## 1. Cross-Country Comparison of Productivity and R&D

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### A. Background: Automotive Production in Czechia
- Czechia’s convergence toward more advanced economies has been driven mostly by the auto industry and requires moving up global value chains to sustain further convergence.
- GDP per capita is reported in 2019 to avoid the inclusion the impact of the pandemic and subsequent recovery.
- Czechia’s relatively lower R&D spending per inhabitant compared with other advanced European economies constrains progress up the value chain.

### B. Czechia Automotive Sector: Size and Integration
- The automotive sector is one of the largest sectors in Czechia in terms of output and employment.
  - Motor vehicle sector value added share: 4.9 percent (as of 2014).
  - Motor vehicle sector employment share: 3.2 percent (as of 2014).
- Adjacent sectors (trade of motor vehicles and repair of equipment) provide important spillovers to the Czechia economy.
- Czechia automotive sector is highly integrated into global value chains with strong upstream and downstream linkages.
  - Germany is the most important supplier and consumer of Czechia auto sector’s intermediate inputs, reflecting ownership links (Volkswagen and Skoda Auto).
  - On the intermediate input supplier side after Czechia and Germany: Poland, Slovakia, and Italy.
  - On the intermediate input consumer side: Russia, France, and Slovakia.

### C. Value Added and Skill Intensity Comparisons
- Czechia automotive sector has one of the lowest value-added shares compared to other countries in the region.
- Czechia has one of the lowest shares of high-skilled workers in the automotive sector and a comparatively lower high-skill population share.
- By comparison, Germany has one of the highest value-added shares in the auto sector and a larger pool of high-skilled workers in the general population.

### D. Key Observed Trends and Risks in Transition to EVs
- Three observed trends/risks regarding electric vehicle (EV) transition:
  - EV production involves shorter value chains than combustion vehicle production; uncertainty exists whether Czechia’s current role will be preserved.
  - EV production tends to be higher value added and involves less labor, implying risk of lower labor demand in Czechia.
  - EV production is more skill-intensive than combustion vehicle production, raising risks for Czechia given a relatively lower-skilled population.
- The energy crisis in Europe could lead to dislocation of European value chains over the medium-term.

### E. Empirical EV Uptake Indicator
- Electric Vehicle Share of Passenger Car Production shown over Jan-21 to May-22 (Percent), illustrating rising EV share in Czechia (figure in source).

### F. Analysis Framework and Structural Model Overview
- Staff analysis uses a stylized structural model of automotive global value chains with distinct production for electric and combustion vehicles to study impacts of transition and policy responses.
- The model embeds domestic capability features, specialization along value chains, and trade linkages.
- Main overlapping structural components:
  - Value chains: two value chains (EV and CV) plus a numeraire good; stages of production denoted by h; relative labor intensity α_h and relative skill intensity β_h.
  - Trade of goods: variable trade cost τ_i,j^h and fixed trade cost f_i,j^h; fixed trade cost implies only most productive goods access foreign markets.
  - Entry of new goods: firms pay a convex cost to create new varieties, determining mass of goods (interpreted as sectoral capabilities / total factor productivity).
  - Capital: not explicitly modeled; effects proxied via entry of new goods; labor share α_h captures role of capital as alternative input.
- The economy consists of I countries modeled as ℐ={CZE, DEU, ROW} (Czechia, Germany, Rest of World).
- Consumer taste parameter γ_t determines relative demand and total EV expenditure; shifting γ_t drives structural transition to EV production.
- Model illustrations in the source depict economic relationships, supply relationships, and the automotive GVC structure for EV and CV production stages.

### G. Calibration (selected parameters as presented)
- Calibration based on combustion vehicle production data; EV parameterization set to match observed differences between CV and EV production.
- Transition to EV is mimicked by changing taste parameter γ.
- Trade costs are estimated to match within-sector trade flows and scaled to match relative use of intermediate inputs for Czechia (~50 percent).
- The calibration is illustrative and not a quantitative forecast.
- Table 1: Selected calibrated parameters
  - Common Parameters:
    - Discount Rate (%)4
    - EV Preference (%)10
    - Productivity Distribution5.0
    - Exit Probability0.1
  - Country-Specific Parameters (Productivity):
    - Productivity of Unskilled Workers: [1.00 , 0.91 , 1.25]
    - Productivity of Skilled Workers: [0.67 , 0.76 , 0.63]
  - Sector Specific Parameters (Elasticity of Substitution, Labor Share, Skill Intensity):
    - Elasticity of Substitution: [3.0 , 3.0 , 3.0 , 2.5 , 3.0 , 2.5]
    - Labor Share: [0.7 , 0.5 , 0.5 , 0.5 , 0.8 , 0.6]
    - Skill Intensity: [0.2 , 0.2 , 0.2 , 0.4 , 0.3 , 0.5]
  - Other Parameters (reported as country average):
    - Entry Cost: [1.07 , 1.02 , 1.03]
    - Variable Trade Cost: [1.07 , 1.06 , 1.06]
    - Fixed Trade Cost: [0.107 , 0.106 , 0.106]
- Sectoral ordering in Table 1: from most upstream to most downstream; EV stages parametrized to be less labor intensive and more skill intensive in later stages relative to CV stages.

### H. Transition to EV Production: Scenario and Metrics
- Baseline equilibrium (current policies) compared with EV equilibrium in which expenditures on electric vehicles increase to 90 percent of automotive expenditures (EV equilibrium).
- The EV equilibrium is interpreted as an economy circa 20 years in the future after the EU’s “Fit for 55” goal—to ban the combustive engine by 2035—has become effective.
- Results are steady-state comparisons and are presented as changes between the EV equilibrium and the benchmark equilibrium; quantitative magnitudes are illustrative.
- Results are scaled so that the absolute value of the change in Czechia is normalized to one.

### I. Modeled Impacts of Full EV Transition (EV expenditure = 90 percent)
- For Czechia:
  - Automotive sector output: increase (comparatively marginal).
  - Skill share (share of high-skilled workers in automotive sector): increase.
  - Value-added share: decrease relative to baseline.
  - Overall employment in automotive sector: decrease relative to baseline.
- Mechanisms:
  - Increase in output driven by narrowing of the value chain allowing Czechia to displace ROW countries that have competitive disadvantage in higher value-added sectors.
  - Decrease in value-added share and increase in skill intensity stem from parameterization differences for EV production.
  - Decline in employment closely linked to decline in value added and lower labor intensity of EV production.
- A partial transition (half of final expenditure on EVs) yields overall changes around one-half of the full-transition results.

### J. Policy Experiments: Three Broad Schemes (implementation in model)
- a. Boosting labor productivity
  - Implemented by increasing Czechia labor productivity to match that of Germany.
  - Interpreted as making skilled labor more abundant and cheaper.
  - Captures policies such as investing in education, upskilling, re-skilling, lifelong learning programs, and digitalization policies that could boost existing skills.
- b. Support for horizontal production capabilities
  - Implemented by reducing the entry cost of Czechia for intermediate sectors in both the electric and combustion vehicle (CV stage 3 and EV stage 2) production by 20 percent.
  - Interpreted as reinforcing current production capabilities and specializations.
  - Practical policy examples: investing in infrastructure, subsidies to operations of current firms, lowering trade costs.
- c. Support for vertical production capabilities
  - Implemented by reducing the entry cost of the most downstream sectors for both electric and combustion vehicle production by around 20 percent.
  - Interpreted as promoting movement up the global value chain toward higher value added and more skill-intensive sectors.
  - Practical policy examples: research and development subsidies, lowering cost of new firm or product entry, labor market policies that allow access to foreign experts.
- Simulation baseline and normalization:
  - Impacts expressed as change in equilibrium outcomes under the policy scheme relative to the electric vehicle equilibrium.
  - Values normalized such that the absolute value of the change in the transition (Figure 8) has value one.
  - Parameters set to match Table 1, with taste parameter for electric vehicles γ set to 90 percent.
- Key quantitative policy parameter values preserved exactly:
  - Entry cost reduction for horizontal policy: 20 percent.
  - Entry cost reduction for vertical policy: around 20 percent.
  - Taste parameter for electric vehicles γ set to 90 percent.

### K. Main Findings from Policy Experiments
- Boosting labor productivity
  - Leads to an increase in output, employment, the skill intensity of the economy, and the value-added share.
  - Allows Czechia to move towards higher value-added sectors and rebalances production between intermediate EV sector and final EV sector relative to the baseline.
  - Some of Czechia’s intermediate EV sector production would be produced in Germany, while part of Germany’s final EV sector production would be produced in Czechia.
- Support for horizontal production capabilities
  - Could paradoxically have negative effects on Czechia automotive sector across four dimensions.
  - Mechanisms:
    - Domestic competitiveness effect: cheaper Czechia intermediate inputs make the final good cheaper to produce and more profitable in both Czechia and abroad, initially benefiting Czechia automotive sector.
    - Global competition effects: increased profitability of final good production incentivizes investments that increase final good capabilities domestically and abroad, increasing global competition that over time negatively impacts Czechia final good producers.
  - Net effect: negative impact dominates because horizontal policies shift activity from relatively favorable stages of production (final good) to relatively unfavorable stages (intermediate production), reducing overall value added and employment outcomes for the automotive sector.
- Support for vertical production capabilities
  - Yields higher value-added, employment and share of skilled labor.
  - Lower cost of entry in the final EV sector allows more goods to be produced in Czechia, increasing economic activity because the final EV sector is higher value added and more labor and skill intensive.
  - Effects of vertical policies are relatively similar to the effects of boosting labor productivity.

### L. Mechanisms, Intuitions, and Policy Design Considerations
- Policies can achieve similar macroeconomic goals by either:
  - Directing economic activity towards specific sectors (sectoral entry-cost reductions), or
  - Making the conditions around those sectors more favorable (labor productivity improvements).
- Horizontal policies increase investment in intermediate goods production but can harm downstream competitiveness through heightened global competition.
- Vertical policies and labor productivity improvements both direct activity toward higher value-added, skill-intensive final stages, increasing employment and value added.
- Recommended focal areas:
  - Scale up investments in skills to boost labor productivity (preparing the economy for new EV-related production processes).
  - Invest in both horizontal and vertical capabilities to take a more active role in the EV production chain.
- Caveats for policymakers:
  - Horizontal and vertical interventions have relatively lower impact if they cause specialization to shift toward lower value-added and lower employment stages of production.
  - These policies require large investments and thus should be well planned, sequenced and targeted to maximize government capacity and labor resources.
- Additional considerations outside the model’s scope:
  - The model assumes final demand shifts uniformly across countries reflecting the EU’s “Fit for 55” goal that all vehicles sold should be zero emissions by 2035; if countries (including Czechia) choose not to fully phase out combustion vehicles, Czechia could retain comparative advantage in CV sectors.
  - The model does not directly consider the role of infrastructure or other capital investment important for EV adoption and production (e.g., charging stations, factories); subsidizing development of new EV production facilities would be qualitatively similar to lowering entry costs for new goods in the model.

### M. Conclusions
- Czechia’s strong integration in automotive GVCs and large economic contribution of the auto sector supported convergence with advanced European economies.
- Sustaining convergence requires moving up global value chains; current constraints include comparatively lower value added, lower R&D investment per inhabitant, and lower skill intensity in the labor market.
- The transition to EV production poses risks to employment and value added in Czechia due to shorter value chains, higher value-added concentration in fewer stages, greater skill intensity, and lower labor intensity.
- Policies that raise labor productivity, strengthen sectoral capabilities, and facilitate moving up the value chain could smooth the transition and help capture the benefits of EV production.

*Source: IMF staff paper "CZECHIA: STRUCTURAL TRANSITIONS TO ELECTRIC VEHICLE PRODUCTION" (December 12, 2022), chapter 1: Cross-Country Comparison of Productivity and R&D.*

### 1. Cross-Country Comparison of Productivity and R&D  ________________________________ 3

### 1. Cross-Country Comparison of Productivity and R&D

### A. Background: Automotive Production in Czechia
- Czechia’s convergence toward more advanced economies has been driven mostly by the auto industry and requires moving up global value chains to sustain further convergence.
- GDP per capita is reported in 2019 to avoid the inclusion the impact of the pandemic and subsequent recovery.
- Czechia’s relatively lower R&D spending per inhabitant compared with other advanced European economies constrains progress up the value chain.

### B. Czechia Automotive Sector: Size and Integration
- The automotive sector is one of the largest sectors in Czechia in terms of output and employment.
  - Motor vehicle sector value added share: 4.9 percent (as of 2014).
  - Motor vehicle sector employment share: 3.2 percent (as of 2014).
- Adjacent sectors (trade of motor vehicles and repair of equipment) provide important spillovers to the Czechia economy.
- Czechia automotive sector is highly integrated into global value chains with strong upstream and downstream linkages.
  - Germany is the most important supplier and consumer of Czechia auto sector’s intermediate inputs, reflecting ownership links (Volkswagen and Skoda Auto).
  - On the intermediate input supplier side after Czechia and Germany: Poland, Slovakia, and Italy.
  - On the intermediate input consumer side: Russia, France, and Slovakia.

### C. Value Added and Skill Intensity Comparisons
- Czechia automotive sector has one of the lowest value-added shares compared to other countries in the region.
- Czechia has one of the lowest shares of high-skilled workers in the automotive sector and a comparatively lower high-skill population share.
- By comparison, Germany has one of the highest value-added shares in the auto sector and a larger pool of high-skilled workers in the general population.

### D. Key Observed Trends and Risks in Transition to EVs
- Three observed trends/risks regarding electric vehicle (EV) transition:
  - EV production involves shorter value chains than combustion vehicle production; uncertainty exists whether Czechia’s current role will be preserved.
  - EV production tends to be higher value added and involves less labor, implying risk of lower labor demand in Czechia.
  - EV production is more skill-intensive than combustion vehicle production, raising risks for Czechia given a relatively lower-skilled population.
- The energy crisis in Europe could lead to dislocation of European value chains over the medium-term.

### E. Empirical EV Uptake Indicator (from source figure)
- Electric Vehicle Share of Passenger Car Production shown over Jan-21 to May-22 (Percent), illustrating rising EV share in Czechia (figure in source).

### F. Analysis Framework
- Staff analysis uses a stylized structural model of automotive global value chains with distinct production for electric and combustion vehicles to study impacts of transition and policy responses.
- The model embeds domestic capability features, specialization along value chains, and trade linkages.

---

### G. Structural Model: Key Features
- Main overlapping structural components:
  - Value chains: two value chains (EV and CV) plus a numeraire good; stages of production denoted by h; relative labor intensity 훼_h and relative skill intensity 훽_h.
  - Trade of goods: variable trade cost 휏_i,j^h and fixed trade cost f_i,j^h; fixed trade cost implies only most productive goods access foreign markets.
  - Entry of new goods: firms pay a convex cost to create new varieties, determining mass of goods (interpreted as sectoral capabilities / total factor productivity).
  - Capital: not explicitly modeled; effects proxied via entry of new goods; labor share 훼_h captures role of capital as alternative input.
- The economy consists of I countries modeled as ℐ={CZE, DEU, ROW} (Czechia, Germany, Rest of World).
- Consumer taste parameter 훾_t determines relative demand and total EV expenditure; shifting 훾_t drives structural transition to EV production.

### H. Model Illustration
- Figures in source illustrate economic relationships, supply relationships, and the automotive GVC structure for EV and CV production stages.

---

### I. Calibration
- Calibration based on combustion vehicle production data; EV parameterization set to match observed differences between CV and EV production.
- Transition to EV is mimicked by changing taste parameter 훾.
- Trade costs are estimated to match within-sector trade flows and scaled to match relative use of intermediate inputs for Czechia (~50 percent).
- The calibration is illustrative and not a quantitative forecast.

- Table 1: Selected calibrated parameters (as presented)
  - Common Parameters:
    - Discount Rate (%)4
    - EV Preference (%)10
    - Productivity Distribution5.0
    - Exit Probability0.1
  - Country-Specific Parameters (Productivity):
    - Productivity of Unskilled Workers: [1.00 , 0.91 , 1.25]
    - Productivity of Skilled Workers: [0.67 , 0.76 , 0.63]
  - Sector Specific Parameters (Elasticity of Substitution, Labor Share, Skill Intensity):
    - Elasticity of Substitution: [3.0 , 3.0 , 3.0 , 2.5 , 3.0 , 2.5]
    - Labor Share: [0.7 , 0.5 , 0.5 , 0.5 , 0.8 , 0.6]
    - Skill Intensity: [0.2 , 0.2 , 0.2 , 0.4 , 0.3 , 0.5]
  - Other Parameters (reported as country average):
    - Entry Cost: [1.07 , 1.02 , 1.03]
    - Variable Trade Cost: [1.07 , 1.06 , 1.06]
    - Fixed Trade Cost: [0.107 , 0.106 , 0.106]

- Sectoral ordering in Table 1: from most upstream to most downstream; EV stages parametrized to be less labor intensive and more skill intensive in later stages relative to CV stages.

---

### J. Transition to EV Production: Scenario and Metrics
- Baseline equilibrium (current policies) compared with EV equilibrium in which expenditures on electric vehicles increase to 90 percent of automotive expenditures (EV equilibrium).
- The EV equilibrium is interpreted as an economy circa 20 years in the future after the EU’s “Fit for 55” goal—to ban the combustive engine by 2035—has become effective.
- Results are steady-state comparisons and are presented as changes between the EV equilibrium and the benchmark equilibrium; quantitative magnitudes are illustrative.
- Results are scaled so that the absolute value of the change in Czechia is normalized to one.

### K. Modeled Impacts of Full EV Transition (EV expenditure = 90 percent)
- For Czechia:
  - Automotive sector output: increase (comparatively marginal).
  - Skill share (share of high-skilled workers in automotive sector): increase.
  - Value-added share: decrease relative to baseline.
  - Overall employment in automotive sector: decrease relative to baseline.
- Mechanisms:
  - Increase in output driven by narrowing of the value chain allowing Czechia to displace ROW countries that have competitive disadvantage in higher value-added sectors.
  - Decrease in value-added share and increase in skill intensity stem from parameterization differences for EV production.
  - Decline in employment closely linked to decline in value added and lower labor intensity of EV production.
- A partial transition (half of final expenditure on EVs) yields overall changes around one-half of the full-transition results.

### L. Policy Levers Examined (framework only; policies analyzed in subsequent sections of source)
- The model accommodates policy channels operating through:
  - Increasing labor productivity.
  - Boosting production capabilities in current specialties (entry of new goods / sectoral capabilities).
  - Moving up the global value chain (shifting toward higher value-added stages and skill-intensive production).

---

### M. Conclusions (from presented material)
- Czechia’s strong integration in automotive GVCs and large economic contribution of the auto sector supported convergence with advanced European economies.
- Sustaining convergence requires moving up global value chains; current constraints include comparatively lower value added, lower R&D investment per inhabitant, and lower skill intensity in the labor market.
- The transition to EV production poses risks to employment and value added in Czechia due to shorter value chains, higher value-added concentration in fewer stages, greater skill intensity, and lower labor intensity.
- Policies that raise labor productivity, strengthen sectoral capabilities, and facilitate moving up the value chain could smooth the transition and help capture the benefits of EV production.

*Source: IMF staff paper "CZECHIA: STRUCTURAL TRANSITIONS TO ELECTRIC VEHICLE PRODUCTION" (December 12, 2022), chapter 1: Cross-Country Comparison of Productivity and R&D.*

### 11.      The model is used to simulate three broad policy schemes that could potentially aid the

### 11.      The model is used to simulate three broad policy schemes that could potentially aid the structural transition to electric vehicle production

### Policy experiments (three broad schemes)
- a. Boosting labor productivity
  - Implemented in the model by increasing Czechia labor productivity to match that of Germany.
  - Interpreted as making skilled labor more abundant and cheaper.
  - Captures policies such as: investing in education, upskilling, re-skilling, lifelong learning programs, and digitalization policies that could boost existing skills.

- b. Support for horizontal production capabilities
  - Implemented in the model by reducing the entry cost of Czechia for intermediate sectors in both the electric and combustion vehicle (CV stage 3 and EV stage 2) production by 20 percent.
  - Interpreted as reinforcing current production capabilities and specializations (improving competitiveness of the current automotive sector).
  - Practical policy examples: investing in infrastructure, subsidies to operations of current firms, lowering trade costs.

- c. Support for vertical production capabilities
  - Implemented in the model by reducing the entry cost of the most downstream sectors for both electric and combustion vehicle production by around 20 percent.
  - Interpreted as promoting movement up the global value chain toward higher value added and more skill-intensive sectors.
  - Practical policy examples: research and development subsidies, lowering cost of new firm or product entry, labor market policies that allow access to foreign experts.

### Simulation results and quantitative settings
- Baseline and normalization
  - Impacts are expressed as the change in equilibrium outcomes under the policy scheme relative to the electric vehicle equilibrium (defined above).
  - Values are normalized such that the absolute value of the change in the transition (Figure 8) has value one.
  - In all cases parameters are set to match Table 1, with noted exceptions, with the taste parameter for electric vehicles γ set to 90 percent.

- Key quantitative policy parameter values preserved exactly from experiments
  - Entry cost reduction for horizontal policy: 20 percent.
  - Entry cost reduction for vertical policy: around 20 percent.
  - Taste parameter for electric vehicles γ set to 90 percent.

### Main findings from policy experiments
- Boosting labor productivity
  - Leads to an increase in output, employment, the skill intensity of the economy, and the value-added share.
  - Allows Czechia to move towards higher value-added sectors and rebalances production between intermediate EV sector and final EV sector relative to the baseline.
  - Some of Czechia’s intermediate EV sector production would be produced in Germany, while part of Germany’s final EV sector production would be produced in Czechia.

- Support for horizontal production capabilities
  - Could paradoxically have negative effects on Czechia automotive sector across four dimensions.
  - Mechanisms:
    - Domestic competitiveness effect: cheaper Czechia intermediate inputs make the final good cheaper to produce and more profitable in both Czechia and abroad, initially benefiting Czechia automotive sector.
    - Global competition effects: increased profitability of final good production incentivizes investments that increase final good capabilities domestically and abroad, increasing global competition that over time negatively impacts Czechia final good producers.
  - Net effect: negative impact dominates because horizontal policies shift activity from relatively favorable stages of production (final good) to relatively unfavorable stages (intermediate production), reducing overall value added and employment outcomes for the automotive sector.

- Support for vertical production capabilities
  - Yields higher value-added, employment and share of skilled labor.
  - Lower cost of entry in the final EV sector allows more goods to be produced in Czechia, increasing economic activity because the final EV sector is higher value added and more labor and skill intensive.
  - Effects of vertical policies are relatively similar to the effects of boosting labor productivity.

### Mechanisms and model intuitions highlighted
- Policies can achieve similar macroeconomic goals by either:
  - Directing economic activity towards specific sectors (sectoral entry-cost reductions), or
  - Making the conditions around those sectors more favorable (labor productivity improvements).
- Horizontal policies increase investment in intermediate goods production but can harm downstream competitiveness through heightened global competition.
- Vertical policies and labor productivity improvements both direct activity toward higher value-added, skill-intensive final stages, increasing employment and value added.

### Policy recommendations and design considerations
- Clear and directed policy can help minimize potential headwinds in the transition to electric vehicle production.
- Recommended focal areas:
  - Scale up investments in skills to boost labor productivity (preparing the economy for new EV-related production processes).
  - Invest in both horizontal and vertical capabilities to take a more active role in the EV production chain.
- Caveats for policymakers:
  - Horizontal and vertical interventions have relatively lower impact if they cause specialization to shift toward lower value-added and lower employment stages of production.
  - These policies require large investments and thus should be well planned, sequenced and targeted to maximize government capacity and labor resources.
- Additional policy considerations outside the model’s scope:
  - The model assumes final demand shifts uniformly across countries reflecting the EU’s “Fit for 55” goal that all vehicles sold should be zero emissions by 2035; if countries (including Czechia) choose not to fully phase out combustion vehicles, Czechia could retain comparative advantage in CV sectors.
  - The model does not directly consider the role of infrastructure or other capital investment important for EV adoption and production (e.g., charging stations, factories); subsidizing development of new EV production facilities would be qualitatively similar to lowering entry costs for new goods in the model.

### Model structure and calibration highlights (Annex I)
- Countries and labor
  - Global economy modeled with countries i ∈ I={1,2,3} corresponding to Czechia (CZE), Germany (DEU), and Rest of World (ROW).
  - Each country has a mass U_i of unskilled workers and S_i of skilled workers.

- Demand and production
  - Final automotive good is a Cobb-Douglas combination of combustion and electric vehicles with parameter γ_t determining the taste for EVs.
  - Production is organized as sequential global value chains: ℋ_CV={0,1,2,3,4} and ℋ_EV={0,1,5,6}, with final stages corresponding to sectors 4 and 6.

- Firm entry, productivity, and trade
  - Entry costs ψ_i^h determine the mass of varieties; new varieties draw productivity a from Pareto 1−a^{−θ}.
  - Trade follows Melitz (2003) with fixed entry costs f_{i,j}^h and iceberg trade costs τ_{i,j}^h.
  - Trade costs d_{i,j}^h estimated using Head-Reis Index; ln d_{i,j}^h relates to ln τ and ln f with parameters θ and σ.

- Calibration specifics
  - Elasticity of substitution σ_h set to 3, with slightly higher value in final stages.
  - Labor shares α_h higher in upstream sectors; skill intensity β_h matches Figure 4, higher in final stages.
  - Electric vehicle production assumed to have lower labor share α_h and higher skill intensity β_h at each stage.
  - Trade costs scaled to match relative use of intermediate inputs for Czechia around 50 percent.
  - Entry costs normalized such that entry cost in the common sector is one for Czechia; Germany has comparative advantage in more downstream sectors; ROW has comparative advantage in most upstream sectors.

*Source: IMF staff analysis in "Policy Impact of Various Policy Options to Ease the Transition to EV Production", Annex I and main text of the chapter.*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2023/english/sipea2023013.pdf_