Showing papers on "Counterfactual conditional published in 2007"

Hunting Causes and Using Them: Approaches in Philosophy and Economics

Abstract: Introduction Part I. Plurality in Causality: 1. Preamble 2. Causation: one word, many things 3. Causes: warranting them and using them 4. Where is the theory in our 'theories' of causality? Part II. Case Studies: Bayes-nets and Invariance Theories: 5. Preamble 6. What is wrong with Bayes-nets? 7. Modularity: it can - and generally does - fail 8. Against modularity, the causal Markov condition and any link between the two: comments on Hausman and Woodward 9. From metaphysics to method: comments on manipulability and the causal Markov condition 10. Two theorems on invariance and causality Part III. Causal Theories in Economics: 11. Preamble 12. Probabilities and experiments 13. How to get causes from probabilities: Cartwright on Simon on causation 14. The merger of cause and strategy: Hoover on Simon on causation 15. The vanity of rigour in economics: theoretical models and Galilean experiments 16. Counterfactuals in economics: a commentary.

When Can History Be Our Guide? The Pitfalls of Counterfactual Inference

Abstract: Inferences about counterfactuals are essential for prediction, answering “what if” questions, and estimating causal effects. However, when the counterfactuals posed are too far from the data at hand, conclusions drawn from well-specified statistical analyses become based on speculation and convenient but indefensible model assumptions rather than empirical evidence. Unfortunately, standard statistical approaches assume the veracity of the model rather than revealing the degree of model-dependence, so this problem can be hard to detect. We develop easy-to-apply methods to evaluate counterfactuals that do not require sensitivity testing over specified classes of models. If an analysis fails the tests we offer, then we know that substantive results are sensitive to at least some modeling choices that are not based on empirical evidence. We use these methods to evaluate the extensive scholarly literatures on the effects of changes in the degree of democracy in a country (on any dependent variable) and separate analyses of the effects of UN peacebuilding efforts. We find evidence that many scholars are inadvertently drawing conclusions based more on modeling hypotheses than on evidence in the data. For some research questions, history contains insufficient information to be our guide. Free software that accompanies this paper implements all our suggestions.

Structural equations and causation

Abstract: Structural equations have become increasingly popular in recent years as tools for understanding causation. But standard structural equations approaches to causation face deep problems. The most philosophically interesting of these consists in their failure to incorporate a distinction between default states of an object or system, and deviations therefrom. Exploring this problem, and how to fix it, helps to illuminate the central role this distinction plays in our causal thinking.

Implications of Counterfactual Structure for Creative Generation and Analytical Problem Solving

Abstract: In the present research, the authors hypothesized that additive counterfactual thinking mind-sets, activated by adding new antecedent elements to reconstruct reality, promote an expansive processing style that broadens conceptual attention and facilitates performance on creative generation tasks, whereas subtractive counter-factual thinking mind-sets, activated by removing antecedent elements to reconstruct reality, promote a relational processing style that enhances tendencies to consider relationships and associations and facilitates performance on analytical problem-solving tasks. A reanalysis of a published data set suggested that the counterfactual mind-set primes previously used in the literature tend to evoke subtractive counterfactuals. Studies 1 and 2 then demonstrated that subtractive counterfactual mind-sets enhanced performance on analytical problem-solving tasks relative to additive counterfactual mind-sets, whereas Studies 3 and 4 found that additive counterfactual mind-sets enhanced perform...

Counterfactual scorekeeping

Abstract: Orthodoxy has it that counterfactuals cannot be treated as strict conditionals. But there is a loophole: if the strictness is a function of context then maybe they can be so treated. I argue for a loophole analysis that treats ‘would’-counterfactuals as strict conditionals that are duals to ‘might’- counterfactuals. Most of the work lies in getting straight about the interaction between context and semantic value. I treat it as a general feature of the dynamics of conversational score.

Précis of The rational imagination: how people create alternatives to reality.

Abstract: The human imagination remains one of the last uncharted terrains of the mind. People often imagine how events might have turned out "if only" something had been different. The "fault lines" of reality, those aspects more readily changed, indicate that counterfactual thoughts are guided by the same principles as rational thoughts. In the past, rationality and imagination have been viewed as opposites. But research has shown that rational thought is more imaginative than cognitive scientists had supposed. In The Rational Imagination, I argue that imaginative thought is more rational than scientists have imagined. People exhibit remarkable similarities in the sorts of things they change in their mental representation of reality when they imagine how the facts could have turned out differently. For example, they tend to imagine alternatives to actions rather than inactions, events within their control rather than those beyond their control, and socially unacceptable events rather than acceptable ones. Their thoughts about how an event might have turned out differently lead them to judge that a strong causal relation exists between an antecedent event and the outcome, and their thoughts about how an event might have turned out the same lead them to judge that a weaker causal relation exists. In a simple temporal sequence, people tend to imagine alternatives to the most recent event. The central claim in the book is that counterfactual thoughts are organised along the same principles as rational thought. The idea that the counterfactual imagination is rational depends on three steps: (1) humans are capable of rational thought; (2) they make inferences by thinking about possibilities; and (3) their counterfactual thoughts rely on thinking about possibilities, just as rational thoughts do. The sorts of possibilities that people envisage explain the mutability of certain aspects of mental representations and the immutability of other aspects.

What counterfactuals can be tested

Abstract: Counterfactual statements, e.g., "my headache would be gone had I taken an aspirin" are central to scientific discourse, and are formally interpreted as statements derived from "alternative worlds". However, since they invoke hypothetical states of affairs, often incompatible with what is actually known or observed, testing counterfactuals is fraught with conceptual and practical difficulties. In this paper, we provide a complete characterization of "testable counterfactuals," namely, counterfactual statements whose probabilities can be inferred from physical experiments. We provide complete procedures for discerning whether a given counterfactual is testable and, if so, expressing its probability in terms of experimental data.

Canceling updating in the comprehension of counterfactuals embedded in narratives.

Abstract: Participants were given counterfactual sentences—for example, “If Mary had won the lottery she would have bought a Mercedes car” —or factual sentences—for example, “Because Mary won the lottery, she bought a Mercedes car” —embedded in short narratives. Reading times showed that readers were immediately sensitive to the special status of counterfactual information (Experiment 1). In addition, probe-recognition latencies demonstrated that old information was more accessible in counterfactual than in factual stories, and new information was equally accessible in both kinds of stories (Experiment 2). However, after reading additional clauses, new information became less accessible in counterfactual than in factual stories (Experiment 3). These results suggest that counterfactual events are momentarily represented but are later suppressed and the readers’ attention goes back to previous events in the story.

When aspect matters: the case of would -conditionals

Abstract: Differences in the interpretation of would-conditionals with simple (perfective) and perfect antecedent clauses are marked enough to discourage a unified view. However, this paper presents a unified, Lewis–Stalnaker style semantics for the modal in such constructions. Differences in the interpretation of the conditionals are derived from the interaction between the interpretation of different types of aspect and the modal. The paper makes a distinction between perfective and perfect aspect in terms of whether they make reference to or quantify over Lewis-style events. In making reference to Lewis-events, perfective aspect is shown to be incompatible with counterfactual would-conditionals. The so-called ‘epistemic flavor’ of perfective conditionals about the future is derived from the use of diagonalization as an interpretive strategy called upon to resolve reference.

Philosophical knowledge and knowledge of counterfactuals

Abstract: Metaphysical modalities are definable from counterfactual conditionals, and the epistemology of the former is a special case of the epistemology of the latter. In particular, the role of conceivability and inconceivability in assessing claims of possibility and impossibility can be explained as a special case of the pervasive role of the imagination in assessing counterfactual conditionals, an account of which is sketched. Thus scepticism about metaphysical modality entails a more far-reaching scepticism about counterfactuals. The account is used to question the significance of the distinction between a priori and a posteriori knowledge.

Were, would, might and a compositional account of counterfactuals

Abstract: This paper has two purposes. We first give a new dynamic account of epistemic modal operators that account for both their test-like behaviour with respect to whole information states and their capacity to induce quantificational dependencies across worlds (modal subordination). We then use this theory, together with an analysis of conditionals and irrealis moods, to give a fully compositional semantics of indicative and counterfactual conditionals. In our analysis, the distinction between counterfactual and indicative conditionals follows directly from the interaction between the semantics of the conditional and irrealis operators and the semantics of the particular modals involved in the conditional consequent. We indicate some theoretical and logical consequences of our approach.

From counterfactuals to sufficient component causes and vice versa.

Abstract: The sufficient component cause model and the counterfactual model have now become cornerstones for causal thinking in epidemiology. Dana Flanders' paper [I] provides a nice exposition of certain rela tionships that hold between these two forms of causal models. The sufficient component cause model con siders sets of actions, events or states of nature which together inevitably bring about the outcome under consideration. The model gives an account of the causes of a particular effect. It addresses the question, "Given a particular effect, what are the various events which might have been its cause?" The potential outcomes or counterfactual model focuses on one particular cause or intervention and gives an account of the various effects of that cause. In contrast to the sufficient component cause framework, the potential outcomes framework addresses the question, "What would have occurred if a particular factor were intervened upon and thus set to a different level than it in fact was?" Unlike the sufficient component cause framework, the counterfactual framework does not require a detailed knowledge of the mechanisms by which the factor affects the outcome. This feature of the counterfactual framework makes it well suited to formalize causal effects in randomized experiments in which only data on exposure and outcome are available. Both the sufficient component cause and the counterfactual models have a long history in the philosophical and in the epidemiologic-statistical lit erature. The philosophical ideas behind counterfac tual models can be traced back at least as far as Hume [2], who defined a cause as a relation between two objects "where, if the first object had not been, the second never [would have] existed."' The philos ophy of counterfactuals has been developed exten sively by Lewis [3, 4] and has received considerable

On the relation between counterfactual and causal reasoning

Abstract: We critique the distinction Byrne makes between strong causes and enabling conditions, and its implications, on both theoretical and empirical grounds. First, we believe that the difference is psychological, not logical. Second, we disagree that there is a strict “dichotomy between the focus of counterfactual and causal thoughts.” Third, we disagree that it is easier for people to generate causes than counterfactuals.

Counterfactual Thought Experiments: A Necessary Teaching Tool

Abstract: COUNTERFACTUALS are routinely used in physical and biological sciences to develop and evaluate sophisticated, non-linear models. They have been used with telling effect in the study of economic history and American politics.' For some historians, counterfactual arguments have no scholarly standing. They consider them flights of fancy, fun over a beer or two in the faculty club, but not the stuff of serious research.2 This dismissive attitude may be encouraged by the emergence and popularity of counterfactual historical works as a fictional genre, and the uncomfortable similarities between some recent works ofcounterfactual scholarship and such fiction. Nevertheless, counterfactuals are an effective research tool, but comprehending this requires a clear understanding of their nature, the circumstances to which they are best suited, and robust protocols for conducting thought experiments. With these ends in mind, I begin by exploring the differences between counterfactual and so-called "factual" arguments and offer the proposition that the difference between them is greatly exaggerated; it is one of degree, not of kind. I go on to discuss different uses ofcounterfactual thought experiments for historians. I distinguish between miracle and plausible world and scholarly and folk counterfactuals, and their respective uses, and I propose several criteria to guide plausible world counterfactuals. I conclude by looking at the special problems of applying counterfactual analysis to a problem

When a small difference makes a big difference: counterfactual thinking and luck

Abstract: Counterfactuals affect the way we feel about events. Failures become worse when we consider how they could have been avoided, and successes become more special and memorable when contrasted with the possibility of failure. Ben Ze’ev (1996, 2000) claims that all emotions are basically of a comparative nature. They arise when we compare our current situation to our prior state, to our goals and expectations, to other people’s conditions, and to purely imagined, counterfactual outcomes. Evaluations based on downward comparisons make us usually feel better, and upward comparisons make us usually feel worse, by a mechanism of affective contrast (Markman and McMullen 2003).

Evaluative stance and counterfactuals in language and literature

Abstract: This article argues that speakers often express attitudes not only toward events that have happened, but also toward counterfactual events; speakers communicate these attitudes by expressing an evaluative stance toward counterfactual scenarios. By analyzing examples from a variety of discourse situations, from conversation to canonical literature, the author demonstrates that counterfactuals and evaluations function jointly to produce rhetorical effects. The options for expressing evaluative stance are described in detail, as are the four configurations of focal scenario and evaluative stance that may arise in discourse. By considering the connection between evaluative stance and emotion, the author explains the rhetorical connection between counterfactuals and feelings of relief and regret. With this theoretical and methodological framework established, the article then moves to consider the role of counterfactuals and evaluative stance in literature. In literature, different speakers, including characte...

Counterfactuals in Quantum Mechanics

Abstract: The truth value of a counterfactual is decided by the analysis of similarities between the actual and possible counterfactual worlds [1]. The difference between a counterfactual (or counterfactual conditional) and a simple conditional: If A, then B, is that in the actual world A is not true and we need some “miracle” in the counterfactual world to make it true. In the analysis of counterfactuals out of the scope of physics, this miracle is crucial for deciding whether B is true. In physics, however, miracles are not involved. Typically: A : A measurement M is performed B : The outcome of M has property P .

Laws of Nature: do we need a metaphysics?

Abstract: In this paper, I briefly present the regularity and necessity views and assess their difficulties. I construe scientific laws as universal propositions satisfied by empirically successful scientific models and made — approximately — true by the real systems represented, albeit partially, by these models. I also conceive a scientific theory as a set of models together with a set of propositions, some of which are laws. A scientific law is a universal proposition or statement that belongs to a scientific theory. Scientific laws also are laws of nature since we can provide arguments in favour of natural causal powers that ground the truth of laws. I argue that the truth of counterfactual conditional statements and the occurrence of regularities in nature provide good reasons to believe that real causal powers exist in nature and that the (approximate) truth of scientific laws is based on a metaphysics of nature.

Reversing the Counterfactual Analysis of Causation

Abstract: The counterfactual analysis of causation has focused on one particular counterfactual conditional, taking as its starting‐point the suggestion that C causes E iff (∼C □→ ∼E). In this paper, some consequences are explored of reversing this counterfactual, and developing an account starting with the idea that C causes E iff (∼E □→ ∼C). This suggestion is discussed in relation to the problem of pre‐emption. It is found that the ‘reversed’ counterfactual analysis can handle even the most difficult cases of pre‐emption with only minimal complications. The paper closes with a discussion of the wider philosophical implications of developing a reversed counterfactual analysis, especially concerning the differentiation of causes from causal conditions, causation by absences, and the extent to which causes suffice for their effects.

Causation, Counterfactuals, and Critical Reading in the Active Classroom

Abstract: Identifying causal claims may be second nature to a seasoned scholar, but the logic of causality is not always so obvious to the undergraduates in our classrooms. In this article I describe the essential features of a reading assignment designed to hone critical thinking skills, especially as they pertain to cause and effect and the associated logic of counterfactual reasoning. The “Critical Reading Exercise” (or CRE) is a brief, highly structured assignment that calls upon the student to read a scholarly article or book chapter and identify the major thesis and key causal relationships presented by the author as well as develop a plausible counterfactual implied by the argument. Among the advantages of the CRE are the incentive it provides to do careful, critical reading of genuine scholarly work and lay the foundation for fruitful discussion in an active learning classroom. Common pitfalls associated with this assignment are also identified. Ultimately the assignment reflects an appropriate way to engage students with both the substance and the methodological foundation of our discipline.

Causal explanation and manipulation

Abstract: Causal explanation proceeds by citing the causes of the explanandum. Any model of causal explanation requires a specification of the relation between cause and effect in virtue of which citing the cause explains the effect. In particular, it requires a specification of what it is for the explanandum to be causally dependent on the explanans and what types of things (broadly understood) the explanans are. There have been a number of such models. For the benefit of the unfamiliar reader, here is a brief statement of some major views. On David Lewis’s account, c causally explains e if c is connected to e with a network of causal chains. For him, causal explanation consists in presenting portions of explanatory information captured by the causal network. On Wesley Salmon’s reading, c causally explains e if c is connected with e by a suitable continuous causal (i.e., capable of transmitting a mark) process. On the standard deductive-nomological reading of causal explanation, for c to causally explain e, c must be a nomologically sufficient condition for e. And for John Mackie, for c to causally explain e there must be event-types C and E such that C is an inus-condition for E. In a series of papers and a book, James Woodward (1997, 2000, 2002, 2003a, 2003b) has put forward a ‘manipulationist’ account of causal explanation. Briefly put, c causally explains e if e causally depends on c, where the notion of causal dependence is understood in terms of relevant (interventionist) counterfactual, that is counterfactuals that describe the outcomes of interventions. A bit more accurately, c causally explains e if, were c to be (actually or counterfactually) manipulated, e would change too. This model ties causal explanation to actual and counterfactual experiments that show how manipulation of factors mentioned in the explanans would alter the explanandum. It also stresses the role of invariant relationships, as opposed to strict laws, in causal explanation. Explanation in this model consists in answering a network of “what-if-things-had-been-different questions”, thereby placing the explanandum within a pattern of counterfactual dependencies (cf. Woodward 2003a, p. 201). For instance, the law of ideal gases is said to be explanatory not because it renders a certain explanandum (e.g., that the pressure of a certain gas increased) nomically expected, but because it can tell us how the

The Limitations of Economic Counterfactuals: The Case of the Lancashire Textile Industry

Abstract: The article presents a history of the Lancashire cotton textile industry from the perspective of decision-making entrepreneurs as embedded historical actors, in contradistinction to the economics-based counterfactuals that dominate the recent historiography of the industry.A simulation approach is used to recreate the decision- making parameters faced by entrepreneurs and is used to support a genealogical path-dependent interpretation to overcome the problems of teleology and hindsight. Using historical evidence and evidence from the simulation, a critique of three economics-based counterfactuals is developed. These are the Lazonick counterfactual, the Keynesian counterfactual and the neo-classical counterfactual. It is shown that none of these take into account the full context of the decisions that were taken and none therefore offer a convincing explanation of the collapse of the industry.

Thinking developmentally about counterfactual possibilities

Abstract: Byrne implies that working memory development underpins children's ability to represent counterfactuals as possibilities at 3 to 4 years of age. Recent findings suggest that (1) developments in the ability to consider alternatives to reality in children of this age are underpinned by improvements in inhibitory control, not working memory, and (2) children do not develop an understanding of counterfactuals as possibilities until mid-childhood.

Conjunctions, Disjunctions and Lewisian Semantics for Counterfactuals

Abstract: Consider the reasonable axioms of subjunctive conditionals (1) if p q 1 and p q 2 at some world, then p (q 1 & q 2) at that world, and (2) if p 1 q and p 2 q at some world, then (p 1 ∨ p 2) q at that world, where p q is the subjunctive conditional. I show that a Lewis-style semantics for subjunctive conditionals satisfies these axioms if and only if one makes a certain technical assumption about the closeness relation, an assumption that is probably false. I will then show how Lewisian semantics can be modified so as to assure (1) and (2) even when the technical assumption fails, and in fact in one sense the semantics actually becomes simpler then.

Narrating near-histories: The effects of counterfactual communication on motivation and performance

Abstract: While research on counterfactuals has demonstrated that thinking counterfactually (imagining how past events could have been different) improves organizationally relevant outcomes, little is known about the effects of narrating these near-histories, or explicitly communicating counterfactuals, on these outcomes. In this article, I advance a framework for understanding the counterfactual communication-performance relationship. Building on previous work linking counterfactual communication with impression formation, I propose that counterfactual communication influences motivation and subsequent performance through its effects on impression formation. Findings from an experiment demonstrated that individuals who received upward counterfactuals (thoughts of how things could have been better) were more motivated than were those who received downward counterfactuals (thoughts of how things could have been worse), and this motivation led to superior performance. Additionally, receivers’ impressions of ...

Effects of Fact Mutability in the Interpretation of Counterfactuals

Abstract: Effects of Fact Mutability in the Interpretation of Counterfactuals Morteza Dehghani (morteza@northwestern.edu) Department of EECS, 2145 Sheridan Rd Evanston, IL 60208-0834 USA Rumen Iliev (r-iliev@northwestern.edu) Department of Psychology, 2029 Sheridan Road Evanston, IL 60208-2710 USA Stefan Kaufmann (kaufmann@northwestern.edu) Department of Linguistics, 2016 Sheridan Road Evanston, IL 60208-4090 USA 2000) and the psychological evidence supporting this model. Also in the same section, we review Hiddelston’s (2005) extension to Causal Bayesian Networks. We then discuss Kahneman and Miller’s Norm Theory (1986) and two psychological experiments designed to test the correctness of the predictions of the AI models. Abstract This paper explores the relationship between fact mutability, intervention and human evaluation of counterfactual conditionals. Two experiments are reported that show the effects of causal strength and causal distance on fact mutability and intervention. Subjects’ answers are compared to the predictions of three models of counterfactual reasoning in Artificial Intelligence. This comparison demonstrates that logical inferences and graph topologies are not sufficient for modeling all aspects of human counterfactual reasoning. The Stalnaker/Lewis Theory Many models of counterfactual reasoning are inspired by the model-theoretic accounts of Stalnaker (1968) and Lewis (1973). Minor differences aside, both crucially rely on a notion of comparative similarity between possible worlds relative to the “actual” world i of evaluation. Thus Lewis’s truth conditions state that a counterfactual ‘If it were that Antecedent, then it would be that Consequent’ (A € C) is then true at world i “if and only if, if there is an antecedent- world accessible from i, then the consequent holds at every antecedent-world at least as close to i as a certain accessible antecedent-world” (p. 49). Assuming for simplicity that there is a set of A-worlds that are maximally similar to i, this means that the counterfactual A € C is true if and only if C is true in all of those maximally similar A-worlds. Stalnaker and Lewis account for various logical properties of counterfactuals by imposing conditions on the underlying similarity relation, but neither attempts a detailed analysis of this notion. However, Lewis (1979), noting that his theory “must be fleshed out with an account of the appropriate similarity relation, and this will differ from context to context,” gives an informal ranked list of general “weights or priorities” in determining similarity: first, to avoid big, widespread, diverse violations of law; second, to maximize the spatio-temporal region of perfect match of particular fact; third, to avoid small, localized violations of law; fourth, to secure approximate similarity of particular facts. Despite the informality of these guidelines, one can discern a priority of laws over particular fact, and of “big” discrepancies over “small” ones. Much of the subsequent work on modeling counterfactual reasoning is based on similar intuitions and can be viewed as attempts to make the notion of similarity more precise. However, in view of Keywords: Counterfactual Reasoning; Causal Networks; Norm Theory. Introduction Counterfactual reasoning has long been a subject of interest to philosophers (e.g. Leibniz, 1686; Hume, 1748; Goodman, 1947; Lewis, 1973; Stalnaker, 1968). More recently linguists, psychologist, and later on cognitive scientists, have become interested in the study of the concept of “what would have been” and how reasoning about events that almost happened provides us with knowledge that cannot be deduced from simple facts or indicative conditionals (e.g. Kahneman and Miller, 1986; Sternberg and Gastel, 1989). In the last two decades there have been several attempts to model counterfactual reasoning in AI (Ginsberg, 1986; Costello and McCarthy, 1999; Pearl, 2000; Hiddleston, 2005, among others). The advantage of such formal models is that they make precise predictions for particular cases. In this paper we briefly review two of these models and demonstrate using evidence from two psychological experiments that these models do not capture the full spectrum of human counterfactual reasoning. Specifically, we illustrate how causal distance and causal strength affect the interpretation of counterfactual statements. In conclusion, we argue that utilizing the psychological findings on fact mutability and similarity are crucial to building cognitively plausible computational models of counterfactual reasoning. First, we briefly review the Stalnaker/Lewis theory of counterfactuals. Next, we discuss Causal Bayesian Networks (Spirtes, Glymour, and Scheines, 1993; Pearl,

Omitted Variables, Intent, and Counterfactuals: A Response to Michael H. Nelson

Abstract: working on similar sets of questions—critiquing and building on one another's work—knowledge accumulation is more likely to occur."1 It is with this statement in mind that I proceed with my response to Michael Nelson's thoughtful critique on my previous article (see Allen Hicken, "Party Fabrication: Constitutional Reform and the Rise of Thai Rack Thai," Journal of East Asian Studies 6, no. 3 [2006]: 381-407). Rather than a point-by-point rebuttal, I will focus on three of the most interest ing and challenging of Nelson's theoretical critiques. The first substantive issue concerns the charge of omitted variable bias—specifically, in refer ence to the omission of local political groups from a macro-institutional account. The second and third criticisms are more methodological. First, can we or should we ascribe motives to political actors? Second, how can we use counterfactuals to solve problems of observational equivalence?

Counterfactuals, Causation, and Preemption

Abstract: Publisher Summary This chapter provides an overview of the concepts related to counterfactuals, causation, and preemption. A counterfactual is a conditional statement in the subjunctive mood. The philosophical importance of counterfactuals stems from the fact that they seem to be closely connected to the concept of causation. The counterfactual “If A were true, then C would be true” with antecedent A and consequent C is sometimes written “A 1→ C” in order to distinguish it from other kinds of conditional statement. For example, the counterfactual must be distinguished from both the material conditional of first-order logic, and the “strict conditional” of entailment. The truth-functional material conditional “A → C” is logically equivalent to “∼A V C” and thus has truth-conditions weaker than those of the corresponding counterfactual conditional. Not every counterfactual with a false antecedent or a true consequent is true. This chapter presents the standard Stalnaker–Lewis semantics for the counterfactual conditional and develops some of the logical features of counterfactuals. It presents Lewis's original counterfactual theory of causation, and explains the problems that eventually led him to abandon the theory in its original form. The chapter also discusses the current state of counterfactual theories of causation, by presenting three recent contending accounts, due to Lewis, Yablo, and Hall.

Counterfactuals need not be comparative: The case of “As if”

Abstract: Byrne (2005) assumes that counterfactual thinking requires a comparison of facts with an imagined alternative. In our view, however, this assumption is unnecessarily restrictive. We argue that individuals do not necessarily engage in counterfactual simulations exclusively to evaluate factual reality. Instead, comparative evaluation is often suspended in favor of experiencing the counterfactual simulation as if it were real.

Causation and counterfactual dependence

Abstract: Recently Stephen Barker has raised stimulating objections to the thesis that, roughly speaking, if two events stand in a relation of counterfactual dependence, they stand in a causal relation. As Ned Hall says, however, this thesis constitutes the strongest part of the counterfactual analysis of causation. Therefore, if successful, Barker’s objections will undermine the cornerstone of the counterfactual analysis of causation, and hence give us compelling reasons to reject the counterfactual analysis of causation. I will argue, however, that they do not withstand scrutiny.