Weather Shocks

Authors

Affiliations

Ewen Gallic

Aix-Marseille School of Economics, Aix-Marseille Univ, France.

Gauthier Vermandel

CMAP, Ecole polytechnique, Institut Polytechnique de Paris

Index

This ebook provides some notebooks to help adapting the methodology of our paper Weather Shock (Gallic and Vermandel (2020)) to new contexts or datasets.

Warning

The notebooks are in construction. Their content is likely to change soon.

Links to Resources

The codes presented in this notebook differ slightly from those used in the paper (and given in the replication codes). The paper and the content of this notebook was presented to the NGFS Workstream on Monetary Policy. The slides of the presentation of the paper can be accessed.

Paper in the EER Author’s version of the paper Technical Appendix Replication Codes (Zip archive) Slides

If you found this ebook useful, please consider sharing our paper:

@article{Gallic_2020_eer,
  doi = {10.1016/j.euroecorev.2020.103409},
  url = {https://doi.org/10.1016%2Fj.euroecorev.2020.103409},
  year = 2020,
  month = {may},
  publisher = {Elsevier {BV}},
  volume = {124},
  pages = {103409},
  author = {Gallic, Ewen and Vermandel, Gauthier},
  title = {Weather shocks},
  journal = {European Economic Review}
}

Structure of the Document

This notebook is organized into three main parts:

1. Data. This part gathers two types of data: weather and macroeconomic. The main challenge lies in constructing a weather variable with a temporal and spatial resolution consistent with quarterly national macroeconomic data.
   Unlike in the paper, this notebook uses gridded weather data from NOAA to build the drought index. The data are available at a monthly frequency and for each grid cell, which can be matched to regional boundaries defined in Chapter 2  Maps.
   All instructions for downloading and importing NOAA data are provided in Chapter 3  Weather Data: Download. Missing observations at the cell level can be imputed using methods described in Chapter 4  Weather Data: Missing Data.
   Weather and climate metrics, including the SMDI (the main drought index used in the paper) and complementary indicators such as the SPEI at various horizons, are introduced in Chapter 5  Weather Data: Metrics.
   Macroeconomic data, primarily from the OECD and Statistics New Zealand, are cleaned and merged with the weather data in Chapter 6  Merge With Macroeconomic Data, producing the dataset used for subsequent analyses. Finally, Chapter 7  Climate Projection presents climate projections under four Representative Concentration Pathways (RCPs).

2. VAR. Chapter 8  Estimation presents the empirical analysis using a structural VAR model to study the dynamic effects of a drought shock on New Zealand’s economy.

3. DSGE. The final part introduces the theoretical DSGE model (Chapter 9  The Theoretical Model) and its empirical implementation using Dynare (version 6.x, with MATLAB interface) in Chapter 10  Estimation.

Gallic, Ewen, and Gauthier Vermandel. 2020. “Weather Shocks.” European Economic Review 124 (May): 103409. https://doi.org/10.1016/j.euroecorev.2020.103409.