## 1. Headline Inflation and Drivers

## Source details

**Canonical URL:** [1. Headline Inflation and Drivers](https://www.imf.org/-/media/files/publications/cr/2024/english/1gmbea2024002.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/cr/2024/english/1gmbea2024002.pdf.md)
- [Structured JSON version](/-/media/files/publications/cr/2024/english/1gmbea2024002.pdf.json)

---

### Overview
- Study period: 2014-2023 (econometric analyses use a range including 2011-2023 and 2014Q1-2023Q1).
- Main objective: investigate drivers of headline inflation and the degree of exchange rate pass-through (ERPT) in The Gambia.
- Key long-term drivers identified: global prices of commodities (food, oil and fertilizer), the exchange rate, and the domestic output gap.
- Short-run dynamics emphasize global food price movements and second-round effects from food prices and the output gap.
- Evidence of asymmetric ERPT; the size of currency depreciation matters for inflation dynamics.
- Monetary policy conclusion: rapid and bold adjustments in the monetary policy rate can tame inflation in the short run.

### Stylized facts and context for The Gambia
- The Gambia is a net importer of essential foods and energy.
- Weight of food items and non-alcoholic beverages in the CPI basket: around 50 percent.
- Observed co-movements (2011–2023):
  - Headline inflation co-moves with global food price inflation.
  - Headline inflation co-moves with global phosphate fertilizer price inflation.
  - Headline inflation co-moves with currency depreciation and with the domestic output gap.
- Inflation path and policy rate:
  - Inflation started to rise in Q1 2021; accelerated in Q2 2022 after the Russian war in Ukraine eruption in March 2022.
  - Central Bank of The Gambia policy rate kept at 10 percent from March 2020 until May 31, 2022, when raised to 11 percent.
  - Real policy rate fell into negative territory as of Q2 2022.
  - From June 2022 to June 2023, the real policy rate was on average negative 0.9 percent.

### Empirical analysis: methods
- Three modelling approaches:
  - Ordinary least squares (OLS) and quantile regressions using data 2011-2023.
  - Non-linear cointegration and error-correction modelling using NARDL (period 2014Q1-2023Q1).
  - Local projection models (Jordà, 2005) under three scenarios to trace dynamic cumulative responses of domestic prices to exchange-rate movements.

### Empirical analysis: OLS and quantile regression results (selected)
- Preferred OLS specification: Inflation = constant + a1*lagged inflation + a2*output gap + a3*global food inflation + a4*global (phosphate, potassium, and nitrogen) fertilizer inflation + a5*rate of change in the monetary policy rate + a6*squared rate of change in the monetary policy rate + a7*currency depreciation (y-o-y) + error term.
- Main OLS and quantile findings:
  - Inflation is highly persistent: first and fourth lags of inflation are highly significant; their sum not statistically different from unity (inertial factors).
  - Domestic output gap coefficient not significant in OLS, but quantile regression at the 80 percent quantile shows a positive and statistically significant coefficient at the 10 percent level—implying the output gap matters at high levels of inflation.
  - Currency depreciation and potassium fertilizer price inflation (lag one) and phosphate fertilizer price inflation (lag two) impact inflation positively and significantly.
  - Fertilizer nitrogen inflation (lag one) coefficient is significant with a negative sign in OLS but not significant in the 80 percent quantile regression.
  - Combined effect of rate of change of policy rate and its square is negative and statistically significant, suggesting sufficiently rapid adjustments in the nominal policy rate can be effective.
- Selected OLS coefficient excerpts (Models 1–6):
  - Inflation(t-1): 0.491***; 0.455***; 0.446***; 0.328**; 0.361***; 0.399***.
  - Inflation(t-4): 0.718***; 0.812***; 0.808***; 0.836***; 0.733***; 0.771***.
  - Growth of MPR: 0.011*; 0.011.; 0.014**; 0.009**; 0.009**.
  - Square of Growth of MPR: -0.026.; -0.027.; -0.036**; -0.033***; -0.032**.
  - Growth of Nominal XR(t-1): 0.005; 0.022*; 0.022*; 0.022*.
  - Growth of Global Food Prices: 0.077***; 0.075***; 0.076***.
  - Covid Dummy: -0.021**; -0.022**; -0.021**; -0.016**; -0.015***; -0.015***.
  - Sample sizes N: 43, 43, 42, 42, 37, 37. R^2 values: 0.918, 0.927, 0.927, 0.966, 0.982, 0.876.

### Empirical analysis: NARDL (non-linear cointegration and ECM) — selected results
- Stationarity: headline inflation, global food prices, the dalasi per US dollar exchange rate, and the domestic output gap are first-difference stationary (unit root test results).
  - ADF unit root tests (selected): Inflation level -0.14; First difference -6.71***. Global food price index level -0.90; First difference -5.38***. Exchange rate level -3.44*; First difference -8.86***. Output gap level -1.70; First difference -8.62***.
- Cointegration: non-linear cointegration between inflation and its three determinants confirmed at the 1 percent level over 2014Q1-2023Q1.
  - Bounds test (NARDL no imposed symmetry): F-PSS 7.17***; 95% lower bound 2.97; 95% upper bound 4.50; Cointegration: Yes.
- Long-run NARDL coefficients and interpretations:
  - Global food prices:
    - A 10 percent increase in global food prices leads to an increase of 0.8 percentage points in the quarterly rate of inflation (equivalent to 3.4 percentage points in the annualized rate of inflation).
  - Exchange rate (asymmetric effects):
    - Long-run coefficient for positive changes: 0.045 (significant at 5 percent).
    - Long-run coefficient for negative changes: -0.036 (not significant at 5 percent).
    - Interpretation: a 10 percent depreciation leads to a 0.45 percentage point increase in the quarterly inflation rate (i.e., 1.8 percentage points annualized); appreciation does not appear to reduce inflation.
  - Output gap (asymmetric effects):
    - Long-run coefficients: positive changes 0.064; negative changes 0.080.
- Parsimonious NARDL short-run estimation (selected):
  - ECT t-1: -1.176*** (standard error 0.148; t-Statistic -7.932; p-Value 0.000).
  - ∆(Ln FoodPI t): 0.106*** (standard error 0.015; t-Statistic 7.235; p-Value 0.000).
  - ∆(Ln FoodPI t-3): -0.080*** (standard error 0.017; t-Statistic -4.704; p-Value 0.000).
  - ∆(Output gap t-1): -0.088*** (standard error 0.017; t-Statistic -5.068; p-Value 0.000).
  - Constant: -0.443*** (standard error 0.056; t-Statistic -7.928; p-Value 0.000).
  - Model fit: R-squared 0.861; Adjusted R-squared 0.807; F-statistic 15.871; Durbin-Watson 1.908; Prob (F-statistic) 0.000.

### Local projection models and ERPT: main findings
- Baseline local projection results:
  - A one percentage point increase in the rate of depreciation of dalasi against the US dollar leads to an increase in inflation by 0.15 percentage points within the first year, and 0.24 percentage points after two years.
- Asymmetry and nonlinearity:
  - ERPT is asymmetric in The Gambia:
    - Reaching 0.3 on average twelve months after the shock during episodes of depreciation.
    - Reaching 0.4 two years after the shock during episodes of depreciation.
    - Prices remain muted in periods of currency appreciation.
  - Nonlinearity by depreciation size:
    - Small currency depreciations are almost inconsequential for inflation.
    - At higher levels of currency depreciation (above 15 percent) the resulting inflation is disproportionately larger:
      - First year inflation response: 0.46.
      - Second year inflation response: 0.36.
    - Larger currency depreciations present considerable risks of inflation de-anchoring, especially if the credibility of the CBG is perceived as weak.
- Robustness and diagnostics:
  - Local projection approach referenced: Jordà (2005); Stock and Watson (2007) and Auerbach and Gorodnichenko (2013).
  - Results justify the choice of four lags length for NARDL analysis.
  - Joint test on ∆MPR and ∆MPR^2: p-value of the F statistic is 0.1718 (greater than the 5 percent level), failing to reject the null that ∆MPR and ∆MPR^2 are jointly insignificant.

### Key findings (enumerated)
- Inflation persistence:
  - Lag structure indicates strong inertia; first and fourth lags significant with sum not different from unity.
- External drivers:
  - Global food prices have a decisive long-term and contemporaneous short-term role.
  - Fertilizer price inflation (potassium and phosphate at specific lags) raises domestic inflation.
- Exchange rate pass-through:
  - Evidence of asymmetric ERPT.
  - Long-run pass-through: positive changes coefficient 0.045; negative changes coefficient -0.036.
  - A 10 percent dalasi depreciation → 0.45 percentage point increase in quarterly inflation (1.8 percentage points annualized).
  - Exchange rate appreciation does not produce symmetric disinflationary effects.
- Output gap:
  - Long-run asymmetric effects: positive changes 0.064; negative changes 0.080.
  - Output gap matters more in high-inflation episodes (quantile regression evidence).
- Monetary policy effectiveness:
  - Combined (non-linear) short-run effect of changes in the policy rate suggests potential effectiveness if adjustments are rapid and bold (combined short-run effect = -1.4).
  - Real policy rate was on average negative 0.9 percent from June 2022 to June 2023, after policy rate increases were limited.

### Policy implications and recommendations (policy-relevant implications from the analysis)
- Monetary policy:
  - Implement rapid and bold increases in the nominal policy rate when faced with rising inflation to achieve a negative combined short-run effect on inflation (evidence supports potential effectiveness).
  - Avoid protracted inaction when inflation accelerates, since delayed and limited policy rate adjustments can lead to negative real policy rates (example: policy rate held at 10 percent until May 31, 2022).
- Exchange rate and external buffers:
  - Recognize asymmetric ERPT: large depreciations materially increase inflation, while appreciations do not symmetrically reduce inflation—policy should emphasize preventing large exchange rate depreciations.
  - Strengthen external buffers and policies that mitigate pass-through from global food and fertilizer price shocks.
- Fiscal and structural considerations:
  - Address fiscal imbalances and factors that can produce demand-pull inflation (fiscal dominance risks).
  - Consider measures to reduce dependence on imported food and fertilizer where feasible to lower vulnerability to global price shocks.
- Short-run preparedness:
  - Monitor global food and fertilizer price developments closely and prepare targeted short-term measures (subsidies, targeted transfers) to manage second-round effects and protect vulnerable households when food prices spike.

---

### Climate vulnerabilities and strategy (selected material)
- Observed climate trends and risks:
  - Average temperature in The Gambia has risen by 1.0°C over the past sixty years, an average rate of 0.19°C per decade.
  - IPCC (2022) estimates for West Africa: temperature may rise by 3–6 °C by the end of the 21st century and sea levels are anticipated to increase by 0.26–0.55 m even under low-emission scenario.
  - The Gambia’s coastal zone: 80 km of open ocean coast and 200 km sheltered coast; at risk of flooding and erosion, threatening Banjul and its port, groundwater resources and ecosystems.
  - The Gambia ranked 106th out of 191 countries on the Climate-driven INFORM Risk Indicator 2022.
- Natural disaster frequency and impacts:
  - Over the past three decades, at least one natural-disaster occurred approximately every two years; flooding accounts for more than half of the events.
  - The drought in 2012 affected 428,000 people (total population in 2012 reported as 2.06 million).
  - Storm in 2021 affected 16,849 people; flood in 2022 affected 17,201 people (EM-DAT database, 2023).
  - Cross-country evidence: GDP per capita can be 2-5 percent lower in the four years after large natural disasters; public debt is 6 percent of GDP higher in the three years after disasters (IMF, 2019).
  - Koks et al. (2019): The Gambia among top twenty countries with highest multi-hazard Expected Annual Damages (EAD) relative to GDP, above 0.2 percent of GDP annually.
  - Local projection regression: real GDP growth remains 2.0–3.1 percent lower than the pre-disaster level in the five years after natural disasters.
- Sectoral vulnerability and policy priorities:
  - Agriculture: about quarter of total output and about a half of total employment; largely rain-fed subsistence farming.
  - Cereal yields have declined over two decades.
  - Policy frameworks: National Climate Change Policy (NCCP, 2016); The Gambia 2050 Climate Vision (2021) targets net zero by 2050; Long-Term Climate-Neutral Development Strategy 2050 estimated financing need: 4 billion USD.
  - Adaptation priorities: land management, crop diversification, irrigation, early-warning systems, crop insurance, National Climate Fund, integrated coastal zone management.
- Climate financing:
  - Annual adaptation needs: 45 million USD versus aid flows received 16 million USD (Fiscal Monitor Oct 2020).
  - Selected climate financing announced 2022-2023:
    - Canada grant: Canada Dollar 20 million.
    - World Bank West Africa Coastal Area Management grant: USD 45 million.
    - French Development Agency grant: Euro 6.9 million.
    - World Bank/EIB co-financed electricity project: USD 27 million (solar plant and eight megawatts energy storage).

### Public finance and investment management for climate resilience
- Strong PFM can attract climate finance; quantified cross-country impacts (frontier improvements): boost annual adaptation funds by 9.2 percent (budget/financial management) and by 33.6 percent (public administration).
- The Gambia’s CPIA indicators in 2018: both assessed as 3.0 versus frontier peers’ scores 4.5 (budgetary and financial management) and 4 (public administration).
- Progress: new PFM Act; PIMA conducted in 2019; approval of a three-year public investment program (PIP) in 2022.
- Recommendation: conduct C-PIMA and integrate climate considerations into PFM/PIM processes to enhance access to, and efficiency of, climate-resilient investments.

---

### Gender, labor markets, and macroeconomic simulations (selected)
- Status of gender equality — key figures:
  - GII (2021): The Gambia scored 0.61; Sub-Sahara average: 0.57.
  - Female LFPR (2021): 48.9 percent; Male LFPR: 66.3 percent.
  - Informality (2022 LFS): 8 out of every 10 working women in informal employment.
  - Women account for less than 3 percent of enrolment in higher education.
  - Primary school completion rate for girls increased from 65 percent to 92 percent between 2010-2021; boys: 79 percent.
  - Access to finance (FinScope 2019): 2 percent of women have bank accounts; 8 percent of men have bank accounts.
  - Share of women in parliament: 8.6 percent; SSA average: 25.7 percent. Cabinet: 3 out of 22 ministers are women.
  - Women in managerial positions (2022 LFS): 36.1 percent.
  - Women Enterprise Fund (WEF) has provided support to 63,000 women.
- Distributional impacts of higher food costs on per-capita consumption (2020-2022), by quintile (In Percent):
  - Quintile-1 (extreme poor): Total population -1.37; Men -1.37; Women -1.36.
  - Quintile-2: Total population -1.06; Men -1.12; Women -1.00.
  - Quintile-3: Total population -0.60; Men -0.65; Women -0.55.
  - Quintile-4: Total population -0.16; Men -0.19; Women -0.13.
  - Quintile-5 (richest): Total population 0.85; Men 0.71; Women 1.00.
- Poverty and consumption regression highlights (selected coefficients):
  - Gender: Female — Absolute poverty -0.113***; Extreme poverty -0.091***; Food poverty -0.069***; Consumption 0.030***.
  - Area: Rural — Absolute poverty 0.723***; Extreme poverty 0.717***; Food poverty 0.207***; Consumption -0.377***.
  - No access to Finance — Absolute poverty 0.801***; Extreme poverty 0.875***; Food poverty 0.464***; Consumption -0.357***.
- Macroeconomic simulations and gains from closing labor market gender gaps:
  - Simulation A (equalizing FLFP): Increase in FLFP 20 ppts; GDP 11 percent increase; GINI reduces by 4.1 points to 34.7; Government revenues 10 percent increase.
  - Simulation B (equalizing returns from experience): Increase in FLFP 7 ppt; Women’s average earnings +11 percent; GDP 10.5 percent increase; Government revenues 8.5 percent increase.
  - Comparative figure values:
    - Change in female labor force participation: Closing FLFP gap: 20.7; Equal return from experience: 11.2.
    - GDP gains after one generation: Closing FLFP gap: 10; Equal return from experience: 10.5.
    - Government revenues grow: Closing FLFP gap: 10; Equal return from experience: 8.5.
    - Gini (points difference): Closing FLFP gap: -4.1; Equal return from experience: -0.1.
- Recommended policy actions (prioritized):
  - Harmonize and standardize laws; revise discretionary laws in family, inheritance, and property rights.
  - Strengthen enforcement and awareness campaigns; train judges, law enforcement, and Cadis courts officers.
  - Leverage gender budgeting; fund women’s health, childcare, and education (including TVET).
  - Expand and scale Women Enterprise Fund; facilitate formalization and support for small-scale farmers; leverage digitalization for MSMEs.
  - Implement National Financial Inclusion plan focused on youth and women.
  - Expand social safety nets via a reliable and dynamic social registry; invest in resilient agricultural production; consider land reform.

*Source: IMF staff estimates and The Gambia country chapter content as provided in the source PDF.*

### 1. Headline Inflation and Drivers ________________________________________________________ 5

### THE GAMBIA: DOMESTIC AND EXTERNAL DRIVERS OF INFLATION

### Overview
- Study period: 2014-2023 (econometric analyses use a range including 2011-2023 and 2014Q1-2023Q1).
- Main objective: investigate drivers of headline inflation and the degree of exchange rate pass-through (ERPT) in The Gambia.
- Key long-term drivers identified: global prices of commodities (food, oil and fertilizer), the exchange rate, and the domestic output gap.
- Short-run dynamics emphasize global food price movements and second-round effects from food prices and the output gap.
- Evidence of asymmetric ERPT; the size of currency depreciation matters for inflation dynamics.
- Monetary policy conclusion: rapid and bold adjustments in the monetary policy rate can tame inflation in the short run.

### Literature Review (summarized theoretical context)
- Demand-pull factors:
  - Fiscal-monetary doctrines (fiscal dominance) and the “fiscal theory of the price level.”
  - Output gap / Phillips curve framework: positive (negative) output gaps imply rising (falling) inflation.
- External factors:
  - Exchange rate movements, prices of imported food and energy, global output gap, remittance inflows.
  - Balance of payments view: currency depreciation raises domestic prices via first-round (import price) and second-round (costs, expectations) effects.
  - Global food prices particularly influential in EMDEs due to large CPI food weights.
- Cost-push / inertial factors:
  - Exogenous domestic food price and wage shocks.
  - Backward-looking indexation mechanisms increasing inflation persistence.
- Empirical background:
  - Prior evidence finds LICs’ core inflation strongly susceptible to external shocks; ERPT to core inflation in LICs is larger than in other country groups.

### Stylized Facts for The Gambia
- The Gambia is a net importer of essential foods and energy.
- Weight of food items and non-alcoholic beverages in the CPI basket: around 50 percent.
- Observed co-movements (2011–2023 figures reported in figures):
  - Headline inflation co-moves with global food price inflation.
  - Headline inflation co-moves with global phosphate fertilizer price inflation.
  - Headline inflation co-moves with currency depreciation and with the domestic output gap.
- Inflation path and policy rate:
  - Inflation started to rise in Q1 2021; accelerated in Q2 2022 after the Russian war in Ukraine eruption in March 2022.
  - Central Bank of The Gambia policy rate kept at 10 percent from March 2020 until May 31, 2022, when raised to 11 percent.
  - Real policy rate fell into negative territory as of Q2 2022.
  - From June 2022 to June 2023, the real policy rate was on average negative 0.9 percent.

### Empirical Analysis: Methods
- Three modeling approaches:
  - Ordinary least squares (OLS) and quantile regressions using data 2011-2023.
  - Non-linear cointegration and error-correction modelling using NARDL (period 2014Q1-2023Q1).
  - Local projection models (Jordà, 2005) under three scenarios to trace dynamic cumulative responses of domestic prices to exchange-rate movements.

### Empirical Analysis: OLS and Quantile Results
- Preferred OLS specification: Inflation = constant + a1*lagged inflation + a2*output gap + a3*global food inflation + a4*global (phosphate, potassium, and nitrogen) fertilizer inflation + a5*rate of change in the monetary policy rate + a6*squared rate of change in the monetary policy rate + a7*currency depreciation (y-o-y) + error term.
- Main OLS findings:
  - Inflation is highly persistent: first and fourth lags of inflation are highly significant; their sum not statistically different from unity (inertial factors).
  - Domestic output gap coefficient not significant in OLS, but quantile regression at the 80 percent quantile shows a positive and statistically significant coefficient at the 10 percent level—implying the output gap matters at high levels of inflation.
  - Currency depreciation and potassium fertilizer price inflation (lag one) and phosphate fertilizer price inflation (lag two) impact inflation positively and significantly.
  - Fertilizer nitrogen inflation (lag one) coefficient is significant with a negative sign in OLS but not significant in the 80 percent quantile regression.
  - Combined effect of rate of change of policy rate and its square is negative and statistically significant, suggesting sufficiently rapid adjustments in the nominal policy rate can be effective.

### Empirical Analysis: NARDL (Non-linear Cointegration and ECM)
- Stationarity: headline inflation, global food prices, the dalasi per US dollar exchange rate, and the domestic output gap are first-difference stationary (unit root test results in Table 2).
- Cointegration: non-linear cointegration between inflation and its three determinants confirmed at the 1 percent level over 2014Q1-2023Q1 (Table 3).
- Long-run NARDL long-run coefficients and interpretations:
  - Global food prices:
    - A 10 percent increase in global food prices leads to an increase of 0.8 percentage points in the quarterly rate of inflation (equivalent to 3.4 percentage points in the annualized rate of inflation).
  - Exchange rate (asymmetric effects):
    - Long-run coefficient for positive changes: 0.045 (significant at 5 percent).
    - Long-run coefficient for negative changes: -0.036 (not significant at 5 percent).
    - Interpretation: a 10 percent depreciation leads to a 0.45 percentage point increase in the quarterly inflation rate (i.e., 1.8 percentage points annualized); appreciation does not appear to reduce inflation.
  - Output gap (asymmetric effects):
    - Long-run coefficients: positive changes 0.064; negative changes 0.080.
- Short-run dynamics from the error-correction model (Table 5):
  - Error-correction coefficient ECT(-1) = -1.176 (negative and very significant), confirming cointegration.
  - Contemporaneous short-run driver: change in (natural logarithm of) global food prices only.
    - Short-run impact of contemporaneous global food price change: 0.106 (stronger than the implied long-run per-quarter value).
  - Lag effects:
    - Three-quarter lagged changes in global food prices and in the output gap, and one- to two-quarters lagged changes in the output gap, affect short-run dynamics significantly but with a negative sign, interpreted as second-round effects reflecting wage and price adjustments and inflationary expectations.
  - Monetary policy variables in ECM:
    - Individual effects of ∆MPR and ∆MPR^2 are positive (0.84) and negative (-2.26), respectively, and they are not significant individually.
    - Short-run combined effect is negative (-1.4), suggesting potential effectiveness of rapid and bold policy rate adjustments to tame inflation.

### Key Findings (enumerated)
- Inflation persistence:
  - Lag structure indicates strong inertia; first and fourth lags significant with sum not different from unity.
- External drivers:
  - Global food prices have a decisive long-term and contemporaneous short-term role.
  - Fertilizer price inflation (potassium and phosphate at specific lags) raises domestic inflation.
- Exchange rate pass-through:
  - Evidence of asymmetric ERPT.
  - Long-run pass-through: positive changes coefficient 0.045; negative changes coefficient -0.036.
  - A 10 percent dalasi depreciation → 0.45 percentage point increase in quarterly inflation (1.8 percentage points annualized).
  - Exchange rate appreciation does not produce symmetric disinflationary effects.
- Output gap:
  - Long-run asymmetric effects: positive changes 0.064; negative changes 0.080.
  - Output gap matters more in high-inflation episodes (quantile regression evidence).
- Monetary policy effectiveness:
  - Combined (non-linear) short-run effect of changes in the policy rate suggests potential effectiveness if adjustments are rapid and bold (combined short-run effect = -1.4).
  - Real policy rate was on average negative 0.9 percent from June 2022 to June 2023, after policy rate increases were limited.

### Policy Implications and Recommendations (inferred from analysis)
- Monetary policy:
  - Implement rapid and bold increases in the nominal policy rate when faced with rising inflation to achieve a negative combined short-run effect on inflation (evidence supports potential effectiveness).
  - Avoid protracted inaction when inflation accelerates, since delayed and limited policy rate adjustments can lead to negative real policy rates (example: policy rate held at 10 percent until May 31, 2022).
- Exchange rate and external buffers:
  - Recognize asymmetric ERPT: large depreciations materially increase inflation, while appreciations do not symmetrically reduce inflation—policy should emphasize preventing large exchange rate depreciations.
  - Strengthen external buffers and policies that mitigate pass-through from global food and fertilizer price shocks.
- Fiscal and structural considerations:
  - Address fiscal imbalances and factors that can produce demand-pull inflation (fiscal dominance risks).
  - Consider measures to reduce dependence on imported food and fertilizer where feasible to lower vulnerability to global price shocks.
- Short-run preparedness:
  - Monitor global food and fertilizer price developments closely and prepare targeted short-term measures (subsidies, targeted transfers) to manage second-round effects and protect vulnerable households when food prices spike.

*Prepared by Jean-Claude Nachega, Glen Kwende, Laurent Kemoe, and Fidel Márquez Barroeta. Analysis covers drivers of inflation and ERPT in The Gambia over 2014-2023, with supporting econometric evidence.*

### 11.      Local projection models confirm evidence of asymmetric ERPT, and the size of the

### 11. Local projection models confirm evidence of asymmetric ERPT, and the size of the currency depreciation matters for inflation dynamics in The Gambia

### Exchange Rate Pass-Through (ERPT) to Inflation: main findings
- Under the baseline model, a one percentage point increase in the rate of depreciation of dalasi against the US dollar leads to an increase in inflation by 0.15 percentage points within the first year, and 0.24 percentage points after two years.
- ERPT is asymmetric in The Gambia:
  - Reaching 0.3 on average twelve months after the shock during episodes of depreciation.
  - Reaching 0.4 two years after the shock during episodes of depreciation.
  - Prices remain muted in periods of currency appreciation, implying that prices may not come down when the dalasi strengthens after periods of depreciation.
- Nonlinearity in the exchange rate–inflation relationship:
  - Small currency depreciations are almost inconsequential for inflation.
  - At higher levels of currency depreciation (i.e., depreciation of the dalasi vis-à-vis the US dollar of above 15 percent) the resulting inflation is disproportionately larger:
    - First year inflation response: 0.46.
    - Second year inflation response: 0.36.
  - Larger currency depreciations present considerable risks of inflation de-anchoring, especially if the credibility of the CBG is perceived as weak.

### Robustness, model choices, and diagnostics
- Local projection approach referenced: Jordà (2005); Stock and Watson (2007) and Auerbach and Gorodnichenko (2013) noted as flexible alternatives to ARDL specifications.
- The results justify the choice of four lags length for NARDL analysis.
- Joint test on ∆MPR and ∆MPR^2: p-value of the F statistic is 0.1718 (which is more than the 5 percent level of significance), leading to failure to reject the null hypothesis that ∆MPR and ∆MPR^2 are jointly insignificant.

### Key regression and cointegration results (selected)
- OLS regressions of inflation and determinants (selected coefficients and significance):
  - Inflation(t-1): 0.491*** (Model 1), 0.455*** (Model 2), 0.446*** (Model 3), 0.328** (Model 4), 0.361*** (Model 5), 0.399*** (Model 6).
  - Inflation(t-4): 0.718*** (Model 1), 0.812*** (Model 2), 0.808*** (Model 3), 0.836*** (Model 4), 0.733*** (Model 5), 0.771*** (Model 6).
  - Growth of MPR: 0.011* (Model 1), 0.011. (Model 2), 0.014** (Model 3), 0.009** (Model 4), 0.009** (Model 5).
  - Square of Growth of MPR: -0.026. (Model 1), -0.027. (Model 2), -0.036** (Model 3), -0.033*** (Model 4), -0.032** (Model 5).
  - Growth of Nominal XR(t-1): 0.005 (Model 1), 0.022* (Model 2), 0.022* (Model 3), 0.022* (Model 4).
  - Growth of Global Food Prices: 0.077*** (Model 3), 0.075*** (Model 4), 0.076*** (Model 5).
  - Covid Dummy: -0.021** (Model 1), -0.022** (Model 2), -0.021** (Model 3), -0.016** (Model 4), -0.015*** (Model 5), -0.015*** (Model 6).
  - Sample sizes: N 43, 43, 42, 42, 37, 37 across Models 1–6.
  - R^2 values: 0.918, 0.927, 0.927, 0.966, 0.982, 0.876 for Models 1–6 respectively.
- ADF unit root tests (selected):
  - Inflation: Level -0.14; First difference -6.71***.
  - Global food price index: Level -0.90; First difference -5.38***.
  - Exchange rate level: Level -3.44*; First difference -8.86***.
  - Output gap: Level -1.70; First difference -8.62***.
- Bounds test for cointegration in non-linear specification (Table 3):
  - NARDL with no imposed symmetry for food prices, exch. rate and the output gap: F-PSS 7.17***; 95% lower bound 2.97; 95% upper bound 4.50; 99% lower bound 4.27; 99% upper bound 6.21; Cointegration result: Yes.
  - NARDL with imposed long-run symmetry for food prices: F-PSS 8.21***; 95% lower bound 3.13; 95% upper bound 4.61; 99% lower bound 4.54; 99% upper bound 6.37; Cointegration result: Yes.
- NARDL long-run cointegrating vector (selected coefficients from Table 4 / Table 5):
  - Ln FoodPI: 0.0836340.00008.306573 (presented as coefficient, p-Value, t-Statistic in source).
  - Ln EXR(-1)+ : 0.0447670.01642.554707.
  - Ln EXR(-1)- : -0.0359280.0518-2.031153.
  - Output gap + : 0.0639660.03212.255042.
  - Output gap - : 0.0796190.01392.624906.
- Parsimonious NARDL short-run estimation (selected from Table 5):
  - ECT t-1: -1.176*** (standard error 0.148; t-Statistic -7.932; p-Value 0.000).
  - ∆(Ln FoodPI t): 0.106*** (standard error 0.015; t-Statistic 7.235; p-Value 0.000).
  - ∆(Ln FoodPI t-1): -0.0186 (standard error 0.015; t-Statistic -1.221; p-Value 0.235).
  - ∆(Ln FoodPI t-3): -0.080*** (standard error 0.017; t-Statistic -4.704; p-Value 0.000).
  - ∆(Output gap t-1): -0.088*** (standard error 0.017; t-Statistic -5.068; p-Value 0.000).
  - Constant: -0.443*** (standard error 0.056; t-Statistic -7.928; p-Value 0.000).
  - Model fit and diagnostics: R-squared 0.861; Adjusted R-squared 0.807; S.D. dependent var 0.008; S.E. of regression 0.004; Akaike info criterion -8.225; Schwarz criterion -7.772; Log likelihood 145.716; Hannan-Quinn criterion -8.073; F-statistic 15.871; Durbin-Watson statistic 1.908; Prob (F-statistic) 0.000.

### Policy-relevant implications from the analysis
- Exchange rate management and monetary credibility matter:
  - Given asymmetric ERPT and nonlinear responses, large depreciations (above 15 percent) risk large and persistent inflationary effects (0.46 in the first year; 0.36 in the second year).
  - Strengthening the credibility of the Central Bank of The Gambia (CBG) is important to reduce risks of inflation de-anchoring following large depreciations.
- Inflation drivers beyond exchange rate:
  - Global food prices have strong and significant short-run effects on inflation (e.g., ∆(Ln FoodPI t) coefficient 0.106*** in the parsimonious NARDL).
  - Monetary policy growth terms (Growth of MPR and its square) show nonlinear effects in OLS regressions, suggesting careful calibration of policy rate changes.

### Climate vulnerabilities and strategy (selected material from adjacent chapter content)
- Climate change vulnerabilities and impacts:
  - Average temperature in The Gambia has risen by 1.0°C over the past sixty years, an average rate of 0.19°C per decade.
  - IPCC (2022) estimates for West Africa: temperature may rise by 3–6 °C by the end of the 21st century and sea levels are anticipated to increase by 0.26–0.55 m even under low-emission scenario.
  - The Gambia’s coastal zone: 80 km of open ocean coast and 200 km sheltered coast; at risk of flooding and erosion, threatening Banjul and its port, groundwater resources and ecosystems.
  - The Gambia is ranked 106th out of 191 countries with the middle-ranged risk according to Climate-driven INFORM Risk Indicator 2022.
- Natural disaster frequency and impacts:
  - Over the past three decades, there has been at least one natural-disaster (flooding, storm, drought) striking approximately every two years; flooding accounts for more than half of the events.
  - The drought in 2012 affected 428,000 people (one out of five of the total population in 2012 reported as 2.06 million).
  - The storm in 2021 affected 16,849 people; the flood in 2022 affected 17,201 people (EM-DAT database, 2023).
  - Cross-country evidence: GDP per capita can be 2-5 percent lower in the four years after large natural disasters; public debt is 6 percent of GDP higher in the three years after disasters (IMF, 2019). Cheng and Han (2022) estimate flooding damage to infrastructure can reach 3.8 percent of GDP when the probability of flooding is one third per year. The Gambia’s probability of flooding in the past three decades is higher than one half.
  - Koks et al. (2019) recognize The Gambia among the top twenty countries with the highest multi-hazard Expected Annual Damages (EAD) relative to GDP, attributable to road and railway exposure, at above 0.2 percent of GDP annually.
  - Local projection regression: real GDP growth remains 2.0–3.1 percent lower than the pre-disaster level in the five years after natural disasters.
- Sectoral vulnerability and policies:
  - Agriculture covers about quarter of total output and about a half of total employment; largely rain-fed subsistence farming.
  - Cereal yields in The Gambia have continuously declined over the past two decades, while Western and Central African countries’ yields remained steady/slightly increased.
  - Policy frameworks: National Climate Change Policy (NCCP, 2016) aims to mainstream climate change into planning by 2025; The Gambia 2050 Climate Vision (2021) targets net zero carbon emissions by 2050 with four strategic axes: 1) Climate-resilient food and landscapes, 2) Low emissions and resilient economy, 3) Climate-resilient people, 4) Climate-aware Integrated Coastal Zone Management.
  - Strengthening adaptive capacity requires improvements in land management, crop diversification, and irrigation systems.

*Source: IMF staff estimates and The Gambia country chapter content as provided in the source PDF.*

### 7.      The Gambia has put climate change at the center of its sustainable development

### 7.      The Gambia has put climate change at the center of its sustainable development

### NDCs, long-term strategy, and national planning
- The Gambia’s second National Determined Contribution (NDC2) submitted in 2021 is assessed by the Climate Action Tracker as an overall almost sufficient, with policies and action against its fair share as 1.5°C compatible.
- NDC2 mitigation target: 49.7 percent by 2030, compared to the baseline emission expected to increase from 4,935 GgCO2e in 2020 to 6,617 GgCO2e in 2030.
- NDC2 sectoral coverage: Agriculture, Forestry and Other Land Use (AFOLU), Industrial Processes and Product Use (IPPU), Energy, Transport and Waste. NDC2 covers the entire AFOLU sector (in line with the 2006 IPCC guidelines); NDC1 (2016) addressed only agricultural emissions. The waste sector in NDC2 includes emissions for both solid waste and wastewater; NDC1 did not include wastewater emissions.
- Long-Term Climate-Neutral Development Strategy 2050 (LTS):
  - Designed to achieve the 2050 Climate Vision and NDC commitments.
  - Estimated financing need: 4 billion USD financing supports.
  - Status: at the stage of detailed cost estimations.
  - Recommendation: include transparent quantifiable targets for switching the LULUCF sector from a net carbon source to a net carbon sink by 2050 or extend coverage of GHG emissions from the current 81 to 95 percent.
- National Development Plan 2023-2027:
  - Climate resilience is a pillar; aims include sustainable environmental and natural resources management, enhanced climate action, and disaster risk reduction through seven program priorities (e.g., AFOLU; sustainable waste management; coastal resilience; hazardous chemical and pesticides management; greening energy and transport; integrated water resources management; disaster risk reduction).
  - Coastal resilience interventions: nature-based solutions (re-vegetation), technical advice to reduce coastal hazard risks, creating natural sinks by avoiding infrastructural development within adjacent wetlands, finalizing the Integrated Coastal Zone Management (ICZM) Bill and Strategy.
  - Disaster risk management measures: urban flood risk management, raising risk awareness, preventative measures, enhancing risk financing via an emergency relief fund, developing policy framework to support insurance schemes, Weather Index Insurance (WII) for climate-related hazards.

### Emissions profile and mitigation opportunities
- The Gambia is a small emitter, contributing less than 0.01 percent to the global CO2e emissions.
- Drivers of emissions increase over the last two decades: primarily population growth and more recently carbon intensity; energy intensity has remained broadly stable.
- Sectoral shares:
  - Agricultural sector: over 40 percent of total emissions excluding LULUCF, with livestock as a major contributor.
  - LULUCF: contributed to almost one fifth of the country’s total emissions in 2019.
- Energy and renewables:
  - The Gambia is highly dependent on fossil fuel imports for energy supply, exposing it to oil market disruptions and stranded-asset risks from potential domestic oil discovery.
  - Renewable capacity pipeline: total of 170 MW in solar PV projects for 2021-2025, partially financed by the World Bank and the European Investment Bank.
- Policy measures:
  - Fossil fuel subsidy reforms recommended to achieve a greener economy and enhance revenue mobility.
  - Initial reforms: process initiated to allow full pass-through of fuel prices; analysis of automatic price mechanism conducted with IMF technical assistance to move to automatic price mechanism in the long-term.
  - Electricity tariff: increased by 30 percent in April 2023 to be more cost reflective and reduced indirect subsidies needed by NAWEC.
- Co-benefits of mitigation: increased renewable generation could improve energy security, facilitate access to electricity and clean fuels for cooking, and reduce air pollution.

### Adaptation needs and priorities
- The Gambia initiated updating its 2007 National Adaptation Plan (NAP) in 2015 with UNDP funding; a NAP roadmap covered a two-year implementation period to address capacity and capability gaps across policy planning, review, development, and outreach.
- Strategic Program for Climate Resilience (SPCR) (2017) focuses on:
  - enabling environment for climate resilience;
  - climate-resilient land use mapping, planning and information systems;
  - climate-resilient infrastructure, services and energy systems;
  - integrated approaches to build rural climate resilience.
- Sectors identified as particularly vulnerable: agriculture, water and sanitation, energy, and roads.
- Urgent adaptation actions recommended:
  - Improve regulations to restrict agriculture and livestock grazing activities to enhance land cover and water retention.
  - Strengthen early-warning and predictive forecasting capabilities.
  - Increase crop diversification and rotation; switch to drought-tolerant crop and animal species.
  - Implement water harvesting and retention, improved irrigation systems.
  - Introduce crop insurance policies and establish a National Climate Fund.
  - Engage local authorities to design adaptation strategies aligned with local requirements.
- Agricultural adaptation:
  - Climate-smart agriculture practices exist among smallholder farmers but overall adaptation capacity remains relatively limited.
  - Scaling up practices requires more and better-structured support and investment, and improved efficiency of support delivery.
  - Progress on SDGs (decent work, quality education, access to affordable and clean energy) can reduce pressure on natural resources (e.g., firewood use for cooking).
- Additional note: central bank has initiated development of a micro insurance program to assist farmers with crop failure due to natural disasters.

### Climate financing: gaps and recent commitments
- International financing aid is critical to achieve mitigation and adaptation goals; multilateral and bilateral donors support renewable energy, marine protected areas, coastal area management, etc.
- Financing gap: The Gambia’s annual adaptation needs are three times aid flows received: 45 million USD versus 16 million USD (Fiscal Monitor Oct 2020).
- Global initiatives: IMF established the Resilience and Sustainability Trust (RST) in April 2022 to provide long-term financing supporting policy reforms that reduce macro-critical risks associated with climate change and pandemic preparedness.
- Selected climate financing announced in 2022-2023 (Table 1):
  - Grant from the Government of Canada on climate related problems: Canada Dollar 20 million
  - Grant from the West Africa Coastal Area Management funded by the World Bank: USD 45 million
  - Grant from the French Development Agency to support five marine protected areas and the communities around them: Euro 6.9 million
  - Grant from the electricity restoration and modernization project co-financed by the World Bank and the European Investment Bank to build the solar plant and an eight megawatts energy storage system: USD 27 million

### Public Finance Management (PFM) and Public Investment Management (PIM)
- PFM and climate finance:
  - Strong PFM can attract climate finance aids.
  - Evidence: improving the quality of budget and financial management and public administration (CPIA) significantly enhances the likelihood and amount of adaptation aid received.
  - Quantified impacts (across countries): increasing quality of budget and financial management to the frontier peer level could boost annual adaptation funds by 9.2 percent; increasing quality of public administration to the frontier could boost funds by 33.6 percent.
  - The Gambia’s CPIA indicators: both assessed as 3.0 in 2018 compared to frontier peers’ scores of 4.5 (quality of budgetary and financial management) and 4 (quality of public administration).
  - IMF (2021a) highlights that compliance with key PFM requirements (effective internal and external audit functions, robust control frameworks, effective procurement processes) supports access to global climate funds.
  - The Gambia’s response: new PFM Act intended to allow better access to global climate funds.
- Public Investment Management:
  - A Public Investment Management Assessment (PIMA) was conducted in 2019 with IMF assistance.
  - Progress during the Extended Credit Facility (ECF) program 2020-2023 includes use of an investment selection tool under The Gambia Strategic Review Board (GSRB) and approval of a three-year public investment program (PIP) in 2022 for selected priority sectors (health, education, agriculture, infrastructure, energy, and environment).
  - Climate-PIMA (C-PIMA): adds climate-responsive dimensions to PIMA to assess capacity to manage climate-related infrastructure. Key institutions for climate-resilient infrastructure: climate-aware planning, coordination between entities, project appraisal and selection, budgeting and portfolio management, risk management; cross-cutting issues: legal and regulatory framework, information systems, government staff capacity.
  - Recommendation: conduct C-PIMA and integrate climate considerations into PFM processes, procedures and tools to enhance attractiveness and efficiency of resilient public investments.

### Conclusion and policy implications
- Climate-driven risk: The Gambia is in the mid-range of countries in terms of climate-driven risk, but natural disasters can have persistent and substantial impacts on affected populations and economic losses; agriculture is the most vulnerable sector.
- Policy priorities:
  - Mitigation: increase renewable energy generation to improve energy security and reduce emissions; pursue fossil fuel subsidy reforms to transition to a greener economy and improve revenue mobility.
  - Adaptation: urgent measures to strengthen land management, early-warning systems, crop diversification, drought-tolerant species, water management, crop insurance, and a National Climate Fund; engage local authorities to tailor adaptation strategies.
  - Finance: strengthen PFM, PIM, and Climate PIM capabilities to attract larger climate financing flows and to deploy funds effectively toward net-zero by 2050 and enhanced resilience.
- Diagnostic work: broad climate-related diagnostic assessments are needed to identify critical policy, legal, data, and institutional gaps to guide effective reform measures and use of climate-resilience financing (e.g., Resilience and Sustainability Facility).

*Source: 7. The Gambia has put climate change at the center of its sustainable development — IMF country chapter content.*

### 1.      There is a growing literature on the positive impact of reducing gender inequality on

### 1.      There is a growing literature on the positive impact of reducing gender inequality on 

### Literature evidence on gender equality and development
- Disparities in female education have negative impact on economic growth (Barro and Sala-i-Martin, 1991).
- Women's participation in the labor force has a strong impact on economic growth; women's education is an important factor to increasing their labor participation (Mehrunisa, M. et al 2016).
- Gender gaps contribute to instability and fragility, and poor governance (Caprioli, 2005 and Branisa and others, 2013).
- Gender equality is associated with better macroeconomic outcomes including higher GDP, greater productivity, lower income inequality, and faster economic growth (IMF 2015, Gonzales and others 2015; Sever and al 2022).
- The 2012 World Development Report: "gender equality is smart economics, and reforming laws for gender equality facilitates changes in social norms and actions that result not only in women's empowerment, but also in more resilient economies and stable societies”.

### Status of gender equality in The Gambia — key facts and figures
- GII (2021): The Gambia scored 0.61; Sub-Sahara average: 0.57.
- Female labor force participation rate (LFPR, 2021): 48.9 percent; Male LFPR: 66.3 percent.
- Informality (2022 LFS): 8 out of every 10 working women work in the informal sector or are engaged in informal employment.
- Higher education: Women account for less than 3 percent of enrolment in higher education.
- Teacher absenteeism: 12-30 percent.
- Primary school completion rate for girls: increased from 65 percent to 92 percent between 2010-2021; boys: 79 percent.
- Health and protection: health outcomes remain poor; protection against gender based violence limited by cultural factors and weak enforcement.
- Access to finance (FinScope 2019): 2 percent of women have bank accounts; 8 percent of men have bank accounts.
- Political and managerial representation:
  - Share of women in parliament: 8.6 percent; SSA average: 25.7 percent.
  - Cabinet: 3 out of 22 ministers are women.
  - Regional governors or heads of SOEs: none are women.
  - Women in managerial positions (2022 LFS): 36.1 percent.
- Women Enterprise Fund (WEF): has provided support to 63,000 women across the country.

### Impact of shocks and the high cost of living — gender perspective
- Pandemic (lockdown): disproportionately affected women in informal employment; more than 9 in every 10 people reported a decrease in income between March and August 2020.
- Food insecurity: number of food insecure households between 2019 and 2023 increased by more than three folds.
- Analysis approach: household consumption per capita used (individual consumption data limited); disaggregated food and non-food inflation comparisons.

Key quantified impacts of higher food cost on per-capita consumption (2020-2022), by quintile (In Percent):
- Quintile-1 (extreme poor): Total population -1.37
  - Men -1.37
  - Women -1.36
- Quintile-2: Total population -1.06
  - Men -1.12
  - Women -1.00
- Quintile-3: Total population -0.60
  - Men -0.65
  - Women -0.55
- Quintile-4: Total population -0.16
  - Men -0.19
  - Women -0.13
- Quintile-5 (richest): Total population 0.85
  - Men 0.71
  - Women 1.00

Additional distributional findings:
- Differences between men and women in first four quintiles: between 0.01 and 0.12 ppt.
- In the fifth quintile, women recorded a higher increase in consumption of about 0.29 percentage point.
- The Gini coefficient deteriorated by 1.3 percent overall; deterioration by gender: 1.4 percent for women and 1.1 percent for men.
- Women most adversely affected: those in rural areas, poor remote municipalities, and married in polygamous relations.

### Determinants of poverty and consumption (selected regression coefficients from Table 2)
- Gender: Female
  - Absolute poverty: -0.113***
  - Extreme poverty: -0.091***
  - Food poverty: -0.069***
  - Consumption: 0.030***
- Area: Rural
  - Absolute poverty: 0.723***
  - Extreme poverty: 0.717***
  - Food poverty: 0.207***
  - Consumption: -0.377***
- Female X Rural interaction
  - Absolute poverty: 0.133***
  - Extreme poverty: 0.072***
  - Food poverty: 0.065***
  - Consumption: -0.013***
- Marital status (2 - Married)
  - Absolute poverty: -0.046***
  - Extreme poverty: -0.111***
  - Food poverty: -0.061***
  - Consumption: 0.006***
- Labor force status (3 - Outside Labor Force)
  - Absolute poverty: 0.103***
  - Extreme poverty: 0.070***
  - Food poverty: 0.091***
  - Consumption: -0.082***
- Education
  - Absolute poverty: -0.033***
  - Extreme poverty: -0.012***
  - Food poverty: -0.027***
  - Consumption: 0.022***
- Household Head: Female
  - Absolute poverty: -0.266***
  - Extreme poverty: -0.356***
  - Food poverty: -0.124***
  - Consumption: 0.148***
- No access to Finance
  - Absolute poverty: 0.801***
  - Extreme poverty: 0.875***
  - Food poverty: 0.464***
  - Consumption: -0.357***
- Has experienced a climate shock
  - Absolute poverty: 0.004
  - Extreme poverty: -0.061***
  - Food poverty: 0.113***
  - Consumption: -0.038***

(Notes: Standard errors in parentheses in original table; source: Staff Calculation using the 2020 IHS.)

### Macroeconomic simulations and gains from closing labor market gender gaps
Model setup:
- General equilibrium model calibrated to The Gambia using 2018 and 2022 Labor Force Surveys and the 2020-2021 Integrated Household Survey.
- Two simulations presented: (i) equalizing female and male labor force participation rates (FLFP); (ii) equalizing males and females returns from experience.

Simulation A — Equalizing female and male labor force participation:
- Mechanism: reduce family’s extra utility cost when woman works to zero (no change in gender salary gaps or returns from education/experience).
- Increase in FLFP: 20 ppts.
- GDP: 11 percent increase.
- GINI index: reduces by 4.1 points, to 34.7.
- Government revenues: 10 percent increase (higher VAT, income, and corporate tax collections).
- Note: gains could be larger if salary and returns gaps also addressed.

Simulation B — Equalizing gains from experience:
- Empirical basis: 2018 LFS shows males receive around 4 percent extra earnings per extra year of experience in 30s-40s; females near 0 percent.
- Increase in FLFP: 7 ppt.
- Women’s average earnings: +11 percent.
- GDP: 10.5 percent increase.
- Government revenues: 8.5 percent increase.
- Distributional note: benefits concentrate more in top 50 percent of income distribution, as better-educated women are hired first.

Comparative summary (figure values reported):
- Change in female labor force participation:
  - Closing FLFP gap: 20.7
  - Equal return from experience: 11.2 (figure labels)
- GDP gains after one generation:
  - Closing FLFP gap: 10
  - Equal return from experience: 10.5
- Government revenues grow:
  - Closing FLFP gap: 10
  - Equal return from experience: 8.5
- Gini (points difference):
  - Closing FLFP gap: -4.1
  - Equal return from experience: -0.1

### Policy recommendations (prioritized actions identified)
- Accelerate harmonization and standardization of existing laws and circumscribe claw-back clauses that affect women’s economic empowerment in the new constitution; revise discretionary laws in family, inheritance, and property rights.
- Ensure effective implementation and strengthen enforcement of laws and government policies through strong sensitization campaigns toward religious and community leaders and civil society; train judges, law enforcement officers, and Cadis courts officers.
- Leverage the gender budgeting pilot to provide adequate funding to key sectors supporting women’s health, childcare, and participation in secondary and tertiary education (including TVET).
- Expand the Women Enterprise Fund (WEF) as a model for alternative funding for women entrepreneurs; facilitate transition from informal to formal sector; support small scale farmers in the agricultural value chain; leverage digitalization to better structure micro and medium sized businesses run by women.
- Create conditions for more women’s access to the formal financial sector via implementation of the National Financial Inclusion plan focused on youth and women.
- Provide opportunities for more women in decision making, including in regions and rural areas where most vulnerable women are located.
- Expand social safety nets to vulnerable Gambians using a reliable and dynamic social registry; invest in food systems to reduce vulnerabilities to food insecurity; implement the green recovery focused National Development Plan to build resilience to shocks.
- Invest in resilient agricultural production to reduce food prices and support rural women; contemplate a land reform in The Gambia given the importance of land as a factor of production.

*Source: Prepared by Mamadou Barry, Momodou Jallow, Glen Kwende, and Vivian Malta; staff analysis and model results as presented in the supplied chapter.*

### References

### References

### Key references on gender, labor markets, and development
- Aguirre, D., L. Hoteit, C. Rupp, and K. Sabbagh, 2012, “Empowering the Third Billion. Women and the World of Work in 2012,” Booz and Company  
- Branisa, B., S. Klasen, & M. Ziegler. 2013. “Gender Inequality in Social Institutions.” World Development. Vol. 40, pp. 252-68.  
- Caprioli, M. 2005. “Primed for Violence: The Role of Gender Inequality in Predicting Internal Conflict.” International Studies Quarterly. Vol. 49, pp. 161-78  
- Gonzales, C., S. Jain-Chandra, K. Kochhar, and M. Newiak, M., and T. Zeinullayev. 2015b. “Catalyst for Change: Empowering Women and Tackling Income Inequality.” Washington, DC: IMF, 2015. Staff Discussion Note 15/20.  
- Kazakhstan, Rasmane Ouedraogo and Diego Gomes, 2023 “Macroeconomic Gains from Closing Gender Educational Gaps in Niger” IMF SIP/2023/006, International Monetary Fund, Washington, DC.  
- World Bank. 2012. “World Development Report: Gender Equality and Development.” Washington, D.C.: World Bank Group.  
- The World Bank ‘Women's economic empowerment through public procurement—A solution multiplier’.  
- The World Bank. “The Gambia Gender and Poverty Assessment 2022—Securing a Robust and Inclusive Growth” World Bank Poverty Team, June 2022.

### IMF and regional country reports and working papers
- IMF, 2015. “Regional Economic Outlook. Sub-Saharan Africa. Dealing with the Gathering Clouds.” Washington, D.C.: International Monetary Fund. October.  
- International Monetary Fund (IMF). 2019a. “IMF 2019 Article IV Report for Nigeria, Selected Issues.” IMF Country Report 19/93, International Monetary Fund, Washington, DC.  
- International Monetary Fund (IMF). 2021. “IMF 2021 Article IV Report for Kenya.” IMF Country Report 21/276, International Monetary Fund, Washington, DC.  
- Kazandjian, R., L. Kolovich, K. Kochhar, and M. Newiak. 2016. “Gender Equality and Economic Diversification.” IMF Working Paper 16/140. Washington, D.C.: International Monetary Fund  
- Malta, V., A. Martinez, and M. M. Tavares. 2019. “A Quantitative Analysis of Female Employment in Senegal.” IMF Working Paper 19/241, International Monetary Fund, Washington, DC.  
- Can Sever, Edward Gemayel. “Legal Gender Equality as a Catalyst for Convergence”. IMF Working Paper. WP/22/155 (2022)

### The Gambia—national and country-specific analyses
- Rasmane Ouedraogo and Diego Gomes, 2023 “Macroeconomic Gains from Closing Gender Educational Gaps in Niger” IMF SIP/2023/006, International Monetary Fund, Washington, DC.  
- World Bank 2022 “Securing a Robust and Inclusive Recovery: The Gambia Poverty and Gender Assessment 2022” Washington, D.C.: World Bank Group.  
- The Ministry of Women Children and Social Welfare (MOWCSW) 2019 “National Review Report on Implementation of the Beijing Declaration and Platform for Action (BPFA) +25”; The Gambia  
- UN Women 2020 “Mapping and Analysis of the Laws of The Gambia from a Gender Perspective: Towards Reversing Discrimination in Law”  
- Nabaneh - ‘Women’s Political Participation and Representation in The Gambia: One step forward or two back?’ (2014)  
- Draft National Development Plan 2023-2027, p 197.  
- The World Bank. “The Gambia Gender and Poverty Assessment 2022—Securing a Robust and Inclusive Growth” World Bank Poverty Team, June 2022.

### Theoretical, methodological, and historical works
- Gene M. Grossman and Elhanan Helpman. “Innovation and Growth in the Global Economy". 384 pp., 6 x 9 in, Hardcover. ISBN : 9780262071369 (1991)  
- Robert J. Barro and Xavier Sala-i-Martin. “Convergence across States and Regions”. Journal of Political Economy, Vol. 100, No. 2 (Apr. 1992), pp. 223-251 (29 pages) Published By: The University of Chicago Press  
- UNDP, "gender equality strategy, 2022–2025". Executive Board of the United Nations Development Programme, the United Nations Population Fund, and the United Nations Office for Project Services (11 April 2022)  
- UN-Women. “Statement policy and texts outcome of Beijing+5”. ISBN: 978-1-936291-95-3. (1995)

*1gmbea2024002 - References*

---


_Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1gmbea2024002.pdf_