Figure 4.
The vertical axis shows beta of tau, and tau on the horizontal axis, ranging from 0.1 to 0.9. Panel A is titled one-quarter-ahead: Climate. Panel B is titled one-year-ahead: Climate. Panel C is titled one-quarter-ahead: current G D P. Panel D is titled one-year-ahead: current G D P. Each panel contains three labelled lines: In-sample fit, Median, and O L S. Shaded bands surround the lines across tau values. In Panel A, beta ranges approximately from minus 0.8 to 0.7. In Panel B, beta ranges approximately from minus 0.6 to 0.9. In Panel C, beta ranges approximately from minus 0.1 to 1.1. In Panel D, beta ranges approximately from 0.0 to 1.8. A horizontal line at zero appears in each panel.Do the estimated quantile regression coefficients align with a flexible and general linear model [that is, a VAR(4)]?
Note(s): This figure displayed estimated quantile coefficients of one-quarter-ahead and one-year-ahead. Following Adrian et al. (2019), we present the 95 % confidence bounds for the null hypothesis that the true data-generating process is a general, flexible linear model for growth and Climate, represented as a vector-auto regression (VAR) with four lags. Gaussian innovations and a constant using Climate and real GDP growth over the full sample. Bounds are computed using 1.000 bootstrapped samples