Today, we are glad to introduce the reason Filippo Natoli Director of the General Directorate of Economics, Statistics and Research of the Bank of Italy. The views expressed in this note are those of the author and do not necessarily reflect the views of Bank of Italy.
Central banks are discussing how best to contribute to the global response to climate change. I provide insights into how U.S. monetary policy has responded to adverse economic shocks from temperature fluctuations over the past 50 years.
Climate scientists and economists agree: climate change is a threat to future economic performance. The literature does show that rising and fluctuating temperatures have severely affected countries’ gross domestic product in recent decades.Although there are significant differences between economies this Econbrowser Post, developed countries like the US are no exception.
This has brought challenges to policy makers. Although the monetary authorities are not as central as the government in response to climate change, people have discussed a warm discussion about the approach to central banks to use their policy tool packages to reduce their economic impact. However, the extent to which the conduct of monetary policy itself may be affected by current climate trends remains unclear. The reason for this lack of evidence is that the common impact of temperature fluctuations on economic output and consumer prices, and the correct monetary policy response, is a suspended issue. Extreme temperatures could have supply-side effects – for example, by reducing labor productivity – and demand-side effects – for example, by increasing household and corporate energy spending – so it is unclear whether and how monetary policy responds to temperature impact.
I deal with this problem By quantifying the impact of temperature oscillations on the U.S. economy. I study how consumption, investment and final GDP are affected, how the CPI index reflects, and how these influences spread to the short -term and long -term interest rates of government bonds.
To this end, I propose a new method to identify unpredictable temperature changes consistent with the concept of shock in macroeconomics. Using the average daily temperature for each county in the United States since the 1970s, I calculate a quarterly county-level “surprise” as the difference between the number of high and low temperature days within the quarter and the average number of days observed for the same quarter over the past five years. The basic idea is that the agent understands the distribution of temperature and based on their recent experience to form their belief in the highest and lowest temperature in the current season. These beliefs are updated every year. County-level surprises were aggregated to get a U.S.-wide “temperature shock.” By focusing on the magnitude of the shock and by identifying exogenous changes associated with recent temperature data, my approach underscores the idea that, by proxy of surprise, unusually hot and cold weather is important in the short term. Thus, it overcomes the deficiencies of other methods proposed in the literature based on positive and negative temperature changes – which can mix good and bad economic shocks – and fixed effects panel estimates – where temperature changes relative to the long-term average are ok Climate change is projected to increase the incidence of extreme temperatures over time.
Figure 1 shows the contingency rates by county (panel a) and the evolution of temperature shocks over time across the United States (panel b). The first picture shows the largest surprises in southern counties from 1975 to 2019; the second shows that, at the national level, the adjustment in the shape of the temperature distribution is largest in the early stages of the sample than in recent times – triggering a larger impact. This does not mean that the range of temperature fluctuations has decreased, and the extreme temperature has become more normal recently, so they are not so surprising compared to the past.
figure 1 -Gun County -level temperature surprise and the temperature impact of the United States
resource: Natoli, F. “temperature surprise shock”, MPRA Working Paper n. 112568, March 2022. [Latest version here]
I then use the constructed U.S.-wide shocks to study the responses of key economic variables using local forecasts. Panel (a) of Figure 2 shows the results for GDP and CPI: while the negative impact on economic activity is large, the negative impact on the CPI index is more moderate, suggesting that the demand and supply side effects are likely to average. The shock elicits a significant Fed response, as shown in panel (b): Consistent with the GDP response, the Fed’s economic now forecast (generated in the Green Book forecast) was revised down months after the shock due to shock. This triggered an expansionary monetary policy response as short-term interest rates fell on the same level. Although the behavior of short -term interest rates itself does not guarantee the Federal Reserve to correctly determine the root cause of economic decline, some evidence shows that the Fed immediately increases the attention of temperature fluctuations after the impact. Indeed, the occurrence of temperature-related phrasing in transcripts for each FOMC increased slightly after adverse temperature shocks (last picture of panel B).
figure 2 -The response to the impact of bad temperature
resource: Natoli, F. “Temperature surprise impact”, MPRA Working Paper n. 112568, March 2022. [Latest version here]
Taken together, these findings suggest that climate-related shocks have collectively shaped the conduct of U.S. monetary policy over the past 50 years, adding another piece of evidence to the debate about the role central banks can play in offsetting climate economic impacts. Change.
This article is by Filippo Natoli.
