## 1. Estimate the short-term economic impact of the pandemic

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---

### Short-term estimation approach and methodology
- Framework: sectoral analysis framework developed by the IMF Research Department that decomposes the effect on each economic sector into:
  - (1) events: policy actions (especially mandatory lockdowns) taken to contain the spread of the virus (the shock);
  - (2) the severity: the output losses associated with these actions (the impact);
  - (3) the persistence of the event as defined by government decrees (persistence of shock and impact).
- Identification of the event: the government's emergency decree that imposed the lockdown.
- Severity estimation:
  - Used interactions between virus dynamics and lockdown strength.
  - Used several high-frequency indicators, such as energy consumption and retail sales, to estimate severity in each sector.
  - Estimate captures direct supply impact and lower demand as households and firms postponed consumption and investment decisions.
- Persistence assumption: assumed no second wave of COVID-19 after the second half of 2020; persistence estimated by assessing the speed of recovery for each sector.
- Data vintage: uses data available up to May 2020.
- Alternative / complementary approaches:
  - Sectoral approach can be combined with real-time indicators; the Colombian MF used such an extension and reported results in the MTFF.
  - An ICD TA mission to Rwanda used real-time data on VAT and retail sales to estimate GDP for 2020 Q1 and Q2.

### Short-term findings (2020)
- Sectors most affected (contact-intensive occupations): arts and entertainment, retail trade, transport, accommodation, and food services.
- Aggregate preliminary result: 6.8% y-o-y contraction of GDP in 2020.
- Use of results: preliminary results were used by BR and MF as near-term forecasts in their quarterly macroeconomic exercises.

### Key methodological notes on short-term forecasting
- Short-term forecasts are useful because:
  - (1) they summarize expert knowledge and convey information not otherwise available to the forecasting exercise;
  - (2) there are time-series econometric methods that in the short term outperform the DSGE forecast.

### COFFEE DSGE model: assessing medium- and long-term effects

#### Model structure and fiscal features
- Model name: COFFEE (Colombian Framework for Fiscal Economics and Evaluation).
- Type: overlapping generation DSGE for a small oil-exporting economy; includes different types of households and firms and incorporates nominal price and wage rigidities.
- Households: includes households with and without access to credit and saving instruments.
- Firms and production:
  - Domestic firms produce a composite good consumed internally, exported, or used by other domestic firms to produce investment goods.
  - Final household consumption and investment baskets include both domestic and imported goods.
  - Imports are also intermediate goods in domestic production.
- Fiscal module:
  - Government revenues and dividends from oil production and taxes on consumption goods (domestic and imported), labor income, household wealth, and profits of firms and capital producers.
  - Government spending on consumption, interest payments, transfers to households, and public capital formation.
  - Fiscal deficits financed with both domestic and foreign debt.
  - Fiscal rule for the deficit considers the output and oil price gaps.
- Calibration anchored to Colombia's fiscal policy targets and long-run ratios; priors reflect the relative importance of structural shocks.

#### Augmentations to capture COVID-19 features
- Incorporated shocks:
  - Domestic demand shocks to capture contraction of private spending (private consumption and investment move in tandem).
  - Labor supply shocks affecting the disutility of labor to reflect households' disincentive to supply labor during the pandemic.
  - These shocks also capture weakening financial conditions (in absence of explicit financial sector, financial frictions captured via a shock).
- Limitations noted: model lacks feedback loops between the real and financial sectors and is not useful for assessing financial stability issues.

#### Calibration: Initial steady state (Table 1)
- Macroeconomic Variables:
  - GDP (constant prices, percent growth) 3.0
  - Private consumption (percent of GDP) 67.6
  - Private investment (percent of GDP) 18.3
  - Public expenditure (percent of GDP) 16.0
  - Trade balance (percent of GDP) -1.9
  - Current account balance (percent of GDP) -2.8
  - Inflation rate (percent) 3.0
  - Monetary policy rate (percent) 5.1
- Public Finances (percent of GDP):
  - Government income 15.8
  - Government expenditure 16.0
  - Primary deficit 0.2
  - Interest payments 0.8
  - Total deficit 1.0
  - Total public debt 17.4

#### Data provided to COFFEE for 2020 (Table 2)
- Observable Variables (Annual estimated value or deviation)
  - Percent
    - GDP growth -6.8  (IMF - TA)
    - Inflation 2.3
    - BR Trade partners GDP growth -4.5
    - Risk-free interest rate 0.5
  - Percent of GDP
    - Government revenue 15.5
    - MF Government expenditure (exc. debt service) 20.6
    - Government debt service 3.2
    - Current account balance -3.7  (BR)
    - Remittances 1.0
  - Percent deviations from Steady State
    - Oil price index -38.8  (BR)
    - Risk premium 1.1

#### Forecast construction steps
- Step 1: Build a dataset for 2020 containing data consistent with the shock's short-term impacts (includes sectoral analysis GDP estimate and estimates for year-end inflation, trade partners’ GDP growth, risk-free interest rate, current account balance, remittances, oil prices, and risk premium). Government spending and revenue estimates obtained from the 2020 MTFF.
- Step 2: Use the model and the Kalman Filter to estimate structural shocks consistent with the observable variables in the database. For 2020, the Kalman Filter identified:
  - Negative demand and supply shocks,
  - Adverse foreign demand shocks,
  - Negative oil price shock,
  - Partly offsetting positive fiscal shocks and lower external interest rate shocks.
  - Interpretation: lockdown policies as supply shocks; voluntary social distancing and income falls as demand shocks; intersectoral adjustment costs as a supply shock reducing aggregate productivity; negative foreign shocks reflect the universality of the pandemic.
- Step 3: Add expert judgment and assumptions about the future path of exogenous variables; iterate until the baseline scenario is considered consistent.

#### Simulation diagnostics and shock decomposition
- Decomposition categories used in simulations:
  - Supply shocks: labor supply and total factor productivity.
  - Local demand shocks: consumption and investment.
  - Foreign demand shocks: GDP growth in trade partners and oil price.
  - Fiscal shocks: government expenditure.
  - Foreign shocks: risk-free interest rate and risk premium.
- Persistency: the persistency of shocks is consistent with previous estimates at the BR and adjusted to reflect likely pandemic duration based on expected duration of lockdowns and social distancing measures.

#### Policy stance in simulations and recommendations
- Simulated policies: both fiscal and monetary policies are expansive.
- Rationale: a mixture of demand and supply shocks leaves room for expansive fiscal and monetary policies to counteract the fall in demand.
- Structural recommendation: structural measures are needed to diminish scarring effects of the pandemic on long-term productivity and employment.

#### Expert assumptions added to the COVID scenario
- 1. A permanent negative oil price shock, implying a different steady-state for GDP owed to income-related channels.
- 2. Shocks to foreign interest rates, reflecting the expected lower-for-longer US Federal Reserve monetary policy rate.

### Key simulation findings (Colombia scenario)
- Permanent macroeconomic effects and near-term dynamics:
  - Permanent loss in GDP driven by destruction of jobs and firms, lower productivity, and lower oil prices.
  - Near-term damage larger due to precautionary saving, voluntary social distancing, and lower incomes from job losses.
  - Reduction in private investment and consumption.
  - Fall in inflation, with prolonged demand contraction expected to keep inflation below target for some time.
  - Trade deficit narrows because contraction of imports more than offsets fall in exports.
- Policy and fiscal outcomes:
  - Monetary policy rate declines in response to the drop in inflation and the negative output gap.
  - Fiscal deficit expands to 8.2% of GDP.
  - Public debt reaches 65.5%.
  - Higher interest payments on public debt, higher government spending, and lower revenues explain the fiscal outcome.
  - After 2021, easing of lockdowns and recovery of private demand would bring GDP growth close to 4%.
  - Debt service could hold at about 3% of GDP.
  - To achieve a public deficit of just 1% of GDP, fiscal revenues should go up by about 2% of GDP by 2022.
- Model and scenario caveat:
  - The preliminary simulation results are not the official forecast of Banco de la República or the Ministry of Finance.
  - According to the MTFF 2020, the government expects the public debt-to-GDP ratio to decline in 2021.

### Cambodia TA project — macroeconomic context and vulnerabilities
- Structural features:
  - Trade and financial openness, a stable exchange rate, and little space for monetary policy.
  - Since liberalization after 1998, Cambodia averaged real GDP growth of 7¾ percent, with inflation averaging about 4 percent.
  - Growth driven by garment exports, tourism, and construction; tourism and light manufacturing represent one-third of the country’s GDP.
  - Economy almost completely dollarized; monetary framework consists of a highly managed and stabilized exchange rate and an open capital account.
- External and fiscal buffers:
  - Gross external debt stabilized at about 30 percent of GDP.
  - Fiscal deposits equal to about 15 percent of GDP at the end of 2019 act as buffers.
  - All government borrowing is on concessional terms from multilateral institutions and bilateral donors.
- Technical assistance:
  - In 2019 authorities requested TA on model-based financial programming, FP2.0, to simulate impacts of domestic and external shocks and build MTBF capacity.

### CAMFI model: structure, calibration, and assumptions
- Model features and building blocks:
  - Semistructural CAMFI model (trend-gap style) with a rudimentary fiscal and debt-accounting block.
  - Five building blocks: (1) aggregate demand (IS curve); (2) price-setting (Philips curve) relating inflation to output gap, exchange rate, oil prices, and past/expected inflation; (3) uncovered interest rate parity; (4) monetary regime; (5) fiscal policy response block.
- Calibration and special features:
  - Dollarization regime approximated by exchange rate peg version of UIP and a credit risk premium in the IS curve.
  - Model blends New Keynesian nominal/real rigidities with real business cycle DSGE elements; allows adaptive and rational expectations and substantial inertia to match data.
  - Model validated with impulse response functions, multivariate filtration, and in-sample forecasting; reproduces main stylized facts for Cambodia.

### Simulation of COVID-19 macroeconomic effects (Cambodia)

#### Three-layer assumption framework
1. Recession in trading partners reduces demand for exports and collapses tourist arrivals.
2. Second-round domestic demand and supply impacts plus country risk premium increases, working through expectations.
3. Government introduces fiscal stimulus to mitigate prior impacts.

#### External assumptions (layer 1)
- Economic activities decline most in France, Germany, the US, and the UK.
- US Federal Reserve keeps policy rate at or near zero in 2020 and 2021 before gradual lift.
- Oil prices plunge in 2020 and recover only slightly in 2021.

#### Domestic assumptions (layer 2)
- Domestic demand decreases by an additional 2 pp each year in 2020 and 2021.
- Country risk premium goes up by 200 basis points each year in 2020 and 2021.
- Food prices rise due to hoarding (domestic food price effects offset partly by slack/lower oil).
- Medium-term supply disruptions: tourism restrictions into 2021 or 2022 and sustained decline in demand for exports.
- Drops in potential GDP envisaged: 4.5 percentage points (pp) in 2020 and 3.5 pp in 2021, fully dissipating by 2024.

#### Fiscal stimulus assumptions (layer 3)
- Public debt target expected to go up by 5 pp in 2020 and return only gradually to original level.
- Fiscal multiplier assumed at 0.5 based on cross-country experience; lower multipliers would reduce stimulus effectiveness.

#### Scenario quantitative outcomes and timing
- Pre-pandemic 2020 growth projection was 6.8 percent.
- First-layer external shock can bring Cambodia's growth down to -1¼ percent in 2020 compared to baseline 6 percent.
- Second-layer domestic effects slow growth to -8¼ percent in 2020.
- Third-layer fiscal stimulus boosts real growth by about 2½ percent, bringing GDP growth to -5¾ percent in 2020.
- Recovery begins in 2021, with growth above 2 percent and closure of the output gap in 2022.
- The fiscal stimulus has only a short-lived impact on growth; increases in debt target are temporary, similar to the GFC episode.
- Sensitivity test: prolonged higher debt-to-GDP ratio would have medium-term impacts on economy and fiscal balances.

### Cambodia simulation: Table 3 — Main macroeconomic variables after COVID-19 (selected series)
- GDP (constant prices, percent growth):
  - 2020: -6.8
  - 2021: 4.8
  - 2022: 4.6
  - 2023: 4.0
  - 2024: 3.5
  - 2025: 3.3
- GDP level (model units)*:
  - 2020: 9.6
  - 2021: 9.7
  - 2022: 9.9
  - 2023: 10.0
  - 2024: 10.1
  - 2025: 10.1
- Private consumption (deviation from ss in % of GDP):
  - 2020: -0.2
  - 2021: -0.9
  - 2022: -1.3
  - 2023: -1.3
  - 2024: -1.2
  - 2025: -1.1
- Private investment (deviation from ss in % of GDP):
  - 2020: -4.5
  - 2021: -2.0
  - 2022: -0.3
  - 2023: 0.5
  - 2024: 0.8
  - 2025: 0.8
- Public expenditure (deviation from ss in % of GDP):
  - 2020: 4.2
  - 2021: 2.3
  - 2022: 1.5
  - 2023: 1.1
  - 2024: 0.9
  - 2025: 0.8
- Trade balance (percent of GDP):
  - 2020: -1.6
  - 2021: -1.4
  - 2022: -2.0
  - 2023: -2.4
  - 2024: -2.6
  - 2025: -2.6
- Current account balance (percent of GDP):
  - 2020: -3.7
  - 2021: -2.9
  - 2022: -2.6
  - 2023: -2.4
  - 2024: -2.4
  - 2025: -2.4
- Remittances (percent of GDP):
  - 2020: 1.0
  - 2021: 1.8
  - 2022: 2.0
  - 2023: 2.0
  - 2024: 2.1
  - 2025: 2.1
- Inflation rate (percent):
  - 2020: 2.3
  - 2021: 2.4
  - 2022: 2.4
  - 2023: 2.7
  - 2024: 2.8
  - 2025: 2.8
- Monetary policy rate (percent):
  - 2020: 2.7
  - 2021: 3.0
  - 2022: 4.0
  - 2023: 4.6
  - 2024: 4.9
  - 2025: 5.1
- Government income (percent of GDP):
  - 2020: 15.5
  - 2021: 16.3
  - 2022: 17.8
  - 2023: 18.2
  - 2024: 18.6
  - 2025: 18.9
- Government expenditure (percent of GDP):
  - 2020: 20.6
  - 2021: 18.7
  - 2022: 17.9
  - 2023: 17.6
  - 2024: 17.3
  - 2025: 17.2
- Primary deficit (percent of GDP):
  - 2020: 5.1
  - 2021: 2.4
  - 2022: 0.2
  - 2023: -0.7
  - 2024: -1.3
  - 2025: -1.8
- Interest payments (percent of GDP):
  - 2020: 3.2
  - 2021: 2.8
  - 2022: 2.9
  - 2023: 3.0
  - 2024: 3.0
  - 2025: 2.9
- Total deficit (percent of GDP):
  - 2020: 8.2
  - 2021: 5.2
  - 2022: 3.1
  - 2023: 2.3
  - 2024: 1.7
  - 2025: 1.2
- Total public debt:
  - 2020: 65.5
  - 2021: 69.1
  - 2022: 67.9
  - 2023: 66.1
  - 2024: 63.9
  - 2025: 61.4
- Note: Units are specified for each variable within the table. *Per capita and adjusted for productivity growth.

### Policy implications and model comparisons
- Policy implications:
  - Fiscal policy plays a dominant operational role where monetary policy space is limited by dollarization and a de facto peg regime.
  - Short-term discretionary fiscal stimulus can cushion demand collapse but has only temporary benefits; fiscal multipliers and implementation lags matter.
  - Returning to medium-term fiscal targets requires revenue increases (example: about 2% of GDP increase in revenues by 2022 to hit a 1% deficit target in the Colombia scenario).
- Model comparison (Colombia DSGE vs. Cambodia semistructural gap model):
  - Both identify supply, demand, financial, and external channels transmitting the pandemic; both highlight aggregate demand’s dominant role and negative output gaps.
  - Semistructural gap model: flexible, easily adapted to alternative monetary/exchange rate regimes, useful for layering external, domestic, and fiscal shocks; fiscal multiplier in Cambodia exercise set at 0.5, limiting smoothing capacity.
  - DSGE model: more granular identification of shocks and transmission channels; allows detailed policy instrument experimentation.
  - Combining data attention, near-term forecasting, and model-based analyses supports coherent policy-making.

*Source: tnmea2021001 - 1. Estimate the short-term economic impact of the pandemic.*

### 1. Estimate the short-term economic impact of the pandemic.

### 1. Estimate the short-term economic impact of the pandemic

### Short-term estimation approach and methodology
- Framework: sectoral analysis framework developed by the IMF Research Department that decomposes the effect on each economic sector into:
  - (1) events: policy actions (especially mandatory lockdowns) taken to contain the spread of the virus (the shock);
  - (2) the severity: the output losses associated with these actions (the impact);
  - (3) the persistence of the event as defined by government decrees (persistence of shock and impact).
- Identification of the event: the government's emergency decree that imposed the lockdown.
- Severity estimation: used interactions between virus dynamics and lockdown strength; several high-frequency indicators, such as energy consumption and retail sales, were used to estimate severity in each sector. The estimate captures direct supply impact and lower demand as households and firms postponed consumption and investment decisions.
- Persistence assumption: assumed no second wave of COVID-19 after the second half of 2020; persistence estimated by assessing the speed of recovery for each sector.
- Data vintage: uses data available up to May 2020.
- Alternative / complementary approaches: sectoral approach can be combined with real-time indicators; the Colombian MF used such an extension and reported results in the MTFF. An ICD TA mission to Rwanda used real-time data on VAT and retail sales to estimate GDP for 2020 Q1 and Q2.

### Short-term findings (2020)
- Sectors most affected (contact-intensive occupations): arts and entertainment, retail trade, transport, accommodation, and food services.
- Aggregate preliminary result: 6.8% y-o-y contraction of GDP in 2020.
- Use of results: preliminary results were used by BR and MF as near-term forecasts in their quarterly macroeconomic exercises.

### Key methodological notes on short-term forecasting
- Short-term forecasts are useful because:
  - (1) they summarize expert knowledge and convey information not otherwise available to the forecasting exercise;
  - (2) there are time-series econometric methods that in the short term outperform the DSGE forecast.

---

### COFFEE DSGE model: assessing medium- and long-term effects

#### Model structure and fiscal features
- Model name: COFFEE (Colombian Framework for Fiscal Economics and Evaluation).
- Type: overlapping generation DSGE for a small oil-exporting economy; includes different types of households and firms and incorporates nominal price and wage rigidities.
- Households: includes households with and without access to credit and saving instruments.
- Firms and production:
  - Domestic firms produce a composite good consumed internally, exported, or used by other domestic firms to produce investment goods.
  - Final household consumption and investment baskets include both domestic and imported goods.
  - Imports are also intermediate goods in domestic production.
- Fiscal module: comprehensive characterization of Colombia’s fiscal policy:
  - Government revenues and dividends from oil production and taxes on consumption goods (domestic and imported), labor income, household wealth, and profits of firms and capital producers.
  - Government spending on consumption, interest payments, transfers to households, and public capital formation.
  - Fiscal deficits financed with both domestic and foreign debt.
  - Fiscal rule for the deficit considers the output and oil price gaps.
- Calibration anchored to Colombia's fiscal policy targets and long-run ratios; priors reflect the relative importance of structural shocks.

#### Augmentations to capture COVID-19 features
- Incorporated shocks:
  - Domestic demand shocks to capture contraction of private spending (private consumption and investment move in tandem).
  - Labor supply shocks affecting the disutility of labor to reflect households' disincentive to supply labor during the pandemic.
  - These shocks also capture weakening financial conditions (in absence of explicit financial sector, financial frictions captured via a shock).
- Limitations noted: model lacks feedback loops between the real and financial sectors and is not useful for assessing financial stability issues.

#### Calibration: Initial steady state (Table 1)
- Macroeconomic Variables:
  - GDP (constant prices, percent growth) 3.0
  - Private consumption (percent of GDP) 67.6
  - Private investment (percent of GDP) 18.3
  - Public expenditure (percent of GDP) 16.0
  - Trade balance (percent of GDP) -1.9
  - Current account balance (percent of GDP) -2.8
  - Inflation rate (percent) 3.0
  - Monetary policy rate (percent) 5.1
- Public Finances (percent of GDP):
  - Government income 15.8
  - Government expenditure 16.0
  - Primary deficit 0.2
  - Interest payments 0.8
  - Total deficit 1.0
  - Total public debt 17.4

#### Data provided to COFFEE for 2020 (Table 2)
- Observable Variables (Annual estimated value or deviation)
  - Percent
    - GDP growth -6.8  (IMF - TA)
    - Inflation 2.3
    - BR Trade partners GDP growth -4.5
    - Risk-free interest rate 0.5
  - Percent of GDP
    - Government revenue 15.5
    - MF Government expenditure (exc. debt service) 20.6
    - Government debt service 3.2
    - Current account balance -3.7  (BR)
    - Remittances 1.0
  - Percent deviations from Steady State
    - Oil price index -38.8  (BR)
    - Risk premium 1.1

#### Forecast construction steps
- Step 1: Build a dataset for 2020 containing data consistent with the shock's short-term impacts (includes sectoral analysis GDP estimate and estimates for year-end inflation, trade partners’ GDP growth, risk-free interest rate, current account balance, remittances, oil prices, and risk premium). Government spending and revenue estimates obtained from the 2020 MTFF.
- Step 2: Use the model and the Kalman Filter to estimate structural shocks consistent with the observable variables in the database. For 2020, the Kalman Filter identified:
  - Negative demand and supply shocks,
  - Adverse foreign demand shocks,
  - Negative oil price shock,
  - Partly offsetting positive fiscal shocks and lower external interest rate shocks.
  - Interpretation: lockdown policies as supply shocks; voluntary social distancing and income falls as demand shocks; intersectoral adjustment costs as a supply shock reducing aggregate productivity; negative foreign shocks reflect the universality of the pandemic.
- Step 3: Add expert judgment and assumptions about the future path of exogenous variables; iterate until the baseline scenario is considered consistent.

#### Simulation diagnostics and shock decomposition
- Decomposition categories used in simulations:
  - Supply shocks: labor supply and total factor productivity.
  - Local demand shocks: consumption and investment.
  - Foreign demand shocks: GDP growth in trade partners and oil price.
  - Fiscal shocks: government expenditure.
  - Foreign shocks: risk-free interest rate and risk premium.
- Persistency: the persistency of shocks is consistent with previous estimates at the BR and adjusted to reflect likely pandemic duration based on expected duration of lockdowns and social distancing measures.

#### Policy stance in simulations and recommendations
- Simulated policies: both fiscal and monetary policies are expansive.
- Rationale: a mixture of demand and supply shocks leaves room for expansive fiscal and monetary policies to counteract the fall in demand.
- Structural recommendation: structural measures are needed to diminish scarring effects of the pandemic on long-term productivity and employment.

#### Expert assumptions added to the COVID scenario
- 1. A permanent negative oil price shock, implying a different steady-state for GDP owed to income-related channels.
- 2. Shocks to foreign interest rates, reflecting the expected lower-for-longer US Federal Reserve monetary policy rate.

*Source: tnmea2021001 - 1. Estimate the short-term economic impact of the pandemic.*

### 3. Shocks to spending to reflect the  path presented in the  2020 MTFF. These shocks are

### 3. Shocks to spending to reflect the  path presented in the  2020 MTFF. These shocks are

### Key simulation findings (Colombia scenario)
- Permanent macroeconomic effects and near-term dynamics:
  - Permanent loss in GDP driven by destruction of jobs and firms, lower productivity, and lower oil prices.
  - Near-term damage larger due to precautionary saving, voluntary social distancing, and lower incomes from job losses.
  - Reduction in private investment and consumption.
  - Fall in inflation, with prolonged demand contraction expected to keep inflation below target for some time.
  - Trade deficit narrows because contraction of imports more than offsets fall in exports.
- Policy and fiscal outcomes:
  - Monetary policy rate declines in response to the drop in inflation and the negative output gap.
  - Fiscal deficit expands to 8.2% of GDP.
  - Public debt reaches 65.5%.
  - Higher interest payments on public debt, higher government spending, and lower revenues explain the fiscal outcome.
  - After 2021, easing of lockdowns and recovery of private demand would bring GDP growth close to 4%.
  - Debt service could hold at about 3% of GDP.
  - To achieve a public deficit of just 1% of GDP, fiscal revenues should go up by about 2% of GDP by 2022.
- Model and scenario caveat:
  - The preliminary simulation results are not the official forecast of Banco de la República or the Ministry of Finance.
  - According to the MTFF 2020, the government expects the public debt-to-GDP ratio to decline in 2021.

### Cambodia TA project — macroeconomic context and vulnerabilities
- Structural features:
  - Trade and financial openness, a stable exchange rate, and little space for monetary policy.
  - Since liberalization after 1998, Cambodia averaged real GDP growth of 7¾ percent, with inflation averaging about 4 percent.
  - Growth driven by garment exports, tourism, and construction; tourism and light manufacturing represent one-third of the country’s GDP.
  - Economy almost completely dollarized; monetary framework consists of a highly managed and stabilized exchange rate and an open capital account.
- External and fiscal buffers:
  - Gross external debt stabilized at about 30 percent of GDP.
  - Fiscal deposits equal to about 15 percent of GDP at the end of 2019 act as buffers.
  - All government borrowing is on concessional terms from multilateral institutions and bilateral donors.
- Technical assistance:
  - In 2019 authorities requested TA on model-based financial programming, FP2.0, to simulate impacts of domestic and external shocks and build MTBF capacity.

### CAMFI model: structure, calibration, and assumptions
- Model features and building blocks:
  - Semistructural CAMFI model (trend-gap style) with a rudimentary fiscal and debt-accounting block.
  - Five building blocks: (1) aggregate demand (IS curve); (2) price-setting (Philips curve) relating inflation to output gap, exchange rate, oil prices, and past/expected inflation; (3) uncovered interest rate parity; (4) monetary regime; (5) fiscal policy response block.
- Calibration and special features:
  - Dollarization regime approximated by exchange rate peg version of UIP and a credit risk premium in the IS curve.
  - Model blends New Keynesian nominal/real rigidities with real business cycle DSGE elements; allows adaptive and rational expectations and substantial inertia to match data.
  - Model validated with impulse response functions, multivariate filtration, and in-sample forecasting; reproduces main stylized facts for Cambodia.

### Simulation of COVID-19 macroeconomic effects (Cambodia)
- Three-layer assumption framework:
  1. Recession in trading partners reduces demand for exports and collapses tourist arrivals.
  2. Second-round domestic demand and supply impacts plus country risk premium increases, working through expectations.
  3. Government introduces fiscal stimulus to mitigate prior impacts.
- External assumptions (layer 1):
  - Economic activities decline most in France, Germany, the US, and the UK.
  - US Federal Reserve keeps policy rate at or near zero in 2020 and 2021 before gradual lift.
  - Oil prices plunge in 2020 and recover only slightly in 2021.
- Domestic assumptions (layer 2):
  - Domestic demand decreases by an additional 2 pp each year in 2020 and 2021.
  - Country risk premium goes up by 200 basis points each year in 2020 and 2021.
  - Food prices rise due to hoarding (domestic food price effects offset partly by slack/lower oil).
  - Medium-term supply disruptions: tourism restrictions into 2021 or 2022 and sustained decline in demand for exports.
  - Drops in potential GDP envisaged: 4.5 percentage points (pp) in 2020 and 3.5 pp in 2021, fully dissipating by 2024.
- Fiscal stimulus assumptions (layer 3):
  - Public debt target expected to go up by 5 pp in 2020 and return only gradually to original level.
  - Fiscal multiplier assumed at 0.5 based on cross-country experience; lower multipliers would reduce stimulus effectiveness.
- Scenario quantitative outcomes and timing:
  - Pre-pandemic 2020 growth projection was 6.8 percent.
  - First-layer external shock can bring Cambodia's growth down to -1¼ percent in 2020 compared to baseline 6 percent.
  - Second-layer domestic effects slow growth to -8¼ percent in 2020.
  - Third-layer fiscal stimulus boosts real growth by about 2½ percent, bringing GDP growth to -5¾ percent in 2020.
  - Recovery begins in 2021, with growth above 2 percent and closure of the output gap in 2022.
  - The fiscal stimulus has only a short-lived impact on growth; increases in debt target are temporary, similar to the GFC episode.
  - Sensitivity test: prolonged higher debt-to-GDP ratio would have medium-term impacts on economy and fiscal balances.

### Cambodia simulation: Table 3 — Main macroeconomic variables after COVID-19 (selected series)
- GDP (constant prices, percent growth):
  - 2020: -6.8
  - 2021: 4.8
  - 2022: 4.6
  - 2023: 4.0
  - 2024: 3.5
  - 2025: 3.3
- GDP level (model units)*:
  - 2020: 9.6
  - 2021: 9.7
  - 2022: 9.9
  - 2023: 10.0
  - 2024: 10.1
  - 2025: 10.1
- Private consumption (deviation from ss in % of GDP):
  - 2020: -0.2
  - 2021: -0.9
  - 2022: -1.3
  - 2023: -1.3
  - 2024: -1.2
  - 2025: -1.1
- Private investment (deviation from ss in % of GDP):
  - 2020: -4.5
  - 2021: -2.0
  - 2022: -0.3
  - 2023: 0.5
  - 2024: 0.8
  - 2025: 0.8
- Public expenditure (deviation from ss in % of GDP):
  - 2020: 4.2
  - 2021: 2.3
  - 2022: 1.5
  - 2023: 1.1
  - 2024: 0.9
  - 2025: 0.8
- Trade balance (percent of GDP):
  - 2020: -1.6
  - 2021: -1.4
  - 2022: -2.0
  - 2023: -2.4
  - 2024: -2.6
  - 2025: -2.6
- Current account balance (percent of GDP):
  - 2020: -3.7
  - 2021: -2.9
  - 2022: -2.6
  - 2023: -2.4
  - 2024: -2.4
  - 2025: -2.4
- Remittances (percent of GDP):
  - 2020: 1.0
  - 2021: 1.8
  - 2022: 2.0
  - 2023: 2.0
  - 2024: 2.1
  - 2025: 2.1
- Inflation rate (percent):
  - 2020: 2.3
  - 2021: 2.4
  - 2022: 2.4
  - 2023: 2.7
  - 2024: 2.8
  - 2025: 2.8
- Monetary policy rate (percent):
  - 2020: 2.7
  - 2021: 3.0
  - 2022: 4.0
  - 2023: 4.6
  - 2024: 4.9
  - 2025: 5.1
- Government income (percent of GDP):
  - 2020: 15.5
  - 2021: 16.3
  - 2022: 17.8
  - 2023: 18.2
  - 2024: 18.6
  - 2025: 18.9
- Government expenditure (percent of GDP):
  - 2020: 20.6
  - 2021: 18.7
  - 2022: 17.9
  - 2023: 17.6
  - 2024: 17.3
  - 2025: 17.2
- Primary deficit (percent of GDP):
  - 2020: 5.1
  - 2021: 2.4
  - 2022: 0.2
  - 2023: -0.7
  - 2024: -1.3
  - 2025: -1.8
- Interest payments (percent of GDP):
  - 2020: 3.2
  - 2021: 2.8
  - 2022: 2.9
  - 2023: 3.0
  - 2024: 3.0
  - 2025: 2.9
- Total deficit (percent of GDP):
  - 2020: 8.2
  - 2021: 5.2
  - 2022: 3.1
  - 2023: 2.3
  - 2024: 1.7
  - 2025: 1.2
- Total public debt:
  - 2020: 65.5
  - 2021: 69.1
  - 2022: 67.9
  - 2023: 66.1
  - 2024: 63.9
  - 2025: 61.4
- Note: Units are specified for each variable within the table. *Per capita and adjusted for productivity growth.

### Policy implications and model comparisons
- Policy implications:
  - Fiscal policy plays a dominant operational role where monetary policy space is limited by dollarization and a de facto peg regime.
  - Short-term discretionary fiscal stimulus can cushion demand collapse but has only temporary benefits; fiscal multipliers and implementation lags matter.
  - Returning to medium-term fiscal targets requires revenue increases (example: about 2% of GDP increase in revenues by 2022 to hit a 1% deficit target in the Colombia scenario).
- Model comparison (Colombia DSGE vs. Cambodia semistructural gap model):
  - Both identify supply, demand, financial, and external channels transmitting the pandemic; both highlight aggregate demand’s dominant role and negative output gaps.
  - Semistructural gap model: flexible, easily adapted to alternative monetary/exchange rate regimes, useful for layering external, domestic, and fiscal shocks; fiscal multiplier in Cambodia exercise set at 0.5, limiting smoothing capacity.
  - DSGE model: more granular identification of shocks and transmission channels; allows detailed policy instrument experimentation.
  - Combining data attention, near-term forecasting, and model-based analyses supports coherent policy-making.

*Source: tnmea2021001.*

### 049. Washington: Board of Governors of the Federal Reserve System.

### 049. Washington: Board of Governors of the Federal Reserve System.

### Core bibliographic entries and thematic coverage
- DOI: 10.17016/FEDS.2020.049.
- The content unit compiles references focused on macroeconomic modeling, policy analysis, and COVID-19 macroeconomic effects, including theory, empirical studies, and model documentation.

### Studies and working papers on COVID-19 macroeconomic effects
- Buera, Francisco J., Roberto N. Fattal-Jaef, Hugo Hopenhayn, P. Andrés Neumeyer, and Yongseok Shin. 2020. “The Economic Ripple Effects of COVID-19.” photocopy. slides-wb-apr12020.pdf.
- Chetty, Raj, John N. Friedman, Nathaniel Hendren, Michael Stepner, and the Opportunity Insights Team 2020, "The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data." Opportunity Insights Working Paper, October 2020, MA.
- Cugat, Gabriela, Melina G., and Felipe Zanna. 2020. "COVID-19 and Government Debt Dynamics in Low Income Developing Countries" Special Series on COVID-19, International Monetary Fund. MA: Note.
- Eichenbaum, Martin, Sergio Rebelo, and Mathias Trabandt. 2020. "The Macroeconomics of Epidemics." NBER Working Paper 26882, National Bureau of Economic Research, Cambridge, MA. https://www.nber.org/papers/w26882.pdf.
- Fornaro, Luca, and Martin Wolf. March 2020. “Covid-19 Coronavirus and Macroeconomic Policy.” CEPR Technical Report, Center for Economic Policy and Research, Washington, DC.
- Guerrieri, Veronica, Guido Lorenzoni, Ludwig Straub, and Ivan Werning. 2020. “Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?” Becker Friedman Institute for Economics Working Paper No. 2020-35, University of Chicago, Illinois.
- Jordà, Òscar, Sanjay R. Singh, and Alan M. Taylor. 2020, "Longer-run Economic Consequences of Pandemics," NBER Working Paper 26934. National Bureau of Economic Research, Cambridge, MA:. https://www.nber.org/papers/w26934.pdf.
- Li, Nan and Mattia Coppo. 2020. "Severe Epidemics in Modern History: Growth, Debt and Civil Unrest", Special Series on COVID-19, International Monetary Fund. MA: Note.
- Melina, Giovanni., and Felipe Zanna. 2020. "DIGNAR-19: A Model for Macro Policy Assessments of the COVID-19 Pandemics in LIDCs." Special Series on COVID-19, International Monetary Fund. MA: Note.
- Narita, Futoshi 2020. "What we can learn from past health-related shocks identified by surges in Google online search volume." Special Series on COVID-19, International Monetary Fund. MA: Note.
- Engler P., N. Pouokam, D. Rodriguez-Guzman., and I. Yakadina. (2020). “the great lockdown: international risk sharing through trade and policy coordination.“ IMF Working Paper, 20/242 International Monetary Fund, Washington, DC.

### DSGE, macroeconomic modeling methods, and critiques
- Blanchard Oliver. 2018. “On the future of macroeconomic models.” Oxford Review of Economic Policy 34:1-2, 43-54.
- Christiano, L., Eichenbaum, M., and Mathias Trabandt. 2018. “On DSGE Models.” Journal of Economic Perspectives 32:3, 113-140.
- Del Negro Marco and Frank Schorfheide 2013. “DSGE Model-Based Forecasting”, Handbook of Economic Forecasting, Vol 2, Part A, Chapter 2, Elsevier.
- Lindé Jesper. 2018. “DSGE models: still useful in policy analysis?” Oxford Review of Economic Policy. 34:1-2, 269-286.
- Smets, Frank, and Rafael Wouters. 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach." American Economic Review 97 (3): 586–606.
- Christiano, L., Eichenbaum, M., and Mathias Trabandt. 2018. “On DSGE Models.” Journal of Economic Perspectives 32:3, 113-140. (duplicate listing in source material)

### Global and multi-country projection models; model documentation
- Carabenciov, I., I. Ermolaev, C. Freedman, M. Juillard, O. Kamenik, D. Korshunov, D. Laxton, and J. Laxton, J. 2008a. “A Small Multi-country Global Projection Model.” IMF Working Paper 08/279, International Monetary Fund, Washington, DC.
- Carabenciov, I., I. Ermolaev, C. Freedman, M. Juillard, O. Kamenik, D. Korshunov, D. Laxton, and J. Laxton. 2008b. “A Small Multi-country Global Projection Model with Financial-Real linkages and Oil Prices.” IMF Working Paper 08/280, International Monetary Fund, Washington, DC.
- Carabenciov, I., C. Freedman, R. Garcia-Saltos, O. Kamenik, D. Laxton, and P. Manchev. 2013. “GPM6: The Global Projection Model with 6 Regions.” IMF Working Paper 13/87, International Monetary Fund, Washington, DC.
- Laxton, D., S. Mursula, M. Kumhof, and D. Muir. 2010. “The Global Integrated Monetary and Fiscal Model (GIMF)—Theoretical Structure.” IMF Working Paper 10/34, International Monetary Fund, Washington, DC.
- Brubakk, L., T. A. Husebø, J. Maih, K. Olsen, and M. Østnor. 2006. "Finding NEMO: Documentation of the Norwegian Economy Model." Norges Bank Staff Memo 6/2006. memo-2006-06.pdf.
- Coats, W., D. Laxton, and D. Rose, eds. (2003). “The Czech National Bank’s Forecasting and Policy Analysis System. Prague: Czech National Bank.
- Fukac, Martin, and Adrian Pagan. 2010. "Structural Macro‐Econometric Modelling in a Policy Environment." Research Working Paper (RWP) 10–08. Federal Reserve Bank of Kansas City). https://www.kansascityfed.org/~/media/files/publicat/reswkpap/pdf/rwp10-08.pdf.

### Country-level models and fiscal/monetary policy analysis
- González, A., D. Rodríguez, Corrales J. S., Wills D., Angel J.P., Moreno N. and, J. Santaella 2021. "Assessing the macroeconomic impact of previous fiscal reforms using the Colombian Framework for Fiscal Economics and Evaluation," Forthcoming IMF working paper.
- González, A., A. Guarín, D. Rodríguez, and H. Vargas. 2020. "4GM: A New Model for Monetary Policy Analysis in Colombia," Banco de la República, Borradores de Economía, Bogota. https://repositorio.banrep.gov.co/bitstream/handle/20.500.12134/9812/be_1106.pdf.
- Leeper, Eric M., Todd B. Walker, and Shu-Chun S. Yang. 2010. "Government investment and Fiscal Stimulus." Journal of Monetary Economics. 57 (8): 1000–12.
- Faria e Castro, Miguel. March 2020. “Fiscal Policy during a Pandemic.” Working Paper 2020-006, Federal Reserve Bank of St. Louis.
- Melina, Giovanni., and Felipe Zanna. 2020. "DIGNAR-19: A Model for Macro Policy Assessments of the COVID-19 Pandemics in LIDCs." Special Series on COVID-19, International Monetary Fund. MA: Note.

### Empirical and thematic contributions related to trade, commodities, and risk sharing
- Fernández, A., A. González, and D. Rodríguez. 2018. "Sharing a Ride on the Commodities Rollercoaster: Common Factors in Business Cycles of Emerging Economies." Journal of International Economics 111: 99–121.
- Engler P., N. Pouokam, D. Rodriguez-Guzman., and I. Yakadina. (2020). “the great lockdown: international risk sharing through trade and policy coordination.“ IMF Working Paper, 20/242 International Monetary Fund, Washington, DC.
- World Bank. June 2020. Global Economic Prospects, (Box 3.2), World Bank, Washington, DC.

### Classic modeling and microfoundations references cited
- Rotemberg, Julio J. 1982. "Sticky Prices in the United States." Journal of Political Economy 90(6): 1187–1211.
- Smets, Frank, and Rafael Wouters. 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach." American Economic Review 97 (3): 586–606.
- Del Negro Marco and Frank Schorfheide 2013. “DSGE Model-Based Forecasting”, Handbook of Economic Forecasting, Vol 2, Part A, Chapter 2, Elsevier.

_*Compiled from TNM/21/XX content unit 049. Washington: Board of Governors of the Federal Reserve System._*

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_Source: https://www.imf.org/-/media/files/publications/tnm/2021/english/tnmea2021001.pdf_