Bridging DSGE models and the raw data

A method to estimate DSGE models using the raw data is proposed. The approachlinks the observables to the model counterparts via a flexible specification which doesnot require the model-based component to be solely located at business cycle frequencies,allows the non model-based component to take various time series patterns, andpermits model misspecification. Applying standard data transformations induce biasesin structural estimates and distortions in the policy conclusions. The proposed approachrecovers important model-based features in selected experimental designs. Twowidely discussed issues are used to illustrate its practical use.

Estimating overidentified, nonrecursive, time-varying coefficients structural VARs

This paper provides a method to estimate time varying coefficients structuralVARs which are non-recursive and potentially overidentified. The procedureallows for linear and non-linear restrictions on the parameters, maintainsthe multi-move structure of standard algorithms and can be used toestimate structural models with different identification restrictions. We studythe transmission of monetary policy shocks and compare the results with thoseobtained with traditional methods.

The effects of structural reforms on productivity and profitability enhancing reallocation: Evidence from Colombia

Estimates for the U.S. suggest that at least in some sectors productivity enhancing reallocationis the dominant factor in accounting for producitivity growth. An open question, particularlyrelevant for developing countries, is whether reallocation is always productivity enhancing. Itmay be that imperfect competition or other barriers to competitive environments imply that thereallocation process is not fully e?cient in these countries. Using a unique plant-levellongitudinal dataset for Colombia for the period 1982-1998, we explore these issues byexamining the interaction between market allocation, and productivity and profitability.Moreover, given the important trade, labor and financial market reforms in Colombia during theearly 1990's, we explore whether and how the contribution of reallocation changed over theperiod of study. Our data permit measurement of plant-level quantities and prices. Takingadvantage of the rich structure of our price data, we propose a sequential mehodology to estimateproductivity and demand shocks at the plant level. First, we estimate total factor productivity(TFP) with plant-level physical output data, where we use downstream demand to instrumentinputs. We then turn to estimating demand shocks and mark-ups with plant-level price data, usingTFP to instrument for output in the inversedemand equation. We examine the evolution of thedistributions of TFP and demand shocks in response to the market reforms in the 1990's. We findthat market reforms are associated with rising overall productivity that is largely driven byreallocation away from low- and towards highproductivity businesses. In addition, we find thatthe allocation of activity across businesses is less driven by demand factors after reforms. Wefind that the increase in aggregate productivity post-reform is entirely accounted for by theimproved allocation of activity.

Spanish monetary policy: A structural VAR analysis

Some past studies analyzed Spanish monetary policy with the standard VAR. Their problem is that this method obliges researchers to impose a certain extreme form of the short run policy rule on their models. Hence, it does not allow researchers to study the possibility of structural changes in this rule, either. This paper overcomes these problems by using the structural VAR. I find that the rule has always been that of partial accommodation. Prior to 1984, it was quite close to money targeting. After 1984, it became closer to the interest rate targeting, with more emphasis on the exchange rate.

Power transformations in correspondence analysis

Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE.

PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.

Structural changes in the US economy: is there a role for monetary policy?

This paper investigates the contribution of monetary policy to the changes in outputgrowth and inflation dynamics in the US. We identify a policy shock and a policy rule ina time-varying coefficients VAR using robust sign restrictions. The transmission of policyshocks has been relatively stable. The variance of the policy shock has decreased over time,but policy shocks account for a small fraction of the level and of the variations in inflationand output growth volatility and persistence. We find little evidence of a significant increasein the long run response of the interest rate to inflation. A more aggressive inflation policyin the 1970s would have produced large output growth costs.

The modal nature of structures in ontic structural realism

Ontic structural realism is the view that structures are what is real in the first place in the domain of fundamental physics. The structures are usually conceived as including a primitive modality. However, it has not been spelled out as yet what exactly that modality amounts to. This paper proposes to fill this lacuna by arguing that the fundamental physical structures possess a causal essence, being powers. Applying the debate about causal vs. categorical properties in analytic metaphysics to ontic structural realism, I show that the standard argument against categorical and for causal properties holds for structures as well. Structural realism, as a position in the metaphysics of science that is a form of scientific realism, is committed to causal structures. The metaphysics of causal structures is supported by physics, and it can provide for a complete and coherent view of the world that includes all domains of empirical science.

The structural nature of perceptual experiences

Intuitively, we think of perception as providing us with direct cognitive access to physical objects and their properties. But this common sense picture of perception becomes problematic when we notice that perception is not always veridical. In fact, reflection on illusions and hallucinations seems to indicate that perception cannot be what it intuitively appears to be. This clash between intuition and reflection is what generates the puzzle of perception. The task and enterprise of unravelling this puzzle took, and still takes, centre stage in the philosophy of perception. The goal of my dissertation is to make a contribution to this enterprise by formulating and defending a new structural approach to perception and perceptual consciousness. The argument for my structural approach is developed in several steps. Firstly, I develop an empirically inspired causal argument against naïve and direct realist conceptions of perceptual consciousness. Basically, the argument says that perception and hallucination can have the same proximal causes and must thus belong to the same mental kind. I emphasise that this insight gives us good reasons to abandon what we are instinctively driven to believe - namely that perception is directly about the outside physical world. The causal argument essentially highlights that the information that the subject acquires in perceiving a worldly object is always indirect. To put it another way, the argument shows that what we, as perceivers, are immediately aware of, is not an aspect of the world but an aspect of our sensory response to it. A view like this is traditionally known as a Representative Theory of Perception. As a second step, emphasis is put on the task of defending and promoting a new structural version of the Representative Theory of Perception; one that is immune to some major objections that have been standardly levelled at other Representative Theories of Perception. As part of this defence and promotion, I argue that it is only the structural features of perceptual experiences that are fit to represent the empirical world. This line of thought is backed up by a detailed study of the intriguing phenomenon of synaesthesia. More precisely, I concentrate on empirical cases of synaesthetic experiences and argue that some of them provide support for a structural approach to perception. The general picture that emerges in this dissertation is a new perspective on perceptual consciousness that is structural through and through.

A structural model of Australia as a small open economy

This paper sets up and estimates a structuralmodel of Australia as a small open economyusing Bayesian techniques. Unlike other recentstudies, the paper shows that a small microfoundedmodel can capture the open economydimensions quite well. Specifically, the modelattributes a substantial fraction of the volatilityof domestic output and inflation to foreigndisturbances, close to what is suggested by unrestrictedVAR studies. The paper also investigatesthe effects of various exogenous shockson the Australian economy.