research paper on new criticism

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9 Practicing New Criticism

Now that you’ve learned about New Criticism, practiced this method of analysis with “Ars Poetica,” and reviewed some examples, you will complete a theoretical response to a text using New Criticism as your approach. You will read three different texts below. Choose one text and respond to the questions in a short essay (500-750 words). I have included questions to guide your reading. You may choose to respond to some or all of these questions; however, your response should be written as a short essay, and you will need to come up with a thesis statement about your chosen text. Post your short essay as a response to the New Criticism Theoretical Response discussion board. I have included the theoretical response assignment instructions at the end of this chapter.

Checklist for New Criticism

Remember, when using the New Criticism approach, the goal is to closely examine the text itself and draw interpretations from its inherent literary qualities rather than relying on external context or authorial intent. Use “the speaker” instead of “the author” when writing about the text, and do not assume that the speaker is the author.

Start with a close reading of the text. If you are working with a poem, number the lines. Then look for meter, rhythm, rhyme, stanzas, etc. (or identify whether the poem is free-verse)
Try to identify the work’s oppositions, tensions, paradoxes, and ironies (complexities in the text).
Look for evidence of unity in the work through specific elements including metaphor, point of view, diction, imagery, meter/rhyme, and structure.
Once you have identified the text’s complexities and found evidence in its elements, create a thesis statement about how the poem’s various elements create unity. What is the the theme of the text, and how do the elements/complexities support that theme?

“The Love Song of J. Alfred Prufrock” by T.S. Eliot (1915)

S’io credesse che mia risposta fosse A persona che mai tornasse al mondo, Questa fiamma staria senza piu scosse. Ma percioche giammai di questo fondo Non torno vivo alcun, s’i’odo il vero, Senza tema d’infamia ti rispondo.

Before the taking of a toast and tea.

My necktie rich and modest, but asserted by a simple pin —

(They will say: “But how his arms and legs are thin!”)

Beneath the music from a farther room.

So how should I presume?

To spit out all the butt-ends of my days and ways?

And how should I presume?

Arms that lie along a table, or wrap about a shawl.

And should I then presume?

And how should I begin?

Scuttling across the floors of silent seas.

And I have seen the eternal Footman hold my coat, and snicker,

And in short, I was afraid.

If one, settling a pillow by her head

That is not it, at all.”

That is not what I meant, at all.”

At times, indeed, almost ridiculous—

Almost, at times, the Fool.

I shall wear the bottoms of my trousers rolled.

I do not think that they will sing to me.

Here are some New Criticism questions you can use to guide your response. You to do not have to use every question. You should formulate a thesis statement about the text and include this thesis statement in your response. Then support the thesis statement with evidence from the text.

How does the poem’s use of imagery and symbolism contribute to the overall meaning of the poem? Explore specific instances of imagery and symbolism, such as the “yellow fog” or the “mermaids,” and discuss how they enhance the poem’s themes.
Analyze the structure and form of the poem. How does the irregular rhyme scheme and meter influence the reader’s experience? How does Eliot’s use of enjambment and punctuation affect the pacing and interpretation of the text?
Examine the diction and word choice in the poem. What impact do specific words and phrases have on the reader’s understanding of Prufrock’s character, his anxieties, and the sense of disillusionment conveyed in the poem?
Explore the use of allusions and references. What are some examples of literary, historical, or cultural allusions in the poem? How do these allusions contribute to the poem’s meaning?
Analyze the shifts in tone and mood throughout the poem. How do these shifts reflect the speaker’s changing emotions and the complexities of his self-perception? How does tone and mood contribute to the poem’s overall themes?
Consider the role of time and temporality in the poem . How does the speaker’s preoccupation with time connect to the larger themes of regret, indecision, and mortality? How does the poem’s structure manipulate time?

2. The Parable of the Prodigal Son (c. 90 CE) King James Version

And he said, A certain man had two sons:

And the younger of them said to his father, Father, give me the portion of goods that falleth to me. And he divided unto them his living.

And not many days after the younger son gathered all together, and took his journey into a far country, and there wasted his substance with riotous living.

And when he had spent all, there arose a mighty famine in that land; and he began to be in want.

And he went and joined himself to a citizen of that country; and he sent him into his fields to feed swine.

And he would fain have filled his belly with the husks that the swine did eat: and no man gave unto him.

And when he came to himself, he said, How many hired servants of my father’s have bread enough and to spare, and I perish with hunger!

I will arise and go to my father, and will say unto him, Father, I have sinned against heaven, and before thee,

And am no more worthy to be called thy son: make me as one of thy hired servants.

And he arose, and came to his father. But when he was yet a great way off, his father saw him, and had compassion, and ran, and fell on his neck, and kissed him.

And the son said unto him, Father, I have sinned against heaven, and in thy sight, and am no more worthy to be called thy son.

But the father said to his servants, Bring forth the best robe, and put it on him; and put a ring on his hand, and shoes on his feet:

And bring hither the fatted calf, and kill it; and let us eat, and be merry:

For this my son was dead, and is alive again; he was lost, and is found. And they began to be merry.

Now his elder son was in the field: and as he came and drew nigh to the house, he heard musick and dancing.

And he called one of the servants, and asked what these things meant.

And he said unto him, Thy brother is come; and thy father hath killed the fatted calf, because he hath received him safe and sound.

And he was angry, and would not go in: therefore came his father out, and intreated him.

And he answering said to his father, Lo, these many years do I serve thee, neither transgressed I at any time thy commandment: and yet thou never gavest me a kid, that I might make merry with my friends:

But as soon as this thy son was come, which hath devoured thy living with harlots, thou hast killed for him the fatted calf.

And he said unto him, Son, thou art ever with me, and all that I have is thine.

It was meet that we should make merry, and be glad: for this thy brother was dead, and is alive again; and was lost, and is found.

The speaker in this text is Jesus, as reported in Luke’s Gospel. This passage is Jesus’s response to an accusation from the scribes and Pharisees that he “welcomes sinners” and even shares a table with them. The story seems to answer this accusation. How does knowing the context affect your reading of the parable? If you were raised and/or follow a Christian religious tradition, you may have extratextual interpretations for this parable. In your response, please try to set those aside. Remember that with New Criticism, the text itself is our focus, not the context or our outside knowledge of the text.

Examine the parable’s structure and narrative sequence. How does the parable’s storytelling structure contribute to its impact? Consider the introduction, the conflict, the climax, and the resolution. How do these elements build tension and emotion?
Analyze the characters’ personalities and development. How are the characters of the prodigal son, the father, and the older brother presented? How does their characterization contribute to the overall message of the parable?
Explore the use of symbolism and metaphors. What symbolic elements in the parable contribute to its deeper meanings? How does the idea of the prodigal son’s journey and return symbolize themes like forgiveness, repentance, and redemption?
Examine the parable’s language and diction. How does a phrase like “the fatted calf” affect the tone of this parable? What other examples of archaic diction contribute to the voice? What impact do specific words and phrases have on the parable’s meaning and emotional resonance?
Analyze the use of repetition and rhetorical devices. How does the repetition of certain phrases or ideas contribute to the parable’s emphasis and rhythm? How do rhetorical techniques like parallelism or contrast enhance the storytelling?
Discuss the use of irony in the parable. What examples of irony can you find? How do they contribute to the text’s meaning?

3. “Recuerdo” by Edna St. Vincent Millay (1922)

Explore the poem’s title and its significance. How does the title “Recuerdo” (Spanish for “I remember”) set the tone for the poem? How does the title’s choice of language relate to the theme and content of the poem?
Analyze the use of imagery and diction in the poem. What vivid images does the speaker use to describe the scene and events in the poem? How does the language style contribute to the poem’s atmosphere and themes? Are there any specific words or phrases that stand out as particularly significant? How does the poem explore the idea of remembering a past experience? What emotions and reflections does the speaker’s recollection evoke, and how are these emotions conveyed through the poem’s language and imagery?
Examine the poem’s tone and mood. How does the tone shift throughout the poem, from the playful and carefree beginning to the reflective and contemplative ending?
Analyze the poem’s structure and form. How do the poem’s rhyme and meter contribute to the work? Does the poem conform to a set genre (e.g., quatrain, sonnet, villanelle, etc.)? How does its use of or rejection of a specific genre contribute to the poem’s overall themes?
Examine the use of punctuation. How does Millay’s use of punctuation affect the rhythm and pacing of the poem? How does it impact the reader’s interpretation?
Discuss the use of the second-person point of view. How does the poem’s use of “you” and “I” create a sense of intimacy and immediacy? How does this choice of point of view contribute to the poem’s unity?

Theoretical Response Assignment Instructions

Instructions.

15 points: theoretical response
10 points: online discussion (5 points per response) OR class attendance.

Share This Book

Rereading the New Criticism

In this Book

Edited by Miranda B. Hickman and John D. McIntyre
Published by: The Ohio State University Press

Title Page, Copyright
Acknowledgments
pp. vii-viii
1. Aesthetics as Ethics: One and a Half Theses on the New Criticism
2. Eliot, the Agrarians, and the Political Subtext of New Critical Formalism
3. Androgyny and Social Upheaval: The Gendered Pretext for John Crowe Ransom’s New Critical Approach
4. The Fugitive and the Exile: Theodor W. Adorno, John Crowe Ransom, and The Kenyon Review
pp. 105-108
5. No Two Ways About It: William Empson’s Enabling Modernist Ambiguities
pp. 109-133
6. In Pursuit of Understanding: Louis Untermeyer, Brooks and Warren, and “The Red Wheelbarrow”
pp. 134-150
7. Through Fields of Cacophonous Modern Masters: James Baldwin and New Critical Modernism
pp. 151-168
pp. 171-172
8. “Disagreeable Intellectual Distance”: Theory and Politics in the Old Regionalism of the New Critics
pp. 173-194
9. Teaching with Style: Brooks and Warren’s Literary Pedagogy
pp. 195-217
10. “A Kind of Dual Attentiveness”: Close Reading after the New Criticism
pp. 218-230
Epilogue: Toward a New Close Reading
pp. 231-238
Suggested Readings
pp. 239-240
Contributors
pp. 241-243
pp. 244-257

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Literary Theory and Criticism

Home › Uncategorized › The American New Critics

The American New Critics

By NASRULLAH MAMBROL on March 17, 2016 • ( 1 )

American New Criticism, emerging in the 1920s and especially dominant in the 1940s and 1950s, is equivalent to the establishing of the new professional criticism in the emerging discipline of ‘English’ in British higher education during the inter-war period. As always, origins and explanations for its rise – in its heyday to almost hegemonic proportions – are complex and finally indefinite, but some suggestions may be sketched in. First, a number of the key figures were also part of a group called the Southern Agrarians, or ‘Fugitives’, a traditional, conservative, Southern-oriented movement which was hostile to the hard-nosed industrialism and materialism of a United States dominated by ‘the North’. Without stretching the point too far, a consanguinity with Arnold, Eliot and, later, Leavis in his opposition to modern ‘inorganic’ civilization may be discerned here.

Second, New Criticism’s high point of influence was during the Second World War and the Cold War succeeding it, and we may see that its privileging of literary texts (their ‘order’, ‘harmony’ and ‘transcendence’ of the historically and ideologically determinate) and of the ‘impersonal’ analysis of what makes them great works of art (their innate value lying in their superiority to material history: see below Cleanth Brooks’s essay about Keats’s ‘Ode on a Grecian Urn’) might represent a haven for alienated intellectuals and, indeed, for whole generations of quietistic students. Third, with the huge expansion of the student population in the States in this period, catering for second-generation products of the American ‘melting pot’, New Criticism with its ‘practical criticism’ basis was at once pedagogically economical (copies of short texts could be distributed equally to everyone) and also a way of coping with masses of individuals who had no ‘history’ in common. In other words, its ahistorical, ‘neutral’ nature – the study only of ‘the words on the page’ – was an apparently equalizing, democratic activity appropriate to the new American experience.

But whatever the socio-cultural explanations for its provenance, New Criticism is clearly characterized in premise and practice: it is not concerned with context – historical, biographical, intellectual and so on; it is not interested in the ‘fallacies’ of ‘intention’ or ‘affect’; it is concerned solely with the ‘text in itself’, with its language and organization; it does not seek a text’s ‘meaning’, but how it ‘speaks itself’ (see Archibald MacLeish’s poem ‘Ars Poetica’, itself a synoptic New Critical document, which opens: ‘A poem must not mean/But be’); it is concerned to trace how the parts of the text relate, how it achieves its ‘order’ and ‘harmony’, how it contains and resolves ‘irony’, ‘paradox’, ‘tension’, ‘ambivalence’ and ‘ambiguity’; and it is concerned essentially with articulating the very ‘poem-ness’ – the formal quintessence – of the poem itself (and it usually is a poem – but see Mark Schorer and Wayne Booth, below).

An early, founding essay in the self-identification of New Criticism is John Crowe Ransom’s ‘Criticism, Inc.’ (1937). (His book on Eliot, Richards and others, entitled The New Criticism, 1941, gave the movement its name.) Ransom, one of the ‘Fugitives’ and editor of the Kenyon Review 1939–59, here lays down the ground rules: ‘Criticism, Inc.’ is the ‘business’ of professional – professors of literature in the universities in particular; criticism should become ‘more scientific, or precise and systematic’; students should ‘study literature, and not merely about literature’; Eliot was right to denounce romantic literature as ‘imperfect in objectivity, or “aesthetic distance”’; criticism is not ethical, linguistic or historical studies, which are merely ‘aids’; the critic should be able to exhibit not the ‘prose core’ to which a poem may be reduced but ‘the differentia, residue, or tissue, which keeps the object poetical or entire. The character of the poem resides for the good critic in its way of exhibiting the residuary quality.’

Many of these precepts are given practical application in the work of Cleanth Brooks, himself also a ‘Fugitive’, professional academic, editor of the Southern Review (with Robert Penn Warren) 1935–42, and one of the most skilled and exemplary practitioners of the New Criticism. His and Warren’s textbook anthologies, Understanding Poetry (1938) and Understanding Fiction (1943), are often regarded as having spread the New Critical doctrine throughout generations of American university literature students, but his most characteristic book of close readings is the significantly titled The Well-Wrought Urn: Studies in the Structure of Poetry (1947), in which the essay on the eponymous urn of Keats’s Ode, ‘Keats’s Sylvan Historian: History Without Footnotes’ (1942), is in our view the best exemplification, explicitly and implicitly, of New Critical practice one could hope to find. Brooks at once quotes the opening of MacLeish’s ‘Ars Poetica’ (see above); refers to Eliot and his notion of the ‘objective correlative’; rejects the relevance of biography; reiterates throughout the terms ‘dramatic propriety’, ‘irony’, ‘paradox’ (repeatedly) and ‘organic context’; performs a bravura reading of the poem which leaves its ‘sententious’ final dictum as a dramatically organic element of the whole; constantly admires the poem’s ‘history’ above the ‘actual’ histories of ‘war and peace’, of ‘our time-ridden minds’, of ‘meaningless’ ‘accumulations of facts’, of ‘the scientific and philosophical generalisations which dominate our world’; explicitly praises the poem’s ‘insight into essential truth’; and confirms the poem’s value to us (in 1942, in the midst of the nightmare of wartime history) precisely because, like Keats’s urn, it is ‘All breathing human passion far above’ – thus stressing ‘the ironic fact that all human passion does leave one cloyed; hence the superiority of art’.

As New Criticism is, by definition, a praxis, much of its ‘theory’ occurs along the way in more specifically practical essays (as with Brooks above) and not as theoretical writing (see below, also, for Leavis’s refusal to theorize his position or engage in ‘philosophical’ extrapolation). But there are two New Critical essays in particular which are overtly theoretical and which have become influential texts more generally in modern critical discourse: ‘The Intentional Fallacy’ (1946) and ‘The Affective Fallacy’ (1949), written by W. K. Wimsatt – a professor of English at Yale University and author of the symptomatically titled book, The Verbal Icon: Studies in the Meaning of Poetry (1954) – in collaboration with Monroe C. Beardsley, a philosopher of aesthetics. Both essays, influenced by Eliot and Richards, engage with the ‘addresser’ (writer) –‘message’ (text) –‘addressee’ (reader) nexus outlined in the Introduction, in the pursuit of an ‘objective’ criticism which abjures both the personal input of the writer (‘intention’) and the emotional effect on the reader (‘affect’) in order purely to study the ‘words on the page’ and how the artefact ‘works’. The first essay argues that ‘the design or intention of the author is neither available nor desirable as a standard for judging the success of a work of literary art’; that a poem ‘goes about the world beyond [the author’s] power to intend about it or control it’ – it ‘belongs to the public’; that it should be understood in terms of the ‘dramatic speaker’ of the text, not the author; and be judged only by whether it ‘works’ or not.

Much critical debate has since raged about the place of intention in criticism, and continues to do so: Wimsatt and Beardsley’s position strikes a chord, for example, with poststructuralist notions of the ‘death of the author’ and with deconstruction’s freeing of the text from ‘presence’ and ‘meaning’. But there the resemblance ends, for the New Critics still basically insist that there is a determinate, ontologically stable ‘poem itself’, which is the ultimate arbiter of its own ‘statement’, and that an ‘objective’ criticism is possible. This runs quite counter to deconstruction’s notion of the ‘iterability’ of a text in its multiplex ‘positioned’ rereadings. This difference becomes very much clearer in the second essay, which argues that the ‘affective fallacy’ represents ‘a confusion between the poem and its results’: ‘trying to derive the standard of criticism from the psychological effects of the poem . . . ends in impressionism and relativism’.

Opposing the ‘classical objectivity’ of New Criticism to ‘romantic reader psychology’, it asserts that the outcome of both fallacies is that ‘the poem itself, as an object of specifically critical judgement, tends to disappear’. And the importance of a poem in classic New Critical terms is that by ‘fixing emotions and making them more permanently perceptible’, by the ‘survival’ of ‘its clear and nicely interrelated meanings, its completeness, balance, and tension’, it represents ‘the most precise emotive report on customs’: ‘In short, though cultures have changed, poems remain and explain.’ Poems, in other words, are our cultural heritage, permanent and valuable artefacts; and therein lies the crucial difference from more contemporary theoretical positions.

As we have noted, New Criticism focused principally on poetry, but two essays by Mark Schorer, ‘Technique as Discovery’ (1948) and ‘Fiction and the Analogical Matrix’ (1949), mark the attempt to deploy New Critical practice in relation to prose fiction. In the first of these, Schorer notes: ‘Modern criticism has shown us that to speak of content as such is not to speak of art at all, but of experience; and that it is only when we speak of the achieved content, the form, the work of art as a work of art, that we speak as critics. The difference between content, or experience, and achieved content, or art, is technique.’ This, he adds, has not been followed through in regard to the novel, whose own ‘technique’ is language, and whose own ‘achieved content’ – or ‘discovery’ of what it is saying – can only, as with a poem, be analysed in terms of that ‘technique’. In the second essay, Schorer extends his analysis of the language of fiction by revealing the unconscious patterns of imagery and symbolism (way beyond the author’s ‘intention’) present in all forms of fiction and not just those which foreground a ‘poetic’ discourse. He shows how the author’s ‘meaning’, often contradicting the surface sense, is embedded in the matrix of linguistic analogues which constitute the text. In this we may see connections with later poststructuralist theories’ concern with the sub-texts, ‘silences’, ‘ruptures’, ‘raptures’ and ‘play’ inherent in all texts, however seemingly stable – although Schorer himself, as a good New Critic, does not deconstruct modern novels, but reiterates the coherence of their ‘technique’ in seeking to capture ‘the whole of the modern consciousness . . . the complexity of the modern spirit’. Perhaps it is, rather, that we should sense an affinity between the American New Critic, Schorer, and the English moral formalist, F. R. Leavis , some of whose most famous criticism of fiction in the 1930s and beyond presents ‘the Novel as Dramatic Poem’.

Finally, we should notice another American ‘movement’ of the midtwentieth century which was especially influential in the study of fiction: the so-called ‘Chicago School’ of ‘Neo-Aristotelians’. Theoretically offering a challenge to the New Critics but in fact often seen as only a New Critical ‘heresy’ in their analysis of formal structure and in their belief, with T. S. Eliot, that criticism should study ‘poetry as poetry and not another thing’, the Neo-Aristotelians were centred, from the later 1930s through the 1940s and 1950s, on R. S. Crane at the University of Chicago. Establishing a theoretical basis derived principally from Aristotle’s Rhetoric and Poetics, Crane and his group sought to emulate the logic, lucidity and scrupulous concern with evidence found there; were worried by the limitations of New Critical practice (its rejection of historical analysis, its tendency to present subjective judgements as though they were objective, its concern primarily with poetry); and attempted therefore to develop a more inclusive and catholic criticism which would cover all genres and draw for its techniques, on a ‘pluralistic and instrumentalist’ basis, from whatever method seemed appropriate to a particular case. The anthology Critics and Criticism: Ancient and Modern (1952; abridged edition with Preface by Crane, 1957) contains many examples of their approach, including Crane’s own exemplary reading of Fielding’s Tom Jones, ‘The Concept of Plot and the Plot of Tom Jones’.

In effect, the Neo-Aristotelians were most influential in the study of narrative structure in the novel, and most particularly by way of the work of a slightly later critic, Wayne C. Booth, who nevertheless acknowledged that he was a Chicago Aristotelian. His book The Rhetoric of Fiction (1961) has been widely read and highly regarded, although latterly contemporary critical theory has demonstrated its limitations and inadequacies . Booth’s project was to examine ‘the art of communicating with readers – the rhetorical resources available to the writer of epic, novel or short story as he tries, consciously or unconsciously, to impose his fictional world upon the reader’. Although accepting in New Critical terms that a novel is an ‘autonomous’ text, Booth develops a key concept with the notion that it nevertheless contains an authorial ‘voice’ – the ‘implied author’ (his or her ‘official scribe’ or ‘second self’) – whom the reader invents by deduction from the attitudes articulated in the fiction. Once this distinction between author and the ‘authorial voice’ is made, the way is open to analyse, in and for themselves, the many and various forms of narration which construct the text. A major legacy of Booth’s is his separating out of ‘reliable’ and ‘unreliable’ narrators – the former, usually in the third person, coming close to the values of the ‘implied author’; the latter, often a character within the story, a deviant from them. What Booth did was at once to enhance the formal equipment available for analysis of the ‘rhetoric of fiction’ and, paradoxically perhaps, to promote the belief that authors do mean to ‘impose’ their values on the reader and that ‘reliability’ is therefore a good thing. We may see here a consonance with the ‘moral formalism’ of Leavis, and the reason why poststructuralist narratology has gone beyond Booth.

New Criticism Essay

Criterion: A Journal of Literary Criticism

Criterion: A Journal of Literary Criticism seeks original, well-researched, and intellectually rigorous essays written from diverse critical perspectives and about texts from any time period or literary tradition. We are now accepting submissions for our Winter 2024 issue .

We invite submissions that address texts from different times and places that could help us navigate current issues. Humans have been adapting their environments to suit their needs for millennia, but over the past three centuries, the relationship between humans and their environments has changed drastically. Technological advances have changed the way humans live, work, and interact with each other. As technology advances at an ever-increasing rate, the relationship between humans and technology has become more complex. While in many ways technological advances benefit humans, some advances may be detrimental.

Submissions should be between 3,000 and 6,000 words (not including the bibliography). While not every submission need respond or even relate directly to the prompt, we will prioritize submissions concerning the topic of the intersection between humanity and technology . All submissions should be double-spaced, written in English, and formatted according to the most recent MLA guidelines. Submissions should be uploaded through our online submission system. ( https://scholarsarchive.byu.edu/criterion/ ).

We prioritize undergraduate submissions, but will consider submissions from those who have recently graduated and students pursuing a master's degree. Because we want to help undergraduates publish their work, we do not publish essays by PhD candidates or research scholars.

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New Criticism

2020, Unpublished

A simple, brief introduction to New Criticism. The paper covers its definition, aspects, and how it differs from Russian formalism.

Related Papers

Dr. NASREEN BANU JAMADAR

One of the most influential movements in modern critical scholarship, the New Criticism is a philosophy of literary interpretation that stresses the importance of studying literary texts as complete works of art in themselves. Although the term New Criticism was first coined in the nineteenth century, it was not until American critic and poet John Crow Ransom, founder of the Kenyon Review wrote a book titled The New Criticism (1941) that it became established in common academic and literary usage. In essence, the New Critics were reacting against established trends in American criticism, arguing for the primacy of the literary text instead of focusing on interpretations based on context. However, as René Wellek has noted in various essays detailing the principles of New Criticism, proponents of this theory had many differences among them, and beyond the importance the New Critics afforded the literary text itself, there were many differences in the way they approached critical study of literary texts. Wellek writes that among the growing number of New Critics in the 1930s, there were few that could be easily grouped together. For example, he puts Ransom, Allen Tate, Cleanth Brooks, and Robert Penn Warren among the leaders of what he calls the " Southern Critics. " Mostly, they are grouped together due to their reaction against previously established schools of criticism, such as impressionist criticism, the humanist movement, the naturalist movement, and the Marxists, and the fact that many of them taught at Southern universities at the time they created the theory of New Criticism. In addition to rallying against traditional modes of literary interpretations, the most significant contribution made by the New Critics, according to Wellek, was the success with which they established criticism itself as a major academic discipline. New criticism first started as movement replacing the bio-critical and historical methods that dominated literary studies in the nineteenth and early twentieth centuries. In these methods instead of the text itself, the biographical-historical contexts of the text were examined whereas the text is the sole evidence for interpreting it. The life and times of the author, may be of interest to the historian, but not necessarily to the critic. The text ought not to be confused with its origins:

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Toward an Understanding of the Economics of Misinformation: Evidence from a Demand Side Field Experiment on Critical Thinking

Misinformation represents a vital threat to the societal fabric of modern economies. While the supply side of the misinformation market has begun to receive increased scrutiny, the demand side has received scant attention. We explore the demand for misinformation through the lens of augmenting critical thinking skills in a field experiment during the 2022 Presidential election in Colombia. Data from roughly 2.000 individuals suggest that our treatments enhance critical thinking, causing subjects to more carefully consider the truthfulness of potential misinformation. We furthermore provide evidence that reducing the demand of fake news can deliver on the dual goal of reducing the spread of fake news by encouraging reporting of misinformation.

The opinions and conclusions expressed herein are solely those of the authors and should not be construed as representing the opinions or policies of the sponsoring agencies and research partners. We thank Gustavo Castillo and Maximilian Hippold for their excellent research assistance. This study was reviewed by the University of Chicago IRB and granted an exemption (IRB22-1217). The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

John List is the Chief Economist at Walmart but this research is not part of work at Walmart.

I thank SURA and Protección for funding this project.

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The economic commitment of climate change

Maximilian Kotz ORCID: orcid.org/0000-0003-2564-5043 1 , 2 ,
Anders Levermann ORCID: orcid.org/0000-0003-4432-4704 1 , 2 &
Leonie Wenz ORCID: orcid.org/0000-0002-8500-1568 1 , 3

Nature volume 628 , pages 551–557 ( 2024 ) Cite this article

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Environmental economics
Environmental health
Interdisciplinary studies
Projection and prediction

Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons 1 , 2 , 3 , 4 , 5 , 6 . Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes 7 , 8 . Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

Climate damage projections beyond annual temperature

Paul Waidelich, Fulden Batibeniz, … Sonia I. Seneviratne

Investment incentive reduced by climate damages can be restored by optimal policy

Sven N. Willner, Nicole Glanemann & Anders Levermann

Climate economics support for the UN climate targets

Martin C. Hänsel, Moritz A. Drupp, … Thomas Sterner

Projections of the macroeconomic damage caused by future climate change are crucial to informing public and policy debates about adaptation, mitigation and climate justice. On the one hand, adaptation against climate impacts must be justified and planned on the basis of an understanding of their future magnitude and spatial distribution 9 . This is also of importance in the context of climate justice 10 , as well as to key societal actors, including governments, central banks and private businesses, which increasingly require the inclusion of climate risks in their macroeconomic forecasts to aid adaptive decision-making 11 , 12 . On the other hand, climate mitigation policy such as the Paris Climate Agreement is often evaluated by balancing the costs of its implementation against the benefits of avoiding projected physical damages. This evaluation occurs both formally through cost–benefit analyses 1 , 4 , 5 , 6 , as well as informally through public perception of mitigation and damage costs 13 .

Projections of future damages meet challenges when informing these debates, in particular the human biases relating to uncertainty and remoteness that are raised by long-term perspectives 14 . Here we aim to overcome such challenges by assessing the extent of economic damages from climate change to which the world is already committed by historical emissions and socio-economic inertia (the range of future emission scenarios that are considered socio-economically plausible 15 ). Such a focus on the near term limits the large uncertainties about diverging future emission trajectories, the resulting long-term climate response and the validity of applying historically observed climate–economic relations over long timescales during which socio-technical conditions may change considerably. As such, this focus aims to simplify the communication and maximize the credibility of projected economic damages from future climate change.

In projecting the future economic damages from climate change, we make use of recent advances in climate econometrics that provide evidence for impacts on sub-national economic growth from numerous components of the distribution of daily temperature and precipitation 3 , 7 , 8 . Using fixed-effects panel regression models to control for potential confounders, these studies exploit within-region variation in local temperature and precipitation in a panel of more than 1,600 regions worldwide, comprising climate and income data over the past 40 years, to identify the plausibly causal effects of changes in several climate variables on economic productivity 16 , 17 . Specifically, macroeconomic impacts have been identified from changing daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall that occur in addition to those already identified from changing average temperature 2 , 3 , 18 . Moreover, regional heterogeneity in these effects based on the prevailing local climatic conditions has been found using interactions terms. The selection of these climate variables follows micro-level evidence for mechanisms related to the impacts of average temperatures on labour and agricultural productivity 2 , of temperature variability on agricultural productivity and health 7 , as well as of precipitation on agricultural productivity, labour outcomes and flood damages 8 (see Extended Data Table 1 for an overview, including more detailed references). References 7 , 8 contain a more detailed motivation for the use of these particular climate variables and provide extensive empirical tests about the robustness and nature of their effects on economic output, which are summarized in Methods . By accounting for these extra climatic variables at the sub-national level, we aim for a more comprehensive description of climate impacts with greater detail across both time and space.

Constraining the persistence of impacts

A key determinant and source of discrepancy in estimates of the magnitude of future climate damages is the extent to which the impact of a climate variable on economic growth rates persists. The two extreme cases in which these impacts persist indefinitely or only instantaneously are commonly referred to as growth or level effects 19 , 20 (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for mathematical definitions). Recent work shows that future damages from climate change depend strongly on whether growth or level effects are assumed 20 . Following refs. 2 , 18 , we provide constraints on this persistence by using distributed lag models to test the significance of delayed effects separately for each climate variable. Notably, and in contrast to refs. 2 , 18 , we use climate variables in their first-differenced form following ref. 3 , implying a dependence of the growth rate on a change in climate variables. This choice means that a baseline specification without any lags constitutes a model prior of purely level effects, in which a permanent change in the climate has only an instantaneous effect on the growth rate 3 , 19 , 21 . By including lags, one can then test whether any effects may persist further. This is in contrast to the specification used by refs. 2 , 18 , in which climate variables are used without taking the first difference, implying a dependence of the growth rate on the level of climate variables. In this alternative case, the baseline specification without any lags constitutes a model prior of pure growth effects, in which a change in climate has an infinitely persistent effect on the growth rate. Consequently, including further lags in this alternative case tests whether the initial growth impact is recovered 18 , 19 , 21 . Both of these specifications suffer from the limiting possibility that, if too few lags are included, one might falsely accept the model prior. The limitations of including a very large number of lags, including loss of data and increasing statistical uncertainty with an increasing number of parameters, mean that such a possibility is likely. By choosing a specification in which the model prior is one of level effects, our approach is therefore conservative by design, avoiding assumptions of infinite persistence of climate impacts on growth and instead providing a lower bound on this persistence based on what is observable empirically (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for further exposition of this framework). The conservative nature of such a choice is probably the reason that ref. 19 finds much greater consistency between the impacts projected by models that use the first difference of climate variables, as opposed to their levels.

We begin our empirical analysis of the persistence of climate impacts on growth using ten lags of the first-differenced climate variables in fixed-effects distributed lag models. We detect substantial effects on economic growth at time lags of up to approximately 8–10 years for the temperature terms and up to approximately 4 years for the precipitation terms (Extended Data Fig. 1 and Extended Data Table 2 ). Furthermore, evaluation by means of information criteria indicates that the inclusion of all five climate variables and the use of these numbers of lags provide a preferable trade-off between best-fitting the data and including further terms that could cause overfitting, in comparison with model specifications excluding climate variables or including more or fewer lags (Extended Data Fig. 3 , Supplementary Methods Section 1 and Supplementary Table 1 ). We therefore remove statistically insignificant terms at later lags (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). Further tests using Monte Carlo simulations demonstrate that the empirical models are robust to autocorrelation in the lagged climate variables (Supplementary Methods Section 2 and Supplementary Figs. 4 and 5 ), that information criteria provide an effective indicator for lag selection (Supplementary Methods Section 2 and Supplementary Fig. 6 ), that the results are robust to concerns of imperfect multicollinearity between climate variables and that including several climate variables is actually necessary to isolate their separate effects (Supplementary Methods Section 3 and Supplementary Fig. 7 ). We provide a further robustness check using a restricted distributed lag model to limit oscillations in the lagged parameter estimates that may result from autocorrelation, finding that it provides similar estimates of cumulative marginal effects to the unrestricted model (Supplementary Methods Section 4 and Supplementary Figs. 8 and 9 ). Finally, to explicitly account for any outstanding uncertainty arising from the precise choice of the number of lags, we include empirical models with marginally different numbers of lags in the error-sampling procedure of our projection of future damages. On the basis of the lag-selection procedure (the significance of lagged terms in Extended Data Fig. 1 and Extended Data Table 2 , as well as information criteria in Extended Data Fig. 3 ), we sample from models with eight to ten lags for temperature and four for precipitation (models shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). In summary, this empirical approach to constrain the persistence of climate impacts on economic growth rates is conservative by design in avoiding assumptions of infinite persistence, but nevertheless provides a lower bound on the extent of impact persistence that is robust to the numerous tests outlined above.

Committed damages until mid-century

We combine these empirical economic response functions (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) with an ensemble of 21 climate models (see Supplementary Table 5 ) from the Coupled Model Intercomparison Project Phase 6 (CMIP-6) 22 to project the macroeconomic damages from these components of physical climate change (see Methods for further details). Bias-adjusted climate models that provide a highly accurate reproduction of observed climatological patterns with limited uncertainty (Supplementary Table 6 ) are used to avoid introducing biases in the projections. Following a well-developed literature 2 , 3 , 19 , these projections do not aim to provide a prediction of future economic growth. Instead, they are a projection of the exogenous impact of future climate conditions on the economy relative to the baselines specified by socio-economic projections, based on the plausibly causal relationships inferred by the empirical models and assuming ceteris paribus. Other exogenous factors relevant for the prediction of economic output are purposefully assumed constant.

A Monte Carlo procedure that samples from climate model projections, empirical models with different numbers of lags and model parameter estimates (obtained by 1,000 block-bootstrap resamples of each of the regressions in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) is used to estimate the combined uncertainty from these sources. Given these uncertainty distributions, we find that projected global damages are statistically indistinguishable across the two most extreme emission scenarios until 2049 (at the 5% significance level; Fig. 1 ). As such, the climate damages occurring before this time constitute those to which the world is already committed owing to the combination of past emissions and the range of future emission scenarios that are considered socio-economically plausible 15 . These committed damages comprise a permanent income reduction of 19% on average globally (population-weighted average) in comparison with a baseline without climate-change impacts (with a likely range of 11–29%, following the likelihood classification adopted by the Intergovernmental Panel on Climate Change (IPCC); see caption of Fig. 1 ). Even though levels of income per capita generally still increase relative to those of today, this constitutes a permanent income reduction for most regions, including North America and Europe (each with median income reductions of approximately 11%) and with South Asia and Africa being the most strongly affected (each with median income reductions of approximately 22%; Fig. 1 ). Under a middle-of-the road scenario of future income development (SSP2, in which SSP stands for Shared Socio-economic Pathway), this corresponds to global annual damages in 2049 of 38 trillion in 2005 international dollars (likely range of 19–59 trillion 2005 international dollars). Compared with empirical specifications that assume pure growth or pure level effects, our preferred specification that provides a robust lower bound on the extent of climate impact persistence produces damages between these two extreme assumptions (Extended Data Fig. 3 ).

Estimates of the projected reduction in income per capita from changes in all climate variables based on empirical models of climate impacts on economic output with a robust lower bound on their persistence (Extended Data Fig. 1 ) under a low-emission scenario compatible with the 2 °C warming target and a high-emission scenario (SSP2-RCP2.6 and SSP5-RCP8.5, respectively) are shown in purple and orange, respectively. Shading represents the 34% and 10% confidence intervals reflecting the likely and very likely ranges, respectively (following the likelihood classification adopted by the IPCC), having estimated uncertainty from a Monte Carlo procedure, which samples the uncertainty from the choice of physical climate models, empirical models with different numbers of lags and bootstrapped estimates of the regression parameters shown in Supplementary Figs. 1 – 3 . Vertical dashed lines show the time at which the climate damages of the two emission scenarios diverge at the 5% and 1% significance levels based on the distribution of differences between emission scenarios arising from the uncertainty sampling discussed above. Note that uncertainty in the difference of the two scenarios is smaller than the combined uncertainty of the two respective scenarios because samples of the uncertainty (climate model and empirical model choice, as well as model parameter bootstrap) are consistent across the two emission scenarios, hence the divergence of damages occurs while the uncertainty bounds of the two separate damage scenarios still overlap. Estimates of global mitigation costs from the three IAMs that provide results for the SSP2 baseline and SSP2-RCP2.6 scenario are shown in light green in the top panel, with the median of these estimates shown in bold.

Damages already outweigh mitigation costs

We compare the damages to which the world is committed over the next 25 years to estimates of the mitigation costs required to achieve the Paris Climate Agreement. Taking estimates of mitigation costs from the three integrated assessment models (IAMs) in the IPCC AR6 database 23 that provide results under comparable scenarios (SSP2 baseline and SSP2-RCP2.6, in which RCP stands for Representative Concentration Pathway), we find that the median committed climate damages are larger than the median mitigation costs in 2050 (six trillion in 2005 international dollars) by a factor of approximately six (note that estimates of mitigation costs are only provided every 10 years by the IAMs and so a comparison in 2049 is not possible). This comparison simply aims to compare the magnitude of future damages against mitigation costs, rather than to conduct a formal cost–benefit analysis of transitioning from one emission path to another. Formal cost–benefit analyses typically find that the net benefits of mitigation only emerge after 2050 (ref. 5 ), which may lead some to conclude that physical damages from climate change are simply not large enough to outweigh mitigation costs until the second half of the century. Our simple comparison of their magnitudes makes clear that damages are actually already considerably larger than mitigation costs and the delayed emergence of net mitigation benefits results primarily from the fact that damages across different emission paths are indistinguishable until mid-century (Fig. 1 ).

Although these near-term damages constitute those to which the world is already committed, we note that damage estimates diverge strongly across emission scenarios after 2049, conveying the clear benefits of mitigation from a purely economic point of view that have been emphasized in previous studies 4 , 24 . As well as the uncertainties assessed in Fig. 1 , these conclusions are robust to structural choices, such as the timescale with which changes in the moderating variables of the empirical models are estimated (Supplementary Figs. 10 and 11 ), as well as the order in which one accounts for the intertemporal and international components of currency comparison (Supplementary Fig. 12 ; see Methods for further details).

Damages from variability and extremes

Committed damages primarily arise through changes in average temperature (Fig. 2 ). This reflects the fact that projected changes in average temperature are larger than those in other climate variables when expressed as a function of their historical interannual variability (Extended Data Fig. 4 ). Because the historical variability is that on which the empirical models are estimated, larger projected changes in comparison with this variability probably lead to larger future impacts in a purely statistical sense. From a mechanistic perspective, one may plausibly interpret this result as implying that future changes in average temperature are the most unprecedented from the perspective of the historical fluctuations to which the economy is accustomed and therefore will cause the most damage. This insight may prove useful in terms of guiding adaptation measures to the sources of greatest damage.

Estimates of the median projected reduction in sub-national income per capita across emission scenarios (SSP2-RCP2.6 and SSP2-RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ). a , Impacts arising from all climate variables. b – f , Impacts arising separately from changes in annual mean temperature ( b ), daily temperature variability ( c ), total annual precipitation ( d ), the annual number of wet days (>1 mm) ( e ) and extreme daily rainfall ( f ) (see Methods for further definitions). Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Nevertheless, future damages based on empirical models that consider changes in annual average temperature only and exclude the other climate variables constitute income reductions of only 13% in 2049 (Extended Data Fig. 5a , likely range 5–21%). This suggests that accounting for the other components of the distribution of temperature and precipitation raises net damages by nearly 50%. This increase arises through the further damages that these climatic components cause, but also because their inclusion reveals a stronger negative economic response to average temperatures (Extended Data Fig. 5b ). The latter finding is consistent with our Monte Carlo simulations, which suggest that the magnitude of the effect of average temperature on economic growth is underestimated unless accounting for the impacts of other correlated climate variables (Supplementary Fig. 7 ).

In terms of the relative contributions of the different climatic components to overall damages, we find that accounting for daily temperature variability causes the largest increase in overall damages relative to empirical frameworks that only consider changes in annual average temperature (4.9 percentage points, likely range 2.4–8.7 percentage points, equivalent to approximately 10 trillion international dollars). Accounting for precipitation causes smaller increases in overall damages, which are—nevertheless—equivalent to approximately 1.2 trillion international dollars: 0.01 percentage points (−0.37–0.33 percentage points), 0.34 percentage points (0.07–0.90 percentage points) and 0.36 percentage points (0.13–0.65 percentage points) from total annual precipitation, the number of wet days and extreme daily precipitation, respectively. Moreover, climate models seem to underestimate future changes in temperature variability 25 and extreme precipitation 26 , 27 in response to anthropogenic forcing as compared with that observed historically, suggesting that the true impacts from these variables may be larger.

The distribution of committed damages

The spatial distribution of committed damages (Fig. 2a ) reflects a complex interplay between the patterns of future change in several climatic components and those of historical economic vulnerability to changes in those variables. Damages resulting from increasing annual mean temperature (Fig. 2b ) are negative almost everywhere globally, and larger at lower latitudes in regions in which temperatures are already higher and economic vulnerability to temperature increases is greatest (see the response heterogeneity to mean temperature embodied in Extended Data Fig. 1a ). This occurs despite the amplified warming projected at higher latitudes 28 , suggesting that regional heterogeneity in economic vulnerability to temperature changes outweighs heterogeneity in the magnitude of future warming (Supplementary Fig. 13a ). Economic damages owing to daily temperature variability (Fig. 2c ) exhibit a strong latitudinal polarisation, primarily reflecting the physical response of daily variability to greenhouse forcing in which increases in variability across lower latitudes (and Europe) contrast decreases at high latitudes 25 (Supplementary Fig. 13b ). These two temperature terms are the dominant determinants of the pattern of overall damages (Fig. 2a ), which exhibits a strong polarity with damages across most of the globe except at the highest northern latitudes. Future changes in total annual precipitation mainly bring economic benefits except in regions of drying, such as the Mediterranean and central South America (Fig. 2d and Supplementary Fig. 13c ), but these benefits are opposed by changes in the number of wet days, which produce damages with a similar pattern of opposite sign (Fig. 2e and Supplementary Fig. 13d ). By contrast, changes in extreme daily rainfall produce damages in all regions, reflecting the intensification of daily rainfall extremes over global land areas 29 , 30 (Fig. 2f and Supplementary Fig. 13e ).

The spatial distribution of committed damages implies considerable injustice along two dimensions: culpability for the historical emissions that have caused climate change and pre-existing levels of socio-economic welfare. Spearman’s rank correlations indicate that committed damages are significantly larger in countries with smaller historical cumulative emissions, as well as in regions with lower current income per capita (Fig. 3 ). This implies that those countries that will suffer the most from the damages already committed are those that are least responsible for climate change and which also have the least resources to adapt to it.

Estimates of the median projected change in national income per capita across emission scenarios (RCP2.6 and RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ) are plotted against cumulative national emissions per capita in 2020 (from the Global Carbon Project) and coloured by national income per capita in 2020 (from the World Bank) in a and vice versa in b . In each panel, the size of each scatter point is weighted by the national population in 2020 (from the World Bank). Inset numbers indicate the Spearman’s rank correlation ρ and P -values for a hypothesis test whose null hypothesis is of no correlation, as well as the Spearman’s rank correlation weighted by national population.

To further quantify this heterogeneity, we assess the difference in committed damages between the upper and lower quartiles of regions when ranked by present income levels and historical cumulative emissions (using a population weighting to both define the quartiles and estimate the group averages). On average, the quartile of countries with lower income are committed to an income loss that is 8.9 percentage points (or 61%) greater than the upper quartile (Extended Data Fig. 6 ), with a likely range of 3.8–14.7 percentage points across the uncertainty sampling of our damage projections (following the likelihood classification adopted by the IPCC). Similarly, the quartile of countries with lower historical cumulative emissions are committed to an income loss that is 6.9 percentage points (or 40%) greater than the upper quartile, with a likely range of 0.27–12 percentage points. These patterns reemphasize the prevalence of injustice in climate impacts 31 , 32 , 33 in the context of the damages to which the world is already committed by historical emissions and socio-economic inertia.

Contextualizing the magnitude of damages

The magnitude of projected economic damages exceeds previous literature estimates 2 , 3 , arising from several developments made on previous approaches. Our estimates are larger than those of ref. 2 (see first row of Extended Data Table 3 ), primarily because of the facts that sub-national estimates typically show a steeper temperature response (see also refs. 3 , 34 ) and that accounting for other climatic components raises damage estimates (Extended Data Fig. 5 ). However, we note that our empirical approach using first-differenced climate variables is conservative compared with that of ref. 2 in regard to the persistence of climate impacts on growth (see introduction and Methods section ‘Empirical model specification: fixed-effects distributed lag models’), an important determinant of the magnitude of long-term damages 19 , 21 . Using a similar empirical specification to ref. 2 , which assumes infinite persistence while maintaining the rest of our approach (sub-national data and further climate variables), produces considerably larger damages (purple curve of Extended Data Fig. 3 ). Compared with studies that do take the first difference of climate variables 3 , 35 , our estimates are also larger (see second and third rows of Extended Data Table 3 ). The inclusion of further climate variables (Extended Data Fig. 5 ) and a sufficient number of lags to more adequately capture the extent of impact persistence (Extended Data Figs. 1 and 2 ) are the main sources of this difference, as is the use of specifications that capture nonlinearities in the temperature response when compared with ref. 35 . In summary, our estimates develop on previous studies by incorporating the latest data and empirical insights 7 , 8 , as well as in providing a robust empirical lower bound on the persistence of impacts on economic growth, which constitutes a middle ground between the extremes of the growth-versus-levels debate 19 , 21 (Extended Data Fig. 3 ).

Compared with the fraction of variance explained by the empirical models historically (<5%), the projection of reductions in income of 19% may seem large. This arises owing to the fact that projected changes in climatic conditions are much larger than those that were experienced historically, particularly for changes in average temperature (Extended Data Fig. 4 ). As such, any assessment of future climate-change impacts necessarily requires an extrapolation outside the range of the historical data on which the empirical impact models were evaluated. Nevertheless, these models constitute the most state-of-the-art methods for inference of plausibly causal climate impacts based on observed data. Moreover, we take explicit steps to limit out-of-sample extrapolation by capping the moderating variables of the interaction terms at the 95th percentile of the historical distribution (see Methods ). This avoids extrapolating the marginal effects outside what was observed historically. Given the nonlinear response of economic output to annual mean temperature (Extended Data Fig. 1 and Extended Data Table 2 ), this is a conservative choice that limits the magnitude of damages that we project. Furthermore, back-of-the-envelope calculations indicate that the projected damages are consistent with the magnitude and patterns of historical economic development (see Supplementary Discussion Section 5 ).

Missing impacts and spatial spillovers

Despite assessing several climatic components from which economic impacts have recently been identified 3 , 7 , 8 , this assessment of aggregate climate damages should not be considered comprehensive. Important channels such as impacts from heatwaves 31 , sea-level rise 36 , tropical cyclones 37 and tipping points 38 , 39 , as well as non-market damages such as those to ecosystems 40 and human health 41 , are not considered in these estimates. Sea-level rise is unlikely to be feasibly incorporated into empirical assessments such as this because historical sea-level variability is mostly small. Non-market damages are inherently intractable within our estimates of impacts on aggregate monetary output and estimates of these impacts could arguably be considered as extra to those identified here. Recent empirical work suggests that accounting for these channels would probably raise estimates of these committed damages, with larger damages continuing to arise in the global south 31 , 36 , 37 , 38 , 39 , 40 , 41 , 42 .

Moreover, our main empirical analysis does not explicitly evaluate the potential for impacts in local regions to produce effects that ‘spill over’ into other regions. Such effects may further mitigate or amplify the impacts we estimate, for example, if companies relocate production from one affected region to another or if impacts propagate along supply chains. The current literature indicates that trade plays a substantial role in propagating spillover effects 43 , 44 , making their assessment at the sub-national level challenging without available data on sub-national trade dependencies. Studies accounting for only spatially adjacent neighbours indicate that negative impacts in one region induce further negative impacts in neighbouring regions 45 , 46 , 47 , 48 , suggesting that our projected damages are probably conservative by excluding these effects. In Supplementary Fig. 14 , we assess spillovers from neighbouring regions using a spatial-lag model. For simplicity, this analysis excludes temporal lags, focusing only on contemporaneous effects. The results show that accounting for spatial spillovers can amplify the overall magnitude, and also the heterogeneity, of impacts. Consistent with previous literature, this indicates that the overall magnitude (Fig. 1 ) and heterogeneity (Fig. 3 ) of damages that we project in our main specification may be conservative without explicitly accounting for spillovers. We note that further analysis that addresses both spatially and trade-connected spillovers, while also accounting for delayed impacts using temporal lags, would be necessary to adequately address this question fully. These approaches offer fruitful avenues for further research but are beyond the scope of this manuscript, which primarily aims to explore the impacts of different climate conditions and their persistence.

Policy implications

We find that the economic damages resulting from climate change until 2049 are those to which the world economy is already committed and that these greatly outweigh the costs required to mitigate emissions in line with the 2 °C target of the Paris Climate Agreement (Fig. 1 ). This assessment is complementary to formal analyses of the net costs and benefits associated with moving from one emission path to another, which typically find that net benefits of mitigation only emerge in the second half of the century 5 . Our simple comparison of the magnitude of damages and mitigation costs makes clear that this is primarily because damages are indistinguishable across emissions scenarios—that is, committed—until mid-century (Fig. 1 ) and that they are actually already much larger than mitigation costs. For simplicity, and owing to the availability of data, we compare damages to mitigation costs at the global level. Regional estimates of mitigation costs may shed further light on the national incentives for mitigation to which our results already hint, of relevance for international climate policy. Although these damages are committed from a mitigation perspective, adaptation may provide an opportunity to reduce them. Moreover, the strong divergence of damages after mid-century reemphasizes the clear benefits of mitigation from a purely economic perspective, as highlighted in previous studies 1 , 4 , 6 , 24 .

Historical climate data

Historical daily 2-m temperature and precipitation totals (in mm) are obtained for the period 1979–2019 from the W5E5 database. The W5E5 dataset comes from ERA-5, a state-of-the-art reanalysis of historical observations, but has been bias-adjusted by applying version 2.0 of the WATCH Forcing Data to ERA-5 reanalysis data and precipitation data from version 2.3 of the Global Precipitation Climatology Project to better reflect ground-based measurements 49 , 50 , 51 . We obtain these data on a 0.5° × 0.5° grid from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database. Notably, these historical data have been used to bias-adjust future climate projections from CMIP-6 (see the following section), ensuring consistency between the distribution of historical daily weather on which our empirical models were estimated and the climate projections used to estimate future damages. These data are publicly available from the ISIMIP database. See refs. 7 , 8 for robustness tests of the empirical models to the choice of climate data reanalysis products.

Future climate data

Daily 2-m temperature and precipitation totals (in mm) are taken from 21 climate models participating in CMIP-6 under a high (RCP8.5) and a low (RCP2.6) greenhouse gas emission scenario from 2015 to 2100. The data have been bias-adjusted and statistically downscaled to a common half-degree grid to reflect the historical distribution of daily temperature and precipitation of the W5E5 dataset using the trend-preserving method developed by the ISIMIP 50 , 52 . As such, the climate model data reproduce observed climatological patterns exceptionally well (Supplementary Table 5 ). Gridded data are publicly available from the ISIMIP database.

Historical economic data

Historical economic data come from the DOSE database of sub-national economic output 53 . We use a recent revision to the DOSE dataset that provides data across 83 countries, 1,660 sub-national regions with varying temporal coverage from 1960 to 2019. Sub-national units constitute the first administrative division below national, for example, states for the USA and provinces for China. Data come from measures of gross regional product per capita (GRPpc) or income per capita in local currencies, reflecting the values reported in national statistical agencies, yearbooks and, in some cases, academic literature. We follow previous literature 3 , 7 , 8 , 54 and assess real sub-national output per capita by first converting values from local currencies to US dollars to account for diverging national inflationary tendencies and then account for US inflation using a US deflator. Alternatively, one might first account for national inflation and then convert between currencies. Supplementary Fig. 12 demonstrates that our conclusions are consistent when accounting for price changes in the reversed order, although the magnitude of estimated damages varies. See the documentation of the DOSE dataset for further discussion of these choices. Conversions between currencies are conducted using exchange rates from the FRED database of the Federal Reserve Bank of St. Louis 55 and the national deflators from the World Bank 56 .

Future socio-economic data

Baseline gridded gross domestic product (GDP) and population data for the period 2015–2100 are taken from the middle-of-the-road scenario SSP2 (ref. 15 ). Population data have been downscaled to a half-degree grid by the ISIMIP following the methodologies of refs. 57 , 58 , which we then aggregate to the sub-national level of our economic data using the spatial aggregation procedure described below. Because current methodologies for downscaling the GDP of the SSPs use downscaled population to do so, per-capita estimates of GDP with a realistic distribution at the sub-national level are not readily available for the SSPs. We therefore use national-level GDP per capita (GDPpc) projections for all sub-national regions of a given country, assuming homogeneity within countries in terms of baseline GDPpc. Here we use projections that have been updated to account for the impact of the COVID-19 pandemic on the trajectory of future income, while remaining consistent with the long-term development of the SSPs 59 . The choice of baseline SSP alters the magnitude of projected climate damages in monetary terms, but when assessed in terms of percentage change from the baseline, the choice of socio-economic scenario is inconsequential. Gridded SSP population data and national-level GDPpc data are publicly available from the ISIMIP database. Sub-national estimates as used in this study are available in the code and data replication files.

Climate variables

Following recent literature 3 , 7 , 8 , we calculate an array of climate variables for which substantial impacts on macroeconomic output have been identified empirically, supported by further evidence at the micro level for plausible underlying mechanisms. See refs. 7 , 8 for an extensive motivation for the use of these particular climate variables and for detailed empirical tests on the nature and robustness of their effects on economic output. To summarize, these studies have found evidence for independent impacts on economic growth rates from annual average temperature, daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall. Assessments of daily temperature variability were motivated by evidence of impacts on agricultural output and human health, as well as macroeconomic literature on the impacts of volatility on growth when manifest in different dimensions, such as government spending, exchange rates and even output itself 7 . Assessments of precipitation impacts were motivated by evidence of impacts on agricultural productivity, metropolitan labour outcomes and conflict, as well as damages caused by flash flooding 8 . See Extended Data Table 1 for detailed references to empirical studies of these physical mechanisms. Marked impacts of daily temperature variability, total annual precipitation, the number of wet days and extreme daily rainfall on macroeconomic output were identified robustly across different climate datasets, spatial aggregation schemes, specifications of regional time trends and error-clustering approaches. They were also found to be robust to the consideration of temperature extremes 7 , 8 . Furthermore, these climate variables were identified as having independent effects on economic output 7 , 8 , which we further explain here using Monte Carlo simulations to demonstrate the robustness of the results to concerns of imperfect multicollinearity between climate variables (Supplementary Methods Section 2 ), as well as by using information criteria (Supplementary Table 1 ) to demonstrate that including several lagged climate variables provides a preferable trade-off between optimally describing the data and limiting the possibility of overfitting.

We calculate these variables from the distribution of daily, d , temperature, T x , d , and precipitation, P x , d , at the grid-cell, x , level for both the historical and future climate data. As well as annual mean temperature, ${\bar{T}}_{x,y}$ , and annual total precipitation, P x , y , we calculate annual, y , measures of daily temperature variability, ${\widetilde{T}}_{x,y}$ :

the number of wet days, Pwd x , y :

and extreme daily rainfall:

in which T x , d , m , y is the grid-cell-specific daily temperature in month m and year y , ${\bar{T}}_{x,m,{y}}$ is the year and grid-cell-specific monthly, m , mean temperature, D m and D y the number of days in a given month m or year y , respectively, H the Heaviside step function, 1 mm the threshold used to define wet days and P 99.9 x is the 99.9th percentile of historical (1979–2019) daily precipitation at the grid-cell level. Units of the climate measures are degrees Celsius for annual mean temperature and daily temperature variability, millimetres for total annual precipitation and extreme daily precipitation, and simply the number of days for the annual number of wet days.

We also calculated weighted standard deviations of monthly rainfall totals as also used in ref. 8 but do not include them in our projections as we find that, when accounting for delayed effects, their effect becomes statistically indistinct and is better captured by changes in total annual rainfall.

Spatial aggregation

We aggregate grid-cell-level historical and future climate measures, as well as grid-cell-level future GDPpc and population, to the level of the first administrative unit below national level of the GADM database, using an area-weighting algorithm that estimates the portion of each grid cell falling within an administrative boundary. We use this as our baseline specification following previous findings that the effect of area or population weighting at the sub-national level is negligible 7 , 8 .

Empirical model specification: fixed-effects distributed lag models

Following a wide range of climate econometric literature 16 , 60 , we use panel regression models with a selection of fixed effects and time trends to isolate plausibly exogenous variation with which to maximize confidence in a causal interpretation of the effects of climate on economic growth rates. The use of region fixed effects, μ r , accounts for unobserved time-invariant differences between regions, such as prevailing climatic norms and growth rates owing to historical and geopolitical factors. The use of yearly fixed effects, η y , accounts for regionally invariant annual shocks to the global climate or economy such as the El Niño–Southern Oscillation or global recessions. In our baseline specification, we also include region-specific linear time trends, k r y , to exclude the possibility of spurious correlations resulting from common slow-moving trends in climate and growth.

The persistence of climate impacts on economic growth rates is a key determinant of the long-term magnitude of damages. Methods for inferring the extent of persistence in impacts on growth rates have typically used lagged climate variables to evaluate the presence of delayed effects or catch-up dynamics 2 , 18 . For example, consider starting from a model in which a climate condition, C r , y , (for example, annual mean temperature) affects the growth rate, Δlgrp r , y (the first difference of the logarithm of gross regional product) of region r in year y :

which we refer to as a ‘pure growth effects’ model in the main text. Typically, further lags are included,

and the cumulative effect of all lagged terms is evaluated to assess the extent to which climate impacts on growth rates persist. Following ref. 18 , in the case that,

the implication is that impacts on the growth rate persist up to NL years after the initial shock (possibly to a weaker or a stronger extent), whereas if

then the initial impact on the growth rate is recovered after NL years and the effect is only one on the level of output. However, we note that such approaches are limited by the fact that, when including an insufficient number of lags to detect a recovery of the growth rates, one may find equation ( 6 ) to be satisfied and incorrectly assume that a change in climatic conditions affects the growth rate indefinitely. In practice, given a limited record of historical data, including too few lags to confidently conclude in an infinitely persistent impact on the growth rate is likely, particularly over the long timescales over which future climate damages are often projected 2 , 24 . To avoid this issue, we instead begin our analysis with a model for which the level of output, lgrp r , y , depends on the level of a climate variable, C r , y :

Given the non-stationarity of the level of output, we follow the literature 19 and estimate such an equation in first-differenced form as,

which we refer to as a model of ‘pure level effects’ in the main text. This model constitutes a baseline specification in which a permanent change in the climate variable produces an instantaneous impact on the growth rate and a permanent effect only on the level of output. By including lagged variables in this specification,

we are able to test whether the impacts on the growth rate persist any further than instantaneously by evaluating whether α L > 0 are statistically significantly different from zero. Even though this framework is also limited by the possibility of including too few lags, the choice of a baseline model specification in which impacts on the growth rate do not persist means that, in the case of including too few lags, the framework reverts to the baseline specification of level effects. As such, this framework is conservative with respect to the persistence of impacts and the magnitude of future damages. It naturally avoids assumptions of infinite persistence and we are able to interpret any persistence that we identify with equation ( 9 ) as a lower bound on the extent of climate impact persistence on growth rates. See the main text for further discussion of this specification choice, in particular about its conservative nature compared with previous literature estimates, such as refs. 2 , 18 .

We allow the response to climatic changes to vary across regions, using interactions of the climate variables with historical average (1979–2019) climatic conditions reflecting heterogenous effects identified in previous work 7 , 8 . Following this previous work, the moderating variables of these interaction terms constitute the historical average of either the variable itself or of the seasonal temperature difference, ${\hat{T}}_{r}$ , or annual mean temperature, ${\bar{T}}_{r}$ , in the case of daily temperature variability 7 and extreme daily rainfall, respectively 8 .

The resulting regression equation with N and M lagged variables, respectively, reads:

in which Δlgrp r , y is the annual, regional GRPpc growth rate, measured as the first difference of the logarithm of real GRPpc, following previous work 2 , 3 , 7 , 8 , 18 , 19 . Fixed-effects regressions were run using the fixest package in R (ref. 61 ).

Estimates of the coefficients of interest α i , L are shown in Extended Data Fig. 1 for N = M = 10 lags and for our preferred choice of the number of lags in Supplementary Figs. 1 – 3 . In Extended Data Fig. 1 , errors are shown clustered at the regional level, but for the construction of damage projections, we block-bootstrap the regressions by region 1,000 times to provide a range of parameter estimates with which to sample the projection uncertainty (following refs. 2 , 31 ).

Spatial-lag model

In Supplementary Fig. 14 , we present the results from a spatial-lag model that explores the potential for climate impacts to ‘spill over’ into spatially neighbouring regions. We measure the distance between centroids of each pair of sub-national regions and construct spatial lags that take the average of the first-differenced climate variables and their interaction terms over neighbouring regions that are at distances of 0–500, 500–1,000, 1,000–1,500 and 1,500–2000 km (spatial lags, ‘SL’, 1 to 4). For simplicity, we then assess a spatial-lag model without temporal lags to assess spatial spillovers of contemporaneous climate impacts. This model takes the form:

in which SL indicates the spatial lag of each climate variable and interaction term. In Supplementary Fig. 14 , we plot the cumulative marginal effect of each climate variable at different baseline climate conditions by summing the coefficients for each climate variable and interaction term, for example, for average temperature impacts as:

These cumulative marginal effects can be regarded as the overall spatially dependent impact to an individual region given a one-unit shock to a climate variable in that region and all neighbouring regions at a given value of the moderating variable of the interaction term.

Constructing projections of economic damage from future climate change

We construct projections of future climate damages by applying the coefficients estimated in equation ( 10 ) and shown in Supplementary Tables 2 – 4 (when including only lags with statistically significant effects in specifications that limit overfitting; see Supplementary Methods Section 1 ) to projections of future climate change from the CMIP-6 models. Year-on-year changes in each primary climate variable of interest are calculated to reflect the year-to-year variations used in the empirical models. 30-year moving averages of the moderating variables of the interaction terms are calculated to reflect the long-term average of climatic conditions that were used for the moderating variables in the empirical models. By using moving averages in the projections, we account for the changing vulnerability to climate shocks based on the evolving long-term conditions (Supplementary Figs. 10 and 11 show that the results are robust to the precise choice of the window of this moving average). Although these climate variables are not differenced, the fact that the bias-adjusted climate models reproduce observed climatological patterns across regions for these moderating variables very accurately (Supplementary Table 6 ) with limited spread across models (<3%) precludes the possibility that any considerable bias or uncertainty is introduced by this methodological choice. However, we impose caps on these moderating variables at the 95th percentile at which they were observed in the historical data to prevent extrapolation of the marginal effects outside the range in which the regressions were estimated. This is a conservative choice that limits the magnitude of our damage projections.

Time series of primary climate variables and moderating climate variables are then combined with estimates of the empirical model parameters to evaluate the regression coefficients in equation ( 10 ), producing a time series of annual GRPpc growth-rate reductions for a given emission scenario, climate model and set of empirical model parameters. The resulting time series of growth-rate impacts reflects those occurring owing to future climate change. By contrast, a future scenario with no climate change would be one in which climate variables do not change (other than with random year-to-year fluctuations) and hence the time-averaged evaluation of equation ( 10 ) would be zero. Our approach therefore implicitly compares the future climate-change scenario to this no-climate-change baseline scenario.

The time series of growth-rate impacts owing to future climate change in region r and year y , δ r , y , are then added to the future baseline growth rates, π r , y (in log-diff form), obtained from the SSP2 scenario to yield trajectories of damaged GRPpc growth rates, ρ r , y . These trajectories are aggregated over time to estimate the future trajectory of GRPpc with future climate impacts:

in which GRPpc r , y =2020 is the initial log level of GRPpc. We begin damage estimates in 2020 to reflect the damages occurring since the end of the period for which we estimate the empirical models (1979–2019) and to match the timing of mitigation-cost estimates from most IAMs (see below).

For each emission scenario, this procedure is repeated 1,000 times while randomly sampling from the selection of climate models, the selection of empirical models with different numbers of lags (shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) and bootstrapped estimates of the regression parameters. The result is an ensemble of future GRPpc trajectories that reflect uncertainty from both physical climate change and the structural and sampling uncertainty of the empirical models.

Estimates of mitigation costs

We obtain IPCC estimates of the aggregate costs of emission mitigation from the AR6 Scenario Explorer and Database hosted by IIASA 23 . Specifically, we search the AR6 Scenarios Database World v1.1 for IAMs that provided estimates of global GDP and population under both a SSP2 baseline and a SSP2-RCP2.6 scenario to maintain consistency with the socio-economic and emission scenarios of the climate damage projections. We find five IAMs that provide data for these scenarios, namely, MESSAGE-GLOBIOM 1.0, REMIND-MAgPIE 1.5, AIM/GCE 2.0, GCAM 4.2 and WITCH-GLOBIOM 3.1. Of these five IAMs, we use the results only from the first three that passed the IPCC vetting procedure for reproducing historical emission and climate trajectories. We then estimate global mitigation costs as the percentage difference in global per capita GDP between the SSP2 baseline and the SSP2-RCP2.6 emission scenario. In the case of one of these IAMs, estimates of mitigation costs begin in 2020, whereas in the case of two others, mitigation costs begin in 2010. The mitigation cost estimates before 2020 in these two IAMs are mostly negligible, and our choice to begin comparison with damage estimates in 2020 is conservative with respect to the relative weight of climate damages compared with mitigation costs for these two IAMs.

Data availability

Data on economic production and ERA-5 climate data are publicly available at https://doi.org/10.5281/zenodo.4681306 (ref. 62 ) and https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , respectively. Data on mitigation costs are publicly available at https://data.ene.iiasa.ac.at/ar6/#/downloads . Processed climate and economic data, as well as all other necessary data for reproduction of the results, are available at the public repository https://doi.org/10.5281/zenodo.10562951 (ref. 63 ).

Code availability

All code necessary for reproduction of the results is available at the public repository https://doi.org/10.5281/zenodo.10562951 (ref. 63 ).

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Acknowledgements

We gratefully acknowledge financing from the Volkswagen Foundation and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the Government of the Federal Republic of Germany and Federal Ministry for Economic Cooperation and Development (BMZ).

Open access funding provided by Potsdam-Institut für Klimafolgenforschung (PIK) e.V.

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All authors contributed to the design of the analysis. M.K. conducted the analysis and produced the figures. All authors contributed to the interpretation and presentation of the results. M.K. and L.W. wrote the manuscript.

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Extended data figures and tables

Extended data fig. 1 constraining the persistence of historical climate impacts on economic growth rates..

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature ( a ), daily temperature variability ( b ), total annual precipitation ( c ), the number of wet days ( d ) and extreme daily precipitation ( e ) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a – e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R 2 , Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2 . The resulting models without later lags are shown in Supplementary Figs. 1 – 3 .

Extended Data Fig. 2 Incremental lag-selection procedure using information criteria and within-region R 2 .

Starting from a panel-based fixed-effects distributed lag model estimating the effects of climate on economic growth using the real historical data (as in equation ( 4 )) with ten lags for all climate variables (as shown in Extended Data Fig. 1 ), lags are incrementally removed for one climate variable at a time. The resulting Bayesian and Akaike information criteria are shown in a – e and f – j , respectively, and the within-region R 2 and number of observations in k – o and p – t , respectively. Different rows show the results when removing lags from different climate variables, ordered from top to bottom as annual mean temperature, daily temperature variability, total annual precipitation, the number of wet days and extreme annual precipitation. Information criteria show minima at approximately four lags for precipitation variables and ten to eight for temperature variables, indicating that including these numbers of lags does not lead to overfitting. See Supplementary Table 1 for an assessment using information criteria to determine whether including further climate variables causes overfitting.

Extended Data Fig. 3 Damages in our preferred specification that provides a robust lower bound on the persistence of climate impacts on economic growth versus damages in specifications of pure growth or pure level effects.

Estimates of future damages as shown in Fig. 1 but under the emission scenario RCP8.5 for three separate empirical specifications: in orange our preferred specification, which provides an empirical lower bound on the persistence of climate impacts on economic growth rates while avoiding assumptions of infinite persistence (see main text for further discussion); in purple a specification of ‘pure growth effects’ in which the first difference of climate variables is not taken and no lagged climate variables are included (the baseline specification of ref. 2 ); and in pink a specification of ‘pure level effects’ in which the first difference of climate variables is taken but no lagged terms are included.

Extended Data Fig. 4 Climate changes in different variables as a function of historical interannual variability.

Changes in each climate variable of interest from 1979–2019 to 2035–2065 under the high-emission scenario SSP5-RCP8.5, expressed as a percentage of the historical variability of each measure. Historical variability is estimated as the standard deviation of each detrended climate variable over the period 1979–2019 during which the empirical models were identified (detrending is appropriate because of the inclusion of region-specific linear time trends in the empirical models). See Supplementary Fig. 13 for changes expressed in standard units. Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Extended Data Fig. 5 Contribution of different climate variables to overall committed damages.

a , Climate damages in 2049 when using empirical models that account for all climate variables, changes in annual mean temperature only or changes in both annual mean temperature and one other climate variable (daily temperature variability, total annual precipitation, the number of wet days and extreme daily precipitation, respectively). b , The cumulative marginal effects of an increase in annual mean temperature of 1 °C, at different baseline temperatures, estimated from empirical models including all climate variables or annual mean temperature only. Estimates and uncertainty bars represent the median and 95% confidence intervals obtained from 1,000 block-bootstrap resamples from each of three different empirical models using eight, nine or ten lags of temperature terms.

Extended Data Fig. 6 The difference in committed damages between the upper and lower quartiles of countries when ranked by GDP and cumulative historical emissions.

Quartiles are defined using a population weighting, as are the average committed damages across each quartile group. The violin plots indicate the distribution of differences between quartiles across the two extreme emission scenarios (RCP2.6 and RCP8.5) and the uncertainty sampling procedure outlined in Methods , which accounts for uncertainty arising from the choice of lags in the empirical models, uncertainty in the empirical model parameter estimates, as well as the climate model projections. Bars indicate the median, as well as the 10th and 90th percentiles and upper and lower sixths of the distribution reflecting the very likely and likely ranges following the likelihood classification adopted by the IPCC.

Supplementary information

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Kotz, M., Levermann, A. & Wenz, L. The economic commitment of climate change. Nature 628 , 551–557 (2024). https://doi.org/10.1038/s41586-024-07219-0

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Fatal Traffic Risks With a Total Solar Eclipse in the US

1 Department of Medicine, University of Toronto, Toronto, Ontario, Canada
2 Evaluative Clinical Science Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
3 Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
4 Division of General Internal Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
5 Center for Leading Injury Prevention Practice Education & Research, Toronto, Ontario, Canada
6 Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
7 Centre for Clinical Epidemiology & Evaluation, University of British Columbia, Vancouver, British Columbia, Canada

A total solar eclipse occurs when the moon temporarily obscures the sun and casts a dark shadow across the earth. This astronomical spectacle has been described for more than 3 millennia and can be predicted with high precision. Eclipse-related solar retinopathy (vision loss from staring at the sun) is an established medical complication; however, other medical outcomes have received little attention. 1

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About 1 in 5 U.S. teens who’ve heard of ChatGPT have used it for schoolwork

Roughly one-in-five teenagers who have heard of ChatGPT say they have used it to help them do their schoolwork, according to a new Pew Research Center survey of U.S. teens ages 13 to 17. With a majority of teens having heard of ChatGPT, that amounts to 13% of all U.S. teens who have used the generative artificial intelligence (AI) chatbot in their schoolwork.

A bar chart showing that, among teens who know of ChatGPT, 19% say they’ve used it for schoolwork.

Teens in higher grade levels are particularly likely to have used the chatbot to help them with schoolwork. About one-quarter of 11th and 12th graders who have heard of ChatGPT say they have done this. This share drops to 17% among 9th and 10th graders and 12% among 7th and 8th graders.

There is no significant difference between teen boys and girls who have used ChatGPT in this way.

The introduction of ChatGPT last year has led to much discussion about its role in schools , especially whether schools should integrate the new technology into the classroom or ban it .

Pew Research Center conducted this analysis to understand American teens’ use and understanding of ChatGPT in the school setting.

The Center conducted an online survey of 1,453 U.S. teens from Sept. 26 to Oct. 23, 2023, via Ipsos. Ipsos recruited the teens via their parents, who were part of its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey was weighted to be representative of U.S. teens ages 13 to 17 who live with their parents by age, gender, race and ethnicity, household income, and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the questions used for this analysis , along with responses, and its methodology .

Teens’ awareness of ChatGPT

Overall, two-thirds of U.S. teens say they have heard of ChatGPT, including 23% who have heard a lot about it. But awareness varies by race and ethnicity, as well as by household income:

A horizontal stacked bar chart showing that most teens have heard of ChatGPT, but awareness varies by race and ethnicity, household income.

72% of White teens say they’ve heard at least a little about ChatGPT, compared with 63% of Hispanic teens and 56% of Black teens.
75% of teens living in households that make $75,000 or more annually have heard of ChatGPT. Much smaller shares in households with incomes between $30,000 and $74,999 (58%) and less than $30,000 (41%) say the same.

Teens who are more aware of ChatGPT are more likely to use it for schoolwork. Roughly a third of teens who have heard a lot about ChatGPT (36%) have used it for schoolwork, far higher than the 10% among those who have heard a little about it.

When do teens think it’s OK for students to use ChatGPT?

For teens, whether it is – or is not – acceptable for students to use ChatGPT depends on what it is being used for.

There is a fair amount of support for using the chatbot to explore a topic. Roughly seven-in-ten teens who have heard of ChatGPT say it’s acceptable to use when they are researching something new, while 13% say it is not acceptable.

A diverging bar chart showing that many teens say it’s acceptable to use ChatGPT for research; few say it’s OK to use it for writing essays.

However, there is much less support for using ChatGPT to do the work itself. Just one-in-five teens who have heard of ChatGPT say it’s acceptable to use it to write essays, while 57% say it is not acceptable. And 39% say it’s acceptable to use ChatGPT to solve math problems, while a similar share of teens (36%) say it’s not acceptable.

Some teens are uncertain about whether it’s acceptable to use ChatGPT for these tasks. Between 18% and 24% say they aren’t sure whether these are acceptable use cases for ChatGPT.

Those who have heard a lot about ChatGPT are more likely than those who have only heard a little about it to say it’s acceptable to use the chatbot to research topics, solve math problems and write essays. For instance, 54% of teens who have heard a lot about ChatGPT say it’s acceptable to use it to solve math problems, compared with 32% among those who have heard a little about it.

Note: Here are the questions used for this analysis , along with responses, and its methodology .

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Many Americans think generative AI programs should credit the sources they rely on

Americans’ use of chatgpt is ticking up, but few trust its election information, q&a: how we used large language models to identify guests on popular podcasts, striking findings from 2023, what the data says about americans’ views of artificial intelligence, most popular.

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6 Common Leadership Styles — and How to Decide Which to Use When

Rebecca Knight

Being a great leader means recognizing that different circumstances call for different approaches.

Research suggests that the most effective leaders adapt their style to different circumstances — be it a change in setting, a shift in organizational dynamics, or a turn in the business cycle. But what if you feel like you’re not equipped to take on a new and different leadership style — let alone more than one? In this article, the author outlines the six leadership styles Daniel Goleman first introduced in his 2000 HBR article, “Leadership That Gets Results,” and explains when to use each one. The good news is that personality is not destiny. Even if you’re naturally introverted or you tend to be driven by data and analysis rather than emotion, you can still learn how to adapt different leadership styles to organize, motivate, and direct your team.

Much has been written about common leadership styles and how to identify the right style for you, whether it’s transactional or transformational, bureaucratic or laissez-faire. But according to Daniel Goleman, a psychologist best known for his work on emotional intelligence, “Being a great leader means recognizing that different circumstances may call for different approaches.”

RK Rebecca Knight is a journalist who writes about all things related to the changing nature of careers and the workplace. Her essays and reported stories have been featured in The Boston Globe, Business Insider, The New York Times, BBC, and The Christian Science Monitor. She was shortlisted as a Reuters Institute Fellow at Oxford University in 2023. Earlier in her career, she spent a decade as an editor and reporter at the Financial Times in New York, London, and Boston.

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Millions of gamers advance biomedical research

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Leveraging gamers and video game technology can dramatically boost scientific research according to a new study published today in Nature Biotechnology .

4.5 million gamers around the world have advanced medical science by helping to reconstruct microbial evolutionary histories using a minigame included inside the critically and commercially successful video game, Borderlands 3 . Their playing has led to a significantly refined estimate of the relationships of microbes in the human gut. The results of this collaboration will both substantially advance our knowledge of the microbiome and improve on the AI programs that will be used to carry out this work in future.

Tracing the evolutionary relationships of bacteria

By playing Borderlands Science , a mini-game within the looter-shooter video game Borderlands 3 , these players have helped trace the evolutionary relationships of more than a million different kinds of bacteria that live in the human gut, some of which play a crucial role in our health. This information represents an exponential increase in what we have discovered about the microbiome up till now. By aligning rows of tiles which represent the genetic building blocks of different microbes, humans have been able to take on tasks that even the best existing computer algorithms have been unable to solve yet.

The project was led by McGill University researchers, developed in collaboration with Gearbox Entertainment Company , an award-winning interactive entertainment company, and Massively Multiplayer Online Science ( MMOS ) , a Swiss IT company connecting scientists to video games), and supported by the expertise and genomic material from the Microsetta Initiative led by Rob Knight from the Departments of Pediatrics, Bioengineering, and Computer Science & Engineering at the University of California San Diego.

Humans improve on existing algorithms and lay groundwork for the future

Not only have the gamers improved on the results produced by the existing programs used to analyze DNA sequences, but they are also helping lay the groundwork for improved AI programs that can be used in future.

“We didn’t know whether the players of a popular game like Borderlands 3 would be interested or whether the results would be good enough to improve on what was already known about microbial evolution. But we’ve been amazed by the results.” says Jérôme Waldispühl , an associate professor in McGill’s School of Computer Science and senior author on the paper published today. “In half a day, the Borderlands Science players collected five times more data about microbial DNA sequences than our earlier game, Phylo , had collected over a 10-year period.”

The idea for integrating DNA analysis into a commercial video game with mass market appeal came from Attila Szantner, an adjunct professor in McGill’s School of Computer Science and CEO and co-founder of MMOS . “As almost half of the world population is playing with videogames, it is of utmost importance that we find new creative ways to extract value from all this time and brainpower that we spend gaming,” says Szantner. “ Borderlands Science shows how far we can get by teaming up with the game industry and its communities to tackle the big challenges of our times.”

“Gearbox’s developers were eager to engage millions of Borderlands players globally with our creation of an appealing in-game experience to demonstrate how clever minds playing Borderlands are capable of producing tangible, useful, and valuable scientific data at a level not approachable with non-interactive technology and mediums,” said Randy Pitchford , founder and CEO of Gearbox Entertainment Company. “I'm proud that Borderlands Science has become one of the largest and most accomplished citizen science projects of all time, forecasting the opportunity for similar projects in future video games and pushing the boundaries of the positive effect that video games can make on the world.”

Relating microbes to disease and lifestyle

The tens of trillions of microbes that colonize our bodies play a crucial role in maintaining human health. But microbial communities can change over time in response to factors such as diet, medications, and lifestyle habits.

Because of the sheer number of microbes involved, scientists are still only in the early days of being able to identify which microorganisms are affected by, or can affect, which conditions.

Which is why the researchers’ project and the results from the gamers are so important.

“We expect to be able to use this information to relate specific kinds of microbes to what we eat, to how we age, and to the many diseases ranging from inflammatory bowel disease to Alzheimer’s that we now know microbes to be involved in,” adds Knight, who also directs the Center for Microbiome Innovation at the UC San Diego. “Because evolution is a great guide to function, having a better tree relating our microbes to one another gives us a more precise view of what they are doing within and around us.”

Building communities to advance knowledge

“Here we have 4.5 million people who contributed to science. In a sense, this result is theirs too and they should feel proud about it,” says Waldispühl . “It shows that we can fight the fear or misconceptions that members of the public may have about science and start building communities who work collectively to advance knowledge.”

“ Borderlands Science created an incredible opportunity to engage with citizen scientists on a novel and important problem, using data generated by a separate massive citizen science project,” adds Daniel McDonald, the Scientific Director of the Microsetta Initiative. “These results demonstrate the remarkable value of open access data, and the scale of what is possible with inclusive practices in scientific endeavors.”

“ Improving microbial phylogeny with citizen science within a mass-market video game ” by Roman Sarrazin-Gendron et al was published in Nature Biotechnology DOI: 10.1038/s41587-024-02175-6

The research was funded in part by Genome Canada and Génome Québec.

About McGill University

Founded in Montreal, Quebec, in 1821, McGill University is Canada’s top ranked medical doctoral university. McGill is consistently ranked as one of the top universities, both nationally and internationally. It is a world-renowned institution of higher learning with research activities spanning three campuses, 12 faculties, 14 professional schools, 300 programs of study and over 39,000 students, including more than 10,400 graduate students. McGill attracts students from over 150 countries around the world, its 12,000 international students making up 30% of the student body. Over half of McGill students claim a first language other than English, including approximately 20% of our students who say French is their mother tongue. 

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Data from roughly 2.000 individuals suggest that our treatments enhance critical thinking, causing subjects to more carefully consider the truthfulness of potential misinformation. We furthermore provide evidence that reducing the demand of fake news can deliver on the dual goal of reducing the spread of fake news by encouraging reporting of ...
The economic commitment of climate change
Analysis of projected sub-national damages from temperature and precipitation show an income reduction of 19% of the world economy within the next 26 years independent of future emission choices.
Fatal Traffic Risks With a Total Solar Eclipse in the US
Antiretroviral Drugs for HIV Treatment and Prevention in Adults - 2022 IAS-USA Recommendations CONSERVE 2021 Guidelines for Reporting Trials Modified for the COVID-19 Pandemic Creation and Adoption of Large Language Models in Medicine Global Burden of Cancer, 2010-2019 Global Burden of Long COVID Global Burden of Melanoma Global Burden of Skin ...
Use of ChatGPT for schoolwork among US teens
About 1 in 5 U.S. teens who've heard of ChatGPT have used it for schoolwork. By. Olivia Sidoti and Jeffrey Gottfried. (Maskot/Getty Images) Roughly one-in-five teenagers who have heard of ChatGPT say they have used it to help them do their schoolwork, according to a new Pew Research Center survey of U.S. teens ages 13 to 17.
6 Common Leadership Styles
Summary. Research suggests that the most effective leaders adapt their style to different circumstances — be it a change in setting, a shift in organizational dynamics, or a turn in the business ...
Millions of gamers advance biomedical research
Largest global citizen science project accelerates knowledge of human microbiome Leveraging gamers and video game technology can dramatically boost scientific research according to a new study published today in Nature Biotechnology. 4.5 million gamers around the world have advanced medical science by helping to reconstruct microbial evolutionary histories using a minigame included inside the ...