Relevant bibliographies by topics / Causality

Academic literature on the topic 'Causality'

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Published: 4 June 2021
Last updated: 26 July 2024

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Journal articles on the topic "Causality"

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Piaget, J. "La causalité chez l'enfant (Children's understanding of causality)." British Journal of Psychology 100, S1 (April 2009): 207–24. http://dx.doi.org/10.1348/000712608x336059.

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Dhavamony, Mariasusai. "Causality." International Philosophical Quarterly 31, no. 2 (1991): 173–87. http://dx.doi.org/10.5840/ipq19913125.

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Sacksteder, William. "CAUSALITY." Southwest Philosophy Review 16, no. 2 (2000): 31–58. http://dx.doi.org/10.5840/swphilreview200016250.

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VanderWeele, Tyler. "Causality." Journal of the Royal Statistical Society: Series A (Statistics in Society) 174, no. 1 (January 2011): 243–44. http://dx.doi.org/10.1111/j.1467-985x.2010.00676_7.x.

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Choi, Tina Young, and Edward Jones-Imhotep. "Causality." Victorian Literature and Culture 46, no. 3-4 (2018): 604–8. http://dx.doi.org/10.1017/s1060150318000360.

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Janes, Joseph. "Causality." Library Hi Tech 19, no. 2 (June 2001): 191–93. http://dx.doi.org/10.1108/07378830110733946.

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Brooks, Michael. "Causality." New Scientist 262, no. 3492 (May 2024): 35. http://dx.doi.org/10.1016/s0262-4079(24)00975-8.

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Minguzzi, E. "K-Causality Coincides with Stable Causality." Communications in Mathematical Physics 290, no. 1 (April 4, 2009): 239–48. http://dx.doi.org/10.1007/s00220-009-0794-4.

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Cravo, Andre Mascioli, Karin Moreira Santos, Marcelo Bussotti Reyes, Marcelo Salvador Caetano, and Peter M. E. Claessens. "Visual Causality Judgments Correlate with the Phase of Alpha Oscillations." Journal of Cognitive Neuroscience 27, no. 10 (October 2015): 1887–94. http://dx.doi.org/10.1162/jocn_a_00832.

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The detection of causality is essential for our understanding of whether distinct events relate. A central requirement for the sensation of causality is temporal contiguity: As the interval between events increases, causality ratings decrease; for intervals longer than approximately 100 msec, the events start to appear independent. It has been suggested that this effect might be due to perception relying on discrete processing. According to this view, two events may be judged as sequential or simultaneous depending on their temporal relationship within a discrete neuronal process. To assess if alpha oscillations underlie this discrete neuronal process, we investigated how these oscillations modulate the judgment of causality. We used the classic launching effect with concurrent recording of EEG signal. In each trial, a disk moved horizontally toward a second disk at the center of the screen and stopped when they touched each other. After a delay that varied between 0 and 400 msec after contact, the right disk began to move. Participants were instructed to judge whether or not they had a feeling that the first disk caused the movement of the second disk. We found that frontocentral alpha phase significantly biased causality estimates. Moreover, we found that alpha phase was concentrated around different angles for trials in which participants judged events as causally related versus not causally related. We conclude that alpha phase plays a key role in biasing causality judgments.
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Arif, Abubakar, and R. Rosiyana Dewi. "ANALISIS KAUSALITAS ANTARA PENERIMAAN PAJAK DENGAN TINGKAT KEGIATAN EKONOMI INDONESIA DENGAN PENDEKATAN GRANGER CAUSALITY." JURNAL INFORMASI, PERPAJAKAN, AKUNTANSI, DAN KEUANGAN PUBLIK 8, no. 1 (May 7, 2019): 1. http://dx.doi.org/10.25105/jipak.v8i1.4502.

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<p>The purpose of this study is to analysis the causality between tax revenue and economy activity in Indonesia period 1990-2010. The design of this research used time series analysis model with Granger Causality Model with the step analusis are (1) determine long of lag to know how long tax revenue and economy activity influence, (2) determine causality test to proof there are causality or there are correlation one direction between tax revenue and economy activity, (3) analyze the power of correlation or influence between tax revenue and economy activity after the result of causali8ty test was reach. The analysis used in this research was time serieswith annual data,starting 1990 too 2010. Tax revenue and economy activity with proxy product domestic bruto are valuables used in this study. The result of this study are not find causality between tax revenue and economy activity in Indonesia but one direction correlation when tax revenue influence economy activity.By the regression analysis can proff that tax revenue influence significant positive to economy activity with multiplier effect less than 1.</p>
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Dissertations / Theses on the topic "Causality"

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Al, Sadoon Trujillo Majid. "Causality along subspaces." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609157.

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Jatta, Abdullah. "Test of Causality in Conditional Variance Hafner and Herwatz Test for Causality." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-47701.

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Wachter, Daniel von. "Modality, causality, and God." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289017.

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Murphy, David V. J. "Time, causality, and concurrency." Thesis, University of Surrey, 1989. http://epubs.surrey.ac.uk/976/.

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Cattle, Kirsty. "Faecal incontinence : obstetric causality." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/faecal-incontinence-obstetric-causality(c98b4d67-566b-4e5c-b17b-6546387d30ea).html.

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Introduction: Faecal incontinence is more common in parous women who have had a difficult vaginal delivery. However, the pathophysiology of the injury resulting in faecal incontinence in such women is incompletely understood. This study therefore aimed to compare anal canal and pelvic floor parameters between continent and incontinent women and measure these during pregnancy and after delivery in order to more fully understand the initial insult to the pelvic floor. Methods: Anal manometry and fatigue (using a water-filled microballoon) and pelvic floor strength and fatigue (using an air-filled vaginal probe connected to a Peritron) were measured in 30 primiparous women at booking, end of pregnancy and 6 months post partum. Ten of these women also underwent measurement of pelvis size using ultrasound. A further 61 women, 39 incontinent and 22 continent, also underwent these measurements in order to compare pelvic floor parameters between continent and incontinent women. Results: Voluntary contraction of the external anal sphincter (EAS) was significantly lower 11 weeks post partum than antenatal values (106.5 ± 43.6 cmH2O antenatally vs 75.5 ± 45.6 cmH2O post partum, p < 0.001) but there was no significant difference between antenatal values and those measured 6 months post partum (p = 0.24). Anal fatigue rate was significantly slower 11 weeks post partum (p = 0.001), but by six months post partum the difference is no longer significant (p = 0.053). Pelvic floor muscle (PFM) strength fell with age and was significantly lower in incontinent women (8.97 ± 12.88 cmH2O) than incontinent women (27.17 ± 18.16 cmH2O; p < 0.001). PFM fatigue rate was also significantly slower in incontinent women (p = 0.01). The PFM strength was significantly higher in nulliparous than parous women (p = 0.002) and fatigue rate was faster (p = 0.022). PFM strength (p = 0.006) and fatigue rate (p =0.004) were significantly lower six months post partum when compared with antenatal values. It was shown that pelvis size can be measured using ultrasound and was found to be repeatable, but inaccurate when compared with magnetic resonance imaging. Insufficient numbers were studied to show an effect on pelvic floor function. Conclusion: Vaginal delivery causes impairment of EAS voluntary contraction which appears to have recovered by six months post partum. It also causes impairment of PFM contraction which is persistent at six months post partum. The reduced PFM function seen post partum also occurs in incontinent women, adding to the evidence that childbirth causes the initial insult to the pelvic floor which results in faecal incontinence, either immediately or some years later.
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AZEVEDO, RONALDO. "GRANGER CAUSALITY IN TIME SERIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1991. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8782@1.

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REDE FERROVIÁRIA FEDERAL SA
Neste trabalho fazemos uma revisita à causalidade no sentido de Granger aplicada às Séries Temporais bivariadas no domínio do tempo e da freqüência. Um programa computacional foi escrito usando a linguagem Pascal para, testando casos reais e simulados, construir modelos de causalidade/feedback, que são então analisados no ambiente espectral, com ênfase maior à discussão da coerência e da fase de causalidade.
In this work causality in the sense defined by Granger is revisited. Applications to bivariante temporal systems in time domain and frequency-domain were analysed, using a computer program written in Pascal. After this, spectral methods were developed, with special emphasis on phase and causality-coerence.
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Larkin, Mark John William. "Retrospective revaluation in causality judgement." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624120.

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McKay, A. C. "Causality in a McDowellian world." Thesis, Queen's University Belfast, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.679262.

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The thesis explores and suggests a solution to a problem that I identify in John McDowell's and Lynne Rudder Baker's approaches to mental and intention-dependent (ID) causation in the physical world. I discuss McDowell's non-reductive and anti-scientistic account of mind and world, which I believe promises to renew and liberate philosophy. Baker's constitution account, I argue, provides a potential link between McDowell's categories of the space of reasons and the realm of law. However, both McDowell and Baker view mental causation as acting unproblematically within the physical world. I argue that this is inconsistent with an understanding of ordinary physical causality as objective, in the sense of being recognition-independent, and as causally complete. I develop an account of what I call manifest physical causation - of objective causal relations in the ordinary world of Wilfrid Sellars's manifest image and its extensions into the special sciences. Manifest physical causation, on my account, is productive, acts through physical mechanisms, and is causally closed. In my view, mental and ID property-instances are not part of the manifest physical causal nexus. I conclude by suggesting a modification of Baker's constitution account, which I call Constituted Causation, whereby higher-level - mental and other ID - causal relations are constituted, in favourable circumstances, by lower-level ones. Causality, I argue, relates property-instances at the same ontological level. ID causal relations belong in their own causal nexus of rational and normative relations, connected to the manifest physical world through constitution, a relation of unity without identity. On Baker's view, the essential properties of constituted entities subsume those of their constituters. Extending this to my account enables us to say that the real cause and explanation of someone's action is that they consciously performed it rather than that certain causal processes occurred at the lower level.
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Centorrino, Samuele. "Causality, endogeneity and nonparametric estimation." Thesis, Toulouse 1, 2013. http://www.theses.fr/2013TOU10020/document.

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Cette thèse porte sur les problèmes de causalité et d'endogénéité avec estimation non-paramétrique de la fonction d’intérêt. On explore ces problèmes dans deux modèles différents. Dans le cas de données en coupe transversale et iid, on considère l'estimation d'un modèle additif séparable, dans lequel la fonction de régression dépend d'une variable endogène. L'endogénéité est définie, dans ce cas, de manière très générale : elle peut être liée à une causalité inverse (la variable dépendante peut aussi intervenir dans la réalisation des régresseurs), ou à la simultanéité (les résidus contiennent de l'information qui peut influencer la variable indépendante). L'identification et l'estimation de la fonction de régression se font par variables instrumentales. Dans le cas de séries temporelles, on étudie les effets de l'hypothèse d'exogénéité dans un modèle de régression en temps continu. Dans un tel modèle, la variable d'état est fonction de son passé, mais aussi du passé d'autres variables et on s'intéresse à l'estimation nonparamétrique de la moyenne et de la variance conditionnelle. Le premier chapitre traite de ce dernier cas. En particulier, on donne des conditions suffisantes pour qu'on puisse faire de l'inférence statistique dans un tel modèle. On montre que la non-causalité est une condition suffisante pour l'exogénéité, quand on ne veut pas faire d'hypothèses sur les dynamiques du processus des covariables. Cependant, si on est prêt à supposer que le processus des covariables suit une simple équation différentielle stochastique, l'hypothèse de non-causalité devient immatérielle. Les chapitres de deux à quatre se concentrent sur le modèle iid simple. Etant donné que la fonction de régression est solution d'un problème mal-posé, on s'intéresse aux méthodes d'estimation par régularisation. Dans le deuxième chapitre, on considère ce modèle dans le cas d'un régularisation sur la norme L2 de la fonction (régularisation de type Tikhonov). On dérive les propriétés d'un critère de validation croisée pour définir le choix du paramètre de régularisation. Dans le chapitre trois, coécrit avec Jean-Pierre Florens, on étend ce modèle au cas où la variable dépendante n'est pas directement observée mais où on observe seulement une transformation binaire de cette dernière. On montre que le modèle peut être identifié en utilisant la décomposition de la variable dépendante dans l'espace des variables instrumentales et en supposant que les résidus de ce modèle réduit ont une distribution connue. On démontre alors, sous ces hypothèses, qu'on préserve les propriétés de convergence de l'estimateur non-paramétrique. Enfin, le chapitre quatre, coécrit avec Frédérique Fève et Jean-Pierre Florens, décrit une étude numérique, qui compare les propriétés de diverses méthodes de régularisation. En particulier, on discute des critères pour le choix adaptatif des paramètres de lissage et de régularisation et on teste la validité du bootstrap sauvage dans le cas des modèles de régression non-paramétrique avec variables instrumentales
This thesis deals with the broad problem of causality and endogeneity in econometrics when the function of interest is estimated nonparametrically. It explores this problem in two separate frameworks. In the cross sectional, iid setting, it considers the estimation of a nonlinear additively separable model, in which the regression function depends on an endogenous explanatory variable. Endogeneity is, in this case, broadly denned. It can relate to reverse causality (the dependent variable can also affects the independent regressor) or to simultaneity (the error term contains information that can be related to the explanatory variable). Identification and estimation of the regression function is performed using the method of instrumental variables. In the time series context, it studies the implications of the assumption of exogeneity in a regression type model in continuous time. In this model, the state variable depends on its past values, but also on some external covariates and the researcher is interested in the nonparametric estimation of both the conditional mean and the conditional variance functions. This first chapter deals with the latter topic. In particular, we give sufficient conditions under which the researcher can make meaningful inference in such a model. It shows that noncausality is a sufficient condition for exogeneity if the researcher is not willing to make any assumption on the dynamics of the covariate process. However, if the researcher is willing to assume that the covariate process follows a simple stochastic differential equation, then the assumption of noncausality becomes irrelevant. Chapters two to four are instead completely devoted to the simple iid model. The function of interest is known to be the solution of an inverse problem. In the second chapter, this estimation problem is considered when the regularization is achieved using a penalization on the L2-norm of the function of interest (so-called Tikhonov regularization). We derive the properties of a leave-one-out cross validation criterion in order to choose the regularization parameter. In the third chapter, coauthored with Jean-Pierre Florens, we extend this model to the case in which the dependent variable is not directly observed, but only a binary transformation of it. We show that identification can be obtained via the decomposition of the dependent variable on the space spanned by the instruments, when the residuals in this reduced form model are taken to have a known distribution. We finally show that, under these assumptions, the consistency properties of the estimator are preserved. Finally, chapter four, coauthored with Frédérique Fève and Jean-Pierre Florens, performs a numerical study, in which the properties of several regularization techniques are investigated. In particular, we gather data-driven techniques for the sequential choice of the smoothing and the regularization parameters and we assess the validity of wild bootstrap in nonparametric instrumental regressions
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Allen, John-Mark. "Reality, causality, and quantum theory." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:01413eef-0944-4ec5-ad53-ac8378bcf4be.

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Quantum theory describes our universe incredibly successfully. To our classically-inclined brains, however, it is a bizarre description that requires a reimagining of what fundamental reality, or 'ontology', could look like. This thesis examines different ontological features in light of the success of quantum theory, what it requires, and what it rules out. While these investigations are primarily foundational, they also have relevance to quantum information, quantum communication, and experiments on quantum systems. The way that quantum theory describes the state of a system is one of its most unintuitive features. It is natural, therefore, to ask whether a similarly strange description of states is required on an ontological level. This thesis proves that almost all quantum superposition states for d > 3 dimensions must be real - that is, present in the ontology in a well-defined sense. This is a strong requirement which prevents intuitive explanations of the many quantum phenomena which are based on superpositions. A new theorem is also presented showing that quantum theory is incompatible with macro-realist ontologies, where certain physical quantities must always have definite values. This improves on the Leggett-Garg argument, which also aims to prove incompatibility with macro-realism but contains loopholes. Variations on both of these results that are error-tolerant (and therefore amenable to experimentation) are presented, as well as numerous related theorems showing that the ontology of quantum states must be somewhat similar to the quantum states themselves in various specific ways. Extending these same methods to quantum communication, a simple proof is found showing that an exponential number of classical bits are required to communicate a linear number of qubits. That is, classical systems are exponentially bad at storing quantum data. Causal influences are another part of ontology where quantum theory demands a revision of our classical notions. This follows from the outcomes of Bell experiments, as rigorously shown in recent analyses. Here, the task of constructing a native quantum framework for reasoning about causal influences is tackled. This is done by first analysing the simple example of a common cause, from which a quantum version of Reichenbach's principle is identified. This quantum principle relies on an identification of quantum conditional independence which can be defined in four ways, each naturally generalising a corresponding definition for classical conditional independence. Not only does this allow one to reason about common causes in a quantum experiments, but it can also be generalised to a full framework of quantum causal models (mirroring how classical causal models generalise Reichenbach's principle). This new definition of quantum causal models is illustrated by examples and strengthened by it's foundation on a robust quantum Reichenbach's principle. An unusual, but surprisingly fruitful, setting for considering quantum ontology is found by considering time travel to the past. This provides a testbed for different ontological concepts in quantum theory and new ways to compare classical and quantum frameworks. It is especially useful for comparing computational properties. In particular, time travel introduces non-linearity to quantum theory, which brings (sometimes implicit) ontological assumptions to the fore while introducing strange new abilities. Here, a model for quantum time travel is presented which arguably has fewer objectionable features than previous attempts, while remaining similarly well-motivated. This model is discussed and compared with previous quantum models, as well as with the classical case. Together, these threads of investigation develop a better understanding of how quantum theory affects possible ontologies and how ontological prejudices influence quantum theory.
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Books on the topic "Causality"

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name, No. La causalit = La causalit = Kausalitt = Causality. Turnhout: Brepols, 2002.

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Turner, Stephen. Causality. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2010. http://dx.doi.org/10.4135/9781446260975.

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Berzuini, Carlo, Philip Dawid, and Luisa Bernardinelli, eds. Causality. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.

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J, Aigner Dennis, and Zellner Arnold, eds. Causality. Amsterdam: North Holland, 1988.

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Fernando, Alvarez. Causality, causality, causality: The view of education inputs and outputs from economics. Chicago, Ill.]: Federal Reserve Bank of Chicago, 2005.

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Carla, Galavotti Maria, Suppes Patrick 1922-, and Costantini Domenico, eds. Stochastic causality. Stanford, Calif: CSLI Publications, 2001.

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Riggs, Peter J. Quantum Causality. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2403-9.

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Vollmer, Fred. Agent Causality. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9225-3.

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Foley, Meeker Barbara, ed. Social causality. Boston: Unwin Hyman, 1988.

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Heckman, James J. Econometric causality. Cambridge, MA: National Bureau of Economic Research, 2008.

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Book chapters on the topic "Causality"

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Cox, D. R. "Statistical Causality: Some Historical Remarks." In Causality, 1–5. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch1.

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Sjölander, Arvid. "Cross-Classifications by Joint Potential Outcomes." In Causality, 114–25. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch10.

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Vansteelandt, Stijn. "Estimation of Direct and Indirect Effects." In Causality, 126–50. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch11.

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Pearl, Judea. "The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models." In Causality, 151–79. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch12.

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VanderWeele, Tyler J. "The Sufficient Cause Framework in Statistics, Philosophy and the Biomedical and Social Sciences." In Causality, 180–91. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch13.

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Berzuini, Carlo, Philip Dawid, Hu Zhang, and Miles Parkes. "Analysis of Interaction for Identifying Causal Mechanisms." In Causality, 192–207. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch14.

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Bernardinelli, Luisa, Carlo Berzuini, Luisa Foco, and Roberta Pastorino. "Ion Channels as a Possible Mechanism of Neurodegeneration in Multiple Sclerosis." In Causality, 208–17. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch15.

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Ramsahai, Roland R. "Supplementary Variables for Causal Estimation." In Causality, 218–33. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch16.

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Daniel, Rhian, Bianca De Stavola, and Simon Cousens. "Time-Varying Confounding: Some Practical Considerations in a Likelihood Framework." In Causality, 234–52. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch17.

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Rutter, Michael. "‘Natural Experiments’ as a Means of Testing Causal Inferences." In Causality, 253–72. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119945710.ch18.

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Conference papers on the topic "Causality"

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Nancel, Mathieu, and Andy Cockburn. "Causality." In CHI '14: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2556288.2556990.

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Jia, Xinxin, Sanqing Hu, Jianhai Zhang, and Wanzeng Kong. "Blockwise Granger causality and blockwise new causality." In 2015 Seventh International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2015. http://dx.doi.org/10.1109/icaci.2015.7184744.

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Sobrino, Alejandro, Jose A. Olivas, and Cristina Puente. "Causality and imperfect causality from texts: A frame for causality in social sciences." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584863.

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KOROTAEV, SERGEY M., and EVGENIY O. KIKTENKO. "Quantum Causality." In Proceedings of the 8th Symposium Honoring Mathematical Physicist Jean-Pierre Vigier. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814504782_0031.

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Piquer, José M. "Large causality." In the 5th workshop. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/506378.506414.

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Snowsill, Tristan Mark, Nick Fyson, Tijl De Bie, and Nello Cristianini. "Refining causality." In the 17th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2020408.2020483.

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Mazlack, L. J. "Granular causality speculations." In IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04. IEEE, 2004. http://dx.doi.org/10.1109/nafips.2004.1337385.

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Pleşca, Cezar, Romulus Grigoraş, Philippe Quéinnec, and Gérard Padiou. "Streaming with causality." In the 13th annual ACM international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1101149.1101205.

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Lian, Xiang, and Lei Chen. "Causality and responsibility." In the 22nd ACM international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2505515.2505754.

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Jeffrey, Alan. "Causality for free!" In the 7th workshop. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2428116.2428127.

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Reports on the topic "Causality"

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Heckman, James. Econometric Causality. Cambridge, MA: National Bureau of Economic Research, April 2008. http://dx.doi.org/10.3386/w13934.

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Heckman, James. Econometric causality. Institute for Fiscal Studies, February 2008. http://dx.doi.org/10.1920/wp.cem.2008.0108.

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Heckman, James, and Rodrigo Pinto. Causality and Econometrics. Cambridge, MA: National Bureau of Economic Research, February 2022. http://dx.doi.org/10.3386/w29787.

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Panizza, Ugo, and Dany Jaimovich. Procyclicality or Reverse Causality? Inter-American Development Bank, March 2007. http://dx.doi.org/10.18235/0010973.

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Abstract:
There is a large literature showing that fiscal policy is either acyclical or countercyclical in industrial countries and procyclical in developing countries. Most of this literature is based on OLS regressions that focus on the correlation between a fiscal variable (usually the budget balance or expenditure growth) and either GDP growth or some measure of the output gap. This paper argues that such a methodology does not permit the identification of the effect of the business cycle on fiscal policy and hence cannot be used to estimate policy reaction functions. The paper proposes a new instrument for GDP growth and shows that, once GDP growth is properly instrumented, procyclicality tends to disappear.
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Raglin, Adrienne, and Brian Sadler. Causality and Machine Learning Review. DEVCOM Army Research Laboratory, October 2022. http://dx.doi.org/10.21236/ad1182780.

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Stock, James, and Mark Watson. Interpreting Evidence on Money-Income Causality. Cambridge, MA: National Bureau of Economic Research, April 1987. http://dx.doi.org/10.3386/w2228.

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Beguelin, Adam, and Erik Seligman. Causality-Preserving Timestamps in Distributed Programs. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada267534.

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Wen, Yi. Granger Causality and Equilibrium Business Cycle Theory. Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.038.

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Buiter, Willem. Granger-Causality and Policy Ineffectiveness: A Rejoinder. Cambridge, MA: National Bureau of Economic Research, October 1986. http://dx.doi.org/10.3386/t0061.

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Angrist, Joshua, and Guido Kuersteiner. Semiparametric Causality Tests Using the Policy Propensity Score. Cambridge, MA: National Bureau of Economic Research, December 2004. http://dx.doi.org/10.3386/w10975.

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You might also be interested in the extended bibliographies on the topic 'Causality' for particular source types:
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