Coal mined on federally managed lands accounts for approximately 40% of U.S. coal consumption and 13% of total U.S. energy-related CO2 emissions. The U.S. Department of the Interior is undertaking a programmatic review of federal coal leasing, including the climate effects of burning federal coal. This paper studies the interaction between a specific upstream policy, incorporating a carbon adder into federal coal royalties, and downstream emissions regulation under the Clean Power Plan (CPP). After providing some comparative statics, we
present quantitative results from a detailed dynamic model of the power sector, the Integrated Planning Model (IPM). The IPM analysis indicates that, in the absence of the CPP, a royalty adder equal to the social cost of carbon could reduce emissions by roughly ¾ of the emissions reduction that the CPP is projected to achieve. If instead the CPP is binding, the royalty adder would: reduce the price of tradeable emissions allowances, produce some additional emissions reductions by reducing leakage, and reduce wholesale power prices under a mass-based CPP but increase them under a rate-based CPP. A federal royalty adder increases mining of non-federal coal, but this substitution is limited by a shift to electricity generation by gas and renewables.

Key words: extraction royalties, social cost of carbon
JEL codes: Q54, Q58, Q38

The classic papers by Newey and West (1987) and Andrews (1991) spurred a large body of work on how to improve heteroskedasticity- and autocorrelation-robust (HAR) inference in time series regression. This literature finds that using a larger than usual truncation parameter to estimate the long-run variance, combined with Kiefer-Vogelsang (2002, 2005) fixed-b critical values, can substantially reduce size distortions, at only a modest cost in (size-adjusted) power. Empirical practice, however, has not kept up. This paper therefore draws on the post-Newey West/Andrews literature to make concrete recommendations for HAR inference. We derive truncation parameter rules that choose a point on the size-power tradeoff to minimize a loss function. If Newey-West tests are used, we recommend the truncation parameter rule S = 1.3T1/2 and (nonstandard) fixed-b critical values. For tests of a single restriction, we find advantages to using the equal-weighted cosine (EWC) test, where the long run variance is estimated by projections onto Type II cosines, using ν = 0.4T2/3 cosine terms; for this test, fixed-b critical values are, conveniently, tν or F. We assess these rules using first an ARMA/GARCH Monte Carlo design, then a dynamic factor model design estimated using a 207 quarterly U.S. macroeconomic time series.