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Macroeconomics faced substantial internal and external criticism related to the 2007-09 financial crisis. Much of it was based on the unsustainable idea that its goal could or should be unconditional forecasting of business cycles. Critics specially singled out dynamic, stochastic general-equilibrium (DSGE) models, and called for various fundamental re-orientations of the field. Predictably, the critic's proposals have not won the day. Critics exaggerated the role of DSGE models in actual policymaking, and their advocates developed the models to address some of the issues raised by the crisis. But DSGE modelers oversold its success, with some prominent advocates having argued that it is the sine qua non of successful macroeconomics. They revive an old controversy in economics between those who prioritize a priori theory and those who prioritize empirical data - a controversy classically exemplified in the Measurement without Theory Debate of the 1940s between the Cowles Commission and the National Bureau of Economic Research. That debate is reviewed for its implications for the recent controversy. In adopting the Cowles-Commission position, some DSGE modelers would essentially straight-jacket macroeconomics and undermine economic science and the pursuit of knowledge in an open-minded, yet critical framework. Some alternative approaches are noted.

The leadership structure of the American Economics Association is documented using a biographical database covering every officer and losing candidate for AEA offices from 1950 to 2019. The analysis focuses on institutional affiliations by education and employment. The structure is strongly hierarchical. A few institutions dominate the leadership, and their dominance has become markedly stronger over time. Broadly two types of explanations are explored: that institutional dominance is based on academic merit or that it based on self-perpetuating privilege. Network effects that might explain the dynamic of increasing concentration are also investigated.

A popular view of models among economists and philosophers alike is that all models are false, but some are useful. Models are frequently treated as convenient fictions, idealizations, stories about credible worlds, or "near enough" to the truth. But such a understandings pose serious questions, among them: if models are false, how is it that they are so useful? how can they have any bearing on what is actually the case in the world? how can we evaluate them empirically? How can we develop them for greater precision? for understanding how models related to the world, how they can successfully support scientific investigation? The paper argues that these and related questions reflect a fundamental confusion: models are, in fact, useful only to the degree that they are instruments for stating truth. The confusion arises from a failure to understand how models relate to the world analogically. Analogies are fundamentally incomplete and perspectival, so that the truths that state are necessarily piecemeal But models may nonetheless be apt. A critical distinction is drawn between accuracy and precision in modeling. Modeling is related to Charles Peirce's analytical inference. And the application of analytical inference in economics is illustrated with a historical case-study of Lawrence Klein's early econometric models of the U.S. economy.

Best known as a monetary economist and prominent proponent of monetarism, Karl Brunner was deeply knowledgeable about the philosophy of science and attempted to explicitly integrate logical empiricist thinking, derived in some measure from his engagement with the work of the philosopher Hans Reichenbach, into his economics. His philosophical commitments are clearly reflected in this empirical work on monetary economics, his monetarist analysis, and in his critical approach to econometrics, microfoundations, and the New Classical macroeconomics.

The role of first principles in economics is examined through the lens of dominant methodological approaches of the classical and neoclassical periods. First principles are most clearly displayed in pure deductive systems. The tension between first principles as the basis for deductivist approaches to economics and the widespread belief that economics is an empirical discipline. Empirical disciplines require some sort of falsifiability. Fallibilism is the doctrine that no empirical beliefs can be certified as true beyond possibility of doubt. Yet, empirical inquiries also require a starting place. Even rejecting foundationalism, any inquiry starts with indubitable beliefs - that is, beliefs that are not in fact doubted. Anti-foundationalism and fallibilism are in tension, as indubitability appears to have necessary consequences, undercutting fallibilism, while fallibilism threatens confidence in the de facto first principles that begin inquiry. This tension is examined in the different attempts to define economics and its method from John Stuart Mill's economics as the science of wealth through Lionel Robbins' and recent neoclassical economists' economics as the optimal use of scare resources. Commitment to first principles risks emptying economics of its empirical content, while commitment to empirical content entails violating supposed first principles and muddles the boundaries of the discipline. Finally, Stigler and Becker's "De Gustibus Non Est Disuptandum" is considered as an attempt to square empiricism with Robbins' deductivism.

Caldwell's Beyond Positivism was a key publication that helped to precipitate the consolidation of the methodology of economics into a distinct subfield within economics. Reconsidering it after thirty-five years, it is striking for its anti-naturalism (i.e., its lack of deference to the actual practices of economics) or, perhaps, for its meta-naturalism (displayed in its excessive deference to the philosophy of science) and for its defense of pluralism. It offers pluralism as an unsuccessful defense against dogmatism. Against Caldwell's pluralism, dogmatism is better opposed by a commitment of fallibilism and scientific humility. Caldwell's defense of Austrian methodology is taken as a case study to illustrate and investigate his key themes and the issues that they raise

Standard histories of economics usually treat the "marginal revolution" of the midnineteenth century as both supplanting the "classical" economics of Smith and Ricardo and as advancing the idea of economics as a mathematical science. The marginalists - especially Jevons and Walras - viewed Cournot's (1838) book on mathematical economics as a seminal work on which they could build. Surprisingly, the scientist, philosopher, and logician Charles S. Peirce discovered Cournot before the marginalist economists and possessed a deeper appreciation of his mathematical approach. While Peirce's contributions to economics are limited, the influence of economics on his philosophy is subtle and not well understood. In a number of fragments, Peirce, who, despite Ricardo's lack of mathematical form, nonetheless regarded him as a paradigmatic mathematical economist, refers to "Ricardian inference," as a fundamental contribution to scientific method. Two, perhaps complementary, options are explored as to exactly what Peirce meant by Ricardian inference. On the one hand, he associates Ricardo with the "primipostnumeral syllogism," which is a sort of generalization to uncountably infinite sets of what Peirce calls Fermatian inference (often referred to as mathematical induction). On the other hand, he holds up Ricardo as an exemplar of the "analytical method," which is Peirce's name for a hybrid form connecting analogy, abduction, and induction. On either account, economics plays a larger and more fundamental role in Peirce's philosophy of science than is generally understood.

A.W.H. Phillips is little known to the economics profession today, except at the creator of the Phillips curve. Bollard's engaging biography tells the story of a provincial New Zealander and practical engineer, who emerges as a hero in World War II, and plots a spectacular rise from 3rd class sociology degree to Tooke Professor of Economics at the LSE in just eight years. Bollard's biograph is a welcome corrective - both in demonstrating that Phillips' most important contributions to economics lay in the realms of macroeconomic dynamics and time-series econometrics and in showing how those aspects of his work must be appreciated to place the more famous Phillips curve into perspective.

Situational analysis (also known as situational logic) was popularized by Karl Popper as an appropriate method for the interpretation of history and as a basis for a scientific social science. It seeks an objective posit ive explanation of behavior through imputing a dominant goal or motive to individuals and then identifying the action that would be objectively appropriate to the situation as the action actually taken. Popper regarded situational analysis as a generalization to all of social science of the prototypical reasoning of economics. Applied to history, situational analysis is largely an interpretive strategy used to understand individual behavior. In social sciences, however, it is applied many to types of beh avior or to group behavior (e.g., to markets) as is used to generate testable hypothesis. Popper's account of situational analysis and some criticisms that have been levied against it are reviewed. The charge that situational analysis contradicts Popper's view that falsification is the hallmark of sciences is examined and rejected: situational analysis is precisely how Popper believes social sciences are able to generate falsifiable, and, therefore, scientific hypotheses. Still, situational analysis is in tension with another of Popper's central ideas: situational analysis as a method for generating testable conjectures amounts to a logic of scientific discovery, something that Popper argued elsewhere was not possible.

The Great Recession and the financial crisis of 2007-09 prompted ca lls for fundamental reforms of economic theory. The role of theory in economics and in recent economic events is considered in light of two recen t books: the sociologist Richard Swedberg's The Art of Social Theory and the economist André Orléan's The Empire of Value: A New Foundation for Economics.

Samuelson and Solow in their 1960 paper in the American Economic Review: Papers and Proceedings were among the first economists to engage with Phillips' famous unemployment/wage-inflation analysis, now referred to as the Phillips curve. They addressed the question of the relevance of Phillips's analysis for the United Kingdom to the United States, and in process formulated the firstunemployment/price-inflation version of the Phillips curve and were the first to interpret the Phillips curve as a menu for policy. Their paper was an informal analysis presented at a conference. The current paper offers a careful reconstruction and assessment of their original formulation, documenting the close relationship between the wage-inflation and price-inflation versions of the Phillips curve. A recent paper of Hall and Hart (2012) that suggests, first, that Samuelson and Solow should have reached different conclusions about the price-Phillips curve on the basis of regression estimates of their own data and, second, that had they done so the "inflationist" course of U.S. macroeconomic policy in the 1960s and 1970s would have been different. With the reconstruction as a background, the current paper demonstrates that Hall and Hart have not grasped the key details of Samuelson and Solow's analysis, and that they ignore the actual context of the paper, so that neither of their suggestions is likely: Samuelson and Solow would have no reason to reach any different conclusion based on Hall and Hart's estimates, and the course of macroeconomic policy is unlikely to have been affected in any case.

In many sciences – physical, but also biology, neuroscience, and other life sciences – one object of reductionism is to purge intentionality from the fundamental basis of both explanations and the explanatory target. The scientifically relevant level – ontologically and epistemologically – is thought to lie deeper than the level of ordinary human interactions. In the material and living world, the more familiar is the less fundamental. In contrast, the economic world of day-to-day life – the world of market interactions – appears to be the relevant level. Macroeconomics is thought to provide an account that is above, not below or behind, ordinary economic decisionmaking. An advantage of a macroeconomic account is that it is possible to employ causal analysis of the economy as a whole analogous to the causal analysis of physical systems. The fear of many economists is that such analyses are untethered to ordinary economic decisionmaking. The object of reductionism in economics – the so-called microfoundations of macroeconomics – is adequately to ground or replace higher level causal analysis with an analysis of the day-to-day interactions of people. The object is not to purge intentionality, but to reclaim it. The paper will attempt to understand the key issues surrounding the microfoundations of macroeconomics from a perspectival realist perspective that elucidates the relationship between economists' methodological preference for microfoundations and need for macroeconomic analysis – that is, between economists' respect for the intentional nature of economic life and the need for a causal analysis of the economy. The paper favors metaphysical humility and methodological pragmatism.

Modern growth theory derives mostly from Robert Solow's "A Contribution to the Theory of Economic Growth" (1956). Solow's own interpretation locates the origins of his "Contribution" in his view that the growth model of Roy Harrod implied a tendency toward progressive collapse of the economy. He formulates his view in terms of Harrod's invoking a fixed-coefficients production function. We challenge Solow's reading of Harrod's "Essay in Dynamic Theory," arguing that Harrod's object in providing a "dynamic" theory had little to do with the problem of long-run growth as Solow understood it, but instead addressed medium-run fluctuations, the "inherent instability" of economies. It was an attempt to isolate conditions under which the economy might tend to run below potential. In making this argument, Harrod does not appeal to a fixed-coefficients production function – or to any production function at all, as that term is understood by Solow. Solow interpreted Harrod's "Essay" in the light of a particular culture of understanding grounded in the practice of formal modeling that emerged in economics in the post-World War II period. The fate of Harrod's analysis is a case study in the difficulties in communicating across distinct interpretive communities and of the potential for losing content and insights in the process. From Harrod's English Keynesian point of view, Solow's interpretation arose out of a culture of misunderstanding, and his objects – particularly, of trying to account for a tendency of the economy toward chronic recessions – were lost to the mainstream literature.

Although Cournot's mathematical economics was generally neglected until the mid- 1870s, he was taken up and carefully studied by the Scientific Club of Cambridge, Massachusetts even before his "discovery" by Walras and Jevons. The episode is reconstructed from fragmentary manuscripts of the pragmatist philosopher Charles S. Peirce, a sophisticated mathematician. Peirce provides a subtle interpretation and anticipates Bertrand's criticisms.

Modern empirical macroeconomic models, known as structural autoregressions (SVARs) are dynamic models that typically claim to represent a causal order among contemporaneously valued variables and to merely represent non-structural (reduced-form) co-occurence between lagged variables and contemporaneous variables. The strategy is held to meet the minimal requirements for identifying the residual errors in particular equations in the model with independent, though otherwise not directly observable, exogenous causes ("shocks") that ultimately account for change in the model. In nonstationary models, such shocks accumulate so that variables have discernible trends. Econometricians have conceived of variables that trend in sympathy with each other (so-called "cointegrated variables") as sharing one or more of these unobserved trends as a common cause. It is possible for estimates of the values of both the otherwise unobservable individual shocks and the otherwise unobservable common trends to be backed-out of cointegrated systems of equations. The issue addressed in this paper is whether and in what circumstances these values can be regarded as observations of real entities rather than merely artifacts of the representation of variables in the model. The issue is related, on the one hand, to practical methodological problems in the use of SVARs for policy analysis – e.g., does it make sense to estimate of shocks or trends in one model and then use them as measures of variables in a conceptually distinct model? The issue is also related to debates in the philosophical analysis of causation – particularly, whether we are entitled, as assumed by the developers of Bayes-net approaches, to rely on the causal Markov condition (a generalization of Reichenbach's common-cause condition) or whether cointegration generates a practical example of Nancy Cartwright's "byproducts" objection to the causal Markov condition.

Modern growth theory derives mostly from Robert Solow's "A Contribution to the Theory of Economic Growth" (1956). Solow's own interpretation locates the origins of his "Contribution" in his view that the growth model of Roy Harrod implied a tendency toward progressive collapse of the economy. He formulates his view in terms of Harrod invoking a fixed-coefficients production function. This paper, first, challenges Solow's reading of Harrod, arguing that Harrod's object in providing a "dynamic" theory had little to do with the problem of long-run growth as Solow understood it, but instead addressed the medium run fluctuations. It was an attempt to isolate conditions under which the economy might tend to run below potential. In making this argument, Harrod does not appeal to a fixed-coefficients production function – or to any production function at all, as that term is understood by Solow. The paper next traces the history of the dominance of Solow's interpretation among growth economists. These tasks belong to the history of economics. The paper's final task belongs to economic history. It offers an informal reexamination of economic history through the lens of Harrod's dynamic model, asking whether there is a prima facie case in favor of Harrod's model properly understood.

The paper is a keynote lecture from the Tilburg-Madrid Conference on Hypothesis Tests: Foundations and Applications at the Universidad Nacional de Educación a Distancia (UNED) Madrid, Spain, 15-16 December 2011. It addresses the role of tests of statistical hypotheses (specification tests) in selection of a statistically admissible model in which to evaluate economic hypotheses. The issue is formulated in the context of recent philosophical accounts on the nature of models and related to some results in the literature on specification search.

Trygve Haavelmo's The Probability Approach in Econometrics (1944) has been widely regarded as the foundation document of modern econometrics. Nevertheless, its significance has been interpreted in widely different ways. Some modern economists regard it as a blueprint for a provocative, but ultimately unsuccessful, program dominated by the need for a priori theoretical identification of econometric models. They call for new techniques that better acknowledge the interrelationship of theory and data. Others credit Haavelmo with an approach that focuses on statistical adequacy rather than theoretical identification. They see many of Haavelmo's deepest insights as having been unduly neglected. The current paper uses bibliometric techniques and a close reading of econometrics articles and textbooks to trace the way in which the economics profession received, interpreted, and transmitted Haavelmo's ideas. A key irony is that the first group calls for a reform of econometric thinking that goes several steps beyond Haavelmo's initial vision; while the second group argues that essentially what the first group advocates was already in Haavelmo's Probability Approach from the beginning.

The potted histories of macroeconomics textbooks are typically Keynes-centric. Keynes is credited with founding macroeconomics, and the central developments in the field through the early 1970s, including large-scale macroeconometric models are usually termed "Keynesian." The story of macroeconomics is framed as support or opposition (e.g., monetarism or the new classical macroeconomics) to Keynes. The real story is more complicated and involves at least two distinct threads. Keynes was important, but perhaps more important for the detailed development of the field were the early macroeconometricians – Ragnar Frisch and Jan Tinbergen. Frisch and Tinbergen adopted physical or mechanical metaphors in which aggregate quantities are central. Keynes's vision of macroeconomics is better described as "medical." It is based in human psychology and individual decision-making and sees the economy as an organic system. Whereas policymakers and economic advisers in Keynes view can operate only within the economic system, Frisch and Tinbergen laid the basis for an optimal-control approach to economic policy in which the policymaker stands outside the system. Recent new classical macroeconomics has adopted an uneasy amalgam of the medical and mechanical metaphors.

A review essay of Roman Frydman & Michael D. Goldberg's Beyond Mechanical Markets: Asset Price Swings, Risk, and the Role of the State.

Shock is a term of art that pervades modern economics appearing in nearly a quarter of all journal articles in economics and in nearly half in macroeconomics. Surprisingly, its rise as an essential element in the vocabulary of economists can be dated only to the early 1970s. The paper traces the history of shocks in macroeconomics from Frisch and Slutzky in the 1920s and 1930s through real-business-cycle and DSGE models and to the use of shocks as generators of impulse-response functions, which are in turn used as data in matching estimators. The history is organized around the observability of shocks. Aswell as documenting a critical conceptual development in economics, the history of shocks provides a case study that illustrates, but also suggests the limitations of, the distinction drawn by the philosophers of science James Bogen and James Woodward between data and phenomena. The history of shocks shows that this distinction must be substantially relativized if it is to be at all plausible.

The substantial questions of macroeconomics itself are very old, going back to the origins of economics itself. But professional self-consciousness of the distinction between macroeconomics and microeconomics dates only to the 1930s. The distinction was drawn quite independently of Keynes, yet Keynes's General Theory led to its widespread adoption. The question of the relationship of microeconomics to macroeconomics encapsulated in the question of whether macroeconomics requires microfoundations was not raised for the first time in the 1960s or '70s, as is sometimes thought, but goes back to the very foundations of macroeconomics. There are in fact at least three microfoundational programs: a Marshallian program with its roots directly in Keynes's own theorizing in the General Theory; a fixed-price general-equilibrium theory, which includes some work of Patinkin, Clower, and Barro and Grossman; and the more recent representative-agent microfoundations, starting with Lucas and the new classicals in the early 1970s. This paper will document the development of each of these microfoundational programs and their interrelationship, especially in relationship to the programs of general-equilibrium theory and econometrics, whose modern incarnations both date from exactly the same period in the 1930s.

Causal relations between federal expenditure and taxation are analyzed using an approach based on the invariance of econometric relationships in the face of structural interventions. Institutional evidence for interventions or changes of regime combined with econometric tests for structural breaks are used to investigate the relative stability of conditional and marginal probability distributions for each variable. The patterns of stability are the products of underlying causal order. The authors find two distinct causal structures operating in the postwar era. Before the mid-1960s, taxes appear to cause spending. After the late 1960s, taxes and spending are causally independent. Copyright 1992 by American Economic Association.

Four talks on Keynes in relation to the Bloomsbury Group: I. Maynard Keynes of Bloomsbury (Craufurd Goodwin); II. Keynes as Policy Advisor (E. Roy Weintraub); III. Keynes and Economics (Kevin D. Hoover); IV. Keynes and Hayek (Bruce Caldwell). The talks were delivered as part of roundtable discussion on John Maynard Keynes of Bloomsbury, the inaugural event of the Center for the History of Political Economy at Duke University, and were held in conjunction with Vision and Design: A Year of Bloomsbury, a campus-wide interdisciplinary program surrounding an exhibition of Bloomsbury art at Duke University's Nasher Museum of Art.

An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo's famous "Probability Approach in Econometrics" (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and the testing of economic theories. In time-series data, the probability approach requires careful specification of the integration and cointegration properties of variables in systems of equations. The relationship between the CVAR approach and wider methodological issues and between it and related approaches (e.g., the LSE approach) are explored. The specific-to-general strategy of widening the scope of econometric models to identify stochastic trends and cointegrating relations and to nest theoretical economic models is illustrated with the example of purchasing-power parity

Graph-theoretic methods of causal search based in the ideas of Pearl (2000), Spirtes, Glymour, and Scheines (2000), and others have been applied by a number of researchers to economic data, particularly by Swanson and Granger (1997) to the problem of finding a data-based contemporaneous causal order for the structural autoregression (SVAR), rather than, as is typically done, assuming a weakly justified Choleski order. Demiralp and Hoover (2003) provided Monte Carlo evidence that such methods were effective, provided that signal strengths were sufficiently high. Unfortunately, in applications to actual data, such Monte Carlo simulations are of limited value, since the causal structure of the true data-generating process is necessarily unknown. In this paper, we present a bootstrap procedure that can be applied to actual data (i.e., without knowledge of the true causal structure). We show with an applied example and a simulation study that the procedure is an effective tool for assessing our confidence in causal orders identified by graph-theoretic search procedures.

Post-Walrasian economics is not a doctrine, but a slogan announcing that something has to change. In this paper, I explore a conservative version of post-Walrasian economics that can be summarized as back to the methodology of Alfred Marshall's - particularly to his essay, "The Present Position of Economics" (1885). The Walrasian approach is a bottom-up, engineering vision: economics must be built on secure foundations of primitive theory, like a building. Marshall's approach is a top-down, archaelogical vision: the structure of economics must be uncovered starting with the observable facts and empirically determining what lies behind them. Marshall's methodology places the relationship between theory and empirical tools on center stage. The dominant tools of macroeconometrics are the vector autoregression (VAR) and calibration techniques, which were developed as reactions to two nearly simultaneous reactions to the Cowles-Commission program in econometrics: the Lucas critique and the Sims critique. The various strands of macroeconometrics are examined through the competing Walrasian and Marshallian visions of the role of theory in econometrics. A suggestion for a truly Marshallian (and post-Walrasian) econometrics is then offered.

In his own view, economic theory was important to Keynes's work as an economists. Aside from the General Theory, most of his economic writings, however policy oriented make explicit reference to theory. Nevertheless, Keynes's theoretical style is so far from what contemporary economics regards as "theory" that some have dismissed Keynes as a theorist altogether or thought of him as a theorist hampered by the lack of modern mathematical tools. In this paper, I argue to the contrary that Keynes's theoretical style is conditioned by a conception of theory as a diagnostic tool. This is a natural development from Marshall, and conceptually very different from modern macroeconomists. It is nonetheless a very attractive conception of the place of theory in economics.

Milton Friedman is usually regarded as an instrumentalist on the basis of his infamous claim that economic theories are to be judged by their predictions and not by the realism of their assumptions. This interpretation sits oddly with Friedman's empirical work - e.g., Friedman and Schwartz's monetary history - and his explicit rejection of theories of the business cycle that, while based on accurate correlations, nevertheless do not make economic sense. In this paper, I try to reconcile Friedman's methodological writings with his practices as an empirical economist by, first, taking his roots in Alfred Marshall seriously and, second, by taking the methodological implications of his empirical work seriously. Friedman dislikes the word "cause". Nevertheless, appearances to the contrary notwithstanding, Friedman is best understood as a causal realist - that is, one who understands the object of scientific inquiry as the discovery through empirical investigation of the true causal mechanisms underlying observable phenomena.

Woodford's Interest and Prices is considered from a methodological point of view. While innovative as a work of macroeconomic theory, it is decidedly in the mainstream methodologically. As such, it provides a good example of the methodological puzzles posed by modern macroeconomics: first, the notion that representative-agent models (or models with very constrained sorts of heterogeneous agents) provide genuine microfoundations; second, the idea that Paretian welfare economics in the context of such models gives any useful policy guidance.

Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that practitioners must choose among them using a priori theory or other criteria not rooted in the data under analysis. We show how to apply graph-theoretic methods of searching for causal structure based on relations of conditional independence to select among the possible causal orders ? or at least to reduce the admissible causal orders to a narrow equivalence class. The graph-theoretic approaches were developed by computer scientists and philosophers (Pearl, Glymour, Spirtes among others) and applied to cross-sectional data. We provide an accessible introduction to this work. Then building on the work of Swanson and Granger (1997), we show how to apply it to searching for the causal order of an SVAR. We present simulation results to show how the efficacy of the search method algorithm varies with signal strength for realistic sample lengths. Our findings suggest that graph-theoretic methods may prove to be a useful tool in the analysis of SVARs.

The 1970s and early 1980s witnessed two main approaches to the analysis of monetary policy. The first is the early new classical approach of Lucas, based on the assumptions of rational expectations and market clearing. The second is the a theoretical econometrics of Simsâ??s VAR program. Both have developed: the new classical approach has been enriched through various accounts of price stickiness, cost of adjustment or alternative expectational schemes; the original VAR program has developed into the structural VAR program. This paper clarifies the relationship between these two programs. Based on work of Cochrane (1998), it shows that the typical method of evaluating unanticipated, unsystematic monetary policy is correct only if the conditions necessary for Lucasâ??s policy-ineffectiveness proposition hold, while recent methods for evaluating systematic monetary policy violate Lucasâ??s policy-noninvariance proposition (â??the Lucas critiqueâ??). The paper shows how to construct and estimate (using regime changes) a model in which some agents form rational-expectations and others follow rules of thumb. In such a model, monetary policy actions can be validly decomposed into systematic and unsystematic components and valid counterfactual experiments on alternative systematic monetary-policy rules can be evaluated.

The work of Levine and Renelt (1992) and Sala-i-Martin (1997a, b) which attempted to test the robustness of various determinants of growth rates of per capita GDP among countries using two variants of Edward Leamerâ??s extreme-bounds analysis is reexamined. In a realistic Monte Carlo experiment in which the universe of potential determinants is drawn from those in Levine and Reneltâ??s study, both versions of the extreme-bounds analysis are evaluated for their ability to recover the true specification. Levine and Reneltâ??s method is shown to have low size and extremely low power: nothing is robust; while Sala-i-Martinâ??s method is shown to have high size and high power: it is undiscriminating. Both methods are compared to a cross-sectional version of the generalto-specific search methodology associated with the LSE approach to econometrics. It is shown to have size near nominal size and high power. Sala-i-Martinâ??s method and the general-to-specific method are then applied to the actual data from the original two studies. The results are consistent with the Monte Carlo results and are suggestive that the factors that most affect differences of growth rates are ones that are beyond the control of policymakers.

Dissertation, In this dissertation, I defend the thesis that an epistemic judgment of probability must be interpreted against the background of the context of inquiry in which it is made: in the abductive context, judgments of probability are matters of decision, made strategically in service to the investigative goal of the inquirer; in deduction, probabilities are derived based on the premises chosen in abduction, in order to explicate the implied commitments the agent may incur from those decisions; during the inductive stage, the inquirer is expected to conduct her empirical investigation in a deliberate manner, in accordance with the assertions and decisions she made during abduction and deduction, collectively referred to as the deliberative context.I set the stage by proposing a pragmatist reading of Bas van Fraassen's Reflection Principle and his voluntarist interpretation of assertions of degrees of beliefs as performative locutions to express the intention to undertake a proportional epistemic commitment. I argue for a refinement of this view that I call deliberativism, which introduces an abductive dimension to understand the normative force that regulates these epistemic judgments. I then argue that decisions made in the context of abduction have inferential repercussions on the validity of inductive inference. In particular, I situate deliberativism in the context of statistical inference by critically examining a problem in the literature called optional stopping, which occurs when the experimenter's intention to stop can manipulate the statistical significance of the data. The last chapter explores the Pericean idea of deductive reasoning as the strategic interrogation of a provisionally chosen hypothesis by focusing on J. M. Keynes' notion of the weight of evidence.