1  User Guide and Climate Policies in CPAT

This document provides guidance to the user on how to use and navigate CPAT and details the various climate policies available. In particular, Section 1.1 presents the different climate policies in CPAT. Section offers a quick start guide of CPAT in which the user can rapidly assess a climate policy via the dashboard. Section 1.2 presents the quick start guide of CPAT. For more in-depth understanding and use of CPAT and the different modules, Section 1.3 describes the different tabs including the dashboard of the CPAT tool and how to navigate through them. It also presents the Multiscenario Tool, which can be used to run CPAT for several countries and/or several scenarios. Section 1.4 provides CPAT’s countries coverage. Finally, Section 1.5 presents the list of parameters of CPAT.

1.1 What climate policies can be assessed using CPAT?

1.1.1 Carbon Pricing Policies

The table below summarizes the climate policies options available in CPAT. The first column displayed the number corresponding to the policy in CPAT Excel-sheet. The carbon tax, ETS, feebate and energy efficiency regulations are qualified general policies as they cover all sectors. Nevertheless, exemptions can be applied for individual fuels and sectors (with the option to phase out exemptions over time). Other policies are sector- or fuel-specific.

Number Policy coverage Description
1 Baseline No climate policy implemented, except from those already captured by the prices data (e.g. existing ETS or carbon tax).
General policies
2 Carbon tax This policy represents a carbon tax applied to the supply of all fossil fuels in proportion to their carbon content. It is modeled by adding to the pre-existing tax on a particular fuel a charge equal to the product of the CO2 emissions factor for that fuel and the tax rate on CO2.
3 ETS These policies are modeled in a similar way to a tax (CPAT is deterministic and does not capture uncertainty over emissions prices associated with ETSs). That is, CPAT requires the user to estimate the likely price of an ETS and then impose that to find the emissions reduction.1
4 Feebates Feebates provide a revenue-neutral, sliding scale of fees on activities (like power generation) or products (like vehicles). Activities or products with above average emission rates pay a net tax; activities or products with below average emission rates get net revenues.
5 Energy efficiency regulations These policies reduce the emissions or energy intensity of a sector but without the same demand response (e.g., reductions in VKT) as under carbon pricing because they do not involve the pass through of carbon tax revenues (or allowance rents) in higher prices (e.g., for electricity or gasoline) – they also produce a partially offsetting increase in emissions through the rebound effect.
Fuel or sector-specific policies
6 Coal excise The coal excise tax is a carbon tax (in the sense of it being defined per ton CO2) only on coal.
7 Road fuel tax Taxes imposed on all fuels in the road transport sector.
8 Electricity emissions tax This policy imposes a carbon tax on the electricity sector.
9 Power feebate This policy covers power supply feebates if the engineer model is selected and covers power usage feebates if the elasticity model is selected.
10 Electricity excise This policy translates into a tax per kWh of electricity used. The tax is set via the standard carbon tax interface. The tax in $/tCO2 is mapped to one per kWh using the year one emission factor as a conversion factor.
11 Vehicle fuel economy This imposes shadow prices (similar to a feebate) in the vehicle sector.
12 Residential efficiency regulations Similar to the energy efficiency regulations, but it only applies to the residential sector.
13 Industrial efficiency regulations Similar to the energy efficiency regulations, but it only applies to the industrial sector.

1.1.2 Fossil Fuel Subsidy Reform Policies.

In addition to these policies, CPAT allows the user to phase out fossil fuel subsidies and reform regulated prices. See the relevant sections below.

1.1.3 Power Sector Policies

The power sector model contains policies that adjust the cost of capital, adjust Power Purchase Agreements etc. See the relevant sections below.

1.2 Quick Start Guide: Climate Policy Assessment Tool (CPAT)

Welcome to CPAT! This guide aims to show you how to use CPAT, give you an idea of some common issues, and indicate CPAT’s data needs.

What is CPAT? CPAT is a tool for analyzing the impacts of carbon pricing and fossil fuel reforms along several economic and non-economic dimensions.

Opening CPAT: CPAT is a spreadsheet-based tool. You need Excel 2016 or later. Since CPAT is a relatively large spreadsheet, please close other apps. Please ensure ‘Automatic Calculations’ are turned on (File > Options > Formulas).

Figure 1.1: Automatic calculations

Navigating CPAT: Please, navigate first to the Dashboard tab.

Figure 1.2: Navigation CPAT

1.2.1 Input: Country and Proposed Policy Trajectory

Policy Input Area: At the top left, you see various input cells. The yellow cells are user-editable. Categorical cells can be altered by clicking the small down arrow. By clicking on the cell which currently shows Carbon tax, you can select a different carbon pricing policy (e.g., an ETS), which comes with sectoral exemptions pre-set. All policies are defined by the carbon price. The carbon price trajectory is defined by the introduction date (here 2022), the start level (here $50/tCO2), the target level of the carbon price (here $75/tCO2), and the year that this target level will be met (here 2030).

Figure 1.3: Country and policy input area

Carbon Price Trajectory: To check that your suggested carbon tax is in place, please see the policy strength graph under Key inputs and outputs. On default settings, the policy is extended linearly beyond the end date. The dotted lines in the left-hand graph show the recommended range for a carbon price recommended by the High-level Commission on Carbon Pricing. The right-hand graph shows the policy’s coverage, including any exemptions (see later for defining exemptions)

Figure 1.4: Carbon price trajectory

1.2.2 Output: Emissions, Revenues, and Co-Benefits

The main outputs are shown under Key inputs and outputs in Panel B. From the left, these graphs show:

Figure 1.5: Key inputs and outputs

  1. GHG emissions relative to baseline (dashed line) & NDC target (dotted horizontal line)

  2. Fiscal revenues (before recycling of funds)

  3. Impact on projected GDP growth

  4. Impacts on households (note: only countries for which household data are available)

  5. Co-benefits: averted air pollution & road accident deaths

  6. Total monetized benefits from the policy

1.2.3 Sense-Checking

The CPAT team is constantly working to keep CPAT up to date, but CPAT is not bulletproof. You should run a few sense-checks as described below. Some of these checks relate to the reliability of input data. Many CPAT users can access national data sources. For continuous improvement of the tool, we would very much appreciate it if such data sources could be shared with us in case data is either missing or substantively different from what is currently in CPAT.

Check 1: Start by ensuring that the graphs show and update when you change carbon price inputs (i.e., there should be no errors in panel B: all graphs should show except, for some countries, the fourth graph on the impact on households).

Defaults for parameters: Click the + button for advanced settings.

Figure 1.6: The ‘+’ button

This expandable panel contains a wide range of parameter settings and adjustments.

Default parameters are indicated with an asterisk (e.g., ‘Base*’). Suppose you change a parameter away from its default setting. In that case, the color changes from yellow to orange. An indicator at the bottom of the ‘Miscellaneous’ section indicates the number of parameters that have departed from default values.

Check 2: Check how many defaults are different from expected. For default use, the line at the bottom of the Miscellaneous row should be blank/invisible.
Example of all settings set to default values Example of two settings NOT set to default values
Example of settings (default) Example of settings (no default)

1.2.4 Exemptions

One can exempt any fuels and sectors from the carbon tax (if unticked). So, if, e.g., Kerosene and Cement are unticked, all Kerosene is exempted (independent of the sector), and all Cement energy use is exempt (independent of fuel).

Check 3: Ensure that all checkboxes are ticked for full policy coverage (recommended) or unticked as desired.

1.2.5 Phase-out exemptions, subsidies, and revenue recycling

On the right-hand side at the top of the dashboard, the user can change settings relating to the phase-out of exemptions, price controls, and subsidies. It also includes supplementing the policy with renewable energy subsidies and the use of revenues. For revenue recycling, there are five options: labor tax reductions, corporate tax reductions, public investment, current spending, and compensatory transfers to households.

Figure 1.7: Phase-out exemptions, subsidies, and revenue recycling

Check 4: The phase-out of exemptions, price controls, and subsidies, as well as the use of revenue, should be as desired by the user.

1.2.6 NDC data

CPAT includes data on countries’ Nationally Determined Contributions (NDCs) under the UNFCCC. The ‘NDCs’ Tab summarizes the NDC baseline data for your country. As countries may be updating their NDCs, please check online in the UNFCCC NDC Registry if the information shown is up to date, and in line with the latest submitted version. If not, please, copy the table, fill it out, and send to the team.

Figure 1.8: NDC data

Check 5: Verify that NDC data are up to date.

1.2.7 Prices

Panel A under the Mitigation module (macro & energy effects) includes a table showing average fuel prices and tax-induced percentage changes. Price changes depend on carbon content as well as pre-existing price distortions (e.g., subsidies).

Note that a significant increase in the price of coal is expected in many countries, even under a moderate carbon tax. For example, $80/t carbon tax with a coal emission factor at ~0.1 tCO2/GJ would correspond to $8/GJ carbon tax. If baseline (subsidized) coal prices were $2/GJ with the subsidy around $0.5/GJ, prices would increase 400%, even without subsidies phase-out. A more moderate situation is shown in the table to the right for Poland, where we see the price of coal increase by 164.8%.

Figure 1.9: Fuel prices

Prices data quality: Look at the heat map to check the quality of the underlying price data. Information is color-coded (see the legend and suggested actions in the map): green shades mean reliable data sources, and yellow/orange cells mean that the users will have to check and confirm prices data.

Figure 1.10: Prices data quality

Prices data form: if the user believes they have better prices data, they can choose to use ‘manual’ prices in calculations and fill the ‘manual inputs’ tab in CPAT. Also we recommend filling and sending this form to the CPAT team so we can update the global CPAT version accordingly.

Check 6: Are prices and percentage changes reasonable?

1.2.8 Distributional consumption effects on households

For distributional results, first, check if household data for your country is already included in CPAT; if not, process your microdata following the Codebook and scripts (3-4 days’ resource commitment); if yes, define how to transfer revenues (drop-down menu under ‘Policy options’); adjust accordingly if red flags appear. If ‘No’ adjustment for behavioral/structural change is selected, the price increases are fully passed on to the consumer, which may overestimate consumption effects (i.e., the tax-induced mitigation effect is not considered). Alternatively, choose to factor in decile-specific, price-driven demand adjustments/elasticities.

Choose whether distributional effects are expressed based on decile-specific mean or median consumption data: While median effects are more representative, some fuels may not be shown if > 50% of households report zero or missing expenses (e.g., due to poor data quality). We recommend that effects not be modeled further than five years out.

Check 7: Make an informed choice on mean/median representation and modelling results without taking into account reduced prices due to behavioral adjustments.

Figure 1.11: Distributional settings

1.2.9 Contribution of sources to ambient particulate matter

Does the contribution by sector look reasonable? A “reasonable number” should be above 20% and below 90% for most countries. The sectorial distribution could be compared to country level information, if available. If the contribution does not look appropriate when comparing with local information available, the user can change the modeling approach.

Figure 1.12: Air pollution settings and sources of ambient particulate matter

The option “Manual-FASST” will allow the user to input their own information, in “Manual inputs tab”. In this case, the user would need to input the contribution of each sector to ambient PM2.5. The recommended default option is “Avg. iF and LS FASST”, which uses the average between the intake fractions model and the Local study-FASST approach.

Check 8: Check sectors’ contribution to ambient PM2.5 and adjust modeling approach if needed.

1.2.10 Road transport co-benefits

In the current version of CPAT, total fatalities from road accidents in 2020 are projected based on 2011-2016 data from World Road Statistics. It is recommended that the user checks the validity of this estimate using local data sources, if available, noting that the underlying assumptions can vary significantly from one data source to another. The user might also want to cross-check “forecasted” total distance driven in 2020 (e.g., around 200 billion vehicle-km for Poland as shown in the left-hand side figure) against national statistics, if available.

Figure 1.13: Transport co-benefits

Check 9: Check data validity on road accidents and total distance driven.

1.2.11 Currency used in CPAT

CPAT is presented in constant US dollars (USD). Monetary variables are presented in CPAT are in USD real terms. CPAT distinguishes between the base year – the first year of model calculations (at the time of writing, 2019) – and the year of real terms constant dollars used (at the time of writing, 2021). These settings are defined in the dashboard around cell G60.

CPAT converts between local currencies and US dollars at year of real terms constant dollars (i.e. 2021) exchange rates, and then uses (projected or historical) US inflation indices to deflate in time. For more information on macroeconomic data sources, please see Appendix A.

1.2.12 Energy Units in CPAT

CPAT uses commonly used units where possible, rather than adopting a fully consistent (SI) approach:

  • For primary and final energy consumption, we use thousand tons of oil equivalent (ktoe) per year.
  • For power consumption and generation, we use GWh per year (or TWh per year in some graphs).

For prices we use different units depending on the fuel type:

  • For coal, natural gas and biomass, we use $/GJ;
  • For gasoline, diesel, kerosene and LPG, we use $/liter;
  • For crude oil and other oil products we use $/bbl (dollars per barrel); and
  • For electricity we use $/kWh.

1.3 In-depth use of CPAT

1.3.1 Using CPAT

1.3.1.1 Running CPAT

CPAT is a large Excel file of about 20Mb in compressed Excel binary (.xlsb) format. Its computational needs are substantial, and you should normally not expect to have other memory-intensive programs open. After changing a policy or other input it should take a few seconds to update (you will need to have calculations turned on). You can tell CPAT is working by the ‘graphs updating’. For example, when you change the country and the carbon price input (e.g. by changing cell I6 of the dashboard), the emissions trajectory (around row 44 of the dashboard) will adjust.

CPAT requires a modern version of Excel (2016 at least) and is tested on PC, rather than the Apple Macintosh version of Excel. You should use the desktop, rather than the web version of Excel.

1.3.1.3 CPAT visual conventions

CPAT adopts various visual conventions to make the model easier to follow and code. User inputs are colored yellow. Calculations are white. CPAT codes are typically in blue. Tan cells (both lighter and darker shades) represent formulae that are different from those around them and so cannot be dragged or dragged-onto. The cover tab describes these visual conventions.

Figure 1.16: CPAT Cover Page

1.3.2 The CPAT dashboard tab

CPAT is controlled by its dashboard which provides the main policy, modelling and parameter inputs, and the main outputs from the policy or policies chosen. The dashboard allows the user to input choices regarding the policy under investigation (such as a carbon tax trajectory, with different options for exemptions and recycling of the revenues, or fossil fuel subsidy reform). The dashboard also has options to allow the user to make different modeling choices (e.g., alternative data sources). The tool produces a series of graphs of the impact of the policy scenarios on several variables, including:

  • Policy inputs and headline overall effects;
  • Mitigation and energy use (i.e., the reduction in Greenhouse gas (GHG) emissions, changes in energy consumption); macroeconomic and fiscal aggregates (GDP, tax revenues);
  • Distributional impacts (per income decile, but also urban/rural, and industrial outputs);
  • Air pollution and health (concentration, but also mortality and morbidity); and
  • Transport (road fatalities and congestion).

Figure 1.17: Illustration of the CPAT 1.0 Dashboard (partial view, see the excel file for the full dashboard)

In the dashboard, the policy scenario and the baseline are sometimes shown on the same graph, with the baseline shown with a dashed line.

Many CPAT settings have default values. These are usually denoted by an asterix suffix – e.g. “Yes*“.

1.3.2.1 Policy input area: Country and proposed policy trajectory

At the top left of CPAT, you see various input cells. The yellow cells are user editable. Categorical cells can be altered by clicking the small down arrow. By clicking on the cell which currently shows carbon tax, you can select a different carbon pricing policy (e.g., an ETS), which comes with sectoral exemptions pre-set. All policies are defined by the carbon price. The carbon price trajectory is defined by the introduction date (here 2022), the start level (here $50/tCO2), the target level of the carbon price (here $75/tCO2), and the year that this target level will be met (here 2030).

On the right-hand side at the top of the dashboard, the user can change settings relating to the phase-out of exemptions, price controls, and subsidies. One can exempt any fuels and sectors from the carbon tax (if unticked). So, if, for example, Kerosene and Cement are unticked, all Kerosene is exempted (independent of the sector), and all Cement energy use is exempted (independent of fuel). It is necessary to ensure that all checkboxes are ticked for full policy coverage (recommended) or unticked as desired. It also includes supplementing policies with renewable energy subsidies and the use of revenues. For revenue recycling, there are five options: labor tax reductions, corporate tax reductions, public investment, current spending, and compensatory transfers to households. The phase-out of exemptions, price controls, and subsidies, as well as the use of revenue, should be as desired by the user.

Figure 1.18: Phase-out policies

1.3.2.2 Policy inputs panel

The first panel shows the result of the policy inputs. This includes Carbon Price Trajectory: To check that the suggested carbon tax is in place, please see the policy strength graph under Key inputs and outputs. On default settings, the policy is extended linearly beyond the end date. The dotted lines in the left-hand graph show the range for a carbon price recommended by the High-level Commission on Carbon Pricing. The right-hand graph shows the policy’s coverage, including any exemptions (see later for defining exemptions).

Figure 1.19: Policy design

There are further graphs in this panel, indicating the use of policy coverage, use of revenue, baseline GDP and energy price assumptions, income and price elasticity assumptions.

The description of both the advanced settings and the settings of the power models are presented in Appendix F - Parameter options in the mitigation module.

1.3.2.3 Overview of policies accounted for in CPAT

CPAT covers carbon pricing, taxes, feebates2, efficiency policies, fossil fuel subsidy reform, and power-sector-specific policies (e.g., Power Pricing Agreement reform). The main carbon pricing and fossil fuel subsidy reform policies are selected in the main dashboard.

Figure 1.20: Main Policy Dashboard

1.3.2.4 Economy-wide carbon pricing options in CPAT

CPAT accounts for an extensive list of carbon pricing instruments. These can be selected in the ‘Policy’ box shown below.

Figure 1.21: Select Policy, CPAT Dashboard

1.3.2.4.1 Carbon taxation

This policy represents a carbon tax applied to the supply of all fossil fuels in proportion to their carbon content. It is modeled by adding to the pre-existing tax on a particular fuel a charge equal to the product of the CO2 emissions factor for that fuel and the tax rate on CO2. The carbon tax can be comprehensive in applying to all fuels and sectors, or exemptions can be applied for individual fuels and sectors (with the option to phase out exemptions over time).

To the extent they are passed on, carbon taxes are reflected in higher prices for electricity. The increase in electricity prices has two components: (i) the pure abatement costs which reflect increase in generation costs per unit due to the shifting to cleaner, but costlier, generation fuels; and (ii) the tax on remaining emissions per unit of production (or carbon charges on fossil fuel inputs per unit of production). The second part can be rebated either by a dedicated policy (see power feebate below) or by a modification of a comprehensive carbon tax.

For carbon taxation and for the other comprehensive carbon pricing schemes, the user can define sectoral or fuel exemptions using the check boxes in the main dashboard.

1.3.2.4.2 Emission Trading Systems

These policies are modeled in a similar way to a tax (CPAT is deterministic and does not capture uncertainty over emissions prices associated with ETSs). That is, CPAT requires the user to estimate the likely price of an ETS and then impose that to find the emissions reduction. That said, there is also a ‘goal seek’ functionality which allows one to change the price in order to meet a particular emissions target in 2030. Because CPAT is set up without macros, the actual goal seek needs to be done by hand set up by the user using in-built Excel goal seek or seeker routine.

A scalar adjustment, set at a default value of 0.9, is applied to the emissions price, which however implies a (moderately smaller) behavioral response from the ETS compared with the equivalent carbon tax with the same price. This scalar could represent: (i) exclusion of small emitting firms from an ETS applied downstream to large firms in the power and industry sectors; (ii) higher price uncertainty under an ETS compared with a tax which potentially dampens investment incentives for low-carbon technologies; and (iii) grandfathering of allowances to incumbent firms creating barriers to new entrants and potentially forestalling innovation.

Figure 1.22: Goal Seek to Determine (ETS or Carbon Tax) Carbon Price consistent with emissions target

In the dashboard, a goal seek tool is available in order to determine the carbon price matching the emissions target. The goal seek is set around cell Y192 of the dashboard near the panel D of the mitigation section. To use it:

  • Connect cell I6 (Target level of carbon price) to be equal to call AC192 (so that the carbon tax is in the same location as the emissions);

  • Define the coverage of the emissions target using the boxes from cell AC194 downwards;

  • Define the coverage percentage of industry in the target;

  • Define the percentage reduction or absolute emissions target; and

  • Modify cell AC192 until cells AB214 and AD214 are as close as possible or set up a goal seek to minimize cell AE214 by changing the target carbon price (cell I6).

Figure 1.23: Goal Seek to Determine (ETS or Carbon Tax) Carbon Price consistent with emissions target

The goal seek only works for 2030 emissions and can be used for NDC or for ETS targeting.

Note that CPAT models new ETSs and Carbon Taxes separately from existing ETSs and Carbon Tax. For the European Union countries for example, the existing ETS price are projected forward: the growth rate in this projection can be set in the dashboard. It should also be noted that new ETSs are modeled as a sector being ‘in’ or ‘out’, whereas existing ETSs use an aggregated percentage of industry and power based on aggregated coverage data. When a sector is partly included, the carbon price is proportionally reduced by the coverage proportion and the reduced carbon price is applied to the whole sector.

1.3.2.4.3 Feebates

In their pure form, feebates provide a revenue-neutral, sliding scale of fees on activities (like power generation) or products (like vehicles). Activities or products with above average emission rates pay a net tax; activities or products with below average emission rates get net revenues. When a feebate is constructed by a carbon tax plus a rebate based on output (e.g., kWh electricity produced, steel produced, etc.) this is called Output Based Rebating (OBR). But there are other feebates differing from this form, for example when the feebate is on the initial purchase decision, rather the ongoing use (e.g., in the case of vehicles).

In most cases, feebates are modeled through shadow prices. Shadow prices are modeled not by a change in prices per se but rather a price-like adjustments to energy use equations. These shadow prices affect the efficiency channel of the energy use (typically about half the overall price-based effect) but not the usage channel.

Power supply feebates are modeled as a rebated carbon tax (i.e. a carbon tax that only increases power prices through pure abatement costs, not the cost of emissions).

1.3.2.5 Sectoral carbon pricing and taxation policies

Coal excise tax. The coal excise tax is a carbon tax (in the sense of it being defined per ton CO2) only on coal.

Electricity emission tax. This imposes a carbon tax on the electricity sector.

Electricity excise. This is a tax per kWh of electricity used. We set the tax via the standard carbon tax interface. The tax in $/tCO2 is mapped to one per kWh using the year one emission factor as a conversion factor. However, this is only a tax on end users of electricity, it does not distinguish between different ways of generating electricity, incentivizing only electricity demand and not the composition of electricity supply.

Power feebate. This policy covers power supply feebates if the engineer model is selected and covers power usage feebates if the elasticity model is selected.

Vehicle fuel economy. This imposes shadow prices (similar to a feebate) in the vehicle sector.

Road fuel tax. Taxes imposed on all fuels in the road transport sector.

Sectoral fossil fuel excise taxes. These can be modeled by the user, using this setting in the dashboard. This allows the user to set sector- and fuel-specific carbon taxes.3

Figure 1.24: Excise Reform Settings

The actual sectoral-fuel tax rates are set in the ‘Manual Inputs’ tab.

Figure 1.25: Excise Reform Settings

1.3.2.6 Regulations and subsidies

Energy efficiency regulations. CPAT can model CO2 emission rate standards per kWh of power generation, per unit of production for individual industries, or per vehicle kilometers traveled (VKT) for vehicles, or energy efficiency standards for electricity demand, and energy use in the industry, transport, and building sectors. These policies reduce the emissions or energy intensity of a sector but without the same demand response (e.g., reductions in VKT) as under carbon pricing because they do not involve the pass through of carbon tax revenues (or allowance rents) in higher prices (e.g., for electricity or gasoline) – they also produce a partially offsetting increase in emissions through the rebound effect. In particular, CPAT focuses on residential and industrial efficiency regulations.

Clean technology subsidies. Subsidies for renewable generation are modeled in CPAT by a subsidy providing a proportionate reduction in the per unit generation cost for renewables. Subsidies for electric vehicles (EV) are not explicitly modeled in CPAT.

1.3.2.7 Fossil fuel subsidy reform and regulated price reform

CPAT includes extensive capabilities to reform fossil fuel subsidies. For each form of subsidy (i.e., producer-side and consumer-side) one can select the phase out check box and then the number of years to phase out that subsidy. CPAT also includes some estimations of price controls, which can also be phased out (although there are interaction effects so doing both at the same time is not advised). We recommend the default assumptions for fossil fuel subsidies to be checked and/or replaced by the user (user defined subsidies are defined in the manual inputs tab and the dashboard or mitigation tab – the dom_prices tab contains the default assumptions on prices and subsidies). For more information, see the Section Fuel prices, taxes and subsidies and Sub-Section Fiscal revenues of this chapter. Note that whether fossil fuel subsidy reform is included in the baseline is in the advanced settings. The user should check the following setting:

Figure 1.26: Excise Reform Settings

1.3.2.8 Power sector-specific policies

CPAT has the capability to adjust the maximum rate of renewable scale up. This is set for default to 2% for wind and 2% for solar, meaning that we could add (gross of retirements) additional generation equal to 2% of the total for each generation type. For many countries, this growth rate is too ambitious, and a tighter cap will be needed. On the other hand, more ambitious renewables policies could lead to this cap being loosened. This constraint is the same in the baseline and the policy scenario.

CPAT includes the ability to set the proportion of fossil-fueled generation that is covered by PPAs and to model the reform of those PPAs by subjecting them to market costs (including carbon pricing).

CPAT can choose which generation types are investible or not. The user has four options: ‘yes’ (i.e. invests according to cost), ‘no’ (i.e. does not invest in this technology type), ‘if present’ (i.e. invests if this option is present) and ‘manual’ (i.e. capacity additions are set in manual inputs).

Thus, CPAT allows one to phase out any power generation type (preventing any new investment being made). CPAT also by default allows retirement of coal power driven by carbon pricing and allows the user to set the proportion of coal power subject to such retirement (by default 80%).

CPAT also has the capacity to adjust the financial characteristics of the power sector (cost of capital, etc.). These settings, both for the baseline and the policy scenario, are set in the power settings part of the dashboard. The user can also set the default costs of capital for each income-level. Those settings are in the ‘Power’ tab.

CPAT by default has a power sector storage requirement which imposes the marginal system cost of needed storage on new variable renewable energy investment. The storage includes short- and long-term components. The latter component is highly uncertain, and the user is encouraged to check and confirm these settings.

Figure 1.27: Power Sector Specific Policies

1.3.2.9 Other policies

Other policies are not included in CPAT at this point. These include public investments (e.g., in smart grids or public transportation), low carbon fuel standards, biofuel mandates, building codes, incentives for specific technologies (e.g., geothermal power, nuclear, carbon capture and storage), emission rate policies for non-road vehicles, measures for extractive industries (e.g., moratoria on extraction, charges on production or fugitive emissions), and mitigation instruments beyond the energy sector. Broader policies to promote R&D into critical technologies are also beyond the scope of CPAT.

1.3.2.10 Metrics for comparing policies

The CPAT Dashboard provides a series of results that can be used to compare policies across different dimensions. The main metrics are described below.

CO2 emissions. CO2 emissions are given by the consumption of each fossil fuel product, aggregated across sectors, multiplied by the CO2 emissions factor for that fuel product, and then aggregated across different fossil fuel products.

Revenue. Revenues from carbon mitigation policies are calculated net of indirect changes in revenues (or outlays) from pre-existing energy taxes (or subsidies). Direct revenues from carbon pricing are simply the carbon price times the CO2 emissions to which they are applied and, in the case of ETSs, the fraction of allowances that are auctioned (rather than freely allocated). Revenues from pre-existing energy taxes are the product of the prior fuel tax rate (which is negative in the case of fuel subsidies) and the fuel consumption to which they are applied, aggregated across fuels and sectors, plus the product of any electricity tax and the electricity consumption to which it applies. Indirect revenue losses from carbon pricing are the difference between revenues from pre-existing energy taxes before and after carbon pricing. Similarly, revenues from new, or increases in existing, energy taxes are the tax increase times the fuel or electricity to which the increase applies, net of indirect revenue changes from pre-existing energy taxes.

For regulations and revenue-neutral feebates there is no direct revenue, though there is generally an indirect revenue loss as these policies erode bases for pre-existing energy taxes. For renewable and clean technology subsidies, there is a direct revenue loss equal to the product of the subsidy rate and the base to which it applies plus indirect revenue losses from pre-existing energy taxes.

Externalities. CPAT estimates externalities due to improved human health (because of reduction in air pollution), reduced road accidents, reduced travel time and reduced road maintenance costs. Please refer to the Air Pollution and Transport chapters for more information on the externalities calculation.

Distributional effects. CPAT also offers an incidence analysis about the consumption effects that household could experience after a carbon pricing policy. The details can be consulted in the Distribution chapter.

GDP Effects. GDP growth will be affected by carbon pricing and the total impact will depend on how the revenues are used and other assumptions and parameters used in CPAT. Please refer to the Output section for details.

Climate benefits. The climate benefits are linked to the GHG emission reductions that can be achieved with a policy and the social cost of carbon. For details on emissions calculations and the social cost of carbon in CPAT, please refer to Chapter 3 on the Mitigation Methodology.

Using the previous metrics, the Section Monetized welfare benefits discusses the estimation of the monetized domestic environmental costs from fuel use. The domestic environmental co-benefits of mitigation policies are calculated by the induced reductions in use of a fuel product in a particular sector, multiplied by the corresponding domestic environmental cost per unit, and aggregated across sectors and fuels. Efficiency costs of policies reflect losses in producer and consumer surplus in fossil fuel markets, which in turn correspond to areas under marginal abatement cost schedules – they can be interpreted as the annualized costs of using cleaner, but costlier technologies, and of reducing energy consumption below levels households would otherwise prefer. Efficiency costs are calculated using applications and extensions of long-established formulas in the public finance literature (e.g., Harberger, 1964) based on second-order approximations. These formulas can be applied with data on the size of tax distortions in fuel and electricity markets, any induced quantity changes in markets affected by these distortions (an output from the model), and any new source of price distortion created by carbon policies.

Figure 1.28: Monetized Welfare Benefits in CPAT Dashboard

1.3.2.11 Headline projected effects panel

The main outputs are shown under Headline projected effects, in Panel B in CPAT Dashboard. Starting from the left, these graphs show:

  1. GHG emissions relative to baseline (dashed line) & NDC target (dotted horizontal line);
  2. Fiscal revenues (before recycling of funds);
  3. Impact on projected GDP growth;
  4. Impacts on households (note: only countries for which household data are available);
  5. Co-benefits: Averted air pollution & road accident deaths; and
  6. Total monetized benefits from the policy.

Figure 1.29: Main outputs, Dashboard tab

1.3.2.12 Advanced settings

Advanced settings can be defined throughout the Dashboard, related to the different CPAT modules. The settings are displayed by clicking the + button to expand.

For instance, for the Mitigation module, the first panel of advanced settings is around row 16 and includes key policy options, sources for key inputs, uncertainty adjustments and miscellaneous effects.

Figure 1.30: General settings

The mitigation module also has wide range of advanced options which are covered around row 58. For example, the user has an option to specify existing ETS permit price growth for future years, can choose to apply the same VAT tax rate in the residential and transport sectors if it is different from the general VAT in the economy, adjust social cost of carbon tax and more.

Figure 1.31: Advanced Mitigation Options

The dashboard includes advanced parameter options for the power models around row 109. This includes, for example, information on the proportion of fossil-fueled generation that is covered by power purchase agreements (PPAs), an important measure of how inflexible the power sector is to prices due to market structure factors. To access this panel, click the plus sign to ungroup.

Figure 1.32: Power model settings

1.3.2.13 Mitigation module: Advanced settings and detailed results

The mitigation module panels show the following results:

  1. Energy baseline externalities, prices, consumption, and targets;
  2. Power sector results;
  3. Fiscal, macroeconomic, and welfare effects;
  4. GHG emissions and short-lived climate pollutants (SLCPs); and
  5. Energy-related CO2 emissions by fuel & sector (power, industries and transport).

The baseline externalities, prices, consumption and targets panel contain information about estimated externalities, energy price changes induced by the policy, and projected and efficient price change. One can select the ‘year of interest’ in the top right of the panel. The lower row shows sectoral and fuel energy consumption changes (the baseline is with the dotted line), changes induced by the policy and national sectoral NDC targets.

Figure 1.33: Prices Panel

The CPAT power panel contains information about the electricity system. The graphs are shown below. One can select the ‘year of interest’ in the top right of the panel. CPAT has two power models: the elasticity-based and technoeconomic (engineer) models, with the default set to the average between the two. However, the more CPAT can be tailored by the user to country-specific settings, the more the user is encouraged to use the ‘engineer’ choice (this is selectable on cell L24 in the original ‘more detailed options’ panel).

Figure 1.34: Power model settings

The fiscal effects contain notably the multipliers used in CPAT (bottom left) - the default is MFmod multipliers. The bottom middle shows the net GDP effects in time.

Figure 1.35: Fiscal, macroeconomic and welfare effects

The emissions panel shows a deep dive into GHG emissions.

Figure 1.36: GHG and short-lived climate pollutants panel

The energy related emissions show a deep dive into CO2 and other energy-related emissions including the Kaya identity which disaggregates the drivers of emissions changes.

Figure 1.37: Energy-related emissions

1.3.2.14 Distributional consumption effects on households

For distributional results, first, check if household data for your country is already included; if yes, define how to transfer revenues (dropdown in ‘Policy options’); adjust accordingly if red flags appear. If ‘No’ adjustment for behavioral/structural change is selected, the price increases are fully passed on to the consumer which may overestimate consumption effects (i.e. tax-induced mitigation effect is not considered). Alternatively, choose to factor in decile-specific price-driven demand adjustments/elasticities.

Choose representation of means or medians: while median effects are more representative, some fuels may not be shown if >50% of households report zero or missing expenses (e.g., if poor data quality). Make an informed choice on mean/median representation and modelling results with/out taking into account reduced prices due to behavior adjustments.

Figure 1.38: Distributional settings

For more information, please see the distribution chapter of CPAT documentation.

1.3.2.15 Air pollution (and associated health effects) results

The recommended default option to estimate concentration changes is “Avg. iF and LS FASST*” or “Local study-FASST”. See the air pollution methodology chapter for more details on what the different options entail. Is important to check the sectors’ contribution to ambient PM2.5 and adjust modeling approach if needed.

As in the other sections of CPAT, the cells in yellow can be modified by the user. For instance, the user can input a local Value of the Statistical Life to value air pollution externalities from fossil fuels.

Figure 1.39: Air Pollution settings in CPAT Dashboard

Some additional parameters can be modified in the “Manual inputs” tab. A link to this tab is at the end of the air pollution settings in the Dashboard. In that tab, the user can input source apportionment information, that reflects the sectoral contribution to ambient PM2.5 in the analyzed country. Notice that for CPAT to use that manual input, the “Emissions to concentrations, PM2.5” parameter needs to be set to “Manual-FASST”.

For more information, please see the air pollution chapter from CPAT documentation.

1.3.2.16 Transport co-benefits (road accidents, congestion, and road damage)

The group of panels shows the results for transport co-benefits. This includes results for distance traveled, fatalities on the road, congestion, fuel prices and the statistical relationship between fuel prices, accidents and congestion.

For more information, please see the transport chapter of this documentation.

1.3.3 Manual inputs tab: Tailoring CPAT

CPAT is designed to be able to be run ‘off the shelf’. Nevertheless, the default settings will usually need to be checked and tested for the country context. In particular:

  • The prices and subsidy information should be checked and, if needed, augmented on the manual settings tab.
  • The user can set the investment trajectory in the power sector, both in the baseline and the policy scenarios. For more information, please see the CPAT quick-start guide.

Most of these tailored inputs are stored in the manual inputs tab. This tab also gives the option to add any combination of additional fuel- and sector-specific taxes (excise reform section).

Figure 1.40: Manual Inputs tab

1.3.5 The Multiscenario Tool (MT)

CPAT run in standalone mode relates to a single country with two scenarios: the baseline and a policy scenario. CPAT can also be run in multiscenario mode, meaning for many countries and/or many scenarios. More information about the multiscenario tool is available on request.

Figure 1.52: The Multiscenario Tool

1.4 Country coverage

CPAT currently covers 192 countries. The table below presents the list of countries and indicates whether the country is covered by CPAT (with ‘Y’ = Yes, indicating the country being covered by CPAT). If the country is not covered, an explanation is provided to detail what are the missing information.

Country code Income Group Country Region Coverage Distribution
AFG LIC Afghanistan South Asia Y
ALB UMIC Albania Europe & Central Asia Y
DZA UMIC Algeria Middle East & North Africa Y
ASM UMIC American Samoa East Asia & Pacific Y
AND HIC Andorra Europe & Central Asia Macro data not available (employment; emissions data)
AGO LMIC Angola Sub-Saharan Africa Y
AIA UMIC Anguilla Latin America & Caribbean Spurious results’ lack of energy consumption data
ATG HIC Antigua and Barbuda Latin America & Caribbean Y
ARG HIC Argentina Latin America & Caribbean Y Y
ARM UMIC Armenia Europe & Central Asia Y
ABW HIC Aruba Latin America & Caribbean Y
AUS HIC Australia East Asia & Pacific Y
AUT HIC Austria Europe & Central Asia Y Y
AZE UMIC Azerbaijan Europe & Central Asia Y
BHS HIC Bahamas, The Latin America & Caribbean Y
BHR HIC Bahrain Middle East & North Africa Y
BGD LMIC Bangladesh South Asia Y Y
BRB HIC Barbados Latin America & Caribbean Y
BLR UMIC Belarus Europe & Central Asia Y
BEL HIC Belgium Europe & Central Asia Y Y
BLZ UMIC Belize Latin America & Caribbean Y
BEN LIC Benin Sub-Saharan Africa Y
BMU HIC Bermuda North America Macro data not available (GDP per capita - real (constant prices); employment)
BTN LMIC Bhutan South Asia Y
BOL LMIC Bolivia Latin America & Caribbean Y Y
BIH UMIC Bosnia and Herzegovina Europe & Central Asia Y
BWA UMIC Botswana Sub-Saharan Africa Y
BRA UMIC Brazil Latin America & Caribbean Y Y
VGB HIC British Virgin Islands Latin America & Caribbean Macro data not available (GDP indicators, employment and population, exchange rate)
BRN HIC Brunei Darussalam East Asia & Pacific Y
BGR UMIC Bulgaria Europe & Central Asia Y Y
BFA LIC Burkina Faso Sub-Saharan Africa Y
BDI LIC Burundi Sub-Saharan Africa Y
CPV LMIC Cabo Verde Sub-Saharan Africa Y
KHM LMIC Cambodia East Asia & Pacific Y
CMR LMIC Cameroon Sub-Saharan Africa Y
CAN HIC Canada North America Y Y
CYM HIC Cayman Islands Latin America & Caribbean Y
CAF LIC Central African Republic Sub-Saharan Africa Y
TCD LIC Chad Sub-Saharan Africa Y
CHI HIC Channel Islands Europe & Central Asia Macro data not available (GDP indicators, employment, population, emissions); problem with externalities.
CHL HIC Chile Latin America & Caribbean Y Y
CHN UMIC China East Asia & Pacific Y Y
COL UMIC Colombia Latin America & Caribbean Y Y
COM LIC Comoros Sub-Saharan Africa Y
COD LIC Congo, Democratic Republic of the Sub-Saharan Africa Y
COG LMIC Congo, Republic of Sub-Saharan Africa Y
CRI UMIC Costa Rica Latin America & Caribbean Y Y
CIV LMIC Côte d’Ivoire Sub-Saharan Africa Y Y
HRV HIC Croatia Europe & Central Asia Y Y
CUB UMIC Cuba Latin America & Caribbean Y
CUW HIC Curaçao Latin America & Caribbean Macro data not available (employment, GDP per capita - real (constant prices), problem with externalities; spurious results’ balances issues).
CYP HIC Cyprus Europe & Central Asia Y Y
CZE HIC Czech Republic Europe & Central Asia Y Y
DNK HIC Denmark Europe & Central Asia Y Y
DJI LMIC Djibouti Middle East & North Africa Y
DMA UMIC Dominica Latin America & Caribbean Y
DOM UMIC Dominican Republic Latin America & Caribbean Y Y
ECU UMIC Ecuador Latin America & Caribbean Y Y
EGY LMIC Egypt Middle East & North Africa Y Y
SLV LMIC El Salvador Latin America & Caribbean Y
GNQ UMIC Equatorial Guinea Sub-Saharan Africa Y
ERI LIC Eritrea Sub-Saharan Africa Y
EST HIC Estonia Europe & Central Asia Y Y
SWZ LMIC Eswatini Sub-Saharan Africa Macro data not available (employment, GDP per capita - real (constant prices); problem with externalities).
ETH LIC Ethiopia Sub-Saharan Africa Y
FRO HIC Faroe Islands Europe & Central Asia Macro data not available (GDP indicators, employment); missing externalities; spurious results’ balances issues.
FJI UMIC Fiji East Asia & Pacific Y
FIN HIC Finland Europe & Central Asia Y Y
FRA HIC France Europe & Central Asia Y Y
PYF HIC French Polynesia East Asia & Pacific Macro data not available (employment, GDP per capita - real (constant prices); problem with externalities).
GAB UMIC Gabon Sub-Saharan Africa Y
GMB LIC Gambia, The Sub-Saharan Africa Y
GEO LMIC Georgia Europe & Central Asia Y
DEU HIC Germany Europe & Central Asia Y Y
GHA LMIC Ghana Sub-Saharan Africa Y Y
GIB HIC Gibraltar Europe & Central Asia Macro data not available (GDP indicators, employment, population); problem with externalities).
GRC HIC Greece Europe & Central Asia Y Y
GRL HIC Greenland Europe & Central Asia Y
GRD UMIC Grenada Latin America & Caribbean Y
GUM HIC Guam East Asia & Pacific Macro data not available (employment, GDP per capita - real (constant prices); problem with externalities).
GTM UMIC Guatemala Latin America & Caribbean Y
GIN LIC Guinea Sub-Saharan Africa Y
GNB LIC Guinea-Bissau Sub-Saharan Africa Y
GUY UMIC Guyana Latin America & Caribbean Y
HTI LIC Haiti Latin America & Caribbean Y
HND LMIC Honduras Latin America & Caribbean Y Y
HKG HIC Hong Kong SAR East Asia & Pacific Y
HUN HIC Hungary Europe & Central Asia Y Y
ISL HIC Iceland Europe & Central Asia Y
IND LMIC India South Asia Y Y
IDN LMIC Indonesia East Asia & Pacific Y Y
IRN UMIC Iran Middle East & North Africa Y
IRQ UMIC Iraq Middle East & North Africa Y
IRL HIC Ireland Europe & Central Asia Y Y
IMN HIC Isle of Man Europe & Central Asia Macro data not available (employment, GDP per capita - real (constant prices), emissions; problem with externalities).
ISR HIC Israel Middle East & North Africa Y
ITA HIC Italy Europe & Central Asia Y Y
JAM UMIC Jamaica Latin America & Caribbean Y
JPN HIC Japan East Asia & Pacific Y
JOR UMIC Jordan Middle East & North Africa Y
KAZ UMIC Kazakhstan Europe & Central Asia Y Y
KEN LMIC Kenya Sub-Saharan Africa Y
KIR LMIC Kiribati East Asia & Pacific Y
KOR HIC Korea East Asia & Pacific Y
PRK LIC Korea, Dem. People’s Rep. East Asia & Pacific Macro data not available (GDP indicators, employment); missing externalities.
XKX LMIC Kosovo Europe & Central Asia Data not available (Historical CO2 & other GHGs emissions).
KWT HIC Kuwait Middle East & North Africa Y
KGZ LMIC Kyrgyz Republic Europe & Central Asia Y
LAO LMIC Lao P.D.R. East Asia & Pacific Y
LVA HIC Latvia Europe & Central Asia Y Y
LBN UMIC Lebanon Middle East & North Africa Y
LSO LMIC Lesotho Sub-Saharan Africa Y
LBR LIC Liberia Sub-Saharan Africa Y
LBY UMIC Libya Middle East & North Africa Y
LIE HIC Liechtenstein Europe & Central Asia Macro data not available (GDP indicators, employment); missing externalities.
LTU HIC Lithuania Europe & Central Asia Y Y
LUX HIC Luxembourg Europe & Central Asia Y Y
MAC HIC Macao SAR East Asia & Pacific Y
MKD UMIC Macedonia, FYR Europe & Central Asia Y Y
MDG LIC Madagascar Sub-Saharan Africa Y Y
MWI LIC Malawi Sub-Saharan Africa Y
MYS UMIC Malaysia East Asia & Pacific Y Y
MDV UMIC Maldives South Asia Y
MLI LIC Mali Sub-Saharan Africa Y Y
MLT HIC Malta Middle East & North Africa Y Y
MHL UMIC Marshall Islands East Asia & Pacific Data not available (Historical CO2 & other GHGs emissions).
MRT LMIC Mauritania Sub-Saharan Africa Y
MUS UMIC Mauritius Sub-Saharan Africa Y
MEX UMIC Mexico Latin America & Caribbean Y Y
FSM LMIC Micronesia East Asia & Pacific Y
MDA LMIC Moldova Europe & Central Asia Y
MCO HIC Monaco Europe & Central Asia Macro data not available (employment, GDP per capita - real (constant prices); problem with air pollution externalities).
MNG LMIC Mongolia East Asia & Pacific Y
MNE UMIC Montenegro, Rep. of Europe & Central Asia Data not available (Historical CO2 & other GHGs emissions).
MSR UMIC Montserrat Latin America & Caribbean Data not available (Historical CO2 & other GHGs emissions).
MAR LMIC Morocco Middle East & North Africa Y
MOZ LIC Mozambique Sub-Saharan Africa Y
MMR LMIC Myanmar East Asia & Pacific Y
NAM UMIC Namibia Sub-Saharan Africa Y
NRU UMIC Nauru East Asia & Pacific Y
NPL LIC Nepal South Asia Y Y
NLD HIC Netherlands Europe & Central Asia Y Y
NCL HIC New Caledonia East Asia & Pacific Macro data not available (GDP indicators, employment); problem with externalities.
NZL HIC New Zealand East Asia & Pacific Y
NIC LMIC Nicaragua Latin America & Caribbean Y
NER LIC Niger Sub-Saharan Africa Y
NGA LMIC Nigeria Sub-Saharan Africa Y
MNP HIC Northern Mariana Islands East Asia & Pacific Macro data not available (employment, GDP per capita - real (constant prices); problem with externalities; balances issues).
NOR HIC Norway Europe & Central Asia Y
OMN HIC Oman Middle East & North Africa Y
PAK LMIC Pakistan South Asia Y Y
PLW HIC Palau East Asia & Pacific Y
PAN HIC Panama Latin America & Caribbean Y
PNG LMIC Papua New Guinea East Asia & Pacific Y
PRY UMIC Paraguay Latin America & Caribbean Y
PER UMIC Peru Latin America & Caribbean Y Y
PHL LMIC Philippines East Asia & Pacific Y Y
POL HIC Poland Europe & Central Asia Y Y
PRT HIC Portugal Europe & Central Asia Y Y
PRI HIC Puerto Rico Latin America & Caribbean Y
QAT HIC Qatar Middle East & North Africa Y
ROU UMIC Romania Europe & Central Asia Y Y
RUS UMIC Russia Europe & Central Asia Y
RWA LIC Rwanda Sub-Saharan Africa Y Y
WSM UMIC Samoa East Asia & Pacific Y
SMR HIC San Marino Europe & Central Asia Data not available (Historical CO2 & other GHGs emissions); Spurious results’ balances issues.
STP LMIC São Tomé and Príncipe Sub-Saharan Africa Y
SAU HIC Saudi Arabia Middle East & North Africa Y
SEN LIC Senegal Sub-Saharan Africa Y
SRB UMIC Serbia Europe & Central Asia Y Y
SYC HIC Seychelles Sub-Saharan Africa Y
SLE LIC Sierra Leone Sub-Saharan Africa Y
SGP HIC Singapore East Asia & Pacific Y
SXM HIC Sint Maarten (Dutch part) Latin America & Caribbean Macro data not available (employment, GDP per capita - real (constant prices); historical CO2 & other GHGs emissions; problem with balances).
SVK HIC Slovak Republic Europe & Central Asia Y Y
SVN HIC Slovenia Europe & Central Asia Y Y
SLB LMIC Solomon Islands East Asia & Pacific Y
SOM LIC Somalia Sub-Saharan Africa Y
ZAF UMIC South Africa Sub-Saharan Africa Y
SSD LIC South Sudan Sub-Saharan Africa Data not available (Historical CO2 & other GHGs emissions); Spurious results’ balances issues.
ESP HIC Spain Europe & Central Asia Y Y
LKA LMIC Sri Lanka South Asia Y Y
KNA HIC St. Kitts and Nevis Latin America & Caribbean Y
LCA UMIC St. Lucia Latin America & Caribbean Y
MAF HIC St. Martin (French part) Latin America & Caribbean Macro data not available (GDP indicators, employment); historical CO2 & other GHGs emissions; problem with externalities.
VCT UMIC St. Vincent and the Grenadines Latin America & Caribbean Y
SDN LMIC Sudan Sub-Saharan Africa Y
SUR UMIC Suriname Latin America & Caribbean Y
SWE HIC Sweden Europe & Central Asia Y Y
CHE HIC Switzerland Europe & Central Asia Y
SYR LIC Syria Middle East & North Africa Macro data not available (GDP indicators, employment); problem with externalities.
TWN HIC Taiwan Province of China East Asia & Pacific Y
TJK LIC Tajikistan Europe & Central Asia Y
TZA LIC Tanzania Sub-Saharan Africa Y
THA UMIC Thailand East Asia & Pacific Y Y
TLS LMIC Timor-Leste East Asia & Pacific Y
TGO LIC Togo Sub-Saharan Africa Y
TON UMIC Tonga East Asia & Pacific Y
TTO HIC Trinidad and Tobago Latin America & Caribbean Y
TUN LMIC Tunisia Middle East & North Africa Y
TUR UMIC Turkey Europe & Central Asia Y Y
TKM UMIC Turkmenistan Europe & Central Asia Y
TCA HIC Turks and Caicos Islands Latin America & Caribbean Y
TUV UMIC Tuvalu East Asia & Pacific Spurious results’ balances issues, missing historical CO2 & other GHGs emissions data.
UGA LIC Uganda Sub-Saharan Africa Y
UKR LMIC Ukraine Europe & Central Asia Y Y
ARE HIC United Arab Emirates Middle East & North Africa Y
GBR HIC United Kingdom Europe & Central Asia Y Y
USA HIC United States North America Y Y
URY HIC Uruguay Latin America & Caribbean Y Y
UZB LMIC Uzbekistan Europe & Central Asia Y
VUT LMIC Vanuatu East Asia & Pacific Y
VEN UMIC Venezuela Latin America & Caribbean Macro data not available (GDP indicators)
VNM LMIC Vietnam East Asia & Pacific Y Y
VIR HIC Virgin Islands (U.S.) Latin America & Caribbean Macro data not available (employment, GDP per capita - real (constant prices); problem with externalities, balances issues).
PSE LMIC West Bank and Gaza Middle East & North Africa Macro data not available (employment, GDP per capita - real (constant prices); missing historical CO2 & other GHGs emissions data).
YEM LIC Yemen Middle East & North Africa Y
ZMB LMIC Zambia Sub-Saharan Africa Y
ZWE LIC Zimbabwe Sub-Saharan Africa Y
WORLDAV World aviation bunkers World aviation bunkers Y
WORLDMAR World marine bunkers World marine bunkers Y

1.5 Parameters in CPAT

When opening CPAT, the tool will be already configurated using a set of assumptions and parameter values. The following table shows the initial or default configuration in CPAT. Notice that an asterisk represents the recommended default values, that the user can select if unsure about the best assumption to use for a particular country and context.

Explanation Code Name Default
Carbon pricing: main inputs    

Carbon pricing start year

CPIntro 2023

Starting carbon price

CPLevelStart 25

Target level of carbon price

CPLevelTarget 75

Year to reach target level

CPOutro 2030
Carbon pricing: fuel coverage    

Apply tax to coal?

MCovCoa TRUE

Apply tax to natural gas?

MCovNga TRUE

Apply tax to gasoline?

MCovGso TRUE

Apply tax to diesel?

MCovDie TRUE

Apply tax to LPG?

MCovLpg TRUE

Apply tax to kerosene?

MCovKer TRUE

Apply tax to non-road oil products?

MCovOop TRUE
Carbon pricing: sector coverage    

Apply tax to power sector?

MCovPow TRUE

Apply tax to road transportation?

MCovRod TRUE

Apply tax to rail transportation?

MCovRal TRUE

Apply tax to domestic aviation?

MCovAvi TRUE

Apply tax to domestic shipping?

MCovNav TRUE

Apply tax to residential sector?

MCovRes TRUE

Apply tax to food & forestry?

MCovFoo TRUE

Apply tax to services (private / public)?

MCovSrv TRUE

Apply tax to mining & chemicals?

MCovMch TRUE

Apply tax to iron and steel?

MCovIrn TRUE

Apply tax to non-ferrous metals?

MCovNfm TRUE

Apply tax to machinery?

MCovMac TRUE

Apply tax to cement?

MCovCem TRUE

Apply tax to other manucfacturing?

MCovOmn TRUE

Apply tax to construction?

MCovCst TRUE

Apply tax to fuel transformation?

MCovFtr TRUE

Apply tax to other energy use?

MCovOen TRUE
Exemptions phaseout    

Apply exemption phaseout?

ExemptPhaseout TRUE

Year to start exemption phaseout (if applicable)

YearPha 2023

Period to reach full exemption phaseout (if applicable)

ExemptPhaseoutPeriod 5
Fossil fuel subsidies (producer-side)    

Apply producer subsidies phaseout in the policy scenario?

ProdSubPh FALSE

Year to start producer subsidies phaseout (if applicable)

YearProdSubPha 2023

Period to reach full producer subsidies phaseout (if applicable)

FFSProdPhaseoutPeriod 5

Share of producer subsidies to phase-out

ShareofProdSubPha 1

Apply producer subsidies phaseout in the baseline?

ProdSubPhaBaseline No

Period to reach full producer subsidies phaseout (baseline)

FFSProdPhaseoutPeriodBA 5

Share of producer subsidies to phase-out in the baseline

ShareOfProdSubPhaBA 1
Fossil fuel subsidies (consumer-side)    

Apply consumer subsidies phaseout?

ConsSubPha FALSE

Year to start consumer subsidies phaseout (if applicable)

YearConsSubPha 2023

Period to reach full consumer subsidies phaseout (if applicable)

FFPhaseOut 5

Share of consumer subsidies to phase-out

ShareOfConsSubPha 1

Apply consumer subsidies phaseout in the baseline?

ConsSubPhaBaseline No

Period to reach full consumer subsidies phaseout (baseline)

FFSConsPhaseoutPeriodBA 5

Share of consumer subsidies to phase-out in the baseline

ShareofConsSubPhaBA 1

Include power subsidies in any phase out?

PowerSubsidyExemptInclude Include*
Price liberalization    

Apply price controls phaseout?

PrcContPha FALSE

Year to start price controls phaseout (if applicable)

YearPrcContPha 2023

Period to reach full price controls phaseout (if applicable)

PrcControlPhaseout 5

Government energy price controls

GovPriceControls Bucketed*

Apply price controls phaseout in the baseline scenario?

PrcContPhaBaseline No
Revenues use    

Labor tax reductions

EXPLabortax 40

Corporate taxes

EXPCIT 0

Public investment

EXPCapex 30

Current spending

EXPGoodsandserv 0

Targeted transfers

EXPTransfers 30
of which:    

targeted percentile

TargettedPercentile 40

coverage rate

CoverageRate 75

leakage rate

LeakageRate 25
Policy options    

Additional mitigation policies in non-energy sectors?

AdditionMitigationPoliciesNonEnergy Yes*

Apply existing ETS (if exists)?

ExistingETSApply Yes*

Existing ETS permit price growth per annum (real terms)

ExistingETSGrowth 0

New carbon tax complementary to existing ETS coverage

CTaxComplimentaryToETS No*

ETS behavioral responses and revenues adjustment

ETSBehavioralAdjustment 0.9

Years to phase in non-climate Pigouvian tax?

AddEfficientTaxesPhaseInYears 5

Apply existing carbon tax (if exists)?

ExistingCTApply Yes*

Assumed existing carbon tax growth per annum (real terms)

ExistingCTGrowth 0

Add additional excise tax (see ‘Manual inputs’ tab)?

AdditionalExcise No*

Add non-climate Pigouvian tax on top?

AddEfficientTaxes No*

Externalities are part of VAT base for optimal taxes?

ExternalityAddVAT Yes*
Sources for key inputs    

International energy price forecasts

IntEnerPricForeSource IMF-WB*

Global energy demand scenario

GlobalEnergyDemand Stated Policies*

GDP growth forecasts

GDPScenario WEO*

Primary source for price elasticities of demand

ElPrcMainSrc Simple*

Primary source for income elasticities of demand

ElIncMainSrc Simple*

CO2 emissions factors

EmissionsFactCO2 IIASA*

Fiscal multipliers

MultipliersSource Income-grp*

Power sector model (elasticity or engineering)?

PowModelSelected Average*
NDC submission NDCs Latest*

General assumptions

   

First year of model calculations?

FirstYearCalculations 2019

Nominal results in real terms of which year?

ResultsYear 2021

Use energy balances or (CPAT) energy consumption data

BalancesOrConsumption Consumption

Generate Matrix of Energy Consumption Projections for Year

EnergyConsumptionsMatrixProjectionsYear 2019

Adjust Annex I country energy-related CO2 EFs to match UNFCCC GHG inventories?

EFsAdjustmentAnnexI Yes*

Adjust non-Annex I country energy-related CO2 EFs to match CAIT GHG inventories?

EFsAdjustmentNonAnnexI Yes*

Industrial process emissions scale with industrial CO2 energy emissions?

IndustrialProcessEmissionsScaleEner Yes*

LULUCF emissions decline at % pa (in absolute value of start year)?

LULUCFAnnualEmissionsDecline 2.50E-02
Additional policy-induced efficiency gains pa by sector:    

Power

AdditionalEfficiencyPower 0

Road vehicles

AdditionalEfficiencyRoadVehicle 0

Residential

AdditionalEfficiencyResidential 0

Industrial

AdditionalEfficiencyIndustrial 0
Adjustment to efficiency margins for shadow pricing policies:    

Energy efficiency regulations

SPPEffAdjEnergyEfficiencyRegulations 0.7

Vehicle fuel economy

SPPEffAdjVehicleFuelEconomy 0.7

Residential efficiency regulations

SPPEffAdjRes 0.7

Industrial efficiency regulations

SPPEffAdjInd 0.7

Feebates

SPPEffAdjFeebates 1

Residential Substitution Implicit Efficiencies

   

LPG

ResSubstLPGEff 0.56

Kerosene

ResSubstKerEff 0.45

Biomass

ResSubstBioEff 0.2

NatGas

ResSubstNatGasEff 0.58
Uncertainty adjustments    

International energy prices adjustment

IntEnerPricForecastAdjustment Base*

GDP growth adjustment

GdpAdj Base*

Price elasticities adjustment

ElastPriceAdjustment Base*

Income elasticities adjustment

ElastIncAdjustment Base*

Adjust income elasticities for GDP levels?

IncElAdj Yes*

Fiscal multipliers adjustment

FmAdj Base*
Miscellaneous    

Price pathway continues to rise after target year?

ExtendCarbonPriceBeyondOutro Linear*

Tax pathway is in nominal or real terms?

NomorReal Real*

Include endogenous GDP effects?

GDPEndogenous Yes*

Residential LPG/kerosene always exempted

AlwaysExemptResLPGKer No*

National social cost of carbon (NSCC) source

NSCCSource Target*

Congestion & road damage attributable to fuels

TransExternAttribPortion 0.01

Override dashboard and impose a linear or exponential carbon price trajectory?

CTaxTrajectoryType Linear*

If overridden and exponential, what is the real escalation rate per year?

CtaxExponentialEscalationRate 0
Social cost of carbon    

NSCC discount rate (ρ)

NSCCDiscountRate 2%*

NSCC elasticity of marginal utility (μ)

NSCCMargUtilofCons 1.5%*

Global social cost of carbon (GSCC) source

GSCCSource Target*

SCC (both NSCC and GSCC)

SCCRise 0.04

Target-consistent carbon price by 2030 (for ‘Target’ option)

SCCTargetConsistentCP 75
Energy pricing assumptions    

Use manual domestic prices?

DomPrTax No

Use uniform global assumption for fuel prices (normally ‘No’)

UseGlobalPrices No

Year of interest for energy externalities & prices

YearFuelPrices 2025
VAT reform    

Apply general VAT rate on residential and transport consumption?

VatRef No*
Existing non-carbon taxes    

Apply existing non-carbon taxes on coal?

ApplyExistingNonCarbonTaxCoa Yes*

Apply existing non-carbon taxes on natural gas?

ApplyExistingNonCarbonTaxNga Yes*

Apply existing non-carbon taxes on gasoline?

ApplyExistingNonCarbonTaxGso Yes*

Apply existing non-carbon taxes on diesel?

ApplyExistingNonCarbonTaxDie Yes*

Apply existing non-carbon taxes on other oil products?

ApplyExistingNonCarbonTaxOop Yes*

Apply existing non-carbon taxes on LPG?

ApplyExistingNonCarbonTaxLpg Yes*

Apply existing non-carbon taxes on kerosene?

ApplyExistingNonCarbonTaxKer Yes*

Apply existing non-carbon taxes on biomass?

ApplyExistingNonCarbonTaxBio Yes*

Apply existing non-carbon taxes on electricity?

ApplyExistingNonCarbonTaxEcy Yes*
Other assumptions: mitigation module    

Use ‘world’ (USA) or country-specific discount factors?

DfSelection World

Sum all oil products in industrial transformation sector

NonEnergyTransformationMethod Converted

LPG in residential implicit (cookstove) efficiency

LPGEff 0.56

Kerosene in residential implicit (cookstove) efficiency

KerEff 0.45

Biomass in residential implicit (cookstove) efficiency

BioEff 0.2

Natural gas in residential implicit (cookstove) efficiency

NatGasEff 0.58
Distributional module assumptions    

Analysis year for distributional module

YearDistn 2030

Targeted transfer type

TransferType Cash

Target households below poverty line (2011 PPP$/day)

TargetBelow No

Public/infrastructure investment type

PublicInfrastructureInvType All Infr.

Current spending type

CurrentSpendingType All Social Protection and Labor

Personal Income Tax (PIT) reduction type

PITReductionType Personal Allowance

“Targeted Exemption” for bottom XX deciles

DistExcCfDec 4

Replace missing PIT data, grouping by country

MissingDataReplacement region

Exempt most-used cooking fossil fuel?

ExemptMostCook No

Exempt cooking fossil fuel for bottom XX deciles:

ExemptCookDeciles 2

Adjust for behavioral & structural change?

InferredDist Yes

Include decile-specific price elasticities?

PEDs No

Adjust GTAP-implied CP revenues to CPAT?

ScaleGTAP Yes

Adjust for deadweight losses?

DWLs No

Imperfect pass-through?

PassthroughDist No

Impacts for average, median, p25, or p75?

QuantilesStatistic mean

Quantiles in LCU?

QuantilesLCU No
Air pollution module assumptions    

Emissions to concentrations, PM2.5

SourceAppSel Avg. iF and LS FASST*

Emissions to concentrations, Ozone

SourceAppO3 TM5-FASST

Emission factors

EFSel Average

Include leakage to biomass in residential sector

BiomassLeakage No

Biomass is a normal good

BiomassNormal No

VSL source

VSLMethod Transfer from OECD

VSL (where manual source)

VSLManual 500000

VSL elasticity source

VslElSource Income group

VSL elasticity (where manual source)

VslEl 1

Discount rate selection

DiscSel 3% (Robinson 2019)

Discount rate (where manual source)

DiscRate 0.03

Other assumptions: air pollution module

   

Number of working days per month

WorkDays 20

Labor share of GDP, default value

ApLabSh 0.65

Max % of households using solid fuels

ApMaxSs 0.99

Leakage converted into % HH using solid fuels

ApLeakHh 0.5

Apply cessation lag when discounting averted deaths

ApCessLag Yes
Power Sector    

Power Rebate

PowerRebates No*

Power price: portion of cost change passed-on:

PowerSectorPriceChangePassOn 1

Year of interest for power sector costs

CostBreakdownYear 2030

Estimate economy-wide or sectoral power demand?

ElasticityModel Economy-wide

k Parameter dispatch

kDispatch 2

k Parameter investment

kInvestment 2

Minimum WACC

MinimumWACC 0.01

Use old or new generation costs in elasticity model?

PowGenCostsOldNew New*

Hydro retirement rate set to zero

HydroDoesntRetire Yes

Minimum (post subsidy) generation cost $/kwh real

MinPostSubsidyPowerPrice 0.01
RE Subsidies    

Baseline renewable energy subsidy, $/kwh nom

RenewableSubsidyBL 0

New renewable energy subsidy, $/kwh nom

RenSubsidyAddUSDkwh 0

New renewable energy subsidy, phaseout

RenSubsidyAddPhaseoutYrs 10

Apply additional RE subsidy to hydroelectric power?

RenewableSubsidyHydro No
RE Scale-up limits    

Max new investment in coal/gas as a percentage of total generation

MaxNonVREAsPCOfTotalGen 0.05

Max new investment oil/hyd/nucl/ore/bio as a percentage of total generation

MaxNonHydNucOreBioAsPCOfTotalGen 0.02

User-Defined Setting for VRE Max-Scale up (if used)

MaxWindSolarScaleup 0.02

Max renewable scaleup rate setting

MaxScaleUpRateCategory CtryDefault*
More Power Generation Settings    

Use Elasticity Model Power Demand In Engineer Model

UseElasticityModelPowerDemandInEngineerModel No*

Cost of capital: User-defined, Inc-dep, or Tech-dep?

WACCSource Income*

If Global, what Value?

WACCUserGlobal 7.50E-02

Renewable Cost Declines

RenewableCostDeclineRate Medium*

Use Spot Fuel Prices in Engineer Power Model

UseSpotFuelPricesInEngineerModel No*

Use Additional Coal Intangible Cost

AdditionalCoalIntangibleCost Yes*

Manual Coal Intangible Cost (short term)

ManualCoalIntangibleCostST 0

Manual Coal Intangible Cost (long term)

ManualCoal ntangibleCost LT 0

Maximum Coal Capacity Factor

MaximumCoalCF 0.9

Maximum Gas Capacity Factor

MaximumGasCF 0.9

Proportion of (2020-21) Covid adjustment passed on to engineer model power demand

EngineerModelProportionOfCovidFactor 0

Override Capacity Factor if below (Wind and Solar)

CFOverrideIfBelowWndSol 0.1

Override Capacity Factor if below (Others)

CFOverrideIfBelowFosOth 0.01

Override Capacity Factor if below (All)

CFOverrideIfAbove 1

Proportion of coal capacity that can be retired

MaxCostBasedEarlyRetirement 0.8

Minimum Thermal Efficiency

MinimumThermalEfficiency 0.1
Coal and Gas Power Purchase Agreements    

Proportion of PPAs in Coal and Gas Generation

PPAProportionCoalGas 0

Phase out any coal and gas PPAs?

PhaseOutCoalAndGasPPAs Yes*

Phase begins when?

YearPPACoalGas 2023

Phase out coal and gas PPAs over n years?

YearsToPhaseOutPPAs 5
Short Term Storage Parameters    

Percent allocation of ST storage costs to VRE

AllocateSTStorageToVRE 1

Total hours short term strorage for 100% VRE

TotalHoursStorageFor100pcVRE 9

kwh storage to kw interface ratio (hours)

StorageToInterfaceRatioSTStorage 2

Long Term Storage Parameters

   

Percent allocation of LT storage costs to VRE

AllocateLTStorageToVRE 0.33

Starting point of long term storage requirement (%VRE)

StartingPointWhenLTStorageIsNeeded 0.75

GW electrolyzer per Gwy/y for 100% VRE (%)

LongTermStorageFor100pcVRE 1

Storage hours for LT storage

StorageHoursForLTStorage 1000
Adjust Baseline Cost of Capital    

Coal - adjust baseline cost of capital?

CostCapCoa No*

Natural gas - adjust baseline cost of capital?

CostCapNga No*

Oil - adjust baseline cost of capital?

CostCapOil No*

Nuclear - adjust baseline cost of capital?

CostCapNuc No*

Wind - adjust baseline cost of capital?

CostCapWind No*

Solar - adjust baseline cost of capital?

CostCapSol No*

Hydro - adjust baseline cost of capital?

CostCapHydro No*

Other renewables - adjust baseline cost of capital?

CostCapOren No*

Biomass - adjust baseline cost of capital?

CostCapBio No*
Override Baseline Cost of Capital if selected    

Coal - baseline cost of capital

CostCapBloverCoa 7.00E-02

Natural gas - baseline cost of capital

CostCapBloverNga 7.00E-02

Oil - baseline cost of capital

CostCapBloverOil 7.00E-02

Nuclear - baseline cost of capital

CostCapBloverNuc 7.00E-02

Wind - baseline cost of capital

CostCapBloverWind 7.00E-02

Solar - baseline cost of capital

CostCapBloverSol 7.00E-02

Hydro - baseline cost of capital

CostCapBloverHydro 7.00E-02

Other renewables - baseline cost of capital

CostCapBloverOren 7.00E-02

Biomass - baseline cost of capital

CostCapBloverBio 7.00E-02
Additional Cost of Capital Increment Policy Scenario    

Coal - add cost of capital increment in policy?

CostCapAddCoa No*

Natural gas - add cost of capital increment in policy?

CostCapAddNga No*

Oil - add cost of capital increment in policy?

CostCapAddOil No*

Nuclear - add cost of capital increment in policy?

CostCapAddNuc No*

Wind - add cost of capital increment in policy?

CostCapAddWind No*

Solar - add cost of capital increment in policy?

CostCapAddSol No*

Hydro - add cost of capital increment in policy?

CostCapAddHydro No*

Other renewables - add cost of capital increment in policy?

CostCapAddOren No*

Biomass - add cost of capital increment in policy?

CostCapAddBio No*
Policy Scenario Cost of Capital Delta if selected    

Coal - Cost of Capital Delta

CostCapDeltaCoa 0

Natural gas - Cost of Capital Delta

CostCapDeltaNga 0

Oil - Cost of Capital Delta

CostCapDeltaOil 0

Nuclear - Cost of Capital Delta

CostCapDeltaNuc 0

Wind - Cost of Capital Delta

CostCapDeltaWind 0

Solar - Cost of Capital Delta

CostCapDeltaSol 0

Hydro - Cost of Capital Delta

CostCapDeltaHydro 0

Other renewables - Cost of Capital Delta

CostCapDeltaOren 0

Biomass - Cost of Capital Delta

CostCapDeltaBio 0
Policy Scenario Cost of Capital Override if selected    

Coal - Cost of Capital Override

CostCapOverCoa 0

Natural gas - Cost of Capital Override

CostCapOverNga 0

Oil - Cost of Capital Override

CostCapOverOil 0

Nuclear - Cost of Capital Override

CostCapOverNuc 0

Wind - Cost of Capital Override

CostCapOverWind 0

Solar - Cost of Capital Override

CostCapOverSol 0

Hydro - Cost of Capital Override

CostCapOverHydro 0

Other renewables - Cost of Capital Override

CostCapOverOren 0

Biomass - Cost of Capital Override

CostCapOverBio 0
Allowed New Investments Override if selected    

Coal - New Investment Override

NewInvCoa If Present*

Natural gas - New Investment Override

NewInvNga If Present*

Oil - New Investment Override

NewInvOil If Present*

Nuclear - New Investment Override

NewInvNuc If Present*

Wind - New Investment Override

NewInvWnd Yes

Solar - New Investment Override

NewInvSol Yes

Hydro - New Investment Override

NewInvHyd If Present*

Other renewables - New Investment Override

NewInvOre If Present*

Biomass - New Investment Override

NewInvBio If Present*
Allowed New Investments (Date of Coming Online)    

Coal

NewInvCoaYear 2019

Natural gas

NewInvNgaYear 2019

Oil

NewInvOilYear 2019

Nuclear

NewInvNucYear 2030

Wind

NewInvWndYear 2019

Solar

NewInvSolYear 2019

Hydro

NewInvHydYear 2030

Other renewables

NewInvOreYear 2030

Biomass

NewInvBioYear 2019

  1. A ‘goal seek’ functionality is set up in the dashboard (see Section 1.3.2.4 for more information) and allows the user to change the price in order to meet a particular emissions target in 2030.↩︎

  2. A feebate is a rebated tax which taxes dirty products or activities to subsidize greener products or activities such that net revenue is zero.↩︎

  3. To convert a carbon tax to an excise duty, please see emissions factors available in the mitigation module.↩︎

  4. ‘Other’ varies by context – it can mean pollutant in the air pollution module or submodel (ie engineer/elastricity) in the power module.↩︎