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Calculates annual net profits on the company-technology level for the baseline and late and sudden scenarios. Climate laggards which need to build out their production in increasing technologies to compensate for their missed targets, are "punished" by adjusting the net profit margin on their additional build out based on their proximity to target within the given technology. Specifically, we measure the ratio of how much of the required build out or reduction in a technology the company will have done at the end of the forecast period. If the technology has an increasing target and the ratio of completion is below one, the net_profit_margin on the additional production build out is multiplied with the proximity to the target. This approximates the additional capital investment such a company would have to make in a short time, which leads to added costs. This ensures that late build out will not proportionally translate into increased profits.

Usage

calculate_net_profits(data, carbon_data, shock_year, market_passthrough)

Arguments

data

A data frame containing the production forecasts of companies under baseline and late and sudden, market prices/costs, company net profit margins, the proximity to target in the production forecast period and an indication of the direction of the technology.

carbon_data

NGFS carbon prices.

shock_year

A numeric vector of length one that indicates in which year the policy shock strikes in a given scenario.

market_passthrough

A firm's ability to pass a carbon tax onto the consumer. companies can be boosted under a shock scenario.