framework enables us to analyze the allocative efficiency consequences of implementing a hypothetical carbon tax at the firm level. Moreover, our model emphasizes the pivotal role of pre-existing distortions within the input market and their implications on the efficacy of such a policy measure.

In our paper, we extend the theoretical framework from Hsieh and Klenow [2009] to allow for differentiated energy inputs such as fuels and electricity and simulate the within-sector interactions of a carbon tax with existing market frictions. We hypothesize the introduction of a carbon tax levied on firms according to their total emissions from the consumption of fuels and electricity. A key insight gleaned from the model is the heterogeneous impact on firms of the carbon tax, contingent on the correlations between the energy distortions with the output and capital wedges, and the correlations between the energy distortions with firm productivity. Specifically, when more productive firms face lower distortions in the energy input markets and when there exists a positive correlation between the capital and output wedges with the energy wedges, the introduction of an environmental tax will decrease aggregate TFP. This occurs because introducing the carbon tax distorts higher-productivity firms more than lower-productivity ones, given that the former initially faced lower distortions. Consequently, resources are shifted from more productive to less productive firms, increasing misallocation and decreasing aggregate TFP. In contrast, if more productive firms face higher distortions or the correlations between the capital and output wedges with the energy wedges are non-positive, then the introduction of a carbon tax can either increase or decrease aggregate TFP.

Using detailed data on firms’ tax declarations and energy expenditures from the Direccion General de Impuestos Internos (DGII) of the Dominican Republic and aggregate information from the National Energy Information System (SIEN) between 2009 and 2018, we calibrate the model at the sector level. Using this data, we first provide a back-of-the envelope calculation of the revenues generated by the introduction of a carbon tax rate using plausible scenarios.<sup>8</sup> We find that, based on the most recent estimates in 2018, a tax of $110/tCO2 would generate carbon tax revenues approximately of $920 millions, or roughly 10% of total taxes collected in 2018.<sup>9</sup> On average, this represents roughly 20% of the total earnings reported by the firms in our sample in the same year, although there is substantial variation across sectors. The sectors with the highest carbon emissions footprint and that are also likely to be particularly impacted by the policy in the short term are transport, cement, and hospitality.

We conduct our main counterfactual exercise on the impact of a carbon tax in the DR accounting for input market frictions within sectors. We do not estimate frictions explicitly, but infer them from observed

> 8The estimated carbon prices are the output of an independent analysis on the DR, and are based on the REMIND-MAgPIE 3.0-4.4 model. For more information, see `https://www.ngfs.net/ngfs-scenarios-portal/explore` .

> 9The percentage of total taxes collected in 2018 is computed using an average exchange rate of 49.54 DOP/USD and 430,629 million DOP of total taxes collected in 2018.

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