Publications by Barci & Martínez
PS3 - Advanced Time Series
QUESTIONS Suppose that you work in a Central Bank and you are asked to estimate a dynamic factor model (like in homework 2) with a quarterly variable and four monthly variables (all contemporaneous, not leading or lagging behavior, exactly like in Homework2). Following the MATLAB codes, seen in class, The matrix filter represents: a The estimati...
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Homework 2
Question 1 Suppose you are hired in the central bank of NERDILAND. You get there the first day and you see that they only have four time series to do their forecast of economic activity. They are all monthly. We denote the log levels of these series as \(Y_{1t}, Y_{2t}, Y_{3t}, Y_{4t}\) and we can assume that all of them share the business cycle ...
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Notes New Keynesian
Household The household sector is made by a representative household maximising his expected lifetime utility \(U(C_t, N_t)\) at period \(t = 0\) . Assume a utility function depending only on consumption \(C_t\) and normalised leisure \(1-N_t\). Assume that regularity conditions on the utility function hold and that it is concave in its arguments...
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TFM Regressions
TFM - Test Regressions Lucía, Cheché & Andrés 19/4/2021 Load libraries and data library(ExPanDaR) library(dplyr) library(tidyr) library(plyr) library(ggplot2) library(kableExtra) library(magrittr) library(plm) library(panelr) library(ggplot2) library(tibble) library(fastDummies) #Load the data dta_wide <- readRDS(url("https://git...
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TFM - Test Regressions
TFM - Test Regressions Lucía, Cheché & Andrés 19/4/2021 Load libraries and data library(ExPanDaR) library(dplyr) library(tidyr) library(plyr) library(ggplot2) library(kableExtra) library(magrittr) library(plm) library(panelr) library(ggplot2) library(tibble) library(fastDummies) library(broom) library(mFilter) #Load the data dt...
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Document
The four variables we are talking about are in y_t (nx1) and we have a vector of x_t where there are variables affecting only y_t (a particular element) and h_t is the common. The observables are in the y_t and the non observables are in h_t. We are saying that there is something not observable which is in h_t. What is the difference between PCA ...
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PS1 - Advanced Time Series
Advanced Time Series - Part II - PS1 You are hired in the central bank of country Listoland. They forecast GDP with univariate methods. Their goal is to forecast quarterly GDP growth. As of today (april 6th 2018), the last observation available is 2017Q4. You think that there is information in other variables that could be related to GDP growth. ...
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What is PCA?
What is PCA? Principal components analysis (PCA) is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss. PCA is an: Unsupervised approach: because it involves only a set of features or variables \(X_1, X_2, ... , X_p\) and no associated response \(Y\) Feature ...
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