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| fingreen:input_data:inputseconomy:shocks [2026/10/30 13:13] – lesi | fingreen:input_data:inputseconomy:shocks [2026/10/30 14:02] (current) – copied from word documentation, still has to be finalised lesi | ||
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| - https:// | - https:// | ||
| - 12ag -- Deaths by age (1-year) and sex, 1980-2023 | - 12ag -- Deaths by age (1-year) and sex, 1980-2023 | ||
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| + | **File:** ‘Mortality by sex and cohort 1980-2024 001_12ag_2023_20241204-153452.xlsx’ | ||
| **Note:** | **Note:** | ||
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| - | ## Data title | + | ## Economic shocks: Imports, Exports, Consumption, |
| - | **Description: | + | **Description: |
| - | **Unit: | + | **Unit: |
| **Source code:** - | **Source code:** - | ||
| **Source data link(s) and access dates:** | **Source data link(s) and access dates:** | ||
| - | - https://example.com/ Date accessed: 2026/10/30 12:08 | + | - https://pxdata.stat.fi/PxWeb/pxweb/en/ |
| + | **File:** ‘Economic shocks 1975-2024 (imports exports consumption GFCF) 001_11sf_2024_20250531-113103.xlsx’ | ||
| - | ## Data title | + | **Notes:** |
| + | - Can use the following variables: | ||
| - | **Description: | + | |
| - | **Unit:** - | + | - P6K Exports of goods and services, expenditure |
| + | |||
| + | - P3K Consumption expenditure, | ||
| + | |||
| + | - P51K Gross fixed capital formation, expenditure | ||
| + | |||
| + | - Why is the shock considered without industry disaggregation? | ||
| + | |||
| + | - More info of Covid effects in Finland: [https:// | ||
| + | |||
| + | - Eurogreen assumed the shock for the years 2020 and 2021. The covid shock was based on the variations of consumption, | ||
| + | |||
| + | - Eurogreen: The covid shock is based on the Bank of Italy’s projections for the variations of consumption, | ||
| + | |||
| + | - Ukraine war economic shock also relates to the energy module à something to consider later. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | - For industry disaggregation for trade impacts, see [14mc -- International trade in services, trade value by activity sector, enterprise size class and region, annually, 2019-2023](https:// | ||
| + | |||
| + | |||
| + | ## Economic shocks: LFPR | ||
| + | |||
| + | **Description:** Change in the Labour Force Participation Rate (15-64y) compared to previous year, during 2020-2021. | ||
| + | |||
| + | **Unit:** rate | ||
| **Source code:** - | **Source code:** - | ||
| **Source data link(s) and access dates:** | **Source data link(s) and access dates:** | ||
| - | - https://example.com/ Date accessed: | + | - 2009-2023: |
| + | - 1989-2020: | ||
| + | |||
| + | **Notes: | ||
| + | - Vensim comment: “DATA FROM ILO, labor force participation rate, 15-64y”, “Assuming complete recover of labor force participation rate to pre-pandemic level 2022, 15-64y: 0.0192; 1,92%” | ||
| + | |||
| + | - According to Finnish data, the labour force was already higher in 2021 than in 2019, with only a minor dip in 2020 (-0.0014) followed by two years of unusually high increases in participation rates, despite stable population. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | {{: | ||
| + | |||
| + | ## LFPR gs shock | ||
| + | |||
| + | **Description: | ||
| + | |||
| + | **Unit:** rate | ||
| + | |||
| + | **Source code:** - | ||
| + | |||
| + | **Source data link(s) and access dates:** | ||
| + | - https:// | ||
| + | |||
| + | **Notes: | ||
| + | - Note: Same data source as LFPR gs | ||
| + | |||
| + | ## Total price shock | ||
| + | |||
| + | **Description: | ||
| + | |||
| + | **Unit:** percent | ||
| + | |||
| + | **Source code:** - | ||
| + | |||
| + | **Source data link(s) and access dates:** | ||
| + | - https:// | ||
| + | |||
| + | **File:** ‘price-shocks-fi-2010-2023’ | ||
| + | |||
| + | **Notes: | ||
| + | - Used R code to extract and process the data. | ||
| + | |||
| + | - Also downloaded data with only value added ‘GVA by industry 2010-2023 Eurostat nama_10_a64__custom_16742335_spreadsheet.xlsx’ | ||
| + | |||
| + | - Vensim comment: “price shocks computed for the year 2022 (Eurostat data on Value added)” | ||
| + | |||
| + | - The total price shocks for 2022 and 2023 were calculated by deriving implicit price deflators from Eurostat Gross Value Added (GVA) data by NACE industry. Specifically, | ||
| + | |||
| + | - Explanation is our best guess, waiting confirmation from Guilherme. | ||
| + | |||
| + | - TODO: Need to switch to the new approach of shocking mark-ups instead of prices | ||
| + | |||
| + | - Guilherme: “We realized that a second strategy could be more flexible and useful for the model structure. Rather than giving a shock on prices, we decided to shock the markups. (check the variable target markup i). You can simply compute how much the necessary shock would be, inverting the price-markup formula. (That is, using mark-up as the unknown as the price as the known variable in the price equation, to get the desired mark-up after the shock as the solution). We also included a time of convergence of the targeted mark-up, to avoid a sharp reduction of prices in the year after the shock. You basically just need to replicate the structure in the Sub-module mark-up in the price view of the updated version of the model. We put a 5 year period of convergence, | ||