difference between a thesis and hypothesis

The Real Differences Between Thesis and Hypothesis (With table)

A thesis and a hypothesis are two very different things, but they are often confused with one another. In this blog post, we will explain the differences between these two terms, and help you understand when to use which one in a research project.

As a whole, the main difference between a thesis and a hypothesis is that a thesis is an assertion that can be proven or disproven, while a hypothesis is a statement that can be tested by scientific research. 

We probably need to expand a bit on this topic to make things clearer for you, let’s start with definitions and examples.

Definitions

As always, let’s start with the definition of each term before going further.

A thesis is a statement or theory that is put forward as a premise to be maintained or proved. A thesis statement is usually one sentence, and it states your position on the topic at hand.

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The best way to understand the slight difference between those terms, is to give you an example for each of them.

If you are writing a paper about the effects of climate change on the environment, your thesis might be “Climate change is causing irreparable damage to our planet, and we must take action to prevent further damage”.

If your hypothesis is correct, then further research should be able to confirm it. However, if your hypothesis is incorrect, research will disprove it. Either way, a hypothesis is an important part of the scientific process.

The word “hypothesis” comes from the Greek words “hupo,” meaning “under”, and “thesis” that we just explained.

Argumentation vs idea

A thesis is usually the result of extensive research and contemplation, and seeks to prove a point or theory.

A hypothesis is only a statement that need to be tested by observation or experimentation.

5 mains differences between thesis and hypothesis

Thesis and hypothesis are different in several ways, here are the 5 keys differences between those terms:

So, in short, a thesis is an argument, while a hypothesis is a prediction. A thesis is more detailed and longer than a hypothesis, and it is based on research. Finally, a thesis must be proven, while a hypothesis does not need to be proven.

Is there a difference between a thesis and a claim?

Is a hypothesis a prediction.

No, a hypothesis is not a prediction. A prediction is a statement about what you think will happen in the future, whereas a hypothesis is a statement about what you think is causing a particular phenomenon.

What’s the difference between thesis and dissertation?

A thesis is usually shorter and more focused than a dissertation, and it is typically achieved in order to earn a bachelor’s degree. A dissertation is usually longer and more comprehensive, and it is typically completed in order to earn a master’s or doctorate degree.

What is a good thesis statement?

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Home » Education » Difference Between Thesis and Hypothesis

Difference Between Thesis and Hypothesis

Main difference –  thesis vs hypothesis                           .

Thesis and hypothesis are two common terms that are often found in research studies. Hypothesis is a logical proposition that is based on existing knowledge that serves as the starting point of an investigation. A thesis is a statement that is put forward as a premise to be maintained or proved. The main difference between thesis and hypothesis is that thesis is found in all research studies whereas a hypothesis is mainly found in experimental quantitative research studies.

This article explains,

1. What is a Thesis?      – Definition, Features, Function

2. What is a Hypothesis?      – Definition, Features, Function

What is a Thesis

The word thesis has two meanings in a research study. Thesis can either refer to a dissertation or a thesis statement. Thesis or dissertation is the long essay or document that consists of the research study.  Thesis can also refer to a theory or statement that is used as a premise to be maintained or proved.

The thesis statement in a research article is a sentence found at the beginning of the paper that presents the main argument of the paper. The rest of the document will gather, organize and present evidence to support this argument. The thesis statement will basically present the topic of the paper and indicate what position the researcher is going to take in relation to this topic. A thesis statement can generally be found at the end of the first paragraph (introductory paragraph) of the paper.

What is a Hypothesis

A hypothesis is a logical assumption based on available evidence. Hypothesis is defined as “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” in the Oxford dictionary and as “an idea or theory that is not proven but that leads to further study or discussion” in the Merriam-Webster dictionary. In simple words, it is an educated guess that is not proven with concrete scientific evidence. Once it is scientifically tested and proven, it becomes a theory. However, it is important to note that a hypothesis can be accurate or inaccurate.

Hypotheses are mostly used in experiments and research studies. However, hypotheses are not used in every research study. They are mostly used in quantitative research studies  that deal with experiments. Hypotheses are often used to test a specific model or theory . They can be used only when the researcher has sufficient knowledge about the subject since hypothesis are always based on the existing knowledge. Once the hypothesis is built, the researcher can find and analyze data and use them to prove or disprove the hypothesis.

Thesis: A thesis is a “statement or theory that is put forward as a premise to be maintained or proved” or a “long essay or dissertation involving personal research, written by a candidate for a university degree” (Oxford dictionary).

Hypothesis: A hypothesis is “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” (Oxford dictionary).

Thesis: Thesis statement can be found in all research papers.

Hypothesis: Hypotheses are usually found in experimental quantitative research studies.

Thesis: Thesis statement may explain the hypothesis and how the researcher intends to support it.

Hypothesis: Hypothesis is an educated guess based on the existing knowledge.

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Thesis Vs Hypothesis: Understanding The Basis And The Key Differences

Hypothesis vs. thesis: They sound similar and seem to discuss the same thing. However, these terms have vastly different meanings and purposes. You may have encountered these concepts in school or research, but understanding them is key to executing quality work. 

In this article, I’ll discuss hypothesis vs. thesis, break down their differences, and show you how to apply this knowledge to create quality written works. Let’s get to it!

Thesis vs. Hypothesis: Understanding the Basis

The power of a thesis.

A thesis statement is typically found at the end of the introduction in an essay or research paper, succinctly summarizing the overarching theme.

Crafting a strong thesis

Hypothesis: the scientific proposition.

In contrast, a hypothesis is a tentative proposition or educated guess. It is the initial step in the scientific method, where researchers formulate a hunch to test their assumptions and theories. 

Formulating a hypothesis

Key differences between thesis vs. hypothesis, 1. nature of statement, 3. testability, 4. research stage, 6. examples.

These differences highlight the distinct roles that the thesis and hypothesis play in academic writing and scientific research, with one providing a point of argumentation and the other guiding the scientific inquiry process.

Can a hypothesis become a thesis?

Do all research papers require a thesis, can a thesis be proven wrong.

Yes. The purpose of a thesis is not only to prove but also to encourage critical analysis. It can be proven wrong with compelling counterarguments and evidence.

How long should a thesis statement be?

Is a hypothesis only used in scientific research, can a hypothesis be vague.

No. When creating a hypothesis, it’s important to make it clear and able to be tested. Developing experiments and making conclusions based on the results can be difficult if the hypothesis needs clarification.

Final Thoughts

In conclusion, understanding the differences between a hypothesis and a thesis is vital to crafting successful research projects and academic papers. While they may seem interchangeable at first glance, these two concepts serve distinct purposes in the research process. 

So, the next time you embark on a research project, take the time to ensure that you understand the fundamental difference between a hypothesis and a thesis. Doing so can lead to more focused, meaningful research that advances knowledge and understanding in your field.

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Answered By: APUS Librarians Last Updated: Apr 15, 2022     Views: 129380

Both the hypothesis statement and the thesis statement answer a research question. 

• A hypothesis is a statement that can be proved or disproved. It is typically used in quantitative research and predicts the relationship between variables.  
• A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research. A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain a hypothesis statement.

NOTE: In some disciplines, the hypothesis is referred to as a thesis statement! This is not accurate but within those disciplines it is understood that "a short, direct sentence that summarizes the main point" will be included.

For more information, see The Research Question and Hypothesis (PDF file from the English Language Support, Department of Student Services, Ryerson University).

How do I write a good thesis statement?

How do I write a good hypothesis statement?

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Hypothesis vs. Thesis

What's the difference.

A hypothesis is a proposed explanation for a phenomenon that can be tested through research and experimentation. It is a tentative statement that serves as the basis for further investigation. On the other hand, a thesis is a statement or theory that is put forward as a premise to be maintained or proved. It is typically a longer, more detailed argument that is supported by evidence and analysis. While a hypothesis is more focused on predicting outcomes and guiding research, a thesis is more comprehensive and aims to persuade the reader of a particular perspective or argument.

Further Detail

A hypothesis is a proposed explanation for a phenomenon or a scientific question that can be tested through experimentation or observation. It is a tentative assumption made in order to draw out and test its logical or empirical consequences. On the other hand, a thesis is a statement or theory that is put forward as a premise to be maintained or proved. It is typically used in academic writing to present an argument or claim that will be supported with evidence and analysis.

Hypotheses are used in scientific research to guide the investigation and testing of a specific question or problem. They help researchers to make predictions about the outcome of experiments and observations. In contrast, a thesis is used in academic writing to present a central argument or claim that the author will support with evidence and analysis. It serves as the main point that the author is trying to prove or persuade the reader to accept.

A hypothesis is typically narrower in scope compared to a thesis. It focuses on a specific question or problem and proposes a possible explanation or solution. In contrast, a thesis is broader in scope as it presents an overarching argument or claim that encompasses the entire paper or essay. It provides a roadmap for the reader to understand the main point of the work and how it will be supported.

Both hypotheses and theses rely on evidence to support their claims. In scientific research, hypotheses are tested through experimentation and observation to gather data that either confirms or refutes the proposed explanation. In academic writing, theses are supported with evidence from sources such as research studies, scholarly articles, and other relevant sources. The quality and relevance of the evidence used can strengthen the credibility of both hypotheses and theses.

Flexibility

Hypotheses are more flexible compared to theses. If a hypothesis is not supported by the data or experiments, researchers can revise or refine it based on the new information gathered. This allows for the hypothesis to evolve as more evidence is collected. On the other hand, a thesis is typically more fixed in academic writing. While it can be revised during the writing process, the central argument or claim remains constant throughout the paper or essay.

In conclusion, while both hypotheses and theses play important roles in scientific research and academic writing, they differ in terms of definition, function, scope, evidence, and flexibility. Understanding the differences between the two can help researchers and writers effectively formulate and support their arguments. Whether testing a scientific question or presenting a central claim in an academic paper, both hypotheses and theses are essential tools for advancing knowledge and understanding in their respective fields.

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B oth the hypothesis statement and the thesis statement answer the research question of the study.  When the statement is one that can be proved or disproved, it is an hypothesis statement.  If, instead, the statement specifically shows the intentions/objectives/position of the researcher, it is a thesis statement.

A hypothesis is a statement that can be proved or disproved.  It is typically used in quantitative research and predicts the relationship between variables.

A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research.  A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain an hypothesis statement.

Jablonski , Judith. What is the difference between a thesis statement and an hypothesis statement? Online Library. American Public University System. Jun 16, 2014. Web.   http://apus.libanswers.com/faq/2374

Let’s say you are interested in the conflict in Darfur, and you conclude that the issues you wish to address include the nature, causes, and effects of the conflict, and the international response. While you could address the issue of international response first, it makes the most sense to start with a description of the conflict, followed by an exploration of the causes, effects, and then to discuss the international response and what more could/should be done.

This hypothetical example may lead to the following title, introduction, and statement of questions:

Conflict in Darfur: Causes, Consequences, and International Response       This paper examines the conflict in Darfur, Sudan. It is organized around the following questions: (1) What is the nature of the conflict in Darfur? (2) What are the causes and effects of the conflict? (3) What has the international community done to address it, and what more could/should it do?

Following the section that presents your questions and background, you will offer a set of responses/answers/(hypo)theses. They should follow the order of the questions. This might look something like this, “The paper argues/contends/ maintains/seeks to develop the position that...etc.” The most important thing you can do in this section is to present as clearly as possible your best thinking on the subject matter guided by course material and research. As you proceed through the research process, your thinking about the issues/questions will become more nuanced, complex, and refined. The statement of your theses will reflect this as you move forward in the research process.

So, looking to our hypothetical example on Darfur:

The current conflict in Darfur goes back more than a decade and consists of fighting between government-supported troops and residents of Darfur. The causes of the conflict include x, y, and z. The effects of the conflict have been a, b, and c. The international community has done 0, and it should do 1, 2, and 3.

Once you have setup your thesis you will be ready to begin amassing supporting evidence for you claims. This is a very important part of the research paper, as you will provide the substance to defend your thesis.

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What is the difference between hypothesis, thesis statement and research goal?

Can someone explain the difference between hypothesis, thesis statement and research goal based on an example?

• terminology

• 1 You should mention which subject you are in. 'Hypothesis' has opposite meanings in maths and physics. –  Jessica B Commented May 31, 2018 at 11:22

2 Answers 2

I had this same question recently and did some research on it. The definitions I found weren't consistent, but from them I derived the following.

Thesis statement -- A definitive statement about the way the world (or your system of interest) works, especially what is most important in causing or influencing the behavior of the system.

"Family expectations has primary significance on the performance in college for Latino girls in the Western US" is an example of a thesis statement.

Research goal -- Expresses what you hope to learn or shed light on in your research. Specifically, the goal should specify what type of results you are hoping to achieve. It contextualizes your work in relation to other research, especially theory. It also feeds into your choice of method.

"My research goal is to develop a theoretical model of cultural influence on college performance, contextualized by gender and ethnicity" is an example of a research goal.

Hypotheses -- What specific conditions or relations do you aim to test or evaluate in your research. Any research that does not include a method for hypothesis testing should not claim to test hypotheses. A hypothesis statement must be specific enough that it is testable by the methods you choose, and also it should be falsifiable -- i.e. it is clear what evidence might prove the hypothesis false, and such evidence should be plausible and possible.

"Low family expectations has a detrimental effect on the college completion rate and time-to-complete for high-achieving Latino girls" is an example of a hypothesis statement.

Notice how there are specific, testable conditions and metrics -- "college completion rates" and "time-to-complete". These conditions should appear as metrics in your research methods -- i.e. instruments and analysis methods.

A thesis statement usually helps guide the research paper. It is a short sentence or summary containing the central idea of the research paper. It helps a reader have a clear glimpse of what the paper is about.

The Hypothesis statement comes in different format but with the intent to help prove or disprove a phenomenon. The hypothesis can help defend, support, explain or disprove, argue against the thesis statement.Usually the hypothesis measures specific issues or variables-two or more and therefore should be testable. The thesis statement creates a background while the hypothesis creates a means to measure the interrelationship.

The research goal takes a look into the future of your study or research paper. |It tries to help you state what the outcomes you seek to achieve by the research work. With a research goal you can set specific milestones to accomplish at the end of the research work.

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Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
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• Stratified sampling
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• Likert scales
• Reproducibility

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Research bias

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• Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved September 9, 2024, from https://www.scribbr.com/methodology/hypothesis/

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Thesis vs. Hypothesis: What's the Difference?

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Thesis vs. Hypothesis — What's the Difference?

Difference Between Thesis and Hypothesis

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Types of Essays in Academic Writing - Quick Guide (2024)

Thesis and Purpose Statements

Use the guidelines below to learn the differences between thesis and purpose statements.

In the first stages of writing, thesis or purpose statements are usually rough or ill-formed and are useful primarily as planning tools.

A thesis statement or purpose statement will emerge as you think and write about a topic. The statement can be restricted or clarified and eventually worked into an introduction.

As you revise your paper, try to phrase your thesis or purpose statement in a precise way so that it matches the content and organization of your paper.

Thesis statements

A thesis statement is a sentence that makes an assertion about a topic and predicts how the topic will be developed. It does not simply announce a topic: it says something about the topic.

Good: X has made a significant impact on the teenage population due to its . . . Bad: In this paper, I will discuss X.

A thesis statement makes a promise to the reader about the scope, purpose, and direction of the paper. It summarizes the conclusions that the writer has reached about the topic.

A thesis statement is generally located near the end of the introduction. Sometimes in a long paper, the thesis will be expressed in several sentences or an entire paragraph.

A thesis statement is focused and specific enough to be proven within the boundaries of the paper. Key words (nouns and verbs) should be specific, accurate, and indicative of the range of research, thrust of the argument or analysis, and the organization of supporting information.

Purpose statements

A purpose statement announces the purpose, scope, and direction of the paper. It tells the reader what to expect in a paper and what the specific focus will be.

Common beginnings include:

“This paper examines . . .,” “The aim of this paper is to . . .,” and “The purpose of this essay is to . . .”

A purpose statement makes a promise to the reader about the development of the argument but does not preview the particular conclusions that the writer has drawn.

A purpose statement usually appears toward the end of the introduction. The purpose statement may be expressed in several sentences or even an entire paragraph.

A purpose statement is specific enough to satisfy the requirements of the assignment. Purpose statements are common in research papers in some academic disciplines, while in other disciplines they are considered too blunt or direct. If you are unsure about using a purpose statement, ask your instructor.

This paper will examine the ecological destruction of the Sahel preceding the drought and the causes of this disintegration of the land. The focus will be on the economic, political, and social relationships which brought about the environmental problems in the Sahel.

Sample purpose and thesis statements

The following example combines a purpose statement and a thesis statement (bold).

The goal of this paper is to examine the effects of Chile’s agrarian reform on the lives of rural peasants. The nature of the topic dictates the use of both a chronological and a comparative analysis of peasant lives at various points during the reform period. . . The Chilean reform example provides evidence that land distribution is an essential component of both the improvement of peasant conditions and the development of a democratic society. More extensive and enduring reforms would likely have allowed Chile the opportunity to further expand these horizons.

For more tips about writing thesis statements, take a look at our new handout on Developing a Thesis Statement.

Writing Process and Structure

This is an accordion element with a series of buttons that open and close related content panels.

Getting Started with Your Paper

Interpreting Writing Assignments from Your Courses

Generating Ideas for Your Paper

Creating an Argument

Thesis vs. Purpose Statements

Developing a Thesis Statement

Architecture of Arguments

Working with Sources

Quoting and Paraphrasing Sources

Using Literary Quotations

Citing Sources in Your Paper

Drafting Your Paper

Introductions

Paragraphing

Developing Strategic Transitions

Conclusions

Revising Your Paper

Peer Reviews

Reverse Outlines

Revising an Argumentative Paper

Revision Strategies for Longer Projects

Finishing Your Paper

Twelve Common Errors: An Editing Checklist

How to Proofread your Paper

Writing Collaboratively

Collaborative and Group Writing

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Theory, Thesis, Hypothesis and the mysterious Theorem

lately I have been thinking about the terms theory, thesis, hypothesis and theorem. I am quite sure about the differences between a thesis and a hypothesis, but I did not really get what a theorem is. I would like to ask you to confirm my definition of each term or don' t. If you disagree with my definition, please explain why and give - if possible - a good example.

As an example I will use the axiom "Nothing is faster than light" of the Theory of Relativity.

Thesis : As far as I have figured out, a thesis is an assertion which a controversy is immanent to. So it needs a argumentative reasoning.

My first question, in reference to my example, is if every axiom is implicitly a thesis or not.

I am not sure about it, because if I took the axiom from the example, I would not know if there is any controversy about this assertion or if it is just an undisputed assertion, although there could be a controversy, because nobody can know if there is not something faster than light. On the other hand, if I have the assertion "There is a God", its clear to me that there will be a controversy. So it must be a thesis.

Further on I will assume the example axiom to be a thesis for further illustration.

Hypothesis : A hypothesis is a derived form of a thesis. It asserts a correlation between - at least - two factors (where a thesis is simply an assertion).

So in reference to the example I could derive the hypothesis "If there was something faster than light, then there would be a God" from my thesis "Nothing is faster than light". It asserts a correlation between the factors "speed of light" and "existence of a God" (although there is no causal relationship).

Theory: A theory is an abstract concept which tries to explain a discipline of reality. It consists of axioms/theses.

Theorem: This is something that I was not really able to figure out. I found a pattern in theoremes: It always seems to be based on some theory and tries to solve some paradoxon or other problem the theory has, but it does not change the theory at all. It is some lego that is put on the theory to fill a hole.

I don' t know if there is any truth in what I have written about the theoreme.

So I hope you can help me understanding :)

• terminology

• The words have different meaning in difference contexts, i.e. you don't prove theorems in physics you prove theories but a theory in physics is more like a conjecture in mathematics. A theorem is something that is proved deductively using logical reasoning or inference (think about what you do in a formal logical system like propositional logic). Mathematical theorems, like the fundamental theorem of arithmetic, are theorems because they can be proved in a completely deductive way. Physical laws are not proved deductively, they are proved inductively through observation and experiment. –  Not_Here Commented Jul 29, 2017 at 10:42
• From wikipedia's article on theorem: "In light of the requirement that theorems be proved, the concept of a theorem is fundamentally deductive, in contrast to the notion of a scientific law, which is experimental." In mathematics, conjectures are a lot more like scientific laws than theorems because they are things that we do not have a deductive proof for yet, but every test we've ever done to the conjecture came up positive. Consider Goldbach's conjecture, it is a conjecture because it doesn't have a proof yet, but we have yet to find a single counterexample, despite massive testing. –  Not_Here Commented Jul 29, 2017 at 10:44
• The biggest issue you're having, I think, is that you're mixing how the words are used in science and how they're used in math. Obviously there is over lap but the words have different meanings when they're used very strictly in those two contexts. For example, your definition of theory (besides the use of the term axioms because those also have different meanings in different contexts) is correct when applied to science but theory has a different definition in mathematical logic where it's a set of axioms and theorems in some formal language. –  Not_Here Commented Jul 29, 2017 at 10:51
• See if any of these definitions help you theorem , axiom , scientific hypotheses and scientific theories , mathematical conjecture , general statement of hypothesis that also touches on how its specifically used in mathematics . –  Not_Here Commented Jul 29, 2017 at 10:55

The biggest trouble that you will face when thinking about these ideas is that you are mixing terminology from two distinct fields into one. Some of those words are used very differently in science than they are in mathematics. It can become even more confusing when you consider how much math is used in science, but an explanation of how the words are used in their specific contexts will help illuminate the delineating line.

In mathematics, "thesis", "hypothesis", and "conjecture" are all used synonymously. From Wolfram's Mathworld:

Hypothesis: "A hypothesis is a proposition that is consistent with known data, but has been neither verified nor shown to be false." "In general mathematical usage, 'hypothesis' is roughly synonymous with 'conjecture.'" Conjecture: "A proposition which is consistent with known data, but has neither been verified nor shown to be false. It is synonymous with hypothesis."

Additionally, if you go to the disambiguation of the word "thesis" on wikipedia you see that in the subjects of mathematics and logic it links to "hypothesis" and "conjecture" as well. An example of a mathematical thesis is the Church-Turing thesis which, as you can see, is also sometimes called the Church-Turing conjecture and is described in that article as being a hypothesis. The reason that the Church-Turing thesis is a thesis is because it tries to take an informal idea (the idea of an algorithm) and give it a precise mathematical statement. Due to the fact that it starts with an informal idea, there isn't a purely deductive way to prove that the idea is true, therefore it's left open as a hypothesis and would be proven untrue if a counter example is shown.

As such, mathematical conjectures, theses, and hypotheses are statements in mathematics that seem probable and no counter example has yet been shown. This means that conjectures have yet to be proven , which delineates them from theorems.

A theorem is something that is not a conjecture, it is something that has been proven true. From Mathworld:

Theorem: "A theorem is a statement that can be demonstrated to be true by accepted mathematical operations and arguments. In general, a theorem is an embodiment of some general principle that makes it part of a larger theory. The process of showing a theorem to be correct is called a proof."

Examples of theorems are proven mathematical statements, things like the fundamental theorems of arithmetic , algebra , and calculus . Other, much simpler theorems, are things like the Pythagorean theorem . The picture of a theorem as something that solves a paradox or other problem is incorrect, a theorem is just a provably true statement. The Pythagorean theorem doesn't resolve a paradox in geometry, it is just a statement that has to be true, is provable, given the initial rules of geometry (the axioms).

Those are how the words are used in mathematics alone and in science they are sometimes used very differently. One important thing to understand is that science does not deal with theorems, scientific theories don't prove theorems. This is because science relies on inductive and abductive reasoning to learn about the world through empirical observation. A scientific theory is a general description of the world that is testable and has withstood repeated testing. In this way, they're usually made up out of scientific laws .

Scott Aaronson , a quantum information scientist who works on both fields, has highlighted the differences in the terminology on multiple occasions:

"I've learned from working in quantum information that there's a difference in terminology between fields. What mathematicians and computer scientists call a conjecture is typically what physicists would call a law." "I think my word is 'theorem'. It's something that you say is true and then you explain why it's true and then you put a box."

The context for the second quote is that Leonard Susskind asked Aaronson to explain a word from his mathematical background that people with a physics background might not understand or use in the same way. The reason everyone laughed is because the other physicists and computer scientists in the room understood how tongue in cheek Aaronson's pick for the word was: physics doesn't deal with theorems, in a mathematical sense, it deals with conjectures. That's why Susskind sarcastically says "A theorem, what's that?" And of course the "box" comment is a reference to what's put at the end of a proof of a theorem .

Ultimately, theorems are things that are deductively proven and as such exist in mathematics and logic. Theorems are used in science as well, you can use the Pythagorean theorem to help you solve a mechanics problem, but science doesn't prove theorems. Science tries to create theoretical models that help explain physical phenomena and those models can always be revised via new information. So if you are trying to apply the word theorem to a physical theory you are going to fail, the only parts of the physical theory that are theorems are the purely mathematical parts.

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Thesis vs Hypothesis vs Theory: the Differences and examples

thesis hypothesis and theory

Many students may have a hard time understanding the differences between a thesis, a hypothesis, and a theory. It is important to understand their differences. Such an understanding will be instrumental.

More so, when writing complex research papers that require a thesis that has a hypothesis and utilizes theories. We have gathered from responses of our college writing service that the difference between the three is confusing.

That being said, this article is meant to explain the differences between a thesis, a hypothesis, and a theory. 

Difference between Hypothesis and Thesis

There are major differences between hypothesis and thesis. While they seem to be related on the face, their differences are huge both in concept and practice.

A hypothesis is a proposed explanation of something or a phenomenon. A scientific hypothesis uses a scientific method that requires any hypothesis to be tested. As such, scientists and researchers base their hypothesis on observations that have been previously made and that which cannot be explained by the available or prevailing scientific theories.

From the definition of a hypothesis, you can see that theories must be included in any scientific method. This is the reason why this article tries to differentiate a thesis, a hypothesis, and a theory. 

Moving forward, a thesis can be defined as a written piece of academic work that is submitted by students to attain a university degree. However, on a smaller scale, there is something that is referred to as a thesis statement.

This is written at the introduction of a research paper or essay that is supported by a credible argument. The link between a hypothesis and thesis is that a thesis is a distinction or an affirmation of the hypothesis.

What this means is that whenever a research paper contains a hypothesis, there should be a thesis that validates it. 

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What is a Hypothesis?

A hypothesis can be defined as the proposed or suggested explanation for an occurrence, something, or a phenomenon. It should be testable through scientific methods. The reason why scholarly works should have a hypothesis is that the observed phenomena could not be explained using the prevailing scientific theories hence the reason why it should be tested. 

Testing the hypothesis may result in the development of new or improved scientific theories that are beneficial to the discipline and society in general. 

What is a Thesis?

A thesis is a written piece of academic work that is submitted by students to attain a university degree. When a thesis is used as a stand-alone word, it denotes academic papers written by university students. It is mostly written by those pursuing postgraduate degrees, at the end of their courses. They demonstrate their proficiency in their disciplines and the topics they have selected for research. 

However, when a thesis is used to refer to a statement, it denotes the statement that is written at the introduction of a research paper or essay. A thesis is supported by a credible argument.

Every research paper must have a thesis statement that acts as a guide to what the research will be all about. It is possible to receive very poor grades or even score a zero if your research paper lacks the thesis statement. 

What is a Theory?

A theory can be defined as a rational form of abstract perspectives or thinking concerning the results of such thinking or a phenomenon. The process of rational and contemplative thinking is mostly associated with processes such as research or observational study.

As such, a theory can be considered to belong to both scientific and non-scientific disciplines. Theories can also belong to no discipline.

From a modernistic scientific approach, a theory can mean scientific theories that have been well confirmed to explain nature and that are created in such a way that they are consistent with the standard scientific method. A theory should fulfill all the criteria required by modern-day science. 

A theory should be described in a way that scientific tests that have been conducted can provide empirical support or contradiction to the theory.

Because of the nature by which scientific theories are developed, they tend to be the most rigorous, reliable, and comprehensive when it comes to describing and supporting scientific knowledge. 

The connection between a theory and a hypothesis is that when a theory has not yet been proven, it can be referred to as a hypothesis.

The thing about theories is that they are not meant to help the scientist or researcher reach a particular goal. Rather, a theory is meant to guide the process of finding facts about a phenomenon or an observation. 

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Difference between a Theory and Thesis

A theory is a rational form of abstract perspectives or thinking concerning the results of such thinking or a phenomenon. The process of rational and contemplative thinking is mostly associated with processes such as research or observational study. On the other hand, a thesis is a written piece of academic work that is submitted by students to attain a university degree.

It denotes academic papers that are written by students in the university, especially those pursuing postgraduate degrees, at the end of their courses to demonstrate their proficiency in their disciplines and the topics they have selected for research. 

To understand the application of these, read our guide on the difference between a research paper and a thesis proposal to get a wider view.

How to write a Good Hypothesis

1. asking a question.

Asking a question is the first step in the scientific method and the question should be based on  who, what, where, when, why,  and  how . The question should be focused, specific, and researchable.

2. Gathering preliminary research 

This is the process of collecting relevant data. It can be done by researching academic journals, conducting case studies, observing phenomena, and conducting experiments. 

3. Formulating an answer

When the research is completed, you should think of how best to answer the question and defend your position. The answer to your question should be objective. 

4. Writing the hypothesis

When your answer is ready, you can move to the next step of formulating the hypothesis. A good hypothesis should contain relevant variables, predicted outcomes, and a study group that can include non-human things. The hypothesis should not be a question but a complete statement. 

5. Refining the hypothesis

Though you may skip this step, it is advisable to include it because your study may involve two groups or be a correlational study. Refining the hypothesis will ensure that you have stated the difference or relationship you expect to find. 

6. Creating a null and alternative hypotheses

A null hypothesis (H0) will postulate that there is no evidence to support the difference. On the other hand, an alternative hypothesis (H1) posits that there is evidence in support of the difference. 

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Frequently Asked Questions

Difference between thesis and hypothesis example.

Thesis:  High levels of alcohol consumption have detrimental effects on your health, such as weight gain, heart disease, and liver complications.

Hypothesis:  The people who consume high levels of alcohol experience detrimental effects on their health such as weight gain, heart disease, and liver complications. 

What is the difference between a summary and a thesis statement?

A summary is a brief account or statement of the main points from the researches. A thesis statement is a statement that is written at the end of the introduction of a research paper or essay that summarizes the main claims of the paper. 

Difference between hypothesis and statement of the problem

A hypothesis can be defined as the proposed or suggested explanation for an occurrence, something, or a phenomenon. The same should be testable through scientific methods. Conversely, a statement of a problem is a concise description of the issue to be addressed on how it can be improved. 

When not handling complex essays and academic writing tasks, Josh is busy advising students on how to pass assignments. In spare time, he loves playing football or walking with his dog around the park.

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“Theory” vs. “Hypothesis”: What Is The Difference?

Chances are you’ve heard of the TV show The Big Bang Theory . Lots of people love this lighthearted sitcom for its quirky characters and their relationships, but others haven’t even given the series a chance for one reason: they don’t like science and assume the show is boring.

However, it only takes a few seconds with Sheldon and Penny to disprove this assumption and realize that this theory ab0ut The Big Bang Theory is wrong—it isn’t a scientific snoozefest.

But wait: is it a theory or a  hypothesis about the show that leads people astray? And would the actual big bang theory— the one that refers to the beginning of the universe—mean the same thing as a big bang hypothesis ?

Let’s take a closer look at theory and hypothesis to nail down what they mean.

What does theory mean?

As a noun, a theory is a group of tested general propositions “commonly regarded as correct, that can be used as principles of explanation and prediction for a class of phenomena .” This is what is known as a scientific   theory , which by definition is “an understanding that is based on already tested data or results .” Einstein’s theory of relativity and the  theory of evolution are both examples of such tested propositions .

Theory is also defined as a proposed explanation you might make about your own life and observations, and it’s one “whose status is still conjectural and subject to experimentation .” For example:  I’ve got my own theories about why he’s missing his deadlines all the time.  This example refers to an idea that has not yet been proven.

There are other uses of the word theory as well.

• In this example,  theory is “a body of principles or theorems belonging to one subject.” It can be a branch of science or art that deals with its principles or methods .
• For example: when she started to follow a new parenting theory based on a trendy book, it caused a conflict with her mother, who kept offering differing opinions .

First recorded in 1590–1600, theory originates from the Late Latin theōria , which stems from the Greek theōría. Synonyms for theory include approach , assumption , doctrine , ideology , method , philosophy , speculation , thesis , and understanding .

What does hypothesis mean?

Hypothesis is a noun that means “a proposition , or set of propositions, set forth as an explanation” that describe “some specified group of phenomena.” Sounds familiar to theory , no?

But, unlike a theory , a scientific  hypothesis is made before testing is done and isn’t based on results. Instead, it is the basis for further investigation . For example: her working hypothesis is that this new drug also has an unintended effect on the heart, and she is curious what the clinical trials  will show .

Hypothesis also refers to “a proposition assumed as a premise in an argument,” or “mere assumption or guess.” For example:

• She decided to drink more water for a week to test out her hypothesis that dehydration was causing her terrible headaches.
• After a night of her spouse’s maddening snoring, she came up with the hypothesis that sleeping on his back was exacerbating the problem.

Hypothesis was first recorded around 1590–1600 and originates from the Greek word hypóthesis (“basis, supposition”). Synonyms for hypothesis include: assumption , conclusion , conjecture , guess , inference , premise , theorem , and thesis .

How to use each

Although theory in terms of science is used to express something based on extensive research and experimentation, typically in everyday life, theory is used more casually to express an educated guess.

So in casual language,  theory and hypothesis are more likely to be used interchangeably to express an idea or speculation .

In most everyday uses, theory and hypothesis convey the same meaning. For example:

• Her opinion is just a theory , of course. She’s just guessing.
• Her opinion is just a hypothesis , of course. She’s just guessing.

It’s important to remember that a scientific   theory is different. It is based on tested results that support or substantiate it, whereas a hypothesis is formed before the research.

For example:

• His  hypothesis  for the class science project is that this brand of plant food is better than the rest for helping grass grow.
• After testing his hypothesis , he developed a new theory based on the experiment results: plant food B is actually more effective than plant food A in helping grass grow.

In these examples, theory “doesn’t mean a hunch or a guess,” according to Kenneth R. Miller, a cell biologist at Brown University. “A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

So if you have a concept that is based on substantiated research, it’s a theory .

But if you’re working off of an assumption that you still need to test, it’s a hypothesis .

So remember, first comes a hypothesis , then comes theory . Now who’s ready for a  Big Bang Theory marathon?

Now that you’ve theorized and hypothesized through this whole article … keep testing your judgment (Or is it judgement?). Find out the correct spelling here!

Or find out the difference between these two common issues below!

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Home > Blog > Tips for Online Students > Dissertation vs Thesis: The Differences that Matter

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Dissertation vs Thesis: The Differences that Matter

Updated: June 19, 2024

Published: April 26, 2020

As a graduate student, you will have many different types of challenging coursework and assignments. However, the biggest project that you’ll work on when earning your master’s or doctoral degree will be your thesis or dissertation . The differences between a dissertation vs thesis are plenty. That’s because each of these pieces of writing happen at different times in one’s educational journey.

Let’s break down what a dissertation and thesis are so that you have a strong handle on what’s expected. For both a thesis and a dissertation, there is an obvious fluency and understanding of the subject one studies.

Let’s take a look at their similarities and differences.

Photo by  Glenn Carstens-Peters  on  Unsplash

What is a dissertation.

When you enter a doctoral program to earn a PhD, you will learn a lot about how to conduct your own research. At the culmination of your degree program, you’ll produce a dissertation.

A dissertation is a lengthy piece of written work that includes original research or expanded research on a new or existing topic. As the doctoral student, you get to choose what you want to explore and write about within your field of study.

What is a Thesis?

A thesis is also a scholarly piece of writing, but it is for those who are graduating from a master’s program. A thesis allows students to showcase their knowledge and expertise within the subject matter they have been studying.

Main Differences Between a Thesis vs. Dissertation

The biggest difference between a thesis and a dissertation is that a thesis is based on existing research.

On the other hand, a dissertation will more than likely require the doctoral student to conduct their own research and then perform analysis. The other big difference is that a thesis is for master’s students and the dissertation is for PhD students.

Structural Differences Between a Thesis and a Dissertation

Structurally, the two pieces of written analysis have many differences.

• A thesis is at least 100 pages in length
• A dissertation is 2-3x that in length
• A thesis expands upon and analyzes existing research
• A dissertation’s content is mostly attributed to the student as the author

Research Content and Oral Presentation

Once completed, some programs require students to orally present their thesis and dissertation to a panel of faculty members.

Typically, a dissertation oral presentation can take several hours. On the other hand, a thesis only takes about an hour to present and answer questions.

Let’s look at how the two scholarly works are similar and different:

Similarities:

• Each is considered a final project and required to graduate
• Both require immense understanding of the material
• Written skills are key to complete both
• Neither can be plagiarized
• Both are used to defend an argument
• Both require analytical skills
• You will have to draft, rewrite, and edit both pieces of writing
• For both, it is useful to have another person look over before submission
• Both papers are given deadlines

Differences:

• A dissertation is longer than a thesis
• A dissertation requires new research
• A dissertation requires a hypothesis that is then proven
• A thesis chooses a stance on an existing idea and defends it with analysis
• A dissertation has a longer oral presentation component

The Differences in Context: Location Matters

The united states.

In the US, everything that was previously listed is how schools differentiate between a thesis and a dissertation. A thesis is performed by master’s students, and a dissertation is written by PhD candidates.

In Europe, the distinction between a thesis and dissertation becomes a little more cloudy. That’s because PhD programs may require a doctoral thesis to graduate. Then, as a part of a broader post-graduate research project, students may complete a dissertation.

Photo by  Russ Ward  on  Unsplash

The purpose behind written research.

Each piece of writing is an opportunity for a student to demonstrate his or her ability to think critically, express their opinions in writing, and present their findings in front of their department.

Graduate degrees take a lot of time, energy, and hard work to complete. When it comes to writing such lengthy and informative pieces, there is a lot of time management that is involved. The purpose of both a thesis and a dissertation are written proof that you understand and have mastered the subject matter of your degree.

Degree Types

A doctoral degree, or PhD, is the highest degree that one can earn. In most cases, students follow the following path to achieve this level of education: Earn a bachelor’s degree, then a master’s, and then a PhD. While not every job title requires this deep educational knowledge, the salaries that come along with each level of higher education increase accordingly.

Earning Your Degree

Whether you are currently a prospective student considering earning your higher education degree or a student enrolled in a master’s or doctoral program, you know the benefits of education.

However, for some, earning a traditional degree on-campus doesn’t make sense. This could be because of the financial challenges, familial obligations, accessibility, or any other number of reasons.

For students who are seeking their higher education degrees but need a flexible, affordable, and quality alternative to traditional college, take a look at the programs that the University of the People has to offer.

University of the People is an entirely online, US accredited and tuition-free institution dedicated to higher education. You can earn your Master’s in Business Administration or your Master’s in Education . Not to mention, there are a handful of associate’s and bachelor’s degree programs to choose from as well.

If you want to learn more, get in touch with us !

The Bottom Line

Regardless of where and when you earn your master’s or doctoral degree, you will likely have to complete a thesis or dissertation. The main difference between a thesis and dissertation is the level at which you complete them. A thesis is for a master’s degree, and a dissertation is for a doctoral degree.

Don’t be overwhelmed by the prospect of having to research and write so much. Your educational journey has prepared you with the right time management skills and writing skills to make this feat achievable!

In this article

At UoPeople, our blog writers are thinkers, researchers, and experts dedicated to curating articles relevant to our mission: making higher education accessible to everyone. Read More

This is the Difference Between a Hypothesis and a Theory

What to Know A hypothesis is an assumption made before any research has been done. It is formed so that it can be tested to see if it might be true. A theory is a principle formed to explain the things already shown in data. Because of the rigors of experiment and control, it is much more likely that a theory will be true than a hypothesis.

As anyone who has worked in a laboratory or out in the field can tell you, science is about process: that of observing, making inferences about those observations, and then performing tests to see if the truth value of those inferences holds up. The scientific method is designed to be a rigorous procedure for acquiring knowledge about the world around us.

In scientific reasoning, a hypothesis is constructed before any applicable research has been done. A theory, on the other hand, is supported by evidence: it's a principle formed as an attempt to explain things that have already been substantiated by data.

Toward that end, science employs a particular vocabulary for describing how ideas are proposed, tested, and supported or disproven. And that's where we see the difference between a hypothesis and a theory .

A hypothesis is an assumption, something proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

What is a Hypothesis?

A hypothesis is usually tentative, an assumption or suggestion made strictly for the objective of being tested.

When a character which has been lost in a breed, reappears after a great number of generations, the most probable hypothesis is, not that the offspring suddenly takes after an ancestor some hundred generations distant, but that in each successive generation there has been a tendency to reproduce the character in question, which at last, under unknown favourable conditions, gains an ascendancy. Charles Darwin, On the Origin of Species , 1859 According to one widely reported hypothesis , cell-phone transmissions were disrupting the bees' navigational abilities. (Few experts took the cell-phone conjecture seriously; as one scientist said to me, "If that were the case, Dave Hackenberg's hives would have been dead a long time ago.") Elizabeth Kolbert, The New Yorker , 6 Aug. 2007

What is a Theory?

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, its likelihood as truth is much higher than that of a hypothesis.

It is evident, on our theory , that coasts merely fringed by reefs cannot have subsided to any perceptible amount; and therefore they must, since the growth of their corals, either have remained stationary or have been upheaved. Now, it is remarkable how generally it can be shown, by the presence of upraised organic remains, that the fringed islands have been elevated: and so far, this is indirect evidence in favour of our theory . Charles Darwin, The Voyage of the Beagle , 1839 An example of a fundamental principle in physics, first proposed by Galileo in 1632 and extended by Einstein in 1905, is the following: All observers traveling at constant velocity relative to one another, should witness identical laws of nature. From this principle, Einstein derived his theory of special relativity. Alan Lightman, Harper's , December 2011

Non-Scientific Use

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch (though theory is more common in this regard):

The theory of the teacher with all these immigrant kids was that if you spoke English loudly enough they would eventually understand. E. L. Doctorow, Loon Lake , 1979 Chicago is famous for asking questions for which there can be no boilerplate answers. Example: given the probability that the federal tax code, nondairy creamer, Dennis Rodman and the art of mime all came from outer space, name something else that has extraterrestrial origins and defend your hypothesis . John McCormick, Newsweek , 5 Apr. 1999 In his mind's eye, Miller saw his case suddenly taking form: Richard Bailey had Helen Brach killed because she was threatening to sue him over the horses she had purchased. It was, he realized, only a theory , but it was one he felt certain he could, in time, prove. Full of urgency, a man with a mission now that he had a hypothesis to guide him, he issued new orders to his troops: Find out everything you can about Richard Bailey and his crowd. Howard Blum, Vanity Fair , January 1995

And sometimes one term is used as a genus, or a means for defining the other:

Laplace's popular version of his astronomy, the Système du monde , was famous for introducing what came to be known as the nebular hypothesis , the theory that the solar system was formed by the condensation, through gradual cooling, of the gaseous atmosphere (the nebulae) surrounding the sun. Louis Menand, The Metaphysical Club , 2001 Researchers use this information to support the gateway drug theory — the hypothesis that using one intoxicating substance leads to future use of another. Jordy Byrd, The Pacific Northwest Inlander , 6 May 2015 Fox, the business and economics columnist for Time magazine, tells the story of the professors who enabled those abuses under the banner of the financial theory known as the efficient market hypothesis . Paul Krugman, The New York Times Book Review , 9 Aug. 2009

Incorrect Interpretations of "Theory"

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general use to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

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Revaluating the Sustainable Development Thesis: exploring the moderating influence of Technological Innovation on the impact of Foreign Direct Investment (FDI) on Green Growth in the OECD Countries

• Open access
• Published: 10 September 2024
• Volume 5 , article number  252 , ( 2024 )

Cite this article

You have full access to this open access article

• Germain Stephane Ketchoua 1 ,
• Sodiq Arogundade 1 &
• Biyase Mduduzi 1  

The Sustainable Development Goals (SDGs) advocate for advancing green growth, a concept that balances economic prosperity with environmental protection. At the core of this vision are principles of sustainable consumption, production, and energy usage, all aimed at mitigating climate change and safeguarding ecosystems. This study investigates how technological innovation influences the relationship between Foreign Direct Investment (FDI) and green growth in OECD member countries. Specifically, we examine two facets of green growth: production-based CO 2 productivity and demand-based CO 2 productivity. We employ empirical analyses using the EKC and STIRPAT framework, which includes Ordinary Least Squares (OLS), smoothed instrumental-variables quantile regression (SIVQR), and System GMM methodologies, to uncover significant insights. Our analysis reveals that FDI impedes green growth, while technological innovation is pivotal in enhancing it. This pattern holds steady across various time frames and renewable energy sources. Furthermore, our findings indicate that combining FDI and technological advancement leads to heightened production-based CO 2 productivity but diminished demand-based CO 2 productivity. We also identify the presence of an environmental Kuznets curve for production-based CO 2 productivity. Adding to significant scientific value by demonstrating how technological innovation moderates FDI's impact on green growth in OECD countries, we advocate for fostering collaborative partnerships between foreign investors and local innovators to leverage global expertise while advancing green objectives. Additionally, policy interventions should focus on stimulating demand for eco-friendly products and services to bolster demand-based CO 2 productivity.

Avoid common mistakes on your manuscript.

1 Introduction

Economists and environmentalists have long been aware that the current economic growth path places immense strain on the natural environment, thereby threatening long-run economic development. Debates on the unintended consequences of pursuing growth at all costs have underscored the need to consider a growth path that signifies resilience, inclusivity, and sustainability as a critical policy imperative. There is a view that green growth is one of the key strategies that policymakers can use to stimulate the economy and achieve climate objectives simultaneously. The Organisation for Economic Co-operation and Development (OECD) defines green growth as fostering economic growth and development while ensuring that natural assets continue to provide the resources and environmental services essential to our well-being [ 1 ].

Moreover, the relevance of green growth is deeply embedded in the Sustainable Development Goals (SDGs), which promote a balance between economic prosperity and environmental protection [ 2 , 3 , 4 ]. Aligning green growth with the SDGs can provide a roadmap for sustainable economic development, ensuring that investments and policies contribute to long-term environmental sustainability. Despite the growing global emphasis on green growth, the impact of economic growth and Foreign Direct Investment (FDI) on achieving this objective remains a contentious issue. Designing effective policies for green growth requires a nuanced understanding of the key factors influencing this growth, with economic growth and FDI being significant factors. Economic growth has long been a double-edged sword for environmental quality. On one hand, it can provide the necessary resources for investing in cleaner technologies and improving environmental standards.

On the other hand, unchecked economic expansion often leads to increased resource consumption, higher emissions, and greater environmental degradation [ 5 , 6 ]. The relationship between economic growth and environmental quality is complex and varies across different contexts. In many cases, economic growth initially leads to environmental deterioration. Still, as economies mature, there is a shift towards more sustainable practices, a concept known as the Environmental Kuznets Curve (EKC) [ 7 , 8 ]. Understanding this dynamic is crucial for policymakers aiming to balance economic development with environmental sustainability. This study explores this intricate balance, particularly how technological innovation moderates the effect of Foreign Direct Investment (FDI) on green growth in OECD countries.

The novelty of this paper is evident through its exploration of the moderating influence of technological innovation on the impact of FDI on green growth, which is a gap in the current literature. By examining both production-based and demand-based CO 2 productivity, the study provides a comprehensive understanding of green growth dynamics. Employing advanced methodologies like smoothed instrumental-variables quantile regression (SIVQR) and System GMM offers new empirical insights, contributing significantly to the existing body of knowledge. Peer review documents suggest that technological innovation is pivotal in enhancing eco-efficiency and promoting green growth, playing a dual role in mitigating environmental degradation while simultaneously driving economic progress. For instance, Wang et al. [ 9 ] and Zhang & Zhou [ 10 ] argue that aligning foreign investment with the host economy's technological capabilities can significantly reduce CO 2 emissions.

Similarly, studies by Bakhsh [ 11 ], Radmehr et al. [ 12 ] and Zhao et al. [ 13 ]emphasize that technological innovation can transform investment into a catalyst for green growth, particularly in regions with robust innovation ecosystems. These technological advancements foster the adoption of cleaner practices, contributing to production and demand-based CO 2 productivity. Consequently, understanding the role of technological innovation is crucial for devising policies that leverage FDI for sustainable development.

The ongoing surge of FDI in OECD economies has ignited debates about its environmental ramifications. Theoretical literature presents conflicting viewpoints on the correlation between FDI and environmental pollution. On one hand, it is argued that FDI influx into countries with lax environmental regulations may exacerbate ecological degradation. This perspective aligns with the pollution haven hypothesis (PHH) first proposed by Brian et al. [ 14 ], suggesting that globalization allows firms from countries with strict environmental standards to relocate their polluting activities to countries with less stringent regulations. Conversely, an opposing perspective emphasizes that FDI fosters technological advancements within host countries, thereby improving environmental conditions [ 15 , 16 ]. Understanding these conflicting views is essential for developing policies that leverage FDI to support green growth without compromising environmental integrity.

In this context, technological innovation improves the eco-efficiency of Foreign Direct Investment (FDI) and instigates structural transformations within industries, influencing their environmental impact. Also, technological spillovers from foreign firms can catalyze domestic innovation capabilities, creating a positive cycle of green technological advancement. However, the extent to which technological innovation mitigates the impact of FDI on the environment and promotes green growth varies among OECD sub-regions due to contextual differences in regulatory frameworks, market structures, and technological capabilities. For example, in regions with stringent eco-role and robust innovation ecosystems, FDI inflows may catalyze the adoption of cleaner technologies and practices, thereby promoting green growth. Conversely, FDI might result in heightened pollution levels and environmental degradation in areas characterized by lenient environmental standards and limited technological capacities.

The relationship between technological innovation, foreign direct investment (FDI), and the green economy, particularly within OECD countries, is not extensively covered in existing literature. This gap is crucial because technological innovation can mitigate or exacerbate the environmental impacts of FDI, depending on the context. In addition, the United Nations Sustainable Development Goals (SDGs) provide a comprehensive framework for achieving sustainable development globally. This study aligns with several SDGs, particularly SDG 9 (Industry, Innovation, and Infrastructure), SDG 13 (Climate Action), and SDG 17 (Partnerships for the Goals). Consequently, by examining how technological innovation shapes the influence of FDI on green growth in the OECD sub-region, this research enhances our understanding of how economic activities can support sustainable development. Specifically, we examine two dimensions of green growth: production-based CO 2 productivity and demand-based CO 2 productivity. To gain meaningful insights into these dynamics, we utilize a range of methodologies.

This research uniquely contributes to environmental economics literature, offering numerous implications and far-reaching impacts. It breaks new ground by investigating the effects of FDI on green growth within OECD member countries. By exploring this relationship using two measures of green growth—production-based CO 2 productivity and demand-based CO 2 productivity—the study provides a comprehensive understanding of the dynamics of carbon emissions. Production-based metrics focus on emissions generated within a country's borders, while demand-based metrics consider emissions embedded in goods and services consumed domestically. Integrating both perspectives enables a holistic assessment of a nation's carbon footprint, facilitating the development of targeted policies addressing production, consumption, and trade-related emissions to mitigate climate change and promote sustainable development effectively.

Additionally, by acknowledging the role of countries' development, the study employs SIVQR (Semi-Parametric Instrumental Variable Quantile Regression) to investigate the nexus across different development levels. This approach provides nuanced insights into varying stages of development, enhancing our understanding of how economic policies and growth trajectories differ globally. Consequently, this method improves the robustness and applicability of the findings across diverse economic contexts. Moreover, the study examines how technological innovation influences the relationship between FDI and green growth. On one hand, this investigation sheds light on whether technological advancements can offset the potential negative environmental impacts of FDI and promote sustainable development.

On the other hand, it provides insights into the dynamics of green growth, informing policymakers on how to leverage FDI and innovation synergies to achieve environmentally sustainable economic growth. Lastly, accounting for time differences in examining this relationship enriches the literature by capturing the dynamic and evolving nature of these relationships. This approach reveals how the impact of FDI on sustainable development changes over time, identifies lag effects, and highlights long-term trends. It enhances the understanding of temporal factors influencing green growth, offering more nuanced and policy-relevant insights into the economic-environmental interplay.

The remainder of the paper unfolds as follows: Sect.  2 provides a concise literature review, followed by Sect.  3 , which outlines the data and methodology utilized. Section  4 delves into the findings, and Sect. 5 offers concluding remarks.

2 Literature review

This section examined the theoretical and empirical literature on the nexus between FDI and the green economy. Several hypotheses and accounts on the nexus between FDI and environmental quality have been established in the literature. The nature of the relationship between the two variables can be summarised into two hypotheses called the pollution halo and pollution heaven hypothesis. The proponent of the pollution haven hypothesis asserts that foreign investors essentially take advantage of loosened environmental-related rules in these developing countries by bringing pollution-intensive production units [ 17 ]. Supporters of this view, such as Anyanwu [ 18 ], also identified factors such as cheap labour and abundant natural resources as the drivers of this process.

However, some scholars have identified a different perspective, named the pollution halo hypothesis. Followers of this view argue that multinational corporations employ clean technologies in their production processes, thereby contributing to a clean environment [ 19 ]. Furthermore, proponents of this viewpoint also emphasize that introducing clean technology has the dual benefits of improving the environment in the host nation and generating jobs through the transferring or linkage effect [ 20 ].

Although the perspective of these theories is explanatory and convincing, most scholars do not generally accept their adequacy. The empirical literature on the nexus between FDI and the environment makes the heterogeneity of opinions more apparent. Empirical studies have produced inconsistent results, with a considerable number of studies indicating a positive relationship and a few indicating a negative impact [ 21 ]. Some studies argue that the nature of the relationship is characterized by nonlinear or inverted U-shaped patterns, supporting the Environmental Kuznets Curve (EKC) theory.

A good portion of this empirical research, primarily from developing countries, accepts the pollution haven theory. For instance, using the quantile model, Chowdhury et al. [ 22 ] accepted the pollution haven hypothesis and argued that FDI positively and significantly impacts the environmental quality of 92 countries. In the same vein, Sabir et al. [ 23 ] used the panel autoregressive distributed lag (ARDL) method to examine the short-run and long-run impact of FDI on the environment in a sample of South Asian countries; the study discovered that FDI increases environmental degradation of the countries. Balsalobre-Lorente et al. [ 24 ] found similar results, stating that FDI improves air quality as multinational corporations bring cleaner and more efficient technology capable of reducing energy consumption. Similarly, empirical outcomes were observed for Udemba [ 25 ] for Turkey, Solarin et al. [ 26 ] for Ghana, and Ahmed et al. [ 27 ] for a sample of Asia–Pacific countries. Shahbaz et al. [ 28 ] examined the impact of FDI, financial development and energy innovations on environmental degradation in France. Using a Fourier ARDL model, the study discovers that FDI deteriorates environmental quality, thereby attesting to the pollution-haven hypothesis.

However, a couple of empirical papers support the pollution halo hypothesis. For instance, Tang and Tan [ 17 ] analyzed the relationship between C0 2 emission, energy consumption, FDI and economic growth in Vietnam. The study confirms the existence of the pollution halo hypothesis, i.e., FDI improves environmental quality in Vietnam. Similarly, Al-Mulali and Tang [ 19 ] investigated the validity of the pollution haven hypothesis in the Gulf Cooperation Council (GCC) countries using Fully Modified OLS. The results suggest that foreign direct investment inflows have a long-run negative relationship with CO 2 emission. Similar empirical outcomes were observed for Kirkulak et al. [ 29 ] and Tamazian and Rao [ 30 ]. Caglar et al. [ 31 ] also examine the impact of economic growth, trade openness, renewable energy, human capital, and competitive industrial performance on the load capacity factor for EU countries. Using the CUP-FM and CUP-BC methodologies that address heterogeneity and cross-sectional dependence, the study lends credence to the pollution haven hypothesis and argues that economic growth, trade openness, and competitiveness worsen environmental quality. In Turkiye, Yavuz et al. [ 32 ] also discovered that gross domestic product, natural resource rents, and primary energy consumption accelerate environmental degradation using the newly developed Augmented Autoregressive Distributed Lag (A-ARDL) with Fourier term.

Some studies support the environmental Kuznets curve (EKC) hypothesis despite the evidence supporting the pollution haven and pollution halo hypotheses. According to these studies, environmental degradation occurs when economic growth occurs (through FDI), and a cleaner environment cannot be attained until FDI reaches an appropriate level. For example, Destek and Okumus [ 33 ] used second-generation panel data analysis on newly industrialized countries. The findings reveal that FDI has a U-shaped relationship with the ecological footprint. Similarly, Sapkota and Bastola [ 34 ] investigated the effect of FDI on pollution emissions in Latin American countries using a fixed-effect model. The study validated the EKC hypothesis. Studies such as Shahbaz et al. [ 28 ] and Doytch and Uctum [ 35 ] also conclude that FDI and environmental quality have an inverted U-shape relationship.

Furthermore, some studies have begun to examine the role of intermittent variables on the impact of FDI on the environment. Starting with the study by Caetano et al. [ 36 ] which analyzed how the energy transition mediates the role of FDI in the green economy. The study concludes that energy transition modulates the impact of FDI on the green economy. Qamri et al. [ 37 ] also examined the role of financial development and economic growth on the impact of FDI on the green sector of 21 Asian countries. Using a panel econometric method, the study discovers that economic growth and financial development mediate the positive impact of FDI on the green economy. Padhan and Bhat [ 38 ] examined the link between FDI and the environmental quality of BRICS and NEXT-11 using green innovation as an intermittent variable. Using a Driscoll–Kraay (DK) standard error model, the study reveals that green innovation modulated the negative impact of FDI on the environment, indicating that the presence of green innovation and FDI proves the existence of the pollution halo hypothesis. Ofori et al. [ 39 ] examined how energy efficiency mediates the impact of FDI on inclusive green growth in Africa. Using a dynamic GMM estimator, the study discovers that energy efficiency reduces the deteriorating impact of FDI on inclusive green economic growth.

While the literature is replete with unremitting debate on the link between FDI and the green economy, there is limited literature on the role of technological innovation on the impact of FDI on the green economy. This study contributes to the extant literature by (1) examining the impact of FDI on the green economy in OECD countries and (2) investigating the role of technological innovation on the nexus between FDI and the green economy.

3 Methodology

The study's analysis relies on a dataset comprising 37 OECD countries Footnote 1 spanning the years 1995 to 2021. The countries were chosen based on the availability of data during the study period. The OECD countries are typically regarded as advanced economies characterized by high-income levels, stable institutions, and robust statistical systems. This makes them an ideal representative sample for studying economic, social, and environmental trends in developed nations. While the period under consideration includes various economic cycles—growth, recession, and recovery—and encompasses significant policy changes in areas such as globalization, trade, fiscal policy, and social policy. This provides a valuable context for examining long-term trends and assessing the impact of economic cycles and policy shifts on different variables.

The data for green growth, Solar thermal energy, Wind energy, and technological innovation are drawn from the OECD database. The data for globalization is obtained from the KOF Swiss Economic Institute database. The remaining data utilized in the study was obtained from the World Bank's World Development Indicators. Table 1 presents the variables' characteristics in terms of mean, standard deviation, minimum, and maximum values, while Table  2 illustrates the correlations among the variables.

3.2 Justification of variables

3.2.1 dependent variable.

Our dependent variable of interest is the green growth proxy by production-based CO 2 productivity, and demand-based CO 2 productivity aligns with SDG indicators for climate action and sustainable consumption and production patterns. Production-based CO 2 productivity is determined by measuring the real GDP generated per unit of CO 2 emitted (expressed in USD/kg). This includes emissions from the combustion of coal, oil, natural gas, and other fuels. On the other hand, demand-based CO 2 productivity reflects the CO 2 emissions from energy use throughout the diverse stages of producing goods and services consumed within domestic final demand, regardless of where these production stages occurred. Both measures provide insights into the sustainability and environmental impact of economic growth. Appendices 3 and 4 show the production-based and demand-based CO 2 productivity across the OECD countries.

3.2.2 Independent variables

The independent variable of the study is foreign direct investment (FDI). Foreign Direct Investment (FDI) involves investment in a business by an entity from another country, facilitating capital flow and technology transfer. FDI can influence green growth positively by introducing sustainable technologies, enhancing environmental standards, and promoting renewable energy [ 2 , 3 ]. Additionally, it can stimulate economic development, leading to increased demand for green products and services. However, without proper regulations, FDI might also exacerbate environmental degradation due to relaxed environmental standards or exploitation of natural resources.

Figure  1 presents the trend of FDI, while Fig.  2 presents a correlation analysis between FDI and green growth proxy by production-based CO 2 productivity (PP) and demand-based CO 2 productivity (DP) in the OECD countries. The correlation analysis serves as preliminary findings on the nature of the relationship between FDI and green growth. The scatter plot indicates a positive effect of FDI on production-based CO 2 productivity (PP) and demand-based CO 2 productivity. The findings on the nature of this relationship are further experimented with using the instrumental quantile regression that accounts for initial levels of FDI and also addresses potential endogeneity.

Source: Authors’ computation from WDI database

The trend of FDI in the OECD countries.

Source: Authors’ computation

The correlation between FDI and green growth.

3.2.3 The moderating variable

The moderating variable of the study is technological innovation to assess progress toward SDG 9. Technological innovation refers to the development of new or improved technologies, processes, or products that enhance efficiency, productivity, or functionality [ 13 , 40 ]. In the context of green growth, technological innovation plays a pivotal role by enabling the creation of sustainable solutions. Advancements in green technology, waste management, and resource-efficient technologies mitigate environmental impact, reduce carbon emissions, and promote eco-friendly practices [ 41 , 42 ]. Such innovations drive economic growth while preserving natural resources, fostering a greener and more sustainable future. The study uses patents as a proxy for technological innovation. Figure  3 shows the evolution of technology innovation in the OECD countries.

Source: Authors’ computation from the OECD database

The trend of technology innovation in the OECD countries.

3.2.4 Control variables

The selection of the control variables is based on the environmental sustainability literature. First, GDP per capita, a measure of economic output per person, affects environmental sustainability from its reliance on resource consumption and production. High GDP often correlates with increased resource extraction, energy use, and waste generation, contributing to environmental degradation and climate change [ 5 ]. Second, renewable energy consumption (% of total final energy consumption) promotes environmental sustainability by reducing greenhouse gas emissions, mitigating air and water pollution, and minimizing dependence on finite fossil fuel resources. It contributes to climate change mitigation and fosters a transition towards cleaner, more sustainable energy systems, thereby preserving ecosystems and enhancing the planet's health. Third, globalisation impacts the green economy through increased trade and industrialisation, leading to resource depletion, pollution, and unequal distribution of environmental burdens and benefits, necessitating comprehensive global and local action [ 43 , 44 , 45 ]. Fourth, urbanization, indicated by the urban population as a percentage of the total population impacts green growth by intensifying resource consumption, pollution, and habitat fragmentation [ 46 , 47 ]. Increased infrastructure development often leads to land degradation and loss of biodiversity. However, well-planned urbanization can promote sustainability by fostering compact, efficient cities with green spaces, public transportation, and renewable energy integration.

3.3 Theoretical and estimation strategy

The theoretical foundation of this paper is grounded in the pollution halo and pollution haven hypotheses (see Brian et al. [ 14 ]; Tang and Tan [ 17 ]; Al-Mulali and Tang [ 19 ]), as well as the Environmental Kuznets Curve (EKC) hypothesis and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework [ 47 , 48 , 49 ]. The EKC hypothesis postulates an inverted U-shaped relationship between environmental degradation and economic growth. Initially, economic growth leads to increased environmental degradation, but after reaching a certain level of income per capita, the trend reverses, leading to environmental improvements. This theory provides a foundational framework for examining of how economic activities, including FDI, impact environmental outcomes at different stages of development. On the other hand, the STIRPAT framework extends the IPAT model (Impact = Population × Affluence × Technology) by incorporating stochastic elements to analyze the impacts of human activities on the environment. The framework allows for the inclusion of multiple variables and their interactions, making it suitable for complex econometrics.

The empirical rigor of this paper is evident from the outset, starting with the specification of models to test the relationships between FDI, technological innovation, and green growth. First, we establish a baseline model to explore the Environmental Kuznets Curve (EKC) hypothesis and examine the impact of control variables on green growth. Finally, adhering to the STIRPAT framework, which accommodates multiple variables and their interactions, we introduce an interaction term to assess how FDI and technological innovation jointly influence green growth. The models are specified as follows:

The baseline model is specified in ( 3 ) as:

To capture the joint effect of FDI and technology innovation, Eq. ( 3 ) is modified to obtained ( 4 )

where i and t represent individual countries and time periods respectively, GG signifies green growth, GDP denotes GDP per capita and it squared, FDI represents foreign direct investment as a percentage of GDP, tech signifies technology innovation, TC indicates the transmission channel through which the effect of FDI on green growth is modulated, with its estimated coefficient denoted by \({\pi }_{i}\) . The TC variable summarises (FDI*tech), \(K\) represents control variables which are renewable energy consumption, globalization, urbanization along with their corresponding estimated coefficients ( \({{\varvec{\delta}}}_{{\varvec{h}}})\) , ε representing the error term.

3.4 Estimation technique

The study utilizes a smoothed instrumental-variables quantile regression (SIVQR) approach to address potential endogeneity concerns. This methodology is of significant importance in assessing the influence of foreign direct investment (FDI) on the distribution of green growth. By analyzing distinct quantile levels within the conditional distribution, the quantile regression method facilitates the identification of countries characterized by varying degrees of green growth, thereby classifying them into low, intermediate, and high levels. The merit of this method, as highlighted by Wirajing et al. [ 50 ], lies in its capacity to elucidate the initial levels of the exogenous variable. Unlike ordinary least squares (OLS) regression, which frequently yields oversimplified and broadly generalized policy suggestions, instrumental quantile regression identifies precise quantiles where independent variables notably impact the dependent variable. This contrasts OLS, which depends on mean values and may result in broad policy implications.

Moreover, the instrumented quantile strategy aims to minimize absolute deviations across various quantile estimates, offering insights that hinge on the prevailing levels of Foreign Direct Investment (FDI) impact on green growth. This methodology diverges from Ordinary Least Squares (OLS), which prioritizes the reduction of the sum of squared residuals. In response to the shortcomings of OLS, quantile regression is being tailored by addressing the maximization problem outlined in Eq.  5 .

where \(\theta\) represents different quantile levels at the conditional distribution of the outcome variable, which belongs to {0, 1}. \(\theta\) can take 0.10, 0.25, 0.50, 0.75 and 0.90. The conditional quantile of green growth is presented in Eq.  6 by weighing the residuals.

Equation  6 introduces y, which symbolizes green growth proxy by production-based CO 2 productivity and demand-based CO 2 productivity. To address potential endogeneity issues with FDI and other control variables in the quantile model, we instrument production-based CO 2 productivity and demand-based CO 2 productivity by utilizing lag values of FDI, while also instrumenting all control variables across quantile levels ranging from the lower (10th and 25th) to the upper (75th and 90th) quantiles.

To optimize computational efficiency and statistical accuracy, this study employs the sivqr quantile instrumentation, integrating the smoothed estimator introduced by Kaplan and Sun [ 51 ]. Standard errors are computed using the Bayesian bootstrap method, employing a selection of 100 at all quantile levels, and are compatible with bootstrap prefixes, thereby ensuring the robustness and reliability of findings. However, it's important to note that quantile regression encounters challenges in addressing cross-sectional dependence, which necessitates supplementation with the Generalised Method of Moments (GMM) strategy.

4 GMM specification

The study additionally employs the system GMM strategy to analyze the indirect effects. Specifically, it examines how technological innovation serves as a pathway through which FDI impacts green growth, moderating the relationship. By employing the GMM strategy, the study offers flexibility in modelling complex relationships, accommodates various types of data, and allows for robust statistical inference. It addresses potential endogeneity issues and tackles problems associated with unobserved heterogeneity, such as time-invariant omitted variables and concerns regarding reverse causality. System GMM was chosen to yield results with a net effect for policy recommendation, which applies to all OECD countries, a feature not easily accommodated by quantile regression. This strategy generates efficient estimates under specific conditions. The primary condition for adopting the GMM is met in our study, as it deals with 37 OECD countries over 26 years from 1995 to 2021, where the number of cross-sections exceeds the time series [ 52 ]. Additionally, the study satisfies the requirement for employing the GMM in panel data analysis.

The two-step system GMM strategy adopted in the study is summarised in the first difference ( 6 ) as follows:

K signifies the vector of control variables. µ i represents the country-specific effect, γ t indicates the time-specific constant term, represents the error term and τ the lagging coefficient.

Additionally, to prevent generic policy recommendations, we calculate the net effect of the modulating variable by utilizing the coefficients of both the direct and indirect effects, as outlined in Eq.  8 .

Ω denotes the average policy-modulating variable. The computation of the net effect is performed exclusively when β 1 and π 1 are both significant and demonstrate opposing signs.

5 Results and discussions

In this section, we delve into the findings of the study and offer a comprehensive analysis. To ensure clarity, the results are categorized into four sub-sections: Firstly, we present the fundamental findings derived from the baseline analysis. Secondly, we present the estimates from the quantile instrumental test results, accompanied by quantile regression plots provided in Appendix 1 and 2. Thirdly, we provided robustness checks by considering time variation and renewable energy by sources. Lastly, we discuss the results concerning the transmission effect and the determination of modulating thresholds obtained from the Two-Step System GMM estimates.

5.1 The Baseline results

The baseline results presented in Table  3 stem from the ordinary least squares model (OLS). These results reveal that FDI, GDP, renewable energy, and globalization exhibit positive correlations with both production-based CO 2 productivity and demand-based CO 2 productivity. Conversely, technological innovation and urbanization demonstrate negative effects. The study refrains from relying on the results of the OLS estimates for its conclusive remarks due to its failure to address issues of endogeneity and unobserved heterogeneity. In lieu of this, the present study opts for instrumental quantile regression as a more robust approach, the findings of which are outlined in Sect.  4.2 .

5.2 The instrumental quantile regression estimates

The quantile approach illustrates the estimated impact of FDI on green growth. These findings, derived from the quantile regression approach, are detailed in Table  4 of the study. The table showcases the results of instrumented quantile regression estimates at various quantiles, including the 10th, 25th, 50th, 75th, and 90th percentiles. Quantile regressions are widely adopted in both contemporary and non-contemporary literature as a robust regression technique, enabling a more typical assumption of normality for the residual term [ 50 , 53 ].

Even after addressing the issue of endogeneity in the OLS results, the discovery of the exclusive positive impact of FDI on production-based CO 2 productivity and demand-based CO 2 productivity remains consistent with the findings of the OLS analysis. Foreign Direct Investment (FDI) often leads to increased industrialization and economic activity, contributing to higher CO 2 emissions. Production-based CO 2 productivity decreases as FDI boosts manufacturing output, intensifying emissions. Similarly, demand-based CO 2 productivity declines as FDI drives consumption, heightening energy use and emissions. Consequently, the correlation between FDI and production-based and demand-based CO2 productivity tends to be positive due to the environmental implications of the heightened economic activity facilitated by FDI. These findings are in line with Tukhtamurodov et al. [ 15 ], Salahuddin et al. [ 54 ], and Zhang and Zhou [ 10 ], who argued that FDI often introduces technologies or production methods that are environmentally unfriendly or energy-inefficient, thus worsening the green growth.

Moreover, the result indicates that GDP increases production-based CO2 productivity- and demand-based CO 2 productivity among the selected OECD countries. As a measure of economic output, GDP often incentivizes consumption and production without regard for environmental consequences. This hinders green growth, which aims for economic development while preserving the environment. GDP-driven policies prioritize short-term gains over long-term sustainability, leading to overexploitation of natural resources, pollution, and ecosystem degradation. Additionally, GDP fails to account for negative externalities such as carbon emissions and habitat destruction, undervaluing the true cost of economic activities. Consequently, investments in environmentally harmful industries might appear beneficial for GDP growth despite their adverse effects on the planet.

On the other hand, the GDP squared has a favourable effect on green growth, albeit not significant for demand-based CO 2 productivity, possibly reflecting heightened awareness of environmental concerns leading to policies advocating sustainability and the reduction of CO 2 emissions as a byproduct of economic progress. These findings align with the Environmental Kuznets Curve literature, which suggests that economic activities often escalate energy consumption in early growth stages, primarily from fossil fuels and major CO 2 emission sources. Conversely, in later stages, maturing economies tend to embrace cleaner technologies, renewable energy sources, and enhanced production methods [ 7 , 8 ].

Furthermore, the results indicate that renewable energy exacerbates production- and demand-based CO 2 productivity in OECD countries. This may stem from the energy-intensive processes involved in renewable infrastructure production and maintenance and the intermittent nature of some renewables, necessitating backup systems that can increase CO 2 emissions. Additionally, manufacturing renewable infrastructure involves energy-intensive processes, contributing to CO 2 emissions. Also, globalization unfavourably impacts green growth by amplifying production-based and demand-based CO 2 productivity through increased trade, transportation, and industrial activities. Meeting global demand results in heightened energy consumption, primarily from fossil fuels. Outsourcing manufacturing to regions with lax environmental regulations further escalates emissions, worsening the global climate crisis. This aligns with Kirikkaleli and Addai's [ 55 ] findings, highlighting how globalization, prioritizing profit over environmental concerns, drives up resource extraction, production-based, and demand-based CO 2 productivity through expansive trade networks.

The results further demonstrate that technological innovation fosters green growth. Specifically, within the OECD sub-region, technological advancements enhance environmental sustainability by improving efficiency, conserving resources, and reducing pollution. These innovations diminish reliance on fossil fuels, thereby curbing greenhouse gas emissions. Smart grid technologies optimize energy distribution, minimizing wastage, while advancements in waste management, such as recycling and composting, reduce landfill usage. Moreover, innovations in transportation, including electric vehicles and efficient logistics, contribute to carbon emission reductions. Indeed, studies by Suki et al. [ 56 ], Nosheen et al. [ 57 ], and Mensah et al. [ 58 ] affirm that technological innovation cultivates a more sustainable balance between human activities and the environment.

Finally, the findings also reveal that urbanization has a negative and significant effect on both production-based and demand-based CO 2 productivity in the OECD countries. This indicates that urbanization contributes to green growth by fostering denser living arrangements, thereby decreasing per capita resource consumption and carbon emissions. Compact cities promote public transportation and shared infrastructure, mitigating urban sprawl and conserving natural habitats. Moreover, centralized services enhance efficiency in waste management and energy distribution, promoting a more environmentally sustainable urban environment.

5.3 Sensitivity check

This section validates the findings by examining potential sources of bias, bolstering the study's credibility, and confirming the generalisability and consistency of the analytical approach. It incorporates assessments of time variances and renewable energy sources to ensure the consistency of the results.

5.3.1 Does time matter in green growth and the FDI relationship?

Different time periods affect green growth due to evolving societal attitudes, technological advancements, and policy frameworks. In the early days, limited awareness of environmental issues led to unsustainable practices. Industrial revolutions accelerated resource exploitation, causing environmental degradation. However, with the emergence of environmental movements in the mid-twentieth century, awareness grew, prompting the adoption of conservation measures and early environmental regulations. As we progressed into the twenty-first century, concerns about climate change intensified, leading to increased emphasis on sustainable practices and green technologies. Today, with a greater understanding of the urgency to address climate change, there's a global push for green growth.

Policies supporting green technologies, circular economies, and sustainable development goals shape contemporary approaches. Therefore, the trajectory of green growth is shaped by the socio-economic context and the level of commitment to sustainable practices across different time periods. Tables 5 and 6 present the effect of FDI on production-based and demand-based CO 2 productivity accounting for different time periods. However, the results generally align with the baseline, although with minor exceptions; for example, GDP's negative impact on demand-based CO 2 productivity in the first quantile across different periods, albeit statistically insignificant.

5.3.2 Robustness checks accounting for renewable energy by sources

Renewable energy sources such as solar and wind power exhibit availability and technological application variability, uniquely affecting their contributions to sustainable development and green growth. Solar thermal energy capitalizes on sunlight to produce heat or electricity, diminishing dependence on fossil fuels and lowering greenhouse gas emissions. Conversely, wind energy employs turbines to generate electricity, reducing carbon emissions. However, wind energy's effectiveness relies on wind availability, whereas solar thermal energy can offer more consistency in specific regions. Both technologies are pivotal in broadening the spectrum of renewable energy sources and advancing sustainable development goals.

This study's choice of solar thermal and wind energy is predicated on data availability for the covered time period. Tables 7 and 8 unveil the impact of FDI on production-based and demand-based CO 2 productivity while considering renewable energy sources, specifically solar thermal and wind energy. After accounting for the difference in renewable energy to check the consistency of our result, we observed that the result remained unchanged. Upon examining the control variables, we observe minimal alterations. For instance, urbanization positively impacts production-based CO 2 productivity, although this effect is deemed insignificant. Additionally, globalization negatively influences demand-based CO 2 productivity in the last two quantiles.

5.4 Indirect effect result

The indirect effect analysis investigates the moderating role of technology innovation on the effect of FDI on green growth within the OECD member state. The indirect effect results have been conducted to examine whether the quest technology advancement enables FDI recipients to adopt cleaner production methods, reduce resource consumption, and minimize environmental impacts. Investments in environmental technology, smart grids, and sustainable infrastructure can be facilitated through technological advancements, promoting green growth [ 57 , 58 ]. Additionally, innovations in waste management, water purification, and pollution control help mitigate negative externalities associated with FDI. Through technology, FDI can catalyze the development and deployment of environmentally friendly solutions, fostering a more sustainable and resilient economy [ 9 , 12 , 13 ]. This synergy between technology innovation and FDI contributes to achieving long-term environmental objectives while stimulating economic growth.

The introduction of the indirect effect guides us towards avoiding broad policy approaches. It offers a framework for devising strategies to enhance green growth within the OCED countries with inadequate environmental management. In this section of the study, the Two-Step System GMM strategy is employed to determine a consolidated net effect of FDI interaction with tech-innovation in the OECD sub-region to easy policy orientation. By utilizing the GMM strategy, the study ensures that the findings are unaffected by endogeneity, cross-sections, autocorrelation, and heteroscedasticity, as suggested by Wirajing et al. [ 50 ]. The outcomes of the system GMM analysis are presented in Table  9 . The findings suggest that FDI exerts a notable and positive influence on production—and demand-based CO 2 productivity, aligning with the core findings. Upon interaction with technological innovation, we discern a positive impact on production-based CO 2 productivity but a negative impact on demand-based CO 2 productivity. This suggests that technological innovation can moderate the influence of FDI on demand-based CO 2 productivity. This finding supports the role of innovation in achieving SDG 9 and underscores the importance of fostering collaborative partnerships between foreign investors and local innovators (SDG 17).

Technological advancements within OECD countries often attract FDI due to their growth potential and profitability. This prioritizes efficiency enhancements over environmental sustainability, consequently boosting production-based CO 2 productivity. Conversely, the synergy between technological innovation and FDI fosters the advancement of cleaner technologies and energy-efficient processes. This leads to a decline in demand-based CO 2 productivity, stemming from reduced energy consumption across various stages of goods and services production consumed domestically, regardless of the production locations.

5.5 Conclusion and policy implication

The Sustainable Development Goals advocate for advancing green growth, which entails fostering economic prosperity while safeguarding the environment. Central to this agenda are the principles of sustainable consumption, production, and energy utilization aimed at addressing climate change and preserving ecosystems. This study examines the moderating influence of technological innovation on the relationship between Foreign Direct Investment (FDI) and green growth within OECD member states. Our examination focuses on two dimensions of green growth: production-based CO 2 productivity and demand-based CO 2 productivity. Employing the EKC and STIRPAT frameworks, we analyze data from 1995 to 2021 across 37 OECD countries. Methodologically, our empirical approach involves employing Ordinary Least Squares (OLS), instrumental quantile, and System GMM methodologies. The results indicate that FDI hinders green growth, while technological innovation is pivotal in enhancing it. This dynamic holds across various periods and renewable energy sources. Moreover, our study reveals that FDI, in conjunction with technological innovation, leads to an increase in production-based CO 2 productivity but a decrease in demand-based CO 2 productivity. Additionally, we observe the presence of an environmental Kuznets curve for production-based CO 2 productivity.

Adding to significant scientific value by demonstrating how technological innovation moderates FDI's impact on green growth in OECD countries, we propose the implementation of a policy framework aimed at fostering domestic technological innovation while prudently managing foreign direct investment (FDI) to support sustainable growth. Also, policy frameworks should prioritize investments in research and development, creating an enabling environment for innovation and the advancement of sustainable technologies. Encouraging collaborative ventures between foreign investors and local innovators can also harness global expertise while furthering green objectives. Concurrently, policies should stimulate demand for environmentally friendly products and services to bolster demand-based CO 2 productivity. Moreover, investing in research and development (R&D) for green technologies is crucial. Lastly, integrating green criteria into FDI agreements and providing tax incentives for eco-friendly innovations will harmonize FDI with environmental goals.

5.6 Limitations and future recommendations

This study offers valuable insights into the interplay between Foreign Direct Investment (FDI), technological innovation, and green growth in OECD countries. However, several limitations stem from the design and methodology constraints, which may impact the interpretation of our findings:

First, the dataset covers 37 OECD countries over 26 years (1995–2021). While comprehensive, this temporal and spatial scope may not capture all relevant fluctuations and anomalies, especially short-term economic shocks or policy changes that could influence FDI and green growth dynamics. Second, using proxies, such as patents for technological innovation and production-based and demand-based CO2 productivity for green growth, introduces potential measurement errors. These proxies may not fully encapsulate the multi-faceted nature of technological innovation and environmental sustainability. Third, the focus on OECD countries, typically advanced economies, limits the generalizability of the findings to developing countries with different economic structures, regulatory frameworks, and technological capabilities. Also, the methodologies employed, including Ordinary Least Squares (OLS), smoothed instrumental-variables quantile regression (SIVQR), and System GMM, each have inherent limitations. For instance, OLS may not adequately address endogeneity issues, while SIVQR and System GMM require strong assumptions about the instruments and error distributions, which might not hold in all cases. Finally, technological innovation is a broad concept, and this study's focus on patents may overlook other forms of innovation, such as process improvements, managerial practices, and informal knowledge transfers that also significantly impact green growth.

Building on the findings and addressing the aforementioned limitations, the following recommendations are proposed for future research:

Future studies should incorporate a more extensive dataset, including non-OECD countries, to enhance the generalizability of the findings. Including data from emerging and developing economies could provide a more comprehensive understanding of the FDI-green growth nexus across different economic contexts. Moreover, employing alternative or supplementary measures for technological innovation, such as R&D expenditures, innovation indices, and qualitative assessments of technological capabilities, can provide a more nuanced understanding of its impact on green growth. Also, utilizing advanced econometric techniques that better handle endogeneity, non-linearity, and dynamic relationships, such as panel vector autoregression (PVAR) and machine learning approaches, can provide more robust insights. These methods can also help uncover complex interactions and causal relationships.

In addition, conducting in-depth case studies and sector-specific analyses can reveal contextual nuances and sectoral variations in the FDI-green growth relationship. This approach can identify best practices and policy interventions tailored to specific industries or regions. Lastly, integrating insights from other disciplines, such as political science, sociology, and environmental science, can enrich the analysis by considering broader socio-political and ecological dimensions influencing the FDI-green growth nexus. By addressing these limitations and following the outlined recommendations, future research can build on robust foundations, yielding valuable insights that inform practical applications and policy decisions to foster sustainable economic development.

Data availability

The data used in this study is available upon request from the corresponding author.

Australia, Belgium, Canada, Chile, Colombia, Costarica, Czech, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Isreal, Italy Japan, Korea, Latvia, Lithaunia, Luxembourg, Mexico, Netherlands, New zealand, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States.

Georgeson L, Maslin M, Poessinouw M. The global green economy: a review of concepts, definitions, measurement methodologies and their interactions. Geo. 2017. https://doi.org/10.1002/geo2.36 .

Article   Google Scholar  

Caglar AE, Avci SB, Ahmed Z, Gökçe N. Assessing the role of green investments and green innovation in ecological sustainability: From a climate action perspective on European countries. Sci Total Environ. 2024;928: 172527. https://doi.org/10.1016/j.scitotenv.2024.172527 .

Article   CAS   Google Scholar  

Caglar AE, Gönenç S, Destek MA. The influence of nuclear energy research and development investments on environmental sustainability: evidence from the United States and France. Int J Sustain Develop World Ecology. 2024. https://doi.org/10.1080/13504509.2024.2341797 .

Caglar AE, Destek MA, Manga M. Analyzing the load capacity curve hypothesis for the Turkiye: A perspective for the sustainable environment. J Clean Prod. 2024;444: 141232. https://doi.org/10.1016/j.jclepro.2024.141232 .

Mirziyoyeva Z, Salahodjaev R. Renewable energy, GDP and CO2 emissions in high-globalized countries. Front Energy Res. 2023. https://doi.org/10.3389/fenrg.2023.1123269 .

Mohsin M, Naseem S, Sarfraz M, Azam T. Assessing the effects of fuel energy consumption, foreign direct investment and GDP on CO2 emission: New data science evidence from Europe & Central Asia. Fuel. 2022;314: 123098. https://doi.org/10.1016/j.fuel.2021.123098 .

Ullah S, Nadeem M, Ali K, Abbas Q. Fossil fuel, industrial growth and inward FDI impact on CO 2 emissions in Vietnam: testing the EKC hypothesis. Manag Environ Qual. 2022;33(2):222–40. https://doi.org/10.1108/MEQ-03-2021-0051 .

Ochoa-Moreno W-S, Quito BA, Moreno-Hurtado CA. Foreign Direct Investment and Environmental Quality: Revisiting the EKC in Latin American Countries. Sustainability. 2021;13(22):12651. https://doi.org/10.3390/su132212651 .

Wang Z, Gao L, Wei Z, Majeed A, Alam I. How FDI and technology innovation mitigate CO2 emissions in high-tech industries: evidence from province-level data of China. Environ Sci Pollut Res. 2022;29(3):4641–53. https://doi.org/10.1007/s11356-021-15946-4 .

Zhang C, Zhou X. Does foreign direct investment lead to lower CO2 emissions? Evidence from a regional analysis in China. Renew Sustain Energy Rev. 2016;58:943–51. https://doi.org/10.1016/j.rser.2015.12.226 .

Bakhsh S, Yin H, Shabir M. Foreign investment and CO2 emissions: do technological innovation and institutional quality matter? Evidence from system GMM approach. Environ Sci Pollut Res. 2021;28(15):19424–38. https://doi.org/10.1007/s11356-020-12237-2 .

Radmehr R, Shayanmehr S, Baba EA, Samour A, Adebayo TS. Spatial spillover effects of green technology innovation and renewable energy on ecological sustainability: New evidence and analysis. Sustain Dev. 2024;32(3):1743–61. https://doi.org/10.1002/sd.2738 .

Zhao W-X, Samour A, Yi K, Al-Faryan MAS. Do technological innovation, natural resources and stock market development promote environmental sustainability? Novel evidence based on the load capacity factor. Resour Policy. 2023;82: 103397. https://doi.org/10.1016/j.resourpol.2023.103397 .

Copeland BR, Taylor MS. North-South Trade and the Environment. Q J Econ. 1994;109(3):755–87. https://doi.org/10.2307/2118421 .

Tukhtamurodov A, Sobirov Y, Toshalieva S, Ibrayimova D, Feruz M. Determinants of CO 2 emissions in the BRICS. A dynamic Panel ARDL approach. BIO Web Conf. 2024;82:06002. https://doi.org/10.1051/bioconf/20248206002 .

Khan M, Rana AT, Ghardallou W. FDI and CO2 emissions in developing countries: the role of human capital. Nat Hazards. 2023;117(1):1125–55. https://doi.org/10.1007/s11069-023-05949-4 .

Tang CF, Tan BW. The impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in Vietnam. Energy. 2015;79:447–54. https://doi.org/10.1016/j.energy.2014.11.033 .

Anyanwu JC. Why Does Foreign Direct Investment Go Where It Goes? New Evidence from African Countries. Ann Econ Financ. 2012;13(2):425–62.

Google Scholar  

Al-mulali U, FoonTang C. Investigating the validity of pollution haven hypothesis in the gulf cooperation council (GCC) countries. Energy Policy. 2013;60:813–9. https://doi.org/10.1016/j.enpol.2013.05.055 .

Tian X. Accounting for sources of FDI technology spillovers: evidence from China. J Int Bus Stud. 2007;38(1):147–59. https://doi.org/10.1057/palgrave.jibs.8400245 .

Shaari MS, Nor EH, Hussin A, Kamil S. Relationship among foreign direct investment, economic growth and co2 emission: a panel data analysis. Int J Energy Econ Policy. 2014;706:15.

Chowdhury MAF, Shanto PA, Ahmed A, Rumana RH. Does foreign direct investments impair the ecological footprint? New evidence from the panel quantile regression. Environ Sci Pollut Res. 2021;28(12):14372–85. https://doi.org/10.1007/s11356-020-11518-0 .

Sabir S, Qayyum U, Majeed T. FDI and environmental degradation: the role of political institutions in South Asian countries. Environ Sci Pollut Res. 2020;27(26):32544–53. https://doi.org/10.1007/s11356-020-09464-y .

Balsalobre-Lorente D, Gokmenoglu KK, Taspinar N, Cantos-Cantos JM. An approach to the pollution haven and pollution halo hypotheses in MINT countries. Environ Sci Pollut Res. 2019;26(22):23010–26. https://doi.org/10.1007/s11356-019-05446-x .

Udemba EN. Moderation of ecological footprint with FDI and agricultural sector for a better environmental performance: New insight from Nigeria. J Public Aff. 2020. https://doi.org/10.1002/pa.2444 .

Solarin SA, Al-Mulali U, Musah I, Ozturk I. Investigating the pollution haven hypothesis in Ghana: An empirical investigation. Energy. 2017;124:706–19. https://doi.org/10.1016/j.energy.2017.02.089 .

Ahmed F, Ali I, Kousar S, Ahmed S. The environmental impact of industrialization and foreign direct investment: empirical evidence from Asia-Pacific region. Environ Sci Pollut Res. 2022;29(20):29778–92. https://doi.org/10.1007/s11356-021-17560-w .

Shahbaz M, Nasir MA, Roubaud D. Environmental degradation in France: The effects of FDI, financial development, and energy innovations. Energy Econ. 2018;74:843–57. https://doi.org/10.1016/j.eneco.2018.07.020 .

Kirkulak B, Qiu B, Yin W. The impact of FDI on air quality: evidence from China. J Chin Econ Foreign Trade Studies. 2011;4(2):81–98. https://doi.org/10.1108/17544401111143436 .

Tamazian A, Bhaskara Rao B. Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies. Energy Econ. 2010;32(1):137–45. https://doi.org/10.1016/j.eneco.2009.04.004 .

Caglar AE, Daştan M, Bulut E, Marangoz C. Evaluating a pathway for environmental sustainability: The role of competitive industrial performance and renewable energy consumption in European countries. Sustain Dev. 2024;32(3):1811–24. https://doi.org/10.1002/sd.2755 .

Yavuz E, Kilic E, Caglar AE. A new hypothesis for the unemployment-environment dilemma: is the environmental Phillips curve valid in the framework of load capacity factor in Turkiye? Environ Dev Sustain. 2023. https://doi.org/10.1007/s10668-023-04258-x .

Destek MA, Okumus I. Does pollution haven hypothesis hold in newly industrialized countries? Evidence from ecological footprint. Environ Sci Pollut Res. 2019;26(23):23689–95. https://doi.org/10.1007/s11356-019-05614-z .

Sapkota P, Bastola U. Foreign direct investment, income, and environmental pollution in developing countries: Panel data analysis of Latin America. Energy Econ. 2017;64:206–12. https://doi.org/10.1016/j.eneco.2017.04.001 .

Doytch N, Uctum M. Spillovers from foreign direct investment in services: Evidence at sub-sectoral level for the Asia-Pacific. J Asian Econ. 2019;60:33–44. https://doi.org/10.1016/j.asieco.2018.10.003 .

Caetano RV, Marques AC, Afonso TL. How can foreign direct investment trigger green growth? the mediating and moderating role of the energy transition. Economies. 2022;10(8):199. https://doi.org/10.3390/economies10080199 .

Qamri GM, Sheng B, Adeel-Farooq RM, Alam GM. The criticality of FDI in Environmental Degradation through financial development and economic growth: Implications for promoting the green sector. Resour Policy. 2022;78: 102765. https://doi.org/10.1016/j.resourpol.2022.102765 .

Padhan L, Bhat S. Nexus between foreign direct investment and ecological footprint in BRICS and Next-11: the moderating role of green innovation. Manag Environ Qual Int J. 2024;35(4):799–817. https://doi.org/10.1108/MEQ-07-2023-0204 .

Ofori IK, Gbolonyo EY, Ojong N. Foreign direct investment and inclusive green growth in Africa: Energy efficiency contingencies and thresholds. Energy Econ. 2023;117: 106414. https://doi.org/10.1016/j.eneco.2022.106414 .

Ali M, Joof F, Samour A, Tursoy T, Balsalobre-Lorente D, Radulescu M. Testing the impacts of renewable energy, natural resources rent, and technological innovation on the ecological footprint in the USA: Evidence from Bootstrapping ARDL. Resour Policy. 2023;86: 104139. https://doi.org/10.1016/j.resourpol.2023.104139 .

Samour A, Jahanger A, Ali M, Joof F, Tursoy T. Renewable energy, natural resources, technological innovation, and consumption-based carbon emissions in China: Tracking environmental neutrality. Nat Resour Forum. 2023. https://doi.org/10.1111/1477-8947.12327 .

Samour A, Mehmood U, Radulescu M, Budu RA, Nitu RM. Examining the Role of Renewable Energy, Technological Innovation, and the Insurance Market in Environmental Sustainability in the United States: A Step toward COP26 Targets. Energies (Basel). 2023;16(17):6138. https://doi.org/10.3390/en16176138 .

Ansari MA, Akram V, Haider S. A link between productivity, globalisation and carbon emissions: evidence from emissions by coal, oil and gas. Environ Sci Pollut Res. 2022;29(22):33826–43. https://doi.org/10.1007/s11356-022-18557-9 .

Koengkan M, Fuinhas JA, Santiago R. Asymmetric impacts of globalisation on CO2 emissions of countries in Latin America and the Caribbean. Environ Syst Decis. 2020;40(1):135–47. https://doi.org/10.1007/s10669-019-09752-0 .

Rahman MM. Environmental degradation: The role of electricity consumption, economic growth and globalisation. J Environ Manage. 2020;253: 109742. https://doi.org/10.1016/j.jenvman.2019.109742 .

Luqman M, Rayner PJ, Gurney KR. On the impact of urbanisation on CO2 emissions. Urban Sustainability. 2023;3(1):6. https://doi.org/10.1038/s42949-023-00084-2 .

Wang Z, Rasool Y, Zhang B, Ahmed Z, Wang B. Dynamic linkage among industrialisation, urbanisation, and CO2 emissions in APEC realms: Evidence based on DSUR estimation. Struct Chang Econ Dyn. 2020;52:382–9. https://doi.org/10.1016/j.strueco.2019.12.001 .

Ojaghlou M, Ugurlu E, Kadłubek M, Thalassinos E. Economic Activities and Management Issues for the Environment: An Environmental Kuznets Curve (EKC) and STIRPAT Analysis in Turkey. Resources. 2023;12(5):57. https://doi.org/10.3390/resources12050057 .

Avenyo EK, Tregenna F. Greening manufacturing: Technology intensity and carbon dioxide emissions in developing countries. Appl Energy. 2022;324: 119726. https://doi.org/10.1016/j.apenergy.2022.119726 .

Wirajing MAK, Nanfosso RT, Kountchou AM. The fishing industry and the growing food insecurity in Africa: an empirical analysis with an instrumented quantile approach. J Environ Econ Policy. 2024. https://doi.org/10.1080/21606544.2024.2328124 .

Kaplan DM, Sun Y. Smoothed estimating equations for instrumental variables quantile regression. Econ Theory. 2017;33(1):105–57. https://doi.org/10.1017/S0266466615000407 .

Bila S, Khumalo Z, Nkosi P, Arogundade S. Foreign aids and economic growth in Africa: Does third-country effect matter? Stud Econ Econ. 2023;47(1):23–42. https://doi.org/10.1080/03796205.2023.2185807 .

Chen X, Gong X, Li D, Zhang J. Can information and communication technology reduce CO2 emission? A quantile regression analysis. Environ Sci Pollut Res. 2019;26(32):32977–92. https://doi.org/10.1007/s11356-019-06380-8 .

Salahuddin M, Alam K, Ozturk I, Sohag K. The effects of electricity consumption, economic growth, financial development and foreign direct investment on CO2 emissions in Kuwait. Renew Sustain Energy Rev. 2018;81:2002–10. https://doi.org/10.1016/j.rser.2017.06.009 .

Kirikkaleli D, Addai K. The asymmetric and long-run effect of demand-based CO 2 emissions productivity on production-based CO 2 emissions in the UK. Energy & Environment. 2023. https://doi.org/10.1177/0958305X231204958 .

Mohd Suki N, Mohd Suki N, Afshan S, Sharif A, Ariff Kasim M, Rosmaini Mohd Hanafi S. How does green technology innovation affect green growth in ASEAN-6 countries? Evidence from advance panel estimations. Gondwana Res. 2022;111:165–73. https://doi.org/10.1016/j.gr.2022.06.019 .

Nosheen M, Iqbal J, Abbasi MA. Do technological innovations promote green growth in the European Union? Environ Sci Pollut Res. 2021;28(17):21717–29. https://doi.org/10.1007/s11356-020-11926-2 .

Mensah CN, et al. Technological innovation and green growth in the Organization for Economic Cooperation and Development economies. J Clean Prod. 2019;240: 118204. https://doi.org/10.1016/j.jclepro.2019.118204 .

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GSK prepared the analysis, interpretation and data curation. SA prepared the literature review, and BM prepared the introduction, editing and supervision of the manuscript.

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1.1 Appendix 1: The quantile plot on the determinants of production-based CO 2 productivity

1.2 Appendix 2: The quantile plot on the determinants of demand-based CO 2 productivity

1.3 Appendix 3. Production-based CO 2 productivity across the OECD countries. Source: Author’s computation from OECD database

1.4 Appendix 4. Demand-based CO 2 productivity across the OECD countries. Source: Author’s computation from OECD database

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Ketchoua, G.S., Arogundade, S. & Mduduzi, B. Revaluating the Sustainable Development Thesis: exploring the moderating influence of Technological Innovation on the impact of Foreign Direct Investment (FDI) on Green Growth in the OECD Countries. Discov Sustain 5 , 252 (2024). https://doi.org/10.1007/s43621-024-00433-w

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Received : 13 May 2024

Accepted : 20 August 2024

Published : 10 September 2024

DOI : https://doi.org/10.1007/s43621-024-00433-w

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