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.

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.

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 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.

A model in which monetary policy pursues full-fledged inflation targeting adapts well to Ghana. Model features include: endogenous policy credibility; non-linearities in the inflation process; and a policy loss function that aims to minimize the variability of output and the interest rate, as well as deviations of inflation from the long-term low-inflation target. The optimal approach from initial high inflation to the ultimate target is gradual; and transitional inflation-reduction objectives are flexible. Over time, as policy earns credibility, expectations of inflation converge towards the long-run target, the output-inflation variability tradeoff improves, and optimal policy responses to shocks moderate.

This book provides empirical applications of macroeconometric methods through discussions on key issues in the Indian economy. It deals with issues of topical relevance in the arena of macroeconomics. The aim is to apply time series and financial econometric methods to macroeconomic issues of an emerging economy such as India. The data sources are given in each chapter, and students and researchers may replicate the analyses.The book is divided into three parts—Part I: Macroeconomic Modelling and Policy; Part II: Forecasting the Indian Economy and Part III: Business Cycles and Global Crises. It provides a holistic understanding of the techniques with each chapter delving into a relevant issue analysed using appropriate methods—Chapter 1: Introduction; Chapter 2: Macroeconomic Modelling and Bayesian Methods; Chapter 3: Monetary Policy Framework in India; Chapter 4: Determinants of Yields on Government Securities in India; Chapter 5: Monetar y Transmission in the Indian Economy; Chapter 6: India’s Bilateral Export Growth and Exchange Rate Volatility: A Panel GMM Approach; Chapter 7: Aggregate and Sectoral Productivity Growth in the Indian Economy: Analysis and Determinants; Chapter 8: Forecasting the INR/USD Exchange Rate: A BVAR Framework; Chapter 9: Forecasting India’s Inflation in a Data-Rich Environment: A FAVAR Study; Chapter 10: A Structural Macroeconometric Model for India; Chapter 11: International Synchronization of Growth Rate Cycles: An Analysis in Frequency Domain; Chapter 12: Inter-Linkages Between Asian and U.S. Stock Market Returns: A Multivariate GARCH Analysis; Chapter 13: The Increasing Synchronization of International Recessions. Since the selection of issues is from macroeconomic aspects of the Indian economy, the book has wide applications and is useful for students and researchers of fields such as applied econometrics, time series econometrics, financial econometrics, forecasting methods and macroeconomics.

Despite strong economic growth since 2000, many low-income countries (LICs) still face numerous macroeconomic challenges, even prior to the COVID-19 pandemic. Despite the deceleration in real GDP growth during the 2008 global financial crisis, LICs on average saw 4.5 percent of real GDP growth during 2000 to 2014, making progress in economic convergence toward higher-income countries. However, the commodity price collapse in 2014–15 hit many commodity-exporting LICs and highlighted their vulnerabilities due to the limited extent of economic diversification. Furthermore, LICs are currently facing a crisis like no other—COVID-19, which requires careful policymaking to save lives and livelihoods in LICs, informed by policy debate and thoughtful research tailored to the COVID-19 situation. There are also other challenges beyond COVID-19, such as climate change, high levels of public debt burdens, and persistent structural issues.

Over the past two decades, many low- and lower-middle income countries (LLMICs) have improved control over fiscal policy, liberalized and deepened financial markets, and stabilized inflation at moderate levels. Monetary policy frameworks that have helped achieve these ends are being challenged by continued financial development and increased exposure to global capital markets. Many policymakers aspire to move beyond the basics of stability to implement monetary policy frameworks that better anchor inflation and promote macroeconomic stability and growth. Many of these LLMICs are thus considering and implementing improvements to their monetary policy frameworks. The recent successes of some LLMICs and the experiences of emerging and advanced economies, both early in their policy modernization process and following the global financial crisis, are valuable in identifying desirable features of such frameworks. This paper draws on those lessons to provide guidance on key elements of effective monetary policy frameworks for LLMICs.

The COVID-19 pandemic underscores the critical need for detailed, timely information on its evolving economic impacts, particularly for Sub-Saharan Africa (SSA) where data availability and lack of generalizable nowcasting methodologies limit efforts for coordinated policy responses. This paper presents a suite of high frequency and granular country-level indicator tools that can be used to nowcast GDP and track changes in economic activity for countries in SSA. We make two main contributions: (1) demonstration of the predictive power of alternative data variables such as Google search trends and mobile payments, and (2) implementation of two types of modelling methodologies, machine learning and parametric factor models, that have flexibility to incorporate mixed-frequency data variables. We present nowcast results for 2019Q4 and 2020Q1 GDP for Kenya, Nigeria, South Africa, Uganda, and Ghana, and argue that our factor model methodology can be generalized to nowcast and forecast GDP for other SSA countries with limited data availability and shorter timeframes.

This book gives a comprehensive description of macroeconometric modeling and its development over time. The first part depicts the history of macroeconometric model building, starting with Jan Tinbergen's and Lawrence R. Klein's contributions. It is unique in summarizing the development and specific structure of macroeconometric models built in North America, Europe, and various other parts of the world. The work thus offers an extensive source for researchers in the field. The second part of the book covers the systematic characteristics of macroeconometric models. It includes the household and enterprise sectors, disequilibria, financial flows, and money market sectors.