Policy Analysis System Research Articles

The ESPAS network and the growth of EU foresight

AbstractThis article examines the European Strategy and Policy Analysis System (ESPAS) network and assesses its impact on efforts to embed strategic foresight in EU policy‐making. It analyses the development of the network through three stages: preparatory steps to 2014, quasi‐institutionalisation from 2015 and high‐level anchoring from 2019. Throughout, the view that a new approach to strategic analysis was needed met concerns about preserving institutional prerogatives and competences. The article suggests that this tension mitigated the network's impact, which has been more significant on matters of process than of substance. Achievements include the creation of foresight capacity and of dialogue across institutional and sectoral boundaries and greater appreciation of the interdependence of global challenges across different domains. Progress towards deeper engagement with worst‐case scenarios and with the challenge of societal fragmentation has been more limited.

Соціальна резильєнтність національної економіки крізь призму досвіду Європейського Союзу та України

The authors deal with the concept of resilience (stress resistance) at the macro level, and reveal its meaning in the societal, economic and social dimensions. It is shown that in the context of the strengthening of global risks and hybrid threats, and the accelerated transformation of the world into a global hybrid "peace-war" system, the priority task of government policy is to ensure the resilience of the national economic system as the ability to maintain functionality and recover after the shock effect of various factors. Based on the logical-historical approach, the authors reveal the stages in the formation of the concept of multidimensional resilience as a strategic basis of modern governance of the European Union. This concept became the basis for the reconfiguration of the EU strategic foresight system in 2020, integrated into the process of forming a Pan-European policy aimed at ensuring an effective transition to a "green", digital and fairer Europe. Within the framework of the European Strategy and Policy Analysis System (ESPAS), the updated EU strategic foresight system provides for the use of "Resiliency Information Panels" as a new monitoring tool, developed with due regard of the specificity in the development of the participating states. The evaluations of the socio-economic resilience of the European Union for the year 2023, which were obtained with the help of the specified monitoring tool, were analyzed and presented by the European Commission. The authors reveal the role of the concept of multidimensional resilience in the formation and implementation of national recovery and stability plans of the EU states at the current stage. Characterized the legislative innovations of the European Union regarding the resilience of the economies and societies of the participating countries in the conditions of overcoming the shock consequences of the COVID-19 pandemic, the Russian-Ukrainian war and climate change. The paper substantiates the need to ensure the social resilience of the economic development of Ukraine as a reliable pillar of its support during the war with the Russian Federation, as well as during the post-war reconstruction and reconstruction. The authors prove that the social resilience of Ukraine’s national economy under the conditions of martial law and post-war reconstruction can be presented in the form of a model that structurally contains three sectors, namely: 1) employment and labor potential; 2) solvent consumer demand; and 3) social protection and provision. Each of these sectors is complexly dependent on many factors that characterize the generation of human and social capital, the quality of people's lives, the development of the spheres of employment, social security and social protection of the population, the state of the ecosystem and the institutional environment, etc. Taking into account the EU’s modern approaches, a list of basic and additional indicators is developed for monitoring and analyzing the social resilience of Ukraine’s national economy. The authors provide various practical recommendations on state policy measures aimed at ensuring the social resilience of this country’s economy of Ukraine in the war and post-war period.

The BSP's Forecasting and Policy Analysis System

The Bangko Sentral ng Pilipinas (BSP) subscribes to the Forecasting and Policy Analysis System (FPAS) as the framework for macroeconomic forecasting and analysis in support of monetary policy formulation. FPAS is a standard framework, adopted by many in"ation-targeting central banks, that organizes the generation, consolidation, and analysis of economic information relavant to monetary policy formulation. This paper aims to describe how macroeconomic forecasts and policy simulations are generated to support monetary policy analysis and formulation at the BSP. To this end, this article summarizes the main features of the process involved in generating the baseline forecasts, alternative scenarios, and policy simulations. We highlight the complementary roles played by the BSP’s suite of models and the expert judgement from the sector specialists as well as the importance of forecast communication in the transmission of monetary policy. Finally, we present a systematic evaluation of the forecasting performance of the BSP from 2010 to 2020 together with some of the lessons in forecasting during the COVID-19 pandemic and the recent efforts to improve the BSP’s FPAS.

Towards Full-Fledged Inflation Targeting Monetary Policy Regime in Mauritius

An increasing number of emerging and developing countries have adopted or are transitioning towards full-fledged inflation targeting (FFIT) as the main monetary policy framework to anchor inflation. In this paper, we explore the FFIT regime as a means for Mauritius to achieve stable inflation, anchor inflationary expectations and establish credibility in committing monetary policy towards price stability as its primary goal. This paper reviews and highlights issues experienced with the current monetary policy framework and the challenges in transitioning towards FFIT. Given that forecasting is central to FFIT, we develop a practical model-based forecasting and policy analysis system (FPAS) to support transition to FFIT, taking into account structural features and shocks that are specific to the Mauritius economy.

Quarterly Projection Model for the National Bank of Rwanda

National Bank of Rwanda (BNR) modernized monetary policy and transited to the price-based policy framework in January 2019. The Forecasting and Policy Analysis System (FPAS) is the cornerstone for the new forward-looking framework, which mobilizes and organizes resources and sets processes for regular forecasting rounds. The core of this system is a structural macroeconomic model for macroeconomic analysis and projections to support the BNR staff’s policy recommendations to the monetary policy committee. This paper documents the quarterly projection model (QPM) at the core of the FPAS at the BNR. The model is an extension of the canonical structure in Berg et al (2006) to reflect specifics of the interest-rate-based policy framework with a managed exchange rate, the effect of agricultural sector and harvests on prices, and the role of fiscal policies and aid flows.

Quarterly Projection Model for the National Bank of Rwanda

National Bank of Rwanda (BNR) modernized monetary policy and transited to the price-based policy framework in January 2019. The Forecasting and Policy Analysis System (FPAS) is the cornerstone for the new forward-looking framework, which mobilizes and organizes resources and sets processes for regular forecasting rounds. The core of this system is a structural macroeconomic model for macroeconomic analysis and projections to support the BNR staff’s policy recommendations to the monetary policy committee. This paper documents the quarterly projection model (QPM) at the core of the FPAS at the BNR. The model is an extension of the canonical structure in Berg et al (2006) to reflect specifics of the interest-rate-based policy framework with a managed exchange rate, the effect of agricultural sector and harvests on prices, and the role of fiscal policies and aid flows.

Republic of Belarus

The NBRB has made substantial progress in improving its forecasting and policy analysis system (FPAS) and integrating it into monetary policy decision-making. The FPAS, and the model-based forecasts and policy analysis, is now well integrated into the policy-making process. Staff are well trained and have become experienced in using the tools developed for policy analysis and forecasting. The forecasting and decision-making process is well structured and has helped increase the two-way interaction between staff and the NBRB board—additional and less formal interaction between staff and board members in between the formal meetings may help enhance the process further.

Republic of Belarus

The National Bank of the Republic of Belarus (NBRB) is reforming its monetary policy framework in line with recommendations of past IMF TA missions and its Road Map for Transitioning to Inflation Targeting with the aim of eventually adopting inflation targeting (IT). Transitioning to IT would require, among other measures and reforms, strengthening the monetary policy forecasting and analysis system (FPAS) and better integrating the core quarterly projection model (QPM) into the decision-making process. This TA mission was the fifth from series of quarterly IMF TA missions focused on the FPAS capacity building. It was mainly aimed to simulate initial conditions and compile a QPM-based forecast scenario as a part of a practical forecasting round at the NBRB in March. Moreover, the mission worked with the modeling team to deepen its understanding of the QPM’s role in policy decision making and in internal communication.

Assessment of the feedstock supply for siting single‐ and multiple‐feedstock biorefineries in the USA and identification of prevalent feedstocks

AbstractAn integrated multi‐feedstock bioenergy (i.e., biofuel, biopower, or bioproduct) supply system has potential to reduce biomass supply system uncertainties and costs. This study identifies optimal configurations of multi‐feedstock biomass‐to‐biorefinery supply chains and pertinent feedstock combinations based on spatial distribution of feedstock and lowest delivered cost to the biorefinery. We used the Supply Characterization Model (SCM) to allocate feedstock supplies to candidate biorefinery facilities. Model runs were performed for herbaceous energy crops, agriculture residue, and woody biomass available in 2017, 2022, 2025, and 2030 as estimated by the Policy Analysis System (POLYSYS) and Forest Sustainable and Economic Analysis Model (ForSEAM) models. Three feedstock supply scenarios were compared: (a) an herbaceous scenario: switchgrass, miscanthus, biosorghum, and corn stover; (b) a woody scenario: coppice wood, noncoppice wood, whole trees, and forestry residues, and (c) a mixed scenario: a combination of all feedstocks in herbaceous and woody scenarios. By 2030 the analyses predicted that 323, 168, and 473 biorefineries were sited in the herbaceous, woody, and mixed scenario, respectively, in the conterminous USA. Feedstock mixes supplied to the biorefineries were mostly dominated by a single feedstock. The most prominent feedstock mixes identified were: (1) switchgrass and miscanthus; (2) coppice and noncoppice wood; and (3) coppice wood, noncoppice wood, switchgrass and miscanthus. Biorefineries using multi‐feedstock would be beneficial for growth of bioeconomy, however flexible and cost‐effective conversion platforms should be developed to efficiently utilize multiple feedstocks. This analysis identifies biorefinery locations and feedstock supply mixes while minimizing delivered feedstock costs based on spatial and temporal feedstock availability. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

Quarterly Projection Model for the National Bank of Rwanda

National Bank of Rwanda (BNR) modernized monetary policy and transited to the price-based policy framework in January 2019. The Forecasting and Policy Analysis System (FPAS) is the cornerstone for the new forward-looking framework, which mobilizes and organizes resources and sets processes for regular forecasting rounds. The core of this system is a structural macroeconomic model for macroeconomic analysis and projections to support the BNR staff's policy recommendations to the monetary policy committee. This paper documents the quarterly projection model (QPM) at the core of the FPAS at the BNR. The model is an extension of the canonical structure in Berg et al (2006) to reflect specifics of the interest-rate-based policy framework with a managed exchange rate, the effect of agricultural sector and harvests on prices, and the role of fiscal policies and aid flows.

Role of Small Islands in UN Climate Negotiations: A Constructivist Viewpoint

This article is about small island developing states (SIDS) and their role in the United Nations (UN) climate negotiations. It presents a discussion about how a constructivist model of foreign policy analysis and international system design can be used to explain the impact of climate ideas of SIDS on UN climate system. The SIDS have been in the UN climate negotiations since the 1980s, committed to a climate agenda with clear ideas about the challenges they face and the type of solutions they seek from the international policy community. In this respect, this article seeks to explain that climate ideas shared among SIDS have established an intersubjective understanding to promote a compelling common voice at international climate negotiations, which is based on an island vulnerability identity. These ideas have shaped the policy thinking and interests of climate negotiators to design institutional frameworks that have given special consideration to SIDS. It concludes that this observation represents a disproportionate impact of SIDS. Despite the weak material powers for being small islands, their climate agenda has influenced the UN system design to address their concerns.

Strengthening the Monetary Policy Framework in Korea

Adoption of inflation targeting by the Bank of Korea (BOK) in 1998 contributed to low and stable inflation. However, after the global financial crisis (GFC) monetary policy faced more challenging conditions. Inflation slipped below the target range in 2012 and remains below it despite a cut in the target to 2 percent in 2016. Policy also became more complex with the addition of financial stability to the central bank’s mandate. To address these challenges, this paper proposes a two-pronged approach to strengthen the effectiveness with which monetary policy can meet its objectives: first, enhanced communication on how the target will be achieved over the medium-term, building on a forecasting and policy analysis system; and, second, by clarifying the complementary role of macroprudential policy in containing financial stability risks so that monetary policy can focus on the inflation target. Simulation of a macro model calibrated to Korea illustrates how it can be used to provide this greater medium-term focus on achieving the inflation target and strengthen communication.

Strengthening the Monetary Policy Framework in Korea

Adoption of inflation targeting by the Bank of Korea (BOK) in 1998 contributed to low and stable inflation. However, after the global financial crisis (GFC) monetary policy faced more challenging conditions. Inflation slipped below the target range in 2012 and remains below it despite a cut in the target to 2 percent in 2016. Policy also became more complex with the addition of financial stability to the central bank's mandate. To address these challenges, this paper proposes a two-pronged approach to strengthen the effectiveness with which monetary policy can meet its objectives: first, enhanced communication on how the target will be achieved over the medium-term, building on a forecasting and policy analysis system; and, second, by clarifying the complementary role of macroprudential policy in containing financial stability risks so that monetary policy can focus on the inflation target. Simulation of a macro model calibrated to Korea illustrates how it can be used to provide this greater medium-term focus on achieving the inflation target and strengthen communication.

Assessment of Perennial Grass Inventories Predicted in the Billion-Ton Studies

Abstract. The U.S. Department of Energy (DOE) has estimated herbaceous biomass availability through simulations with the Policy Analysis System (POLYSYS) agricultural modeling framework. An operational assumption for POLYSYS limited conversion of pastureland to perennial grass crops to counties east of the 100th meridian as a proxy for precipitation sufficient for economically viable yield, but allowed cropland conversion regardless of location. Knowledge of local conditions raised questions about predicted biomass quantities for Texas counties in the 2011 assessment. POLYSYS was rerun with different assumptions, specifically replacing the 100th meridian boundary with annual average precipitation data and limiting cropland conversion in low-rainfall counties. Perennial grass production was found to be overestimated by 8% and 87% in the U.S. and Texas, respectively (at $66.14 DMg-1), when limiting all land conversion to regions with >635 mm precipitation. Total herbaceous biomass predicted was approximately the same as in the BT2, but the biomass geographical location changed across the nation. Texas’ biomass contribution decreased from 6% to 1% at $66.14 DMg-1 and from 16% to 11% at $88.18 DMg-1. Subsequent to this research being conducted, the DOE released the 2016 biomass inventory assessment, and these results are compared to those newest estimates. Keywords: Billion-Ton Study, Biomass, Perennial grass, Precipitation, Switchgrass.

Morocco: A Practical Approach to Monetary Policy Analysis in a Country with Capital Controls

The Central Bank of Morocco has been working on developing a Forecasting and Policy Analysis System (FPAS) to support a gradual move toward a more flexible exchange rate regime and the eventual adoption of a full-fledged inflation-targeting (IT) regime. At the center of the FPAS is a quarterly projection model that was tailored for two different types of exchange rate regimes. Presently, the fixed exchange rate model version is to be used during the pre-IT period, while the flexible exchange rate model version is to be used to prepare alternative scenarios for monetary policy decision makers to discuss the potential policy implications of shocks under an IT regime.

Structural Quarterly Projection Model for Belarus

Belarusian authorities contemplate transiting to inflation targeting. The paper suggests a small structural model at the core of the forecasting and policy analysis system. A well-researched canonical structure of Berg, A., Karam, P. and D. Laxton (2006) is extended to capture specifics of Belarusian economy and macroeconomic policy. The modified model's policy block reflects a monetary targeting regime and allows for transition from it to an interest-rate-based framework. Adding wages, directed lending and dollarization allow for studying implications of activist wage policy, state program lending, and dollarization for macroeconomic stability and the strength of the policy transmission mechanism.

An Index for Transparency for Inflation-Targeting Central Banks: Application to the Czech National Bank

This paper develops a new central bank transparency index for inflation-targeting central banks (CBT-IT index). It applies the CBT-IT index to the Czech National Bank (CNB), one of the most transparent inflation-targeting central banks. The CNB has invested heavily in developing a Forecasting and Policy Analysis System (FPAS) to implement a full-fledged inflation-forecast-targeting (IFT) regime. The components of CBT-IT index include measures of transparency about monetary policy objectives, the FPAS designed to support IFT, and the monetary policymaking process. For the CNB, all three components have shown substantial improvements over time but a few gaps remain. The CNB is currently working on eliminating some of these gaps.

An Index for Transparency for Inflation-Targeting Central Banks: Application to the Czech National Bank

This paper develops a new central bank transparency index for inflation-targeting central banks (CBT-IT index). It applies the CBT-IT index to the Czech National Bank (CNB), one of the most transparent inflation-targeting central banks. The CNB has invested heavily in developing a Forecasting and Policy Analysis System (FPAS) to implement a full-fledged inflation-forecast-targeting (IFT) regime. The components of CBT-IT index include measures of transparency about monetary policy objectives, the FPAS designed to support IFT, and the monetary policymaking process. For the CNB, all three components have shown substantial improvements over time but a few gaps remain. The CNB is currently working on eliminating some of these gaps.

Structural Quarterly Projection Model for Belarus

Belarusian authorities contemplate transiting to inflation targeting. The paper suggests a small structural model at the core of the forecasting and policy analysis system. A well-researched canonical structure of Berg, A., Karam, P. and D. Laxton (2006) is extended to capture specifics of Belarusian economy and macroeconomic policy. The modified model’s policy block reflects a monetary targeting regime and allows for transition from it to an interest-rate-based framework. Adding wages, directed lending and dollarization allow for studying implications of activist wage policy, state program lending, and dollarization for macroeconomic stability and the strength of the policy transmission mechanism.

电动汽车产业政策对电动汽车推广量的影响研究—以典型示范城市为例

电动汽车不仅是国家战略上的重要举措，也将成为未来中国经济可持续增长重要支柱产业。目前中国电动汽车依靠产业政策在全国各大城市广泛推广，受到了较多关注。为了研究电动汽车产业政策对汽车推广的有效性问题，本文以中国典型城市的发展为例，研究城市层面发布的产业政策对电动汽车推广数量的影响机理。首先，本文建立了以产业创新链和“需求–供给”侧政策的政策分析体系；其次，利用内容分析法系统地研究示范推广以来5个典型城市：北京、上海、深圳、杭州、武汉颁布的有关电动汽车发展的政策条文165条，应用政策分析体系对电动汽车产业政策进行了类别划分；最后，通过多元统计分析方法，探索电动产业政策对汽车推广的影响变化，为电动汽车产业政策的进一步实施和完善提供了参考。 Electric vehicle is an important strategy for the state, but also an important pillar industry for the sustainable growth of China’s economy in the future. At present, China’s electric vehicles rely on industrial policies widely promoted in major cities across the country, receiving more attention. This paper takes the typical cities in China as examples to study the influence mechanism of the industrial policies issued by the city level on the promotion of the number of electric vehicles. First of all, this paper establishes a policy analysis system based on industrial innovation chain and “demand-supply” policy. Secondly, we use content analysis method to systematically study five typical cities in five years: Beijing, Shanghai, Shenzhen, Hangzhou and Wuhan’s policies, then apply the policy analysis system for the electric vehicles industry policies to classify. Finally, through multivariate statistical analysis methods to explore the impact of electric vehicles industry policy on the promotion of electric vehicles changes in order to provide the reference for implementation of the electric vehicles industry policy in future.