Assessing simple policy rules: a view from a complete macro model

We explore two popular approaches to empirical analysis of monetary policy: the New Keynesian and the identified vector autoregression approaches. Stylized models of private behavior coupled with simple rules describing policy behavior characterize New Keynesian work. Vector autoregressions consist of minimally identified dynamic descriptions of private behavior coupled with a detailed rule for policy behavior. The simplicity of New Keynesian models aids in communication but leaves the models’ implications vulnerable. By relating the New Keynesian models to identified vector autoregressions, we explore the differences and similarities in the two approaches and assess some of the key conclusions to emerge from New Keynesian research.Vector autoregression ; Monetary policy ; Forecasting

Modest policy interventions

The authors present a framework for computing and evaluating linear projections of macro variables conditional on hypothetical paths of monetary policy. A modest policy intervention is a change in policy that does not significantly shift agents' beliefs about policy regime and does not generate quantitatively important expectations-formation effects of the kind Lucas (1976) emphasizes. The framework is applied to an econometric model of U.S. postwar monetary policy behavior. It finds that a rich class of interventions routinely considered by the Federal Reserve are modest and their impacts can be reliably forecast by an accurately identified linear model. Moreover, modest interventions can matter: They may shift the projected paths and probability distributions of macro variables in economically meaningful ways.Monetary policy ; Forecasting ; Vector autoregression

Modest policy interventions

The authors present a theoretical and empirical framework for computing and evaluating linear projections conditional on hypothetical paths of monetary policy. A modest policy intervention does not significantly shift agents' beliefs about policy regime and does not induce the changes in behavior that Lucas (1976) emphasizes. Applied to an econometric model of U.S. monetary policy, the authors find that a rich class of interventions routinely considered by the Federal Reserve is modest and their impacts can be reliably forecast by an identified linear model. Modest interventions can shift projected paths and probability distributions of macro variables in economically meaningful ways.Equilibrium (Economics) ; Monetary policy ; Macroeconomics ; Inflation (Finance) ; Econometric models

Modest policy interventions

This paper brings together identification and forecasting in a positive econometric analysis of policy. We contend that a broad range of important policy questions is consistent with the existing policy process and is not subject to Lucas's critique. We analyze the economics of "business as usual" and show that modest policy interventions, whose effects can be projected even if expectations are modeled as depending solely on past policy, can address routine questions like those raised at regular policy meetings. And modest interventions matter: they can shift the projected paths and probability distributions of macro variables in economically meaningful ways.Monetary policy ; Forecasting ; Vector autoregression ; Econometrics

Assessing simple policy rules: A view from a complete macroeconomic model

Monetary policy analysts looking for a model on which to base decisions may consider two popular approaches-the New Keynesian (NK) and the identified vector autoregression (VAR) approaches. Choosing between the two can be difficult: NK models are stylized and have simple rules while structural VAR models have complex dynamics and loose behavioral interpretations. ; The simpler NK models often produce stark conclusions. For example, NK analyses consistently find that the Federal Reserve's monetary policy has improved markedly in the past two decades compared with the 1960s and 1970s. In contrast, VARs find little instability in the policy parameters or in the dynamic impacts of exogenous shifts in policy. ; Taking the view that NK models are simply restricted VARs, the authors estimate systems of structural equations implied by NK models. They find that these estimated equations vary considerably over different periods. The authors also investigate the role of money by incorporating money (M2) into the NK model; they find that including money substantially alters the model's conclusions about monetary policy. This result conflicts with the NK theoretical assumption that money is irrelevant. ; Both NK models and VARs have their place in policy advising, the authors believe. But they caution that it is treacherous to draw inferences about policy effects solely from policy rules estimated in isolation from a complete macro model.Macroeconomics ; Econometric models ; Monetary policy

Assessing simple policy rules: a view from a complete macroeconomic model

Macroeconomics ; Econometric models

Bipartite graph partitioning and data clustering

Many data types arising from data mining applications can be modeled as bipartite graphs, examples include terms and documents in a text corpus, customers and purchasing items in market basket analysis and reviewers and movies in a movie recommender system. In this paper, we propose a new data clustering method based on partitioning the underlying bipartite graph. The partition is constructed by minimizing a normalized sum of edge weights between unmatched pairs of vertices of the bipartite graph. We show that an approximate solution to the minimization problem can be obtained by computing a partial singular value decomposition (SVD) of the associated edge weight matrix of the bipartite graph. We point out the connection of our clustering algorithm to correspondence analysis used in multivariate analysis. We also briefly discuss the issue of assigning data objects to multiple clusters. In the experimental results, we apply our clustering algorithm to the problem of document clustering to illustrate its effectiveness and efficiency.Comment: Proceedings of ACM CIKM 2001, the Tenth International Conference on Information and Knowledge Management, 200