Credit Supply and the Housing Boom Justiniano, Alejandro; Primiceri, Giorgio E.; Tambalotti, Andrea
The Journal of political economy,
06/2019, Letnik:
127, Številka:
3
Journal Article
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An increase in credit supply driven by looser lending constraints in the mortgage market is the key force behind four empirical features of the housing boom before the Great Recession: the ...unprecedented rise in home prices, the surge in household debt, the stability of debt relative to house values, and the fall in mortgage rates. These facts are more difficult to reconcile with the popular view that attributes the housing boom only to looser borrowing constraints associated with lower collateral requirements, because they shift the demand for credit.
PRIOR SELECTION FOR VECTOR AUTOREGRESSIONS Giannone, Domenico; Lenza, Michele; Primiceri, Giorgio E.
The review of economics and statistics,
05/2015, Letnik:
97, Številka:
2
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Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to ...unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables. A solution to this problem is to use informative priors in order to shrink the richly parameterized unrestricted model toward a parsimonious naive benchmark, and thus reduce estimation uncertainty. This paper studies the optimal choice of the informativeness of these priors, which we treat as additional parameters, in the spirit of hierarchical modeling. This approach, theoretically grounded and easy to implement, greatly reduces the number and importance of subjective choices in the setting of the prior. Moreover, it performs very well in terms of both out-of-sample forecasting—as well as factor models—and accuracy in the estimation of impulse response functions.
ECONOMIC PREDICTIONS WITH BIG DATA Giannone, Domenico; Lenza, Michele; Primiceri, Giorgio E.
Econometrica,
September 2021, Letnik:
89, Številka:
5
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We compare sparse and dense representations of predictive models in macroeconomics, microeconomics, and finance. To deal with a large number of possible predictors, we specify a prior that allows for ...both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse model, but on a wide set of models that often include many predictors.
Mutational activation of KRAS promotes the initiation and progression of cancers, especially in the colorectum, pancreas, lung, and blood plasma, with varying prevalence of specific activating ...missense mutations. Although epidemiological studies connect specific alleles to clinical outcomes, the mechanisms underlying the distinct clinical characteristics of mutant KRAS alleles are unclear. Here, we analyze 13,492 samples from these four tumor types to examine allele- and tissue-specific genetic properties associated with oncogenic KRAS mutations. The prevalence of known mutagenic mechanisms partially explains the observed spectrum of KRAS activating mutations. However, there are substantial differences between the observed and predicted frequencies for many alleles, suggesting that biological selection underlies the tissue-specific frequencies of mutant alleles. Consistent with experimental studies that have identified distinct signaling properties associated with each mutant form of KRAS, our genetic analysis reveals that each KRAS allele is associated with a distinct tissue-specific comutation network. Moreover, we identify tissue-specific genetic dependencies associated with specific mutant KRAS alleles. Overall, this analysis demonstrates that the genetic interactions of oncogenic KRAS mutations are allele- and tissue-specific, underscoring the complexity that drives their clinical consequences.
This note shows how to apply the procedure of Kim et al. (1998) to the estimation of VAR, DSGE, factor, and unobserved components models with stochastic volatility. In particular, it revisits the ...estimation algorithm of the time-varying VAR model of Primiceri (2005). The main difference of the new algorithm is the ordering of the various MCMC steps, with each individual step remaining the same.
We present our assessment of tertiary structure predictions for hard targets in Critical Assessment of Structure Prediction round 13 (CASP13). The analysis includes (a) assignment and discussion of ...best models through scores‐aided visual inspection of models for each evaluation unit (EU); (b) ranking of predictors resulting from this evaluation and from global scores; and (c) evaluation of progress, state of the art, and current limitations of protein structure prediction. We witness a sizable improvement in tertiary structure prediction building on the progress observed from CASP11 to CASP12, with (a) top models reaching backbone RMSD <3 å for several EUs of size <150 residues, contributed by many groups; (b) at least one model that roughly captures global topology for all EUs, probably unprecedented in this track of CASP; and (c) even quite good models for full, unsplit targets. Better structure predictions are brought about mainly by improved residue‐residue contact predictions, and since this CASP also by distance predictions, achieved through state‐of‐the‐art machine learning methods which also progressed to work with slightly shallower alignments compared to CASP12. As we reach a new realm of tertiary structure prediction quality, new directions are proposed and explored for future CASPs: (a) dropping splitting into EUs, (b) rethinking difficulty metrics probably in terms of contact and distance predictions, (c) assessing also side chains for models of high backbone accuracy, and (d) assessing residue‐wise and possibly residue‐residue quality estimates.
Summary
This paper illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID‐19 pandemic—when estimating a vector autoregression, which is the most popular ...time‐series model in macroeconomics. Our results show that the ad hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it may underestimate uncertainty.
El metacaolín es el producto obtenido de la calcinación del caolín. La alta actividad puzolánica del metacaolín permite su utilización como un material sustituto del cemento en el concreto. Esta y ...otras propiedades fisicoquímicas se ven afectadas por las condiciones de procesamiento del caolín. Por lo tanto, este estudio tuvo como objetivo caracterizar los cambios del color y densidad de dos tipos de caolín (toba triturada e hidrotermal) por medio de un análisis termogravimétrico del proceso de calcinación. Para la evaluación de la densidad se empleó la norma ASTM C188, mientras que la valoración de los cambios de color utilizó un espectrofotómetro CIE-L*a*b* en conjunto con la norma UNE 80117. Asimismo, la pérdida de peso y la densidad se correlacionaron con las coordenadas de color mediante una regresión polinomial. Los resultados demostraron que la deshidroxilación de los caolines ocurrió entre 400ºC y 650ºC, caracterizándose por un máximo en el delta E * de 12.9 y 4.3 para el caolín hidrotermal y de toba, respectivamente. Además, el caolín de toba triturada presentó la máxima luminosidad (L* = 92.84) de todos los tratamientos a los 21ºC. Este valor disminuyó 11.75% al incrementar la temperatura hasta 450ºC. A partir de esta temperatura, L* incrementó linealmente hasta alcanzar un valor final de 87.3 a 900ºC. La regresión polinomial obtenida explica en un 93% y 92% la variación del peso en función de los parámetros CIE-L*a*b* para el caolín de toba triturada e hidrotermal, respectivamente.
We present our assessment of CASP12 modeling efforts for targets with no obvious templates of high sequence/structure similarity in the PDB, that is for evaluation units of the free modeling (FM) and ...free modeling/template‐based modeling (FM/TBM) categories. Models were clustered and ranked using the Global Distance Test‐Total Score and 5 additional metrics developed in previous CASP rounds, producing short lists of models that were subject to visual inspection in comparison to the target structures. The whole procedure was implemented as a web app that facilitates model selection and visual inspection, and could become useful to facilitate and standardize future assessments. We describe cases of (1) targets with remarkably good predictions, (2) targets whose models captured some global shape and topology features, and (3) targets for which models fail to capture even coarse features. We note that despite this CASP being among the most challenging ones, a measurable improvement of the top predictions is apparent, that we attribute to the emergence of accurate contact prediction methods and the increased number of available sequences. We also briefly discuss current limitations in tertiary structure prediction exemplified by CASP12 targets. Overall, the Baker, Zhang, and Lee manual groups and servers were identified as the top global performing groups.
We investigate the sources of the important shifts in the volatility of US macroeconomic variables in the postwar period. To this end, we propose the estimation of DSGE models allowing for time ...variation in the volatility of the structural innovations. We apply our estimation strategy to a large-scale model of the business cycle and find that shocks specific to the equilibrium condition of investment account for most of the sharp decline in volatility of the last two decades.
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