An alternative explanation of the price puzzle

This paper proposes a simple explanation for the frequent appearance of a price puzzle in VARs designed for monetary policy analysis. It suggests that the best method of solving the puzzle implies a close connection between theory and empirics rather than the introduction of a commodity price. It proves that the omission of a measure of output gap (or potential output) spuriously produces a price puzzle (and several other incorrect conclusions) in a wide class of commonly used models. This can happen even if the model admits a triangular identification and if the forecasts produced by the misspecified VAR are optimal. When the model is tested on US data, all predictions are supported.Price puzzle; monetary policy; misspecification; output gap; potential output; technology shocks; VAR;

Stronger evidence of long-run neutrality: a comment on Bernanke and Mihov

Few propositions in macroeconomics are less controversial than long-run money neutrality, yet clear and robust empirical support has not been found in time series studies. Bernanke and Mihov (1998) are comparatively successful in this hunt, but their output response to monetary policy shocks remains stubbornly persistent. This paper argues that the omission of a measure of output gap from the VAR estimated by Bernanke and Mihov lies at the heart of this ''excessive'' persistence. In the theoretical framework of a New Keynesian model similar to that of Svensson (1997) and Clarida, Gali and Gertler (1999), I prove that this omission induces persistence overestimation under relatively mild assumptions. The inclusion of a proxy for the output gap in the VAR is then shown to drastically increase the evidence for long-run money neutrality on US data, as predicted by the theoretical analysis.long-run money neutrality; technology shocks; output gap; VAR misspecification

Possibilistic and fuzzy clustering methods for robust analysis of non-precise data

This work focuses on robust clustering of data affected by imprecision. The imprecision is managed in terms of fuzzy sets. The clustering process is based on the fuzzy and possibilistic approaches. In both approaches the observations are assigned to the clusters by means of membership degrees. In fuzzy clustering the membership degrees express the degrees of sharing of the observations to the clusters. In contrast, in possibilistic clustering the membership degrees are degrees of typicality. These two sources of information are complementary because the former helps to discover the best fuzzy partition of the observations while the latter reflects how well the observations are described by the centroids and, therefore, is helpful to identify outliers. First, a fully possibilistic k-means clustering procedure is suggested. Then, in order to exploit the benefits of both the approaches, a joint possibilistic and fuzzy clustering method for fuzzy data is proposed. A selection procedure for choosing the parameters of the new clustering method is introduced. The effectiveness of the proposal is investigated by means of simulated and real-life data

The Immigration Policy Puzzle

This paper revisits the puzzle of immigration policy: standard economic theory predicts that free immigration improves natives' welfare, but (with few historical exceptions) an open door policy is never implemented in practice. What rationalizes the puzzle? We first review the model of immigration policy where the policy maker maximizes national income of natives net of the tax burden of immigration (Borjas, 1995). We show that this model fails to provide realistic policy outcomes when the receiving region's technology is described by a standard Cobb-Douglas or CES function, as the optimal policy imposes a complete ban on immigration or implies an unrealistically large number of immigrants relative to natives. Then the paper describes three extensions of this basic model that reconcile the theory with the evidence. The first introduces a cost of integration of the immigrant community in the destination country; the second takes into account the policy maker's redistributive concern across different social groups; the last extension considers positive spillover effects of (skilled) migrants on the receiving economy.Costs and benefits from immigration; immigration policy.

A possibilistic approach to latent structure analysis for symmetric fuzzy data.

In many situations the available amount of data is huge and can be intractable. When the data set is single valued, latent structure models are recognized techniques, which provide a useful compression of the information. This is done by considering a regression model between observed and unobserved (latent) fuzzy variables. In this paper, an extension of latent structure analysis to deal with fuzzy data is proposed. Our extension follows the possibilistic approach, widely used both in the cluster and regression frameworks. In this case, the possibilistic approach involves the formulation of a latent structure analysis for fuzzy data by optimization. Specifically, a non-linear programming problem in which the fuzziness of the model is minimized is introduced. In order to show how our model works, the results of two applications are given.Latent structure analysis, symmetric fuzzy data set, possibilistic approach.

A least squares approach to Principal Component Analysis for interval valued data

Principal Component Analysis (PCA) is a well known technique the aim of which is to synthesize huge amounts of numerical data by means of a low number of unobserved variables, called components. In this paper, an extension of PCA to deal with interval valued data is proposed. The method, called Midpoint Radius Principal Component Analysis (MR-PCA) recovers the underlying structure of interval valued data by using both the midpoints (or centers) and the radii (a measure of the interval width) information. In order to analyze how MR-PCA works, the results of a simulation study and two applications on chemical data are proposed.Principal Component Analysis, Least squares approach, Interval valued data, Chemical data

Reconsidering the Role of Money for Output, Prices and Interest Rates

New Keynesian models of monetary policy assign no role to monetary aggregates, in the sense that the level of output, prices, and interest rates can be determined without knowledge of the quantity of money. We evaluate the empirical validity of this prediction by studying the effects of shocks to monetary aggregates using an identified VAR. Shocks to monetary aggregates are isolated by means of identifying restrictions suggested by this class of models. Contrary to the theoretical predictions, shocks to broad monetary aggregates have substantial and persistent effects on output and prices.New-Keynesian models; LM shocks; VAR; Block-exogeneity

Is there Evidence of Pessimism and Doubt in Subjective Distributions? A Comment on Abel

Abel (2002) shows that pessimism and doubt in the subjective distribution of the growth rate of consumption reduce the riskfree rate puzzle and the equity premium puzzle. We quantify the amount of pessimism and doubt in survey data on US consumption and income. Individual forecasters are in fact pessimistic, but show marked overconfidence rather than doubt. Whether this implies that overconfidence should be built into Abel's model depends on how the empirically heterogeneous subjective distributions are mapped into the distribution of a fictitious representative agent. We work out the form of this mapping in an Arrow-Debreu economy and show that the equity premium increases with the dispersion of beliefs. We then estimate this aggregate distribution and find little evidence of either overconfidence or doubt.equity premium; riskfree rate; aggregation of beliefs; Survey of Professional Forecasters; Livingston Survey

Solution of Macromodels with Hansen-Sargent Robust Policies: Some Extensions

We summarize some methods useful in formulating and solving Hansen-Sargent robust control problems, and suggest extensions to discretion and simple rules. Matlab, Octave, and Gauss software is provided. We illustrate these extensions with applications to the term structure of interest rates, the time inconsistency of optimal monetary policy, the effects of expectations on the variances of inflation and output, and on whether central banks should make their forecasts public.robustness; model uncertainty; discretion; simple rules

Inflation Forecast Uncertainty

We study the inflation uncertainty reported by individual forecasters in the Survey of Professional Forecasters 1969-2001. Three popular measures of uncertainty built from survey data are analyzed in the context of models for forecasting and asset pricing, and improved estimation methods are suggested. Popular time series models are evaluated for their ability to reproduce survey measures of uncertainty. The results show that disagreement is a better proxy of inflation uncertainty than what previous literature has indicated, and that forecasters underestimate inflation uncertainty. We obtain similar results for output growth uncertainty.survey data; Survey of Professional Forecasters; GDP growth; VAR; T-GARCH