The cross-correlation between output and nominal variables in new keynesian models calibrated to Brazil and the U.S.

Abstract

Este artigo investiga se a interação entre formação de hábito e uma regra de Taylor prospectiva consegue reproduzir o padrão de correlação entre produto e variáveis nominais (inflação e taxa de juros) para o Brasil e os Estados Unidos. O estudo emprega um modelo Novo-Keynesiano com rigidez de preço ou de informação. O padrão de correlações vindo dos dados para o Brasil é diferente do padrão para os Estados Unidos. Para ambos os países, os modelos considerados não conseguem reproduzir com um bom grau de precisão os padrões de correlação entre produto e variáveis nominais, embora os modelos de rigidez de preços e de informação impliquem em diferentes mecanismos de propagação dos choques macroeconômicos.Keywords: correlação cruzada, Novo-Keynesiano, variáveis nominais Abstract This paper investigates if the interaction between habit formation and a forward-looking Taylor rule can mimic the observed dynamic correlations between output and nominal variables (inflation and interest rates) in Brazil and in the U.S. I carry out the analysis in a new Keynesian model under sticky price or sticky information. The empirical cross-correlation pattern, obtained from the data, for Brazil is different from the U.S. pattern. For both countries, the models that I considered cannot replicate with a fair amount of accuracy the dynamic correlations between output and nominal variables, though sticky price models and sticky information models imply different propagation mechanisms for macroeconomic shocks.

The relationship between new PCR positive cases and going out in public during the COVID-19 epidemic in Japan

“…In addition, CCF was used to estimate the speed of influenza epidemics by comparing the lag in drug sales between geographically separated pharmacies in Japan [ 63 ]. Moreover, it has been used to detect the correlation pattern between output and nominal variables in economics [ 64 ]. Following the previous study [ 63 ], CCF was defined as the following equation.…”

The relationship between new PCR positive cases and going out in public during the COVID-19 epidemic in Japan

“…In addition, CCF was used to estimate the speed of influenza epidemics by comparing lag in drug sales between pharmacies that were geographically separated in Japan [47]. Moreover, it has been used to detect the correlation pattern between output and nominal variables in economics [48]. Following the previous study [47], CCF was defined as: 1) where CCF ( l ) denotes the cross-correlation function between two time series, X ( t ) and Y ( t ), E[.]…”

“…The copyright holder for this preprint this version posted March 8, 2021. ; https://doi.org/10.1101/2021.03.07.21252959 doi: medRxiv preprint geographically separated in Japan [47]. Moreover, it has been used to detect the correlation pattern between output and nominal variables in economics [48]. Following the previous study [47], CCF was defined as: 1 Interpreting the results of CCF analysis focuses on two points: the sign of the lag and the sign of the cross-correlation.…”