Weather Shocks

Gallic, Ewen and Vermandel, Gauthier (2017): Weather Shocks.

Abstract

How much do weather shocks matter? The literature addresses this question in two isolated ways: either by looking at long-term effects through the prism of theoretical models, or by focusing on short-term effects using empirical analysis. We propose a framework to bring together both the short and long-term effects through the lens of an estimated DSGE model with a weather-dependent agricultural sector. The model is estimated using Bayesian methods and quarterly data for New Zealand using the weather as an observable variable. In the short-run, our analysis underlines the key role of weather as a driver of business cycles over the sample period. An adverse weather shock generates a recession, boosts the non-agricultural sector and entails a domestic currency depreciation. Taking a long-term perspective, a welfare analysis reveals that weather shocks are not a free lunch: the welfare cost of weather is currently estimated at 0.19% of permanent consumption. Climate change critically increases the variability of key macroeconomic variables (such as GDP, agricultural output or the real exchange rate) resulting in a higher welfare cost peaking to 0.29% in the worst case scenario.

• Item Type: MPRA Paper
• Language: English
• Keywords: Business Cycles; Climate Change; Weather Shocks; DSGE
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate ; Natural Disasters and Their Management ; Global Warming

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A Building Projections up to 2100

To investigate the potential impact of climate change on aggregate fluctuations, we assume that the volatility the weather (ηtW ) (Equation 1) will be affected by climate change. Instead of arbitrarily setting a value for this shift, we provide an approximation using a proxy for the drought index. To do so, we rely on monthly climatic data simulated from a circulation climate model, the Community Climate System Model (CCSM). The resolution of the dataset is a 0.9◦ × 1.25◦ grid. Simulated data are divided into two sets: one of historical data up to 2005 and one of projected data from 2006 to 2100. The projected data are given for four scenarios of greenhouse gas concentration trajectories, the so-called Representative Concentration Pathways (RCPs). The first three, i.e., the RCPs of 2.6, 4.5 and 6.0, are characterized by increasing greenhouse gas concentrations, which peak and then decline. The date of this peak varies among scenarios: around 2020 for the RCP 2.6 scenario, around 2040 for the RCP 4.5 and around 2080 for the RCP 6.0. The last scenario, the doom and gloom 8.5 pathway, is based on