Results of the Research, establishes a profit function that illustrates the relationship between the project's profitability (�) and various influencing factors such as K.

RESEARCH METHOD

Selection of research methods

As described in Chapter 1, Section 1.4, the quantitative approach is selected to apply in this thesis to find the answers the following two research questions.

(1) What are effects of carbon taxation uncertainties on investors’ investment decision in irreversible FDI projects?

(2) What are the levels of capital per labor selected by the investors in irreversible FDI projects under uncertainties of carbon taxation?

A recent study highlights the lack of research in Vietnam regarding the future uncertainties of carbon taxation and its effects on investment decisions for irreversible projects To address this gap, various research methods, both qualitative and quantitative, can be employed However, it's crucial to assess practical conditions and research settings to determine the most suitable method for effectively answering the research questions.

Qualitative research methods, such as in-depth interviews with CEOs and investment consultants regarding the impacts of carbon taxation on investment decisions, may introduce significant bias due to the uncertainties surrounding carbon taxation Since these uncertainties have yet to materialize, gathering expert opinions on future scenarios becomes complex, leading to unreliable data for analysis Consequently, in-depth and focused interviews will not be utilized in this thesis.

To assess the impact of carbon tax uncertainties on investment decisions, we can utilize econometric models and formulate hypotheses, with regression functions that incorporate firm profits and independent variables related to carbon taxation uncertainties However, the feasibility of collecting quantitative data, such as firms' investment levels, is limited due to the absence of implemented carbon taxes, which means their effects are not yet observable Additionally, empirical research summarized in Chapter 2 indicates that investment data in developed countries is often specialized and typically sourced from banks, lenders, and investment funds, which is currently unavailable in Vietnam, particularly for irreversible projects.

There is currently a lack of empirical studies examining the uncertainties influencing investment decisions in irreversible projects in Vietnam, leading to an absence of tested econometric models This gap complicates the feasibility of conducting research in this area Successful empirical research using econometric models requires reliable research frameworks and extensive, dependable data collected over many years to ensure the validity of regression outcomes As noted by Pindyck (1990), econometric models often struggle to predict investment changes, particularly for irreversible projects characterized by high irreversibility Consequently, it is reasonable to conclude that quantitative empirical research methods may not be suitable for this context.

To address existing constraints, employing a quantitative research approach through mathematical modeling is feasible Once a mathematical research model is established, it can be enhanced using algorithmic techniques to compute results and conduct simulations with hypothetical data This methodology is deemed suitable for theoretical research.

Mathematical modeling is recognized as a vital tool for economists, enhancing research at multiple levels (1994) Lawson & Marion (2008) highlight the strengths of algorithmic modeling, noting that algorithms provide the appropriate language for formulating research elements and assumptions They emphasize that algorithms offer a concise framework with clear rules for detailed development and computation Furthermore, the mathematical techniques used in these models have been validated over centuries, and the advancement of computational software today enables the execution of complex calculations with exceptional accuracy.

Numerous studies have employed quantitative methods and algorithmic modeling in this research area, including notable works by Lucas et al (1971), Abel (1983), and Majd & Pindyck (1987) Recently, Milne & Whalley (1999) introduced a firm value model based on the premise that companies invest to enhance or maximize their value Additionally, Agliardi (2011) and Kauffman et al (2015) utilized Return on Assets (ROA) and algorithm development to evaluate the effects of taxes and investment decisions on firms Other significant contributions to this field include the research of Hartman (1972) and Abel.

(1983, 1984, 1985); Caballero (1991); Dixit & Pindyck (1994), and Abel & Eberly

In the studies conducted in 1994 and 1997, researchers employed mathematical modeling to analyze firm investment decisions They posited that firms, as rational investors, prioritize profit maximization and will invest in projects only when their profitability is positive Consequently, firms aim to optimize their production operations by selecting the ideal levels of capital (K) and labor (L) to enhance overall profit.

Research model

Research related to the thesis in Chapter 2 suggests key statements for selecting a research model Firms consistently make rational investment decisions aimed at maximizing returns To effectively attract foreign direct investment (FDI), policies should be developed from a broad model to enhance the generalizability of research findings This thesis adopts the economic profit function outlined by Varian (1992), aligning with previous studies by Hartman (1972), Abel (1983, 1984, 1985), and Dixit & Pindyck (1994) The fundamental profit function is defined as the revenue function minus the cost function, where the revenue function is derived from the average price multiplied by the production function, representing the firm's output.

The profit function utilized in research by Abel & Eberly (1993, 1997) and Caballero (1991) is based on the Cobb-Douglas production function The development of this profit function model by these esteemed scholars supports its selection as the foundational model for this thesis for several reasons: first, it is featured in the widely recognized book "Microeconomic Analysis," which is adopted by numerous prestigious universities and boasts a high citation index of over 9,000 since its first edition in 1992 (according to Google Scholar); second, the outcomes derived from this model are expected to yield significant theoretical and scholarly insights.

The profit function encompasses key production inputs, namely capital stock (K) and labor (L), which indicate the quality of investment By incorporating uncertainties related to carbon tax into the model, we can analyze the interplay between K, L, and these uncertainties, thereby addressing the second research question.

Based on the above discussion, the profit function model according to Varian

(1992) was constructed in general and put into development, calculated as follows:

- � : the profit function of the firm.

- F (K, L): is the production volume of the firm depending on capital level (K) and labor level (L).

- C (r, w): is the cost of the business operation depending on the cost of capital (r) and labor wage (w), not including the cost of carbon tax.

- T (τ): is the cost of carbon tax that the firm needs to pay when the government imposes carbon tax on the volume of carbon emission.

- p is average selling price of products

The function operates under the fundamental assumption that a firm consistently invests when Л > 0, aiming to maximize profits as a rational investor Consequently, the firm selects optimal input levels of capital (K), labor (L), interest rate (r), and wage (w) to achieve this profit maximization Utilizing this model, along with reasonable assumptions detailed in Chapter 4 - Results of the Research, we derive a profit function that illustrates the relationship between the project's profitability (�) and its influencing factors, including K.

L, r, w and cost of carbon tax We can easily add other costs or factors due to one or more uncertainties to expand the research scope The similar model of profit function based on Varian (1992) is also selected and developed by Wei & et.al (2016, 2018) for analyzing effects of carbon taxation on firm’s investment in both technology & labor in developed countries and giving the positive results.

It could be interesting if we compare the profit function and the function NPV in Section 2.1.2 (page 20) quoted as below.

Net Present Value (NPV) is a crucial financial metric that incorporates two primary variables: revenue (Bt) and cost (Ct) throughout a project's life cycle It is calculated by discounting future cash flows at an interest rate (r) to determine their present value Revenue (Bt) is derived from the product of price and volume, while cost (Ct) consists of the initial investment (C0) and ongoing operating costs (C1, C2,…Cn), which include production expenses and taxes The NPV function differs from traditional profit calculations by factoring in the time value of money and explicitly reflecting the risk-taking behavior of investors This makes NPV a valuable tool for analyzing investment decisions under uncertainty, as demonstrated by various authors such as Hartman, Abel, and Dixit & Pindyck.

Model development based on risk response of investors

Investors base their investment decisions on the value of the profit function (Л), as outlined in Chapter 2 Typically, when the net present value (NPV) exceeds zero, investors are inclined to proceed with the investment To achieve accurate results for the profit function, careful calculations are essential.

To effectively assess the Net Present Value (NPV), investors need to transform uncertainty into measurable risk by determining its probability and scale, as outlined in Section 2.1.3 By quantifying the uncertainty factor, investors can calculate the NPV as a straightforward arithmetic value rather than relying on complex functions.

Investors often rely on expert evaluations to assess the probability and cost of risks using quantitative tools, with the Delphi method being a common approach This method involves experts answering the same questions regarding carbon tax risks, followed by a focus group discussion in a "brainstorming" format Despite some academic debate on the effectiveness of brainstorming, Furnham's study (2000) indicates that managers prefer this method alongside others, as it fosters reliability and consensus among decision-makers Ultimately, the outcomes of these discussions inform the board of directors, who make final investment decisions based on the agreed insights from the experts and managers.

Investor attitudes towards risk significantly influence their investment decisions Wiseman & Gomez-Mejia (1998) identify five distinct types of investors based on their risk responses Additionally, when classifying investors by the level of risk they are willing to accept, assuming equal probabilities, two primary types of investors emerge.

Risk-averse investors prioritize minimizing potential losses and typically opt for the lowest-risk investment options available When faced with two investment choices, they will select the one with the least risk exposure For these investors, the carbon tax significantly influences their decision-making, as they will only invest if the profit function remains positive after accounting for the maximum carbon tax cost Essentially, risk-averse investors require a profit function that incorporates the highest carbon tax cost with absolute certainty (probability of 100%) to justify their investment.

Risk-taking investors prioritize profitability and are willing to choose higher-risk investment options when presented with multiple projects Unlike risk-averse investors, they do not factor in carbon tax costs into their investment decisions, viewing the risk of carbon tax as negligible Consequently, the profit function for risk-taking investors focuses solely on potential returns, emphasizing their willingness to embrace uncertainty for the sake of greater profits.

Optimization techniques by math

Optimization techniques focus on two main strategies: maximizing profit or revenue and minimizing costs This thesis specifically addresses the maximization of profits within a firm's projects, drawing on a long-standing history of optimization methods utilized in economics, administration, and technology (Kiranyaz, Ince & Gabbouj, 2014) The optimization techniques presented here are developed through algorithms, with the profit function (π) influenced by variables such as price (p), capital (K), labor (L), interest rate (r), wage (w), and others By analyzing these variables, we can identify optimal input combinations of K and L that maximize the profit function (π) under specified conditions, thereby addressing the research questions posed in this thesis.

L, so that ( � ) is maximized with the assumption that the remaining variables are given Then optimization techniques are implemented as follows:

- Step 1: Consider reasonable assumptions close to practice and in accordance to common managerial, financial and tax economics, to ensure that the profit function

( � ) has economic significance and can be developed and solved mathematically.

Specifically, the values p (product price), K (capital), L (labor), r (cost price), w (salary), τ (tax rate), must be positive.

- Step 2: We apply the rule of first-order derivative according to variable K and variable

L, and set up the system of two equations of two variables K, and L.

To maximize profit (�), it is essential to solve the two-variable equation system by making reasonable assumptions to identify the optimal value pair of K* and L* Rational investors are driven by the goal of maximizing their returns, leading them to invest at these optimal levels of K* and L*.

The values K* and L* are anticipated to be influenced by various factors, including the interest rate (r), wage level (w), and tax rate (τ) This relationship establishes a function connecting K* and L* to these variables and others Chapter 4 provides a comprehensive analysis of optimization outcomes across different scenarios involving various investors.

Simulation of research results

According to Pindyck (1990, p 48), simulations serve as a valuable tool for examining the impacts of "irreversible nature" and uncertainty on investment decisions Following the development of the model, Chapter 4 will present the results calculated through optimization techniques This thesis employs simulation in the form of numerical solutions, utilizing assumed arithmetic data to clearly illustrate theoretical outcomes, making them easily understandable and comparable Furthermore, the numerical simulation results facilitate the creation of graphs that depict relationships between two factors or composite graphs that represent multiple factors, enhancing the ability to express these interrelationships.

According to Batz (2007), simulation is highly effective for addressing optimization problems, particularly in product manufacturing where it aids in selecting inputs like technology, equipment, and labor to enhance the investment process This complex issue allows manufacturers to utilize simulations to compare various options by adjusting inputs that fluctuate over time, providing a range of alternatives for decision-makers Often, investors may need to settle for the "second best option," as the optimal solution may not be feasible Ultimately, simulations enhance investors' ability to visualize potential investment choices and anticipate the outcomes of their plans based on realistic projections.

Investors aiming to avoid carbon taxes, often referred to as carbon leakage, encounter significant uncertainties regarding future carbon tax regulations Key questions include whether the government of the target investment country will implement carbon taxes and, if so, what the tax rate will be to ensure long-term project profitability and competitiveness Unfortunately, these critical inquiries remain unanswered due to a lack of empirical research, as there is currently no available data on the imposition of carbon taxes.

This thesis involves modeling the profit function and optimizing it to produce theoretical results, followed by numerical simulations for practical application The input data will be presented in an arithmetic format, closely mirroring real-world scenarios, and will be discussed in detail in Section 4.4.1.

Various software options are available for arithmetic simulations, including Simulink, Maple, and Math Lab Among these, Math Lab is recommended based on Brandimarte's (2002) insights due to its significant advantages: it offers a highly interactive computing environment for processing functions ranging from basic to complex, provides robust graphing capabilities, and effectively handles both linear and non-linear functions.

In the absence of adequate real data for large asset investment projects, both quantitative and qualitative, we will generate reasonable assumed data This data will be sourced from credible references, and any gaps will be filled with values closely aligned with practical insights or verified secondary sources.

The analysis of carbon tax rates will utilize data from reputable organizations, including the World Bank and the Carbon Tax Center in the United States, as well as insights from the review conducted by Zimmermannová et al.

(2018) on the European carbon tax rate Detailed assumptions are presented in Section 4.4.1.

In this study, a quantitative approach utilizing an algorithmic modeling tool is adopted, aligning with the research questions and existing literature in the field The outcomes of model development and calculations will be presented through numerical simulations, effectively showcasing the findings derived from theoretical research.

In Chapter 3, Varian's (1992) profit function serves as the foundational model for estimating and analyzing investment decisions through algorithmic techniques Rational investors will choose to invest when the maximum profit is greater than or equal to zero.

- � : the profit function of the firm.

- F (K, L): is the production volume of the firm depending on capital level (K) and labor level (L).

- C (r, w): is the cost of the business operation depending on the cost of capital

(r) and labor wage (w), not including the cost of carbon tax.

- p is average selling price of products

If the symbol (τ) is the tax payable by the investor, the function � is expanded as follows:

� = pF(K,L) – C(r,w) - T(τ) or � = pAK α L β − rK – wL – T(τ)

- T (τ): is the cost of carbon tax that the firm needs to pay when the government imposes carbon tax on the volume of carbon emission.

- A is total factor productivity Normally, the higher technology leads to higher value of A.

In this model, it is assumed that investors have access to unlimited capital (K) and an abundant supply of domestic labor (L) for their projects The capital is treated as infinitely elastic, allowing for the mobilization of as much capital and labor as needed The model sets the price (p) at 1, indicating that K represents the total capital rather than the number of machinery units Productivity is fixed at A = 1, and both inflation (δ) and the project's discount rate (£) are assumed to be zero throughout its lifecycle Consequently, the net present value (NPV) calculations incorporate a constant discount rate, leading to a defined profit function.

Where: α and β are the elasticity of output of capital and labor respectively. These are fixed and determined by technology level.

If α + β = 1, the production function yields a constant rate of change to scale If: α + β 1, the yield function increases with scale.

The capital stock fluctuates from year zero to year t, represented as (K0, K1, K2, Kn) The initial investment capital is denoted as I0, while the operating capital for subsequent years is represented as (I1, I2, In) This establishes the K values for each year of operation.

If we assume that the project discount rate £ = δ = 0 to simply the calculation, we have the below.

Table 4.1: Summary of abbreviation using in Chapter 4

� Project profit Amount of money

K Capital stock Amount of money

( r ) Cost of capital Percentage or

(w) Average Wage of worker Amount of money

(τ) Carbon tax rate Percentage or number

Optimum or Maximized profit Number

K* Optimum capital stock at which the profit is maximized

L* Optimum labor level at which the profit is maximized

A Productivity of investor Number or coefficient

4.2Modeling the cases of carbon and non-carbon taxation

This article analyzes the profit function of foreign-invested firms operating in carbon-taxed countries, specifically focusing on projects in developing nations like Vietnam We examine two scenarios: one without carbon taxes and another with applicable carbon taxes By determining the optimal values of K* and L* in both scenarios, we can compare these values to propose Theorem 1.

4.2.1 Modeling the case of non-carbon taxation

We have the following profit function in case the government has not yet applied carbon taxation. below:

Denote {K1*, L1*} are optimal values which are solution of the equation (13) as

In order to find the optimum value of K1 and L1 so that at that values of K and

L, the profit function is maximized, we take the first order derivatives according to K1 and L1 Then, we have the below equations.

Let call {K1*, L1*} as optimal value of K and L We move r 1 and w 1 to the right sides and divide the equations (5) by (6), we have the equation (7) and then K and L as below:

We substitute L1 of equation (8) into equation (5), and we have the value K1* as follows.

By taking natural logarit for both sides of equation (10), we have the below.

Because that( ) , we could divide both sides for it and we have the ( ) below.

By the same mathematical development, we have the as below.

Investors aim to maximize their profits by selecting production levels that align with the optimal values of capital and labor, denoted as {K1*, L1*} These optimal values are derived from equations (5) and (6), ensuring that the chosen output level corresponds to the most efficient allocation of resources.

4.2.2 Modelling the case of carbon taxation

If a host government implements carbon taxes on producers of carbon emissions, the tax is typically based on the volume of emissions generated, which correlates directly with production levels (Donald & Eric, 2014) This means that higher production results in greater carbon emissions In this context, the carbon tax rate is represented by the symbol (τ), while (θ) denotes the emission coefficient influenced by the production technology used The profit function for firms under a carbon tax regime assumes that the interest rate (r1) and wage (w1) remain unchanged compared to a scenario without carbon taxation.

The first condition is that (1- τ θ) must be larger than 0 to secure that � 2 >0 so that the firm will invest and otherwise not.

If we denote the symbol {K2 *, L2 *} is the solution of function (18) or this is the optimal value of K and L, then, we have the maximized profit value symbolized as

By taking the same method and technique as the section 4.2.1, we have the

By the same mathematical development, we have the as below.

+ Theorem 1: We decalare the theorem 1 (proposition 1) as follows.

In a scenario where a non-carbon taxed country introduces a carbon tax on carbon emission producers, investors are likely to adjust their investments to optimal levels of {K2*, L2*} These levels would be lower than the previous investment levels of {K1*, L1*} observed in the absence of carbon taxation.

Comparing {K2*, K1*} by using the equation (17) and (27), we have the

( ) Because that 00 so that the firm will invest and otherwise not.

If we denote the symbol {K2 *, L2 *} is the solution of function (18) or this is the optimal value of K and L, then, we have the maximized profit value symbolized as

By taking the same method and technique as the section 4.2.1, we have the

By the same mathematical development, we have the as below.

+ Theorem 1: We decalare the theorem 1 (proposition 1) as follows.

In a non-carbon taxed country that implements a carbon tax on emissions, investors are likely to adjust their investments to optimal levels of {K2*, L2*}, which are lower than the previous levels of {K1*, L1*} seen in a non-taxed scenario.

Comparing {K2*, K1*} by using the equation (17) and (27), we have the

( ) Because that 0 0, β > 0 Assume that the productivity AL > AH.

4.5.1 The case of non-carbon taxation.

Investor L will choose to maximize their profit based on the below function:

The first order derivative is as below.

Assuming equal labor costs (w) in both scenarios (wH = wL), we can set the first derivatives of equations (34) and (35) to zero to determine the solutions, which can be further developed into equations (36) and (37).

Thus, we have the below.

Replace LL into (36), we have:

The same calculation is applied to have LL as below.

( ) Then, by applying the above calculation, we KH, LH as follow.

The ratio increases with higher levels of AL and rH, while it decreases when AH and rL are reduced This ratio will exceed 1 only under specific conditions.

4.5.2 The case of carbon taxation.

In this analysis, we explore the implementation of carbon taxation by the host country's government, targeting the carbon emissions produced by individual investors We will examine the specific carbon emission volumes attributed to two distinct investors, highlighting the implications of this taxation strategy on their environmental impact and economic behavior.

Two technologies are classified based on their carbon emissions: (L) for low carbon emissions and (H) for high carbon emissions, with the assumption that the emission coefficient for low carbon (eL) is less than that for high carbon (eH) Additionally, a carbon tax rate, represented by the symbol (τ), applies to both types of investors.

The investor L will maximize profits by the following function and conditions:

The investor H will maximize profits by the following function and conditions:

When a carbon tax is imposed at a rate of (τ), investor L can determine the optimal allocation of capital and labor by applying the first-order derivative and substituting K with L and vice versa.

Similarly as above, we have the following result for investor H choosing the optimal level of capital/technology and labor when carbon tax is imposed at the rate of (τ):

According to calculations in Section 4.2, when there is a carbon tax, investors always choose lower level of K and L than that of the case of non-carbon taxation.

Theorem 4 (Proposition 4) states that implementing a carbon tax on carbon emissions incentivizes investors with lower emissions to increase their investment levels, in contrast to those with higher emissions.

Based on the findings in sections 4.5.1 and 4.5.2, we can determine the ratio (γ) that illustrates the relationship between the capital levels and technologies of two investors, L and H, in the context of a carbon tax rate (τ).

An increase in the carbon tax rate (τ) leads to a rise in the variable γ τ, indicating that as the government raises the carbon tax, both investors are affected Notably, this impact is more pronounced for investors with lower carbon emissions.

( emission volume will choose to invest in higher capital than that of investor with higher carbon emission volume Then, we have the theorem 4 (proposition 4).

4.6 Numerical results of simulation from the case of carbon and non-carbon taxation.

Vietnam currently lacks carbon taxation, which limits our ability to gather empirical data for testing our modeling results As a viable alternative, we propose to use assumed data for simulations, representing the best option available to us.

In this article, we employ simulation techniques to validate the modeling results presented in Section 4.2, specifically subsections 4.2.1 and 4.2.2, through numerical solutions The simulation data, outlined in Table 4.6.1, includes key assumptions such as an interest rate of 15% and an average worker salary of approximately 800 USD per month Two critical parameters, α = 0.3 and β = 0.6, are derived from the research of Ashfaq Ahmad & Muhammad Khan (2015), utilizing empirical data from Pakistan, which is comparable to Vietnam Additionally, the value of θ is informed by technical data on carbon emissions from coal-fired power plants, while the carbon tax rate varies across different values—10, 50, 100, and 150 USD per ton—based on survey findings.

According to the commands outlined in Appendix 2 of Math Lab software, the results indicate that the values of � *, K *, and L * decrease as the carbon tax (τ) increases, aligning with theoretical expectations Utilizing the values of � *, K *, and L * in relation to (τ), we can generate the graphs displayed in Appendix 4 It's important to note that the model employs a short-run profit function, and therefore, timing is not incorporated into the simulated model Additionally, the average price is set at (1), with capital (K) measured in monetary terms rather than the number of machinery units.

Table 4.6.1: Assumed Data for Simulation

(θ) 0.004 : current carbon coefficient of coal fired power

The simulation results reveal the optimal values of K*, L*, and Π* calculated using the formulas outlined in Sections 4.2.1 and 4.2.2 Table 4.6.1 presents various levels of the carbon tax rate (τ), while Table 4.6.2 displays the corresponding calculation results for K*, L*, and Π* Additionally, Appendix 2 illustrates the graphical relationship between K*, L*, Π*, and τ.

The results of calculation as presented in the Table 4.6.2 show that all values of

An increase in tax rates leads to a reduction in K *, L *, and Π *, indicating that the implementation of carbon taxation will cause investors to lower their optimal levels of capital and labor, as outlined in Theorem 1 (Proposition 1).

Table 4.6.2: Calculation of optimized values K*, L* and Π *

Conclusion of Chapter 4

This article explores various modeling cases to establish a fundamental profit function model, focusing on (1) the impact of non-carbon and carbon taxation on a single investor, (2) the uncertainty surrounding the timing of carbon taxation for one investor, and (3) the effects of a uniform carbon tax rate on two investors with differing carbon emission levels By assuming rational investor behavior that adheres to profit maximization principles, we employ optimization techniques to determine the optimal capital stock (K) and labor level (L) that maximize profits The theoretical findings from each case offer novel insights and serve as a scientific foundation for future research, along with important policy and managerial implications discussed in Chapter 5.

This research employs a quantitative approach through mathematical modeling to analyze how uncertainties related to carbon taxation impact firm profitability and investment decisions If the findings from the mathematical model are validated, they could be applied to other uncertainties affecting firm profits This could lead to the development of targeted policies aimed at reducing both the level and number of uncertainties, ultimately enhancing foreign direct investment (FDI) as an alternative to conventional methods like tax reductions and lower land rentals.

This thesis introduces a novel approach suggesting that carbon taxes can be leveraged to discourage low-technology investments while promoting higher ones By utilizing a Cobb-Douglas production function that incorporates capital (K) and labor (L), the study aims to explore the interplay between these factors and carbon taxes This model will facilitate the design of tax policies that effectively influence firms' decisions regarding K and L To ensure practicality, the research model must be based on reasonable assumptions that align closely with real-world practices Consequently, the implementation of carbon taxation can enhance capital stock in foreign direct investment (FDI) projects, fostering advancements in technology Currently, there are no economic measures in place to effectively guide the technology levels of FDI projects; instead, government agencies rely on administrative methods, such as manufacturer certificates and qualitative assessments, to evaluate imported second-hand equipment for FDI projects in Vietnam.

These measures are purely administrative ones which could violate the commitments of WTO In addition, it could allow the corruption in approving incentives and licenses to FDI projects.

Under different modeling cases involving uncertainties of carbon taxation affecting investor profitability, the results of algorithmic modeling and calculations show the interesting implication as follows.

When comparing scenarios with and without carbon taxation, it is evident that implementing carbon taxes leads to a decrease in the optimal capital stock and labor levels for investors However, the optimal capital-to-labor ratio under carbon taxation is greater than that without it, indicating that carbon taxation effectively enhances the technological advancement of projects.

Investors contemplating investments in non-carbon taxed countries often face uncertainties regarding the timing of potential carbon tax implementation Risk-averse investors typically prepare for the worst-case scenario, assuming that the government may introduce carbon taxes as early as the first year of their project's life cycle Consequently, they tend to opt for lower levels of capital, technology, and labor, aligning their strategies with the anticipated impact of carbon taxation.

The implementation of carbon taxation encourages investors with lower carbon emission rates to allocate a higher ratio of capital to labor compared to their higher carbon-emitting counterparts.

Specifically, the answers for two research questions come as follow:

The uncertainties surrounding carbon taxation significantly impact investors' decisions regarding irreversible foreign direct investment (FDI) projects This study identifies two key uncertainties: the level of carbon taxation and the timing of its implementation Both factors adversely affect the capital and labor levels that investors are willing to commit to projects that emit carbon dioxide Consequently, the potential application of carbon taxation leads investors to opt for lower levels of both capital and labor in their FDI projects.

Investors in irreversible foreign direct investment (FDI) projects under carbon taxation uncertainties tend to increase their capital per labor ratio, reflecting a higher level of technology Specifically, as carbon taxation rises, investors with lower carbon emissions are more likely to adopt advanced technologies compared to those with higher emissions.

The findings presented rely on mathematical modeling and calculations grounded in several reasonable assumptions To enhance the mathematical reliability of these results, it is essential to explore various scenarios with different assumed conditions This approach will ensure that the model is adequately prepared for empirical testing.

From the results of model development and calculations in different cases of carbon taxation related uncertainties affecting project profits, we could develop some policy implications as follows.

+ Should the government to apply carbon taxation?

The debate among policymakers regarding carbon taxation remains contentious, as it can lead to reduced capital levels in foreign direct investment (FDI) projects, as indicated by modeling results However, findings suggest that the implementation of carbon taxation may enhance technology levels This presents a trade-off between lower investment capital and improved technological advancement Ultimately, the decision to adopt carbon taxation hinges on a country's priorities Notably, this research does not clarify the specific carbon tax level at which the trade-off between reduced FDI and the benefits of carbon taxation becomes balanced, highlighting a limitation and potential area for further investigation.

The government should proactively communicate its schedule for implementing carbon taxation and potential tax rates to reduce uncertainties for investors By providing this information in advance, investors can make more informed decisions, leading to increased capital investment and higher labor levels compared to a scenario where such details are not disclosed.

The implementation of carbon taxes should be communicated based on the principles of signaling theory and information asymmetry, ensuring investors receive timely information about the tax preparation process, including expected rates, taxpayers, and tax bases It is crucial to notify the estimated tax rate as early as possible, allowing investors ample time for necessary adjustments For existing taxpayers, changing technology can be challenging, so partial exemptions should be considered to facilitate a gradual adaptation to the new carbon tax costs.

Governments should conduct thorough research on regional and international carbon tax rates to establish a competitive and reasonable carbon tax framework for investors This approach aims to minimize investment risks while maintaining regional attractiveness for investment opportunities.

+ Attracting high technology investors for better environment:

Implementing carbon taxation is essential for curbing investments from low-tech industries with high carbon emission rates By imposing carbon taxes, high-tech investors, who typically have lower emissions, are incentivized to invest more in capital and labor compared to their low-tech counterparts Consequently, the government should establish a carbon tax rate that targets specific technology levels, enabling investments from higher-tech firms while discouraging those from lower-tech investors.

Managers and CEOs must recognize that uncertainty is distinct from risk; not all uncertainties translate into risks It is essential to clarify uncertainties before categorizing them as risks Therefore, management should prioritize gathering and analyzing information related to uncertainties, and only when these uncertainties are identified as potential risks should they apply risk management techniques.

POLICY AND MANAGERIAL IMPLICATIONS

General conclusions

This research employs a quantitative approach through mathematical modeling to analyze the effects of carbon taxation uncertainties on firm profit levels and investment decisions If the findings are validated, they can be extended to other uncertainties impacting profits, enabling the design of targeted policies to mitigate both the level and number of uncertainties This strategy aims to enhance foreign direct investment (FDI) as an alternative to traditional solutions like tax reductions and lower land rentals.

This thesis introduces the concept that carbon taxes can be strategically utilized to discourage low-technology investors while promoting higher-technology investments By employing a Cobb-Douglas profit function that incorporates production and cost functions, we can analyze the interplay between capital (K), labor (L), and carbon taxes This model will facilitate the development of tax policies aimed at influencing firm behaviors regarding K and L choices It is essential that the assumptions underlying this research model are realistic and closely aligned with practical applications to ensure its viability Consequently, the implementation of carbon taxation could enhance the capital stock in foreign direct investment (FDI) projects, thereby elevating technology levels Currently, there are no effective economic measures in place to influence the technology levels of FDI projects; instead, government bodies rely on administrative measures, such as manufacturer certificates and qualitative assessments, to evaluate second-hand equipment imported into FDI projects in Vietnam.

These measures are purely administrative ones which could violate the commitments of WTO In addition, it could allow the corruption in approving incentives and licenses to FDI projects.

Under different modeling cases involving uncertainties of carbon taxation affecting investor profitability, the results of algorithmic modeling and calculations show the interesting implication as follows.

Comparing scenarios with and without carbon taxation reveals that implementing carbon taxes leads to a decrease in the optimal capital stock and labor levels for investors However, the capital-to-labor ratio is higher under carbon taxation, indicating that such taxes effectively promote advancements in technology within projects.

Investors evaluating opportunities in non-carbon taxed countries often face uncertainties regarding the timing of potential carbon tax implementation Risk-averse investors may assume the worst-case scenario, anticipating that the government could introduce carbon taxes as early as the first year of their project Consequently, they tend to opt for lower levels of capital, technology, and labor, aligning their strategies with the assumption that carbon taxes will eventually be enforced.

The implementation of carbon taxation encourages investors with lower carbon emissions to allocate a higher ratio of capital to labor compared to those with higher carbon emissions.

Specifically, the answers for two research questions come as follow:

Carbon taxation uncertainties significantly impact investors' decisions regarding irreversible foreign direct investment (FDI) projects This study identifies two main uncertainties: the level of carbon taxation and the timing of its implementation Both uncertainties adversely affect the capital and labor levels chosen by investors in projects that emit carbon dioxide If carbon taxation is enforced, it leads investors to opt for lower levels of both capital and labor, ultimately hindering investment in these projects.

Investors in irreversible foreign direct investment (FDI) projects adjust their capital per labor ratios in response to uncertainties surrounding carbon taxation Under specific modeling conditions, the application of carbon taxation leads to an increase in the technology level, as indicated by the capital-to-labor ratio Furthermore, as carbon taxation rises, investors with lower carbon emissions are more inclined to invest in higher technology levels compared to those with higher emissions.

The findings presented are derived from mathematical modeling and calculations grounded in several reasonable assumptions To enhance the mathematical reliability of these results, it is essential to further develop the model under various assumed conditions This approach will ensure that the model is better suited for empirical testing.

Policy and managerial implications

From the results of model development and calculations in different cases of carbon taxation related uncertainties affecting project profits, we could develop some policy implications as follows.

+ Should the government to apply carbon taxation?

The debate among policymakers regarding carbon tax remains contentious, as it is shown to potentially reduce capital levels in foreign direct investment (FDI) projects, as indicated in Section 4.2 Conversely, the findings in Section 4.3 reveal that implementing carbon taxation could lead to higher technology levels This presents a trade-off between reduced investment capital and enhanced technology Ultimately, the decision to impose carbon taxation depends on a country's priorities However, this research does not clarify the specific level of carbon taxation at which the trade-off between its implementation and reduced FDI would balance, highlighting a limitation and an opportunity for future research.

The government should proactively communicate its schedule for implementing carbon taxation and potential tax rates By doing so, it can alleviate uncertainties for investors, enabling them to make more informed investment decisions This transparency will ultimately lead to increased capital stock and higher labor levels, compared to a scenario where the government does not provide advance notice.

The advance notice regarding the implementation of carbon taxes should be grounded in the principles of signaling theory and information asymmetry, ensuring that investors receive timely information about the tax preparation process, expected rates, taxpayers, and tax bases Prompt notification of estimated tax rates is crucial for investors to make necessary adjustments before committing to investments For existing taxpayers, changing technology can be challenging; therefore, it is essential to consider partial exemptions in the roadmap, allowing firms to gradually adapt to the new costs associated with carbon taxes.

Governments must analyze both regional and international carbon tax rates to establish a competitive and reasonable carbon tax rate for investors This proactive approach will help mitigate investment risks associated with fluctuating carbon tax rates while maintaining regional competitiveness in attracting investments.

+ Attracting high technology investors for better environment:

Implementing carbon taxation is essential for limiting investments from low-tech industries with high carbon emission rates By imposing such taxes, high-tech investors, who typically have lower emissions, are incentivized to allocate more capital and labor towards sustainable practices Consequently, the government should establish a carbon tax rate that targets specific technology levels, encouraging investment from cleaner technologies while discouraging lower-tech investors that contribute to higher emissions.

Managers and CEOs must recognize that uncertainty and risk are distinct concepts; not all uncertainties translate into risks To effectively navigate uncertainties, management should prioritize clarifying information to determine whether these uncertainties could evolve into risks Once identified, appropriate risk management techniques can be employed to address potential threats.

Uncertainties surrounding carbon taxation significantly impact a firm's investment decisions and the optimal allocation of capital and labor, which are crucial for profit maximization To enhance project appraisal, managers must integrate these uncertainties into the project's profit model Selecting the optimal capital for large projects is complex, necessitating technical design, cost estimation, and initial investment formation Early identification and clarification of carbon tax uncertainties can streamline project preparation and improve the efficiency of total initial investment costs, resulting in more accurate evaluations of NPV, IRR, and ROA for project assessment.

Research limitations and recommendation for further research directions

This study emphasizes theoretical research and utilizes hypothetical simulations to demonstrate the outcomes of mathematical modeling While hypothetical data enhances the understanding of theoretical results, it cannot substitute for empirical data Consequently, it is essential to conduct further empirical research to validate and calibrate the theoretical findings before applying them in real-world scenarios.

Investor responses to uncertainties surrounding carbon taxation vary based on their psychological traits, including risk-taking, risk neutrality, and risk aversion However, this thesis assumes uniformity in risk tolerance among all investors, omitting these characteristics from the research model.

5.3.2 Recommendation for further research directions

In addition to further researches to overcome the limitations of the thesis, the following research directions need to be taken into account in practical requirements in Vietnam.

To enhance project appraisal methods, particularly real option analysis, it is essential to explore its advantages for evaluating large fixed assets, as supported by numerous scholars Conducting case studies in Vietnam with a blend of collected and assumed data for specific project types can provide valuable insights These empirical studies will lay the groundwork for proposing a formal real option appraisal method in Vietnam, complementing the traditional Discounted Cash Flow (DCF) approach.

The next crucial research direction involves determining the optimal carbon tax rate necessary to phase out high carbon emission investors utilizing low technology This study aims to identify the effective tax level that can incentivize a transition towards cleaner technologies and reduce overall carbon emissions.

Implementing a carbon tax in Vietnam could serve as a crucial regulatory tool to manage technology and labor standards in investment projects, particularly for foreign direct investment (FDI) initiatives This policy aims to promote sustainable development while encouraging responsible investment practices.

The basic research model is static in the short run, but developing it into a dynamic model for the long run could yield more intriguing insights Although a dynamic model may introduce complexity, it can reveal significant findings about how rising labor wages influence investors' technology choices These insights could be valuable for policy implications related to carbon taxation.

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Publications of author (Relating to the thesis)

- Lê Quốc Thành (2018) Các nhân tố bất định ảnh hưởng đến quyết định đầu tư trong dự án FDI không thể hủy ngang tại Việt Nam , số 48 Tháng 12 n m 2018.

- Phạm Khắc Quốc Bảo & Lê Quốc Thành (2019) Thẩm định dự án không hủy ngang trong điều kiện bất định: Trường hợp bất định về thuế carbon

- Wei Zhou, Stefano Bosi & Le Quoc Thanh (2016) Carbon optimal taxation and carbon emission leakage Hội thảo VEAM 2016, tại Đà Nẵng.

Coding in do.file of mathLab and Graphs

TH2 format long r=0.15 %r la chi phi von w0 %w la chi phi lao dong a=0.3 b=0.6 phi=0.004 %He so hieu suat = 0.004 tau=[0 10 50 100 150]tau la thue?

%Truong hop 1: Khong thue k1=nthroot(P*(b/a)^b*(r/w)^b*(a/r),1-a- b) %k1,l1 là toi uu TH1 l1=(b*r*k1)/(a*w)

Pi=zeros(1,4) kk=zeros(1,3) %su thay doi cua K ll=zeros(1,3) %su thay doi L for i=1:4

K(i)=nthroot((P-tau(i)*phi)*(b/a)^b*(r/w)^b*(a/r),1-a-b) %k,l là toi uu

%Ve do thi figure plot(tau,K)

TB1 = annotation('textbox', [.45, 93, 17, 065], 'String', 'Do thi

TB2 = annotation('textbox', [.45, 0, 1, 05], 'String', '$\tau (USD)$', 'BackgroundColor', [1, 1, 1], 'Interpreter', 'latex') ylabel('K* (USD)') figure plot(tau,L)

TB3 = annotation('textbox', [.45, 93, 17, 065], 'String', 'Do thi

$L^*(\tau$)', 'BackgroundColor', [1, 1, 1], 'Interpreter', 'latex') ylabel('L* (USD)')

TB4 = annotation('textbox', [.45, 0, 1, 05], 'String', '$\tau (USD)$', 'BackgroundColor', [1, 1, 1], 'Interpreter', 'latex') figure plot(tau,Pi)

TB5 = annotation('textbox', [.45, 93, 17, 065], 'String', 'Do thi

$\Pi^*(\tau$)', 'BackgroundColor', [1, 1, 1], 'Interpreter', 'latex') ylabel('Pi* (USD)')

TB6 = annotation('textbox', [.45, 0, 1, 05], 'String', '$\tau (USD)$', 'BackgroundColor', [1, 1, 1], 'Interpreter', 'latex')

129 disp(K) disp('Cac gia tri L*') disp(L) disp('Cac gia tri Pi*') disp(Pi) disp('Su thay doi cua K*') disp(kk) disp('Su thay doi cua L*') disp(ll)

KYOTO PROTOCOL TO THE UNITED NATIONS FRAMEWORK

The Parties to this Protocol,

Being Parties to the United Nations Framework Convention on Climate Change, hereinafter referred to as “the Convention”,

In pursuit of the ultimate objective of the Convention as stated in its Article 2, Recalling the provisions of the Convention,

Being guided by Article 3 of the Convention,

Pursuant to the Berlin Mandate adopted by decision 1/CP.1 of the Conference of the

Parties to the Convention at its first session,

For the purposes of this Protocol, the definitions contained in Article 1 of the Convention shall apply In addition:

1 “Conference of the Parties” means the Conference of the Parties to the Convention.

2 “Convention” means the United Nations Framework Convention on Climate Change, adopted in New York on 9 May 1992.

3 “Intergovernmental Panel on Climate Change” means the Intergovernmental Panel on Climate

Change established in 1988 jointly by the World Meteorological Organization and the United Nations Environment Programme.

4 “Montreal Protocol” means the Montreal Protocol on Substances that Deplete the Ozone Layer, adopted in Montreal on 16 September 1987 and as subsequently adjusted and amended.

5 “Parties present and voting” means Parties present and casting an affirmative or negative vote.

6 “Party” means, unless the context otherwise indicates, a Party to this Protocol.

7 “Party included in Annex I” means a Party included in Annex I to the Convention, as may be amended, or a Party which has made a notification under Article 4, paragraph 2 (g), of the Convention.

1 Each Party included in Annex I, in achieving its quantified emission limitation and reduction commitments under Article 3, in order to promote sustainable development, shall:

(a) Implement and/or further elaborate policies and measures in accordance with its national circumstances, such as:

(i) Enhancement of energy efficiency in relevant sectors of the national economy;

The protection and enhancement of greenhouse gas sinks and reservoirs, not governed by the Montreal Protocol, should align with commitments under international environmental agreements This includes promoting sustainable forest management practices, as well as afforestation and reforestation efforts.

(iii) Promotion of sustainable forms of agriculture in light of climate change considerations;

(iv) Research on, and promotion, development and increased use of, new and renewable forms of energy, of carbon dioxide sequestration technologies and of advanced and innovative environmentally sound technologies;

To achieve the objectives of the Convention, it is essential to progressively reduce or eliminate market imperfections, fiscal incentives, tax and duty exemptions, and subsidies in all sectors that emit greenhouse gases Implementing market instruments will support this transition and promote a more sustainable approach to emissions management.

(vi) Encouragement of appropriate reforms in relevant sectors aimed at promoting policies and measures which limit or reduce emissions of greenhouse gases not controlled by the Montreal Protocol;

(vii) Measures to limit and/or reduce emissions of greenhouse gases not controlled by the Montreal Protocol in the transport sector;

(viii) Limitation and/or reduction of methane emissions through recovery and use in waste management, as well as in the production, transport and distribution of energy;

Parties are encouraged to collaborate to enhance the effectiveness of their policies and measures as outlined in Article 4, paragraph 2 (e) (i) of the Convention This collaboration involves sharing experiences and exchanging information to improve the comparability, transparency, and effectiveness of their initiatives The Conference of the Parties will address methods to facilitate this cooperation at its first session or as soon as possible thereafter, considering all relevant information.

Parties listed in Annex I are committed to limiting or reducing greenhouse gas emissions from aviation and marine bunker fuels, which are not regulated by the Montreal Protocol This effort will be coordinated through the International Civil Aviation Organization and the International Maritime Organization.

The international trade landscape is significantly influenced by social, environmental, and economic impacts, particularly affecting developing countries as outlined in Article 4, paragraphs 8 and 9 of the Convention It is essential to consider Article 3 of the Convention in this context The Conference of the Parties, acting as the meeting of the Parties to this Protocol, may take additional measures to enhance the implementation of these provisions.

The Conference of the Parties, acting as the meeting of the Parties to this Protocol, may find it advantageous to coordinate the policies and measures outlined in paragraph 1 (a) In doing so, it will take into account varying national circumstances and potential impacts, and will explore methods to enhance the coordination of these policies and measures.

Parties listed in Annex I must ensure that their total anthropogenic carbon dioxide equivalent emissions do not surpass their assigned limits, which are based on their quantified commitments for emission limitations and reductions outlined in Annex B This is aimed at achieving at least a 5% reduction in overall greenhouse gas emissions compared to 1990 levels during the commitment period from 2008 to 2012.

2 Each Party included in Annex I shall, by 2005, have made demonstrable progress in achieving its commitments under this Protocol.

Since 1990, the net changes in greenhouse gas emissions resulting from human-induced land-use changes and forestry activities, specifically afforestation, reforestation, and deforestation, must be measured as verifiable alterations in carbon stocks for each commitment period These changes will be utilized by Annex I Parties to fulfill their commitments under this Article Furthermore, the associated greenhouse gas emissions and removals must be reported transparently and verifiably, with reviews conducted in accordance with Articles 7 and 8.

Before the inaugural session of the Conference of the Parties, each Annex I Party must submit data to the Subsidiary Body for Scientific and Technological Advice, detailing their carbon stocks in 1990 and subsequent changes The Conference will then establish rules and guidelines for incorporating additional human-induced activities affecting greenhouse gas emissions and removals in agricultural soils and land-use change This decision will consider factors such as uncertainties, transparency, verifiability, and the Intergovernmental Panel on Climate Change's methodology The agreed-upon framework will be effective in the second commitment period, although Parties may opt to apply it to their first commitment period if the relevant activities occurred post-1990.

Parties in Annex I transitioning to a market economy must utilize the base year established by decision 9/CP.2 for their commitments under this Article Additionally, any other Annex I Party in transition that has not submitted its first national communication may notify the Conference of the Parties of its intention to use a different historical base year instead of 1990 The acceptance of such notifications will be determined by the Conference of the Parties.

According to Article 4, paragraph 6, of the Convention, the Conference of the Parties, acting as the meeting of the Parties to this Protocol, will permit a degree of flexibility for Annex I Parties that are transitioning to a market economy in fulfilling their commitments under this Protocol.

During the first commitment period for quantified emission limitations from 2008 to 2012, the assigned amount for each Annex I Party was calculated based on their percentage in Annex B, reflecting their aggregate anthropogenic carbon dioxide equivalent emissions from 1990 or an established base year This amount was then multiplied by five Additionally, Parties in Annex I that had land-use change and forestry as a net source of greenhouse gas emissions in 1990 were required to factor in the total anthropogenic carbon dioxide equivalent emissions from land-use change, after accounting for removals by sinks, to determine their assigned amount.

8 Any Party included in Annex I may use 1995 as its base year for hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride, for the purposes of the calculation referred to in paragraph 7 above.

Commitments for future periods for Annex I Parties will be defined through amendments to Annex B of this Protocol, following the guidelines of Article 21, paragraph 7 The Conference of the Parties, acting as the meeting for the Parties to this Protocol, will begin discussing these commitments at least seven years prior to the conclusion of the initial commitment period mentioned in paragraph 1.

Any emission reduction units or portions of an assigned amount acquired by a Party from another Party, as outlined in Article 6 or Article 17, will be added to the acquiring Party's assigned amount.

Any emission reduction units or portions of an assigned amount that a Party transfers to another Party, as outlined in Article 6 or Article 17, will be deducted from the transferring Party's assigned amount.

12 Any certified emission reductions which a Party acquires from another Party in accordance with the provisions of Article 12 shall be added to the assigned amount for the acquiring

- 4 - amount for that Party for subsequent commitment periods.