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# Acres Burned to Date

Summary:
Not a record year, yet. Source: WaPo. Figure 1: Acres burned (blue) and acres burned year-to-date 6 August (red), and log linear regression fit (black). Data before 1983 is collected using a different methodology, and hence is not strictly comparable to 1983-2018 data. Source: NIFC1, NIFC2. The regression equation used to estimate the trend is: log(ACRES) = 10.91 + 0.0433×TIME bold denotes significance at 1% msl using HAC robust standard errors. Adj.-R2 = 0.46. DW = 2.09. The coefficient on time can be interpreted as indicating that the number of acres burned is trending up at 4.3% per year, although a 95% confidence interval would encompass a figure as low as 2.9% and as high as 5.7%. The correlation between suppression costs and acres burned is high (see this post). 2017 suppression

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Not a record year, yet.

Source: WaPo.

Figure 1: Acres burned (blue) and acres burned year-to-date 6 August (red), and log linear regression fit (black). Data before 1983 is collected using a different methodology, and hence is not strictly comparable to 1983-2018 data. Source: NIFC1, NIFC2.

The regression equation used to estimate the trend is:

log(ACRES) = 10.91 + 0.0433×TIME

bold denotes significance at 1% msl using HAC robust standard errors. Adj.-R2 = 0.46. DW = 2.09.

The coefficient on time can be interpreted as indicating that the number of acres burned is trending up at 4.3% per year, although a 95% confidence interval would encompass a figure as low as 2.9% and as high as 5.7%.

The correlation between suppression costs and acres burned is high (see this post). 2017 suppression costs by the Federal government (i.e., not including state costs) was \$2.9 billion.

He is Professor of Public Affairs and Economics at the University of Wisconsin, Madison