This paper takes stock of forecasting and policy analysis system capacity development (FPAS CD), drawing extensively on the experience and lessons learned from developing FPAS capacity in the central banks. By sharing the insights gained during FPAS CD delivery and outlining the typical tools developed in the process, the paper aims to facilitate the understanding of FPAS CD within the IMF and to inform future CD on building macroeconomic frameworks. As such, the paper offers a qualitative assessment of the experience with FPAS CD delivery and the use of FPAS in the decision-making process in central banks.

This technical assistance (TA) report presents the outcomes of the multi-year Bank of Ghana (BOG) Forecasting and Policy Analysis System (FPAS) TA project, conducted between late-2019 and mid-2024 over a total of seven missions, three in-person and four virtual. The project has focused on upgrading and building new institutional capacity for model-based policy analysis and macroeconomic forecasting, along its integration into monetary policy processes and external communications. BOG staff has made remarkable progress and built a strong skillset in providing analytical support to the policymakers. Model-based work plays an important role in the BOG internal deliberations and represents the key input in forward-looking monetary policy formulation, including in regular external communications. Remaining recommendations relate to ensuring FPAS work sustainability and further streamline external communications.

Amidst a global backdrop of persistent post-COVID inflation and spillovers from Russia’s war in Ukraine, the countries of the Caucasus and Central Asia (CCA) region have faced strong price pressures in recent years. Inflation is estimated to have peaked in early 2023, but still exceeds central bank targets. In particular, core inflation remains stubbornly high reflecting a combination of second-round effects, surges in global energy and food prices, and domestic demand pressures. More broadly, uncertainty and downside risks also weigh on the economic outlook, including due to regional tensions, financial turmoil related to international monetary policy normalization, and a growth slowdown in key trading partners. In this context, CCA countries’ ability to contain inflationary pressures and anchor inflation expectations hinges on the credibility and effectiveness of their monetary policy frameworks. Since gaining independence in the 1990s, countries in the CCA region have made considerable progress in modernizing their monetary policy frameworks. CCA central banks have strengthened their legal frameworks and established broad de-jure independence. Armenia, Georgia, Kazakhstan, the Kyrgyz Republic, and Uzbekistan are transitioning to inflation targeting regimes, while the central banks of Azerbaijan, Tajikistan, and Turkmenistan rely on the exchange rate as an operational target. However, the post-COVID surge in inflation has highlighted the limitations of current frameworks and triggered a fresh policy debate on the need to strengthen monetary policy effectiveness in the CCA. This paper reviews the CCA region’s monetary policy landscape, highlights challenges in monetary policy design and implementation, and identifies areas that warrant strengthening. It draws on original surveys of country authorities, IMF country teams, and the work by Unsal and others (2022). It uses novel empirical work to analyze monetary policy transmission, the link between foreign exchange interventions and exchange rate dynamics, the drivers of financial de-dollarization, and the effects of central bank communication in the CCA.

The paper describes the Quarterly Projection Model (QPM) that underlies the Bank of Ghana Forecasting and Policy Analysis System (FPAS). The New Keynesian semi-structural model incorporates the main features of the Ghanaian economy, transmission channels and policy framework, including an inflation targeting central bank and aggregate demand effects of fiscal policy. The shock propagation mechanisms embedded in the calibrated QPM demonstrate its theoretical consistency, while out-of-sample forecasting accuracy validates its empirical robustness. Another important part of the QPM is endogenous policy credibility, which may aggravate policy trade-offs in the model and make it more realistic for developing economies. Historical track record of real time policy analysis and medium-term forecasting conducted with the QPM – as a component of the broader FPAS analytical organization – establishes its critical role in supporting the Bank’s forward-looking monetary policy framework.

Republic of Armenia: Selected Issues

The Central Bank of Jordan (CBJ) has developed a Forecasting and Policy Analysis System (FPAS) to serve as a reliable analytical framework for macroeconomic analysis, forecasting and decision-making under a pegged exchange rate regime. At the heart of the FPAS is the CBJ’s extended Jordan Analysis Model (JAM2.0). The model captures the monetary transmission mechanism and provides a consistent monetary policy framework that uses the exchange rate as an effective nominal anchor. This paper outlines the structure and properties of JAM2.0 and emphasizes the enhanced interplay and tradeoffs among monetary, fiscal, and foreign exchange management policies. Simulation and forecasting exercises demonstrate JAM2.0’s ability to match key stylized facts of the Jordanian economy, produce accurate forecasts of important macroeconomic variables, and explain the critical relationships among policies.

The paper introduces a semi-structural Quarterly Projection Model (QPM) tailored for the Democratic Republic of the Congo (DRC), highlighting its resource richness and high degree of dollarization. We provide an overview of the model's specifications to elucidate key features of the DRC economy and present its properties, evaluating its alignment with DRC data and assessing its goodness of fit. Additionally, the paper demonstrates the QPM's practical application through a counterfactual scenario, comparing policy recommendations with the actual policy responses of the Central Bank of the Republic of Congo to observed exchange rate and inflation pressures in 2023. Beyond the QPM, the paper showcases supplementary tools that enhance its utility for generating medium-term forecasts and developiong narratives in support of monetary policymaking. Specifically, we introduce the Nowcasting and Near-Term Forecast models, designed to assess the economy in real-time and predict short-term inflationary trends.

The Bangko Sentral ng Pilipinas (BSP) has enhanced its macroeconomic modeling through the Forecasting and Policy Analysis System (FPAS), transitioning from a multi-equation econometric model to a modernized system centered on the Quarterly Projection Model (QPM). In its new version, the Policy Analysis Model for the Philippines (PAMPh2.0) integrates forward-looking projections, endogenous monetary policy, fiscal and macroprudential considerations, labor dynamics, and addresses complex shocks and policy trade-offs, facilitating effective policy mix determination and supporting real-time policy evaluation. The BSP’s modernization efforts also include refining forecast calendars and strengthening communication channels to accommodate the operationalization of PAMPh2.0. Detailed validation methods ensure empirical consistency. Finally, future refinements will align the model with evolving empirical findings and theoretical insights, ensuring its continued relevance.

This paper presents a semi-structural macroeconomic model aimed at facilitating policy analysis and forecasting, primarily in countries with imperfect capital mobility and hybrid monetary policy regimes. Compared to earlier gap-trend projection models, the Forecasting Model of Internal and External Balance (FINEX) contains three main innovations: it accentuates external and internal balances; explicitly incorporates fiscal policy; and partly endogenizes the main trends. FINEX thus covers a broad set of policy instruments, including foreign exchange interventions (FXI), capital flow management measures (CFM), as well as common fiscal policy instruments. The model incorporates insights from the recent DSGE literature, while maintaining a more accessible gap-trend structure that lends itself to practical policy applications. While the paper refrains from drawing broad policy lessons, it emphasizes the model's ability to interpret recent data in terms of structural shocks and policy responses, thereby aiding policymakers in constructing coherent economic narratives and considering alternative scenarios.